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Proteus Discover is the world's first Digital Medicine offering designed for health organizations searching for an efficient, patient-centric approach to measure, manage and improve the health of patient populations. Proteus Discover provides the tools needed to build efficiency and measurement into the delivery of care, and an opportunity to mitigate the high costs of uncontrolled diseases.

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Comprehensive health enhancement support system (CHESS)
The services that are included on the online tool are as followed:
- Instant library
-Action plan
-Getting help

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Smartphone apps have been found to be a flexible way in providing tailored mate support for the user. Interventions that are customisable have been found to be important in creating a positive behaviour change (Noar, 2011).

Limitations of previous apps that will be eradicated in the current app:
Apps for HIV positive people have been found to lack psychological and emotional support resources. The current app will invest in this and have a page solely on coping strategies to ensure psychological needs are met.
Few apps have included tools that encourage a link between the user/ patient and their health care team. For my app, features such as real time feedback and health coaching across would be beneficial for the user.

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Monitoring Editor: Gunther Eysenbach

Reviewed by Elia Gabarron

Kathryn E Muessig, PhD, ¹ Emily C Pike, BS, ¹ Sara LeGrand, PhD, ² and Lisa B Hightow-Weidman, MD, MPH ¹

Abstract

Background

Mobile phone applications (apps) provide a new platform for delivering tailored human immunodeficiency virus (HIV) and sexually transmitted disease (STD) prevention and care.

Objective

To identify and evaluate currently available mobile phone apps related to the prevention and care of HIV and other STDs.

Methods

We searched the Apple iTunes and Android Google Play stores for HIV/STD-related apps, excluding apps that exclusively targeted industry, providers, and researchers. Each eligible app was downloaded, tested, and assessed for user ratings and functionality as well as 6 broad content areas of HIV prevention and care: HIV/STD disease knowledge, risk reduction/safer sex, condom promotion, HIV/STD testing information, resources for HIV-positive persons, and focus on key populations.

Results

Search queries up to May 2012 identified 1937 apps. Of these, 55 unique apps met the inclusion criteria (12 for Android, 29 for iPhone, and 14 for both platforms). Among these apps, 71% provided disease information about HIV/STDs, 36% provided HIV/STD testing information or resources, 29% included information about condom use or assistance locating condoms, and 24% promoted safer sex. Only 6 apps (11%) covered all 4 of these prevention areas. Eight apps (15%) provided tools or resources specifically for HIV/STD positive persons. Ten apps included information for a range of sexual orientations, 9 apps appeared to be designed for racially/ethnically diverse audiences, and 15 apps featured interactive components. Apps were infrequently downloaded (median 100-500 downloads) and not highly rated (average customer rating 3.7 out of 5 stars).

Conclusions

Most available HIV/STD apps have failed to attract user attention and positive reviews. Public health practitioners should work with app developers to incorporate elements of evidence-based interventions for risk reduction and improve app inclusiveness and interactivity.

Keywords: HIV, technology, mobile phone applications

Introduction

Mobile phone health interventions are increasingly being used for the prevention and care of human immunodeficiency virus (HIV) and other sexually transmitted diseases (STDs) [ 1- 3]. These initiatives have been designed to promote prevention messages [ 4], facilitate test result notification [ 5, 6], improve HIV medication adherence, and increase adherence to clinic appointments [ 7- 12]. Although phone-based interventions have typically used the voice or text-based Short Message Service (SMS) features of mobile phones [ 1, 3, 13], the increasing popularity of smartphones and smartphone applications (apps) [ 14, 15] has greatly expanded the possibilities for phone-based HIV/STD interventions [ 13]. These interventions are critical for reversing the HIV epidemic; 34.2 million people worldwide are living with HIV and 2.5 million people became newly infected in 2011 alone [ 16].

Smartphones have revolutionized mobile communication markets by offering enhanced mobile phones featuring improved Internet access and the capacity to perform more advanced computer functions. Consumer research from June 2012 estimates that 54.9% of mobile phone subscribers in the United States own a smartphone, with phones running on Apple's iPhone operating systems (iOS) and Android's operating systems (Android OS) representing over 86% of this market [ 15]. Smartphone apps are downloadable programs that run on the smartphone's OS, which may include Web-based features. As of March 2012, Apple's iTunes apps had received over 25 billion downloads [ 14] and the Android Google Play Store exceeded 15 billion app downloads in May 2012 [ 17]. These numbers continue to rise at over 1 billion app downloads per month for each store [ 17].

Many of these apps are health related. A search on August 1, 2012, for apps categorized as "health & fitness" and "medical" yielded 13,479 apps available for iPhone consumers [ 18] and 15,891 apps available for Android consumers [ 19]. This widespread use of apps provides a promising new platform for delivering tailored HIV prevention messages and interactive care services. But are public health practitioners utilizing this new opportunity? In this paper, we review the characteristics and content of HIV- and STD-related apps that are available through the two primary online app providers: the Apple iTunes Store and the Android Google Play Store. This review describes the current landscape and content of HIV/STD apps, assesses utilization and acceptability of these apps, and provides recommendations to guide the design and development of future apps.

Methods

Search and Screening Strategy

On May 1 to 3, 2012, the following terms were used to search the Apple iTunes Store and the Android Google Play Store: HIV, human immunodeficiency virus, acquired immune deficiency syndrome, sexually transmitted diseases, STD, sexually transmitted infections, STI, sexual health, safe sex, and condom. An app was excluded if it did not include HIV/STD content; exclusively targeted industry, health care, research, or medical professionals; or was not available in English. Two researchers (KEM and ECP) searched each store and compiled lists of all identified apps. App titles and descriptions were screened for relevance and lists of apps to download were created. Lists were compared and differences resolved by a third member of the study team (LBH). Any eligible app that was identified in only one store was searched for by name in the other store to confirm its exclusive availability.

Data Extraction and App Assessment

The following data was extracted for each eligible app on May 1 to 3, 2012: name, platform (iPhone, Android, or both), category as defined by site (eg, medical, education, health and fitness, lifestyle), description of app content as provided by site, price, user star rating, number of customer downloads (available for Android only), number of customer ratings (available for iPhone only), and the date the app was last updated by the developer. For apps that were available in both the Google Play and iTunes stores, we recorded separate price and user rating information for each store. From May 7 to 24, 2012, we downloaded each eligible app (both free and fee-based) and tested all features and functions. If an app had both a free and fee-based version, only the free version was downloaded and assessed.

To evaluate the apps we identified 6 broad content areas for advancing the prevention and treatment of HIV based on the World Health Organization's Global Health Sector Strategy on HIV/AIDS 2011-2015 [ 20] and the National AIDS Strategy for the United States [ 21]. These content areas include HIV/STD knowledge and awareness, behavior change/risk reduction/safer sex promotion, condom use/promotion, HIV/STD testing, resources and linkage to care for HIV/STD-positive persons, and intensified or focused efforts for key communities/populations. Each app was assessed for inclusion of the 5 content areas, operationalized as:

1. Does the app provide information about HIV or other STDs?

2. Does the app provide information or descriptions about ways to reduce the risk of sexually transmitting or acquiring HIV/STDs?

3. Does the app provide information about how to use or obtain male or female condoms?

4. Does the app promote or provide information or resources about HIV/STD testing?

5. Does the app provide resources specifically for HIV/STD-positive persons? (Features and resources provided through apps for HIV/STD-positive persons were tested and described.)

If the app also covered other content areas, these were listed and described. These descriptions were then compiled and grouped, resulting in the following additional 5 content categories: drug and alcohol risk, relationships, HIV/STD news, HIV/STD stigma, and an HIV/STD status verification service.

To assess whether the app fulfilled the criteria of intensified or focused efforts for key communities or populations, we reviewed the text and images used in each app. Key populations for HIV prevention vary depending on the local epidemic context. Thus, this assessment included an open-ended description of text and images used and a subjective assessment of whether the app appeared to be inclusive or tailored. For example, if an app included images of black men or women among a variety of racial and ethnic images, this app would be characterized as "inclusive." If an app explicitly or exclusively addressed black men or women, this app would be considered "tailored." Finally, we assessed whether each app included any interactive component, such as a game, quiz, diary, or goal tracker.

Results

Search and Screening

Search queries identified 1937 apps. After screening the app titles and the site-provided app descriptions, 84 eligible apps were downloaded for full review (). A further 15 apps were then excluded because they did not include HIV/STD-related content or were not functional (list available upon request). A total of 69 apps met the final inclusion criteria: 43 from the Apple iTunes Store and 26 from Android's Google Play Store. Of these, 55 apps were unique with 14 apps available in both stores (29 iTunes only, 12 Google Play only, and 14 available in both stores).

Descriptive Characteristics

provides a summary of app characteristics and lists the name, details, and primary content areas of each eligible app. Approximately half (27/55, 49%) of the apps had been updated within the past year (May 2011 to May 2012). Seventy-one percent (39/55) of apps provided information about HIV/STDs and 24% (13/55) provided information about reducing sexual transmission risk. Twenty-nine percent (16/55) of apps included instructions for condom use or assistance locating condoms and 36% (20/55) included information about HIV/STD testing or resources for finding testing centers. Only 6 apps covered all 4 of these broad areas of HIV/STD prevention (knowledge, risk reduction, condom promotion, and testing): Action for AIDS [ 22], Pos or Not [ 23], STD411 [ 24], STDiQ [ 25], Safe Sex Tips [ 26], and Sexual Health Guide [ 27]. In addition, one app supported a third-party service that provided an electronic certificate verifying negative HIV/STD test results (Chec-Mate) [ 28]. Five (9%) apps addressed (noninjection) drug or alcohol use and HIV/STD risk. A small number of apps discussed HIV/STDs in the context of relationships (n=5), provided links to online news stories featuring HIV/STDs (n=4), or addressed HIV stigma (n=1).

Table 1

Table 2

Apps for Persons Diagnosed With HIV or Other STDs

Out of the 55 apps, 8 (15%) were developed for persons diagnosed with HIV or other STDs. These apps typically included interactive tools for the following areas: medication adherence tracking and reminders, medication interaction information, medical appointment calendars and reminders, doctor/clinic names and locations, symptoms/side effects trackers, and viral load/lymphocyte (CD4) cell count trackers (). One social networking app (PositiveSingles) [ 29] facilitated connections with other persons diagnosed with HIV or other STDs.

Table 3

The two highest user-rated apps for HIV/STD-positive persons were HIV and Your Heart [ 30] (5 stars) and iStayHealthy [ 31] for both the iPhone and Android (4.7 stars). The HIV and Your Heart [ 30] app included videos featuring providers, experts, and HIV-positive persons. This app also provided information about HIV and heart health, smoking cessation, diet and exercise, and a wellness checklist for tracking 9 health measures, including viral load and CD4 cell counts. The iStayHealthy [ 31] app provided a tracking and charting feature for viral load and CD4 cell counts (), a component to record missed medication doses and medication side effects, a medication reminder alarm, and a place to record other medical history data, such as clinic locations and illness events. This app also included a photo library of HIV medication pill images that could be tailored to a daily medication schedule ().

Interactive App Components

Fifteen apps (27%) that did not specifically target HIV-infected persons included an interactive component, such as a game/quiz (n=9) or a risk assessment activity (n=6). Here we highlight 4 examples of different types of interactive components (full descriptions of all interactive app components available upon request). In Condom Pro [ 32], players advance through 10 game levels by using the phone's touchscreen to carefully "open" a condom, correctly place it over an object (), and correctly remove it from the object. It's Your Shout [ 33] asks the user a series of humorous personality questions and then matches the user's profile with a superhero or celebrity's profile. The final message with each quiz announces that, "Even superheroes can get Chlamydia. Be tested. Be sure." The user is then given the option to order a home testing kit for chlamydia screening. The STD411 [ 24] app features an interactive chart for gay, bisexual, and transgender men where flashing colored condoms (red, yellow, and green) indicate the level of risk of different sexual activities for various STDs (). As the user selects various colored condoms, diseases, or sexual activities, a brief risk explanation appears above the graphic. Finally, SeX Factor [ 34] includes a game in which the user moves across a game board by choosing and correctly answering an HIV/STD quiz question. Users who successfully cross the game board win a free chlamydia home test kit.

App Ratings

Customer ratings and number of app downloads roughly measure an app's acceptability and popularity. More than half (38/69, 55%) of the apps were customer rated yielding an average store rating of 3.7 out of 5 stars. In general, apps were infrequently downloaded (median 100-500 downloads) with only 11 apps exceeding 1000 downloads. Most (46/69, 67%) of the apps were free; the remainder ranged in price from US $0.99 to $9.99. Among apps that charged a fee, those charging over the median of US $0.99 all received fewer than 100 downloads.

The most popular app based on reported number of downloads was Sex Facts [ 35] that had a star rating of 4.0 and downloads between 500,000 and 1,000,000. This app featured a revolving index of sex-related factoids that could be shared with friends via social network sites (eg, Facebook and Twitter) or email. The included HIV/STD facts on this app were not comprehensive and it was not clear how the specific facts were chosen. For example, only 2 facts referred to HIV transmission/acquisition: "HIV is transmitted through the blood" and "According to the Centers for Disease Control and Prevention (CDC), using a condom every time you have sex can lower your risk of HIV infection." Regarding other sexually transmitted diseases, only human papillomavirus (HPV) was mentioned by name in a factoid that stated that HPV "is the world's most common sexually transmitted infection." Although sexuality was listed in the app's description, the overwhelming majority of facts centered on heterosexuality.

Apps Tailored for Specific Populations

A small proportion of apps appeared to include or target specific populations. Approximately one-quarter (13/55, 24%) of apps were designed for a particular geographic area: England (Big Night Out [ 36], It's Your Shout [ 33], Protection-Sex [ 37], Safer Sex [ 38], Sex Guide [ 39]); China/Singapore (Action For AIDS [ 22], My First Time [ 40]), Denmark (Safesex Guide [ 41]); Ireland (Sexual Health Guide [ 27]); Birmingham, Alabama (Birmingham AIDS Outreach [ 42]); Massachusetts (MASTDinfo [ 43]), New York City (NYC Condom Finder [ 44]); Philadelphia, Pennsylvania (iCondom Philly [ 45]); and San Francisco, California (STD411 [ 24]).

A minority of apps (n=10) were inclusive of information about anal sex or featured information for lesbian, gay, bisexual, or transgender (LGBT) persons. These apps included Birmingham AIDS Outreach [ 42], HIV RISK Calculator [ 46], MASTDinfo [ 43], Safe Sex Tips [ 26], Safer Sex [ 38], Sex Detective [ 47], Sex Guide [ 39], Sexual Health Guide [ 27], STD Risk Calculator Lite [ 48], and STD411 [ 24]. Of these, the only tailored apps were MASTDinfo [ 43], which provided information and testing center locations for men who have sex with men (MSM) in Massachusetts, and STD411 [ 24] that provided information and resources for gay, bisexual, and transgender men in San Francisco ().

Nine apps included pictures, text, or videos with persons from racial or ethnic minority groups: AfterSex [ 49], AIDSinfo HIV/AIDS Glossary [ 50], Birmingham AIDS Outreach [ 42], HIV and Your Heart [ 30], Kenny Condom [ 51], Men's Sexual Health [ 52], Pos or Not [ 23], STDiQ [ 25], and TKNO [ 53]. Among these, STDiQ [ 25] was tailored for black and Latino men and women. This app features videos from the Safe in the City campaign ( and ), a theory-based intervention found to reduce incident STD cases [ 54]. Kenny Condom [ 51] is based on a previously developed character and Web initiative tailored toward young African American men and "the hip-hop generation."

Discussion

In our review of Apple iTunes and Android Google Play apps, we found 55 unique apps that fostered HIV/STD prevention and care services. In general, these apps were underutilized and only a few apps received high user ratings. Apps primarily focused on providing disease information, and only 6 apps covered all 4 areas of a basic prevention strategy (knowledge raising, risk reduction, condom promotion, and testing). However, we also found examples of apps that used a tailored and/or interactive approach and apps that illustrated the potential for integrating mobile phone technologies into more comprehensive HIV prevention and care.

There are a number of benefits to using mobile phone apps to provide HIV/STD prevention and care services. Apps offer convenience to both the user and the developer because they provide a flexible way to reach a large audience at an affordable cost. Apps can provide individually tailored and interactive HIV/STD prevention interventions that are constantly accessible and allow the user to seek information while maintaining anonymity. Intervention customization and interactivity have been found to be important for effectiveness in behavior change interventions, including those that are technology based [ 55]. Well-designed mobile phone apps accommodate self-tailoring and personalization by allowing the user to choose which app features they wish to use and selecting messages and notifications they wish to receive through the app, email, or SMS. Unlike SMS and automated voice messages that are sent at specific times, the interactive functions of mobile phone apps are constantly available, allowing users to engage with the app at their convenience.

The HIV/STD phone apps also capitalize on delivering an intervention in a way that is familiar, desirable, and discrete to at-risk populations including youth, MSM, and racial and ethnic minorities [ 56]. Within the United States, the black population represents the most active and fastest growing user group of the mobile Internet [ 57]. And MSM have also been shown to have greater access to and use of cell phone technologies compared to heterosexual populations [ 58], increasing the likelihood of delivering highly engaging prevention messages to this hard-to-reach population, including those who are not reached through in-person or group interventions [ 59].

Unfortunately, many of the very features that make apps such a promising platform for delivering HIV/STD prevention and care services appear to be lacking in the currently available HIV/STD-related apps. Based on our review, as of August 1, 2012, less than 0.3% of the more than 29,000 health-related apps available for iPhone and Android consumers [ 18, 19] were dedicated to HIV/STD information and prevention. Furthermore, existing HIV/STD apps have generally failed to attract the attention and positive reviews of target audiences. This is likely because of a combination of inadequate app promotion and failure to create engaging, attractive apps. How can we do better?

Many of the core elements of social marketing offer an appropriate guiding framework for developing health interventions with mobile technologies [ 60, 61]. Limited downloads and low user ratings indicate that most HIV/STD apps have not achieved the ideal social marketing mix of "product, price, place, and promotion." Social marketing principles, such as audience analysis and segmentation, and the use of formative research during product design would ensure that apps are developed with the user in mind [ 62]. For example, in focus groups we have held with young, black MSM in North Carolina, more men owned mobile phones that operated on an Android OS rather than an iOS platform (Muessig et al, unpublished). Thus, although a larger overall number of users in this age bracket may own iPhones, those who face a disproportionately high risk of HIV infection (young, black, and MSM) [ 63] might be better reached with an Android-supported app. Similarly, HIV/STD app developers need detailed information about who does and does not have access to these technologies. For example, general consumer research shows disparities in smartphone ownership by income. However, in our focus groups among young, black MSM, we found consistent smartphone ownership even among men with annual income under US $12,000 (Muessig et al, unpublished).

Relatedly, apps should include content and form that resonates with specific populations and that they want or need to use [ 64]. For example, an app that features a 3-paragraph narrative description about HIV clinic visits could be transformed into an interactive 10-point checklist of questions and topics that a patient could use to prepare for the appointment. This altered format engages the user and could be designed to allow users to self-tailor by entering their own checklist items.

Social marketing approaches also incorporate systems for process evaluation and iterative feedback. Ideally, app developers should be collecting target audience input throughout the development and usability testing process, as well as regularly updating their apps based on user feedback and advances in the HIV/STD field. Updates are especially critical for apps that provide information about rapidly evolving topics, such as testing locations, support services, and available HIV medications. As with any other intervention, these apps should be evaluated for measures of effectiveness. This requires identifying outcome goals and measurement metrics at the start of app design and development (eg, increased medication adherence, increased condom use, increased HIV testing frequency). Successful technology interventions such as these will require more involved collaborations between developers and public health HIV/STD researchers and practitioners [ 65].

Market research shows that smartphone owners regularly remove unused apps from their phones, thus design and content must be sufficiently useful and entertaining for consumers to keep them on their phones [ 66]. One analysis of app retention (as defined by the use of an app in the past 7 days) found a global retention rate of only 14.8% and US rates at a lower 12% [ 67]. Apps that incorporate more interactive components, such as games, quizzes, and activities, may be able to improve attractiveness and user retention. The categories of "entertainment" and "games" comprise the largest market share of available, active apps (27% to 29%) [ 19, 68] and half of the top 10 most-downloaded apps of 2011 were gaming apps [ 69]. Game features of health interventions (eg, health-related challenges and rewards, ability to "level up," and use of avatars) have been shown to promote and sustain healthy behaviors [ 70- 73]. Thus, building in more interactive and gaming features in HIV/STD apps could improve their attractiveness and chances for successful intervention.

In addition to a need for better tailoring, design, and interaction, there were a number of content areas missing from most apps. First, apps for HIV-positive persons generally lacked psychological and emotional support resources and messages about the prevention of STDs and onward HIV transmission. Second, additional tools are needed to promote HIV medication adherence, support clinical monitoring, and facilitate patient-provider relationships. Active technology tools for self-monitoring have facilitated a variety of health improvement programs from increases in physical activity [ 74] to depression management [ 75]. Interventions using electronic drug monitoring devices suggest that these tools could also provide benefits for HIV-positive persons in improving medication adherence [ 76, 77]. A few of the apps we identified included these types of tools, and assessments are needed to identify optimal design and efficacy. Additional mechanisms should be tested for providing linkage between the user/patient and their health care team. These features could include remote health coaching, symptom and side effect monitoring, and provision of real-time feedback. Third, a stronger emphasis is needed on interpersonal skills in the context of HIV/STD risk. Very few apps modeled condom negotiation, HIV/STD status disclosure, or sexual decision making in the context of relationships (see STDiQ [ 25] and Pos or Not [ 23] for notable exceptions). Finally, there were almost no descriptions of biomedical HIV prevention options, such as earlier initiation of antiretroviral therapy or preexposure and postexposure prophylaxis.

This review has several limitations. Our searches were restricted to the Apple iTunes and Google Play app stores. We selected these phone platforms (iPhone and Android) because they account for over 85% of the global app market [ 78, 79] and, thus, are likely to be representative of the apps available to the majority of smartphone users. However, there may be HIV/STD-related apps available through other platforms that were not captured in our review. In addition, the field of app development is in constant motion with large numbers of new apps being created and other apps being deleted every day. Illustrating the speed of this development, the number of available apps in the 4 leading app stores (Apple iTunes Store, Google Play Store, Windows Phone Store, and Blackberry App World) increased from 989,476 in December 2011 [ 79] to 1,574,645 in September 2012 [ 78]. Importantly, our review was not designed to evaluate the effectiveness of identified apps in achieving positive prevention or treatment outcomes. Furthermore, we were not able to assess the user profiles of those who downloaded these apps. Although a growing body of evidence suggests high acceptability and smartphone ownership across diverse users [ 62, 80], as discussed previously, detailed sociodemographic information (eg, user age, education, socioeconomic class, sexual orientation, race/ethnicity, and native language) should critically inform the tailoring and targeting of HIV/STD prevention and care apps.

Providing HIV/STD prevention and care services through mobile phone apps shows great potential for growth, both in improving the acceptability and adoption of existing apps, and creating new HIV/STD apps. Future HIV/STD app development could be informed by the principles of social marketing to build appropriately tailored, interactive apps. As biomedical advances in antiretroviral treatment are bringing the prevention of onward HIV transmission within our reach, we can use the powerful, widespread technologies offered through mobile phone apps to explore behavioral interventions for risk reduction and close gaps in HIV/STD testing, treatment adherence, and retention in care.

Acknowledgments

The University of North Carolina at Chapel Hill's Libraries provided support for open access publication. Kathryn E Muessig is supported by an NIH institutional training grant (5T32AI007001-35). Lisa Hightow-Weidman and Emily Pike are supported by the NIH (R01 MH093275-01). The views expressed herein do not reflect the official stance of any funding agencies.

Abbreviations

Footnotes

Conflicts of Interest:

Conflicts of Interest: None declared.

References

62. Ramanathan N, Swendeman D, Comulada WS, Estrin D, Rotheram-Borus MJ. Identifying preferences for mobile health applications for self-monitoring and self-management: Focus group findings from HIV-positive persons and young mothers. Int J Med Inform. 2012 Jun 13; doi: 10.1016/j.ijmedinf.2012.05.009. [ PMC free article]

73. Lieberman D. Health Promotion and Interactive Technology: Theoretical Applications and Future Directions. Mahwah, NJ: Lawrence Erlbaum Associates; 1997. Interactive video games for health promotion: Effects on knowledge, self-efficacy, social support,health; pp. 103-120.

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Mobile Phone Applications for the Care and Prevention of HIV and Other Sexually Transmitted Diseases: A Review

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Monitoring Editor: Gunther Eysenbach Reviewed by Elia Gabarron Kathryn E Muessig, PhD, 1 Emily C Pike, BS, 1 Sara LeGrand, PhD, 2 and Lisa B Hightow-Weidman, MD, MPH 1 Mobile phone applications (apps) provide a new platform for delivering tailored human immunodeficiency virus (HIV) and sexually transmitted disease (STD) prevention and care.

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Smartphone app- Methods to improve adherence 

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Smartphone app- Methods to improve adherence 

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- Traditional reminders: These are proactive reminders as it was found that current reminders fail to provide relevant information ( Dayer, Heldenbrand, Anderson, Gubbins and Martin, 2013).
- Providing all the users information on one convenient app that will provide a more streamlined service. Features such as doses can be logged and the app will provide medication information ( dosages, adverse effects and any special requirements etc: storage).

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Lindsey Dayer, PharmD, Assistant Professor, Seth Heldenbrand, PharmD, Assistant Professor, Paul Anderson, graduate student in pharmaceutical evaluation and policy, Paul O. Gubbins, PharmD, Professor, and Bradley C. Martin, PharmD, PhD, Professor of Pharmaceutical Evaluation and Policy

Abstract

Objectives

To provide an overview of medication adherence, discuss the potential for smartphone medication adherence applications (adherence apps) to improve medication nonadherence, evaluate features of adherence apps across operating systems (OSs), and identify future opportunities and barriers facing adherence apps.

Practice description

Medication nonadherence is a common, complex, and costly problem that contributes to poor treatment outcomes and consumes health care resources. Nonadherence is difficult to measure precisely, and interventions to mitigate it have been largely unsuccessful.

Practice innovation

Using smartphone adherence apps represents a novel approach to improving adherence. This readily available technology offers many features that can be designed to help patients and health care providers improve medication-taking behavior.

Main outcome measures

Currently available apps were identified from the three main smartphone OSs (Apple, Android, and Blackberry). In addition, desirable features for adherence apps were identified and ranked by perceived importance to user desirability using a three-point rating system: 1, modest; 2, moderate; or 3, high. The 10 highest-rated apps were installed and subjected to user testing to assess app attributes using a standard medication regimen.

Results

160 adherence apps were identified and ranked. These apps were most prevalent for the Android OS. Adherence apps with advanced functionality were more prevalent on the Apple iPhone OS. Among all apps, MyMedSchedule, MyMeds, and RxmindMe rated the highest because of their basic medication reminder features coupled with their enhanced levels of functionality.

Conclusion

Despite being untested, medication apps represent a possible strategy that pharmacists can recommend to nonadherent patients and incorporate into their practice.

Keywords: Smartphones, nonadherence, applications

Medication adherence

Epidemiology of nonadherence

According to the International Society for Pharmacoeconomics and Outcome Research (ISPOR), adherence is "the extent to which a patient acts in accordance with the prescribed interval, and dose of a dosing regimen." Medication nonadherence can affect patient health adversely, negatively impact a patient's relationship with his/her care provider, skew results of clinical therapy trials, and increase health resource consumption. Medication nonadherence remains a common health care problem. Poor adherence causes approximately 33% to 69% of medication-related hospitalizations and accounts for $100 billion in annual health care costs. Irrespective of disease, medication complexity, or how adherence is measured, the average adherence rate to chronic medication therapy is approximately 50%. Adherence monitoring should be performed routinely to ensure therapeutic efficacy, avoid unnecessary dose and regimen changes, contain health care costs, and in certain cases, prevent resistance to therapy from emerging.

Measurement of adherence

Methods to measure adherence, including patient self-reports, pill counts, refill rates, biological monitoring, and electronic monitoring, have limitations and are only proxy measures. Patient self-reports rely on memory and are prone to inaccuracies and recall bias. Pill counts are unreliable if patients fail to return bottles or dump pills before the count. Biological monitoring (e.g., sampling blood, urine) is either impractical, invasive, or intrusive and does not measure adherence unless the time and dose administered before sampling are verified. Refill rates or electronic monitoring cannot determine whether patients actually take the medication. Although the process of cap removal does not necessarily reflect dose ingestion, medication electronic monitoring systems are useful for calculating adherence rates for dose taking and dose timing and often are viewed as the best method to measure adherence. Nonetheless, despite their limitations, all of these methods are adequate for documenting nonadherence, but in general, only self-report methods can distinguish among the various types of nonadherence described below.

Types of nonadherence

The cause of medication nonadherence varies among patients and is broadly categorized as unintentional or intentional. Unintentional nonadherence involves intending to take a medication as instructed but failing to do so for some reason (e.g., forgetfulness, carelessness). Unintentional nonadherence is influenced by patient characteristics, treatment factors, and patient-provider issues. In contrast, intentional nonadherence involves making a reasoned decision not to take a medication as instructed based on perceptions, feelings, or beliefs. Intentional nonadherence reflects a rational decision-making process by the patient whereby the benefits of treatment are weighed against any adverse effects of the treatment. Broadly characterizing nonadherence may oversimplify the complexities involved with nonadherence, but it is practical and illustrates that mitigating nonadherence requires different interventions.

Behavioral models of adherence

Most medication adherence models are based on several social cognition models, including the health belief model, social cognitive theory, and theory of planned behavior. These models are similar, and all assume that beliefs developed by individuals shape how they interpret information and experiences and ultimately influence their behavior. Accordingly, health behavior (e.g., medication taking) results from rational decisions based on all available information.

Methods to improve medication adherence

Many methods to improve medication adherence have been studied. Most methods attempt to change patient behavior by using reminders, counseling, reinforcement, education, dosage simplification, or a combination of these methods. Generally, adherence interventions are categorized as behavioral, educational, or organizational based on modifying the patient's environment or incentives, providing more information, or lifting barriers associated with medication complexity and communication with care providers.

Traditional reminders

Intuitively, pill reminder systems (e.g., weekly pill boxes, packaged calendars, unit-of-use packaging), are helpful adherence aids, especially when nonadherence is unintentional. Current traditional reminder systems minimally involve the patient in the self-medication process and do not provide them access to their adherence data or other educational information. Although pill reminder systems have been tested and shown to be useful across many medications, these systems are cumbersome for complex regimens and only passively remind patients to take their medication. Electronic systems proactively deliver reminders by telephone, pager, and audiovisual devices but may be impractical for widespread use and more efficacious if combined with alternative behavioral strategies.

Counseling and other behavioral interventions

Most studies on improving adherence involve behavioral interventions. Data suggest that patient education is one of the best methods for improving adherence, especially for those simultaneously managing more than six medications. Depending on the type of nonadherence and patient characteristics, using a combination of tailored interventions such as patient education, patient self-monitoring of specialized care, and stimuli to take medications have the greatest potential for improving adherence.

Medication adherence and mobile devices

Smartphones are Internet-ready multipurpose devices that allow constant access to communication and information and perform many tasks. Most tasks are performed by specialized applications (apps) that consumers can easily download and use to assist them in a variety of functions. Using a smartphone app is a novel approach to improving adherence and patient behavior; it is constantly accessible, involves and educates the patient, and provides a repository for patient- and medication-specific information. A smartphone medication adherence-oriented app (adherence apps) can potentially consolidate all of the user's medication-specific information and thereby provide a more streamlined process to educate the individual about his/her disease or care.

Adherence apps can be downloaded for little to no cost, and their benefits may be realized by anyone taking prescription medications. However, these apps may prove most beneficial for patients with complex medication regimens or for caregivers of others or family members. The growing prevalence of smartphones in the United States and their constant, easy accessibility make adherence apps appealing to many because they cost little and can provide user-specific information.

The number of apps aimed at aiding the user in organizing and taking their medications is increasing across the dominant smartphone platforms. Among the currently marketed adherence apps, features include reminders that can be set for consumption and refills, doses that can be logged, data logs that can be accessed by patients or uploaded to care providers, and medication information (e.g., dosages, adverse effects, toxicities, specialized provider notes), all of which can be immediately accessible with the touch of a finger. In addition, these apps may also include calendar-based alarm reminders with specific dosage or functionality that integrates medication lists with specific drug information or combines pharmacy and primary care contact information or includes prescription drug discount cards. Efforts are under way to integrate smartphones with health-monitoring devices that transmit the output data directly to patients or physicians. Literature on the clinical application of the smartphone and use of apps in areas of health wellness (e.g., weight management) is growing, but empirical analyses of patient use of the smartphones with apps as an aid to facilitate adherence are lacking.

Effectiveness of smartphone adherence apps

Although smartphone apps can potentially improve the effectiveness and reduce the costs of traditional medication adherence interventions, their efficacy is currently untested. Data demonstrate that electronic mobile devices using reminder systems through traditional means of telecommunication, like Short Message Service (SMS) text messaging, improve adherence and behavior and can be useful in measuring adherence in the short term. Investigators determined that sending photographs of medication capsules through cellular phones before ingestion provided more accurate time measures of adherence. One study found that teenagers with asthma who used a specialized system to create and schedule personal text message reminders gave the system high ratings for acceptability, ease of use, and usefulness; however, their asthma control was similar to baseline. In a study using a comprehensive, Web-based education system with Internet and cellular phone access to help control blood glucose levels in patients with diabetes, the frequency of accessing the eMOD (electronic Management of Diabetes) system through a cellular phone was significantly related to the change in glycosylated hemoglobin levels. Although a systematic review of Internet-based adherence interventions found promising results, it also found that the 13 studies lacked quality measurements of adherence. Various studies of the use of smartphones in the clinical setting have been performed, but studies empirically testing smartphone apps to improve adherence are lacking.

Currently available mobile app adherence technologies

Currently, a resource does not exist that compares the features of available apps. To develop such a resource, we searched the available medication adherence-oriented apps, provider websites, and app sources for Apple iTunes, Android Marketplace, and BlackBerry App World during August and September of 2012, which reflects a snapshot of the app market space for that time period. Search terms included adherence, compliance, dose, drug, med(s), medication(s), remind, reminder, Rx, take, therapy, treat, treatment. Apps also were identified using the alphabetical browse feature at each of the three sources. App descriptions and available screenshots were analyzed for content and app functionality.

To be included in our analysis, apps had to be described in English, medication related, capable of generating medication reminders, and available for the Apple (iPhone operating system [iOS]), Android, and/or Black- Berry operating systems (OSs). Apps were excluded if they were designed specifically for one medication type or a single disease. Lastly, those lacking a general description of functionality also were excluded.

To identify the apps that might have the most utility for patients that could be recommended by pharmacy practitioners, the authors developed a list of desirable attributes of these apps by consensus of all of the authors to evaluate them for comparison. These attributes are described in , and whether the app possessed each attribute was assessed based on each app's features described on their website or their respective product listing on their app source (e.g., iTunes). The relative desirability or usefulness of these features then were rated by the study authors using a three-point rating system (1, modest; 2, moderate; or 3, high) based on the perceived importance of each feature or characteristic (). This rating system was developed based on author consensus before evaluating the individual apps and only reflects the provider/researcher perspectives of the authors and does not directly assess the desirability of these features by patients. This rating system was used to score and ultimately rank the apps identified based on features claimed by manufacturers. After rating all of the apps, the 10 with the highest composite ratings were selected, then two of the authors installed and tested the apps and rated them by directly assessing the feature available against the claimed functionality. To test the apps on their corresponding OSs, a standardized medication regimen consisting of four medications was entered: lisinopril 10 mg daily, naproxen 500 mg twice daily, Neurontin 300 mg three times daily, and a prednisone 20-mg tapering regimen. Apps were evaluated for each manufacturer claim that met the authors' scoring criteria, functionality of the reminder system, and ability to process reminders from the test medication regimen. Medication reminders were evaluated for each app for a period of at least 24 hours.

Table 1

Our search included 160 app descriptions in the three online marketplaces, yielding 147 unique apps after incorporating multiplatform functionality. There were 13 multiplatform apps, with 12 apps available on both iOS and Android platforms and only one app available for use on both the Android and Blackberry OSs. Because a portion of the apps are available across multiple platforms and the descriptions and feature may vary by platform, we evaluated 160 unique, platform-specific apps. summarizes the frequency of the medication app features or characteristics by OS. We found that the Android OS had the most medication adherence apps available, followed by iOS and Blackberry. Although the ability to track missed doses and export data for provider analysis are important tools to assess adherence, these features were available on only 29.4% and 24.4% of the apps evaluated, respectively. Not surprisingly, notable differences existed among the OS platforms. More multilingual apps are available for the iOS (21.3%) compared with the Android (10.7%) and BlackBerry (0%) OSs. In addition, advanced features, including the ability to export medication regimen or medication-taking behavior data from the device or the ability to manage multiple patient profiles are more prevalent on apps using the iOS platform (36.1% and 32.8%, respectively) compared with the Android (19% and 15.5%, respectively) or Blackberry (6.7% and 20%, respectively) OSs. Lastly, Blackberry OS apps were the most expensive compared with apps using other OSs.

Table 2

A total of 10 apps with the highest number of desirable features claimed by their developers were installed on their respective platforms for testing and evaluation of actual functionality. Each app that was available on multiple platforms (i.e., iOS, Android OS) was tested and evaluated on each available OS. Of the 10 apps that were installed and subjected to direct testing, 6 met or exceeded manufacturer claims listed on marketplace websites. The features available for these 10 apps are described in . Overall, the majority of apps were intuitive, easy to use, met developer claims, and provided satisfactory medication reminders. Only one app, MediMemory, stood out as being more cumbersome and difficult to set up initially. The reminders generated by most of the apps resembled a SMS text message or a "push notification" style alert. Most apps provide a generic initial reminder, such as "you have a medication to take," at which time you can open the app to see what medication is due. Some apps, including Med Agenda, Dosecast, and MedSimple display the drug, dose, and/or strength of the medication you are to take on your homescreen within the reminder itself, which may be a more effective reminder for patients who take multiple medications but also may pose patient privacy concerns. Apps that track doses taken or missed, including Med Agenda, RxmindMe, Dosecast, Med-sIQ, PillManager, and MediMemory, require a box to be checked to indicate that a dose has been taken or skipped with each reminder. Apps lacking dose-tracking capabilities generally provide simple alert-type reminders.

Although the functionality of most apps matched the app descriptions, three apps possessed more features than described in their respective app description, resulting in a higher overall rating. MedsIQ could not be opened and used following installation on a variety of Android devices and was rated as a zero; we would not recommend use of this app. The rank of another app, MediMemory, decreased when it was unable to process complex medication instructions such as stop dates or medication tapers. TRxC, a multiplatform app, did not possess several of the claimed features upon testing, and its companion website could only be used if the patient's provider entered an agreement with the app developer. PillManager's scoring was reduced when multilingual functionality could not be found on the Android app.

can serve as a starting point for pharmacists to identify apps to possibly recommend to patients or use in their practice. Many of these apps, if used consistently, could be an asset to patients who struggle with their medication regimens. From a provider perspective, apps with functionality beyond a simple medication reminder system may offer significant advantages. Providers might find value in features such as the ability to input patients' regimens and then "pushing" them to patients' devices; the ability to process complex medication-taking instructions; multiple-platform functionality; the use of a cloud back-up system; the ability to export data, including administered and missed doses; and the incorporation of a medication database to assist in accurate data entry into the device.

Providers caring for patients taking complex medication regimens may value having the ability to input patients' prescribed regimens and then pushing them directly to patients' devices. This feature removes the data entry burden from the patient and reduces the possibility of patient-generated medication regimen mistakes. Websites like www.medactionplan.com, the companion site for the app MyMedSchedule (), offer regimen-building options that are useful for patients in specialty areas that often carry a high medication burden (e.g., organ transplant, human immunodeficiency virus [HIV], hematology, oncology). Health professionals can enter simple or complex medication regimens using extensive medications databases that can be pushed to patients' mobile device with reminders enabled. Regimens also are stored on a Health Insurance Portability and Accountability Act (HIPAA)-compliant cloud server that enables patient profiles to be retrieved and modified with any new instructions and then resent to patients' devices on subsequent encounters.

Other apps feature companion websites for patient use. MyMeds () and its companion website www.my-meds.com enable patients to enter their regimens online (subscription fee of $5.99/year) rather than doing so only via their device. This feature offers the convenience of HIPAA-compliant cloud data storage that can be retrieved and modified from any Web-accessible computer and pushed back to patients' mobile devices.

RxmindMe (), MyMedSchedule, and MyMeds feature medication databases that enable patients or providers to save time and improve accuracy when entering regimens. However, only RxmindMe and MyMeds have the capability to track taken and missed doses and export that data to health professionals for review. When the patient properly uses the app, this feature can provide information to help health care providers assess medication adherence.

Simple medication reminder systems may be suitable for most patients needing assistance with their regimens, and all of the apps evaluated fit this criterion. However, health care providers are likely to appreciate a higher level of functionality and evaluative capabilities provided by MyMedSchedule, MyMeds, and RxmindMe. The basic medication reminder features coupled with their enhanced levels of functionality led to their being ranked as the top three apps.

Implications for pharmacy practice and future directions

There has been a proliferation of consumer- rather than clinician-oriented adherence apps. We evaluated more than 160 apps and suspect that many more will be available in the foreseeable future, until the market consolidates to the apps that garner a substantial market share and support a viable business model. As previously stated, currently no evidence exists regarding the efficacy or effectiveness of apps at actually improving adherence or clinically relevant outcomes. This lack of data underscores a critical need for research in this field. However, insights can be gained from data regarding the effectiveness of SMS text messaging, which uses similar prompts as those provided by mobile apps. Three of four studies demonstrate that SMS text messaging improved adherence in several chronic conditions. Given that many apps possess greater functionality that includes customizable audio and visual prompts capable of providing more robust reminders, the efficacy of apps may be equal to or greater than SMS text messaging.

Adherence apps can only be used by individuals who have access to a smartphone, which includes 55% of the U.S. adult population. Smartphone ownership is more likely for those with higher incomes and of younger age; however, between 14% and 42% of people 65 years or older own smartphones depending on income, suggesting that a sizable proportion of the older population has access to these devices. Clearly, these evolving technologies will not be available to all patients in a pharmacist's practice but do represent a viable alternative for a large and growing proportion of the population. Another key limitation of the current market is that adherence apps are targeted primarily to consumers rather than health care professionals (e.g., pharmacists) to assist patients with adherence. Nearly all adherence apps require patients to enter and manage their prescription data, and most require manual data entry on the smartphone device by patients. Of the apps evaluated in this report, only five had a drug database that enabled autocompletion and/or allowed users to select prescription products. Further evidence that marketed adherence apps are more oriented toward consumers is that only three apps had a HIPAA policy statement, which would be an essential feature for providers to consider. Despite these limitations, adherence apps represent a low-cost strategy that could be incorporated into a variety of pharmacy services, including medication reconciliation and discharge planning in institutional settings and medication therapy management or other services in the community, ambulatory, or other outpatient practice settings. Some community chains already have incorporated adherence features into their brand apps; however, the extent to which these are being incorporated into pharmacists' practices in these settings is unknown.

Interconnectivity of adherence apps

Currently, very few marketed adherence apps are interconnected with other information systems. Of the apps evaluated in this report, five offer cloud storage of prescription data, of which only one has a companion website. However, none of the apps evaluated is fully integrated with patient record systems (e.g., community pharmacy prescription databases, electronic medical records). Therefore, interoperability with existing prescription and medical records systems represents a vital frontier for future app development. For example, interfacing adherence apps with pharmacy prescription records could enable pharmacists to easily push patients' drug regimens to smartphone apps, allowing seamless transmission of reminders to patients. More importantly, pharmacists and patients could collaborate to customize reminders for regimens where adherence has proven to be challenging. This interoperability would shift the current orientation of adherence apps to a more provider-focused technology and thereby provide pharmacists a potentially valuable tool to improve medication adherence.

In addition to connectivity to medical records systems, smartphone apps can be interfaced or synced to other devices with adherence capabilities. On the forefront of these technologies is Proteus Digital Health Feedback System (the Proteus system; www.proteusbiomed.com/technology), whereby solid oral dosage forms are combined with ingestible sensors that record basic physiologic parameters after ingestion and transmit the information to a dermal sensor or patch that can sync with smartphone devices. This unique system can record actual ingestion of individual doses and the precise timing of ingestion-the "holy grail" of adherence measurement. Adherence apps working in tandem with such a system could send customized reminders only when doses are actually missed. Although such an integrated system has obvious applicability to the clinical trial research setting, its cost and the inconvenience of wearing a monitoring patch likely limit its utility in routine clinical practice to therapies for which adherence is especially critical (e.g., management in tuberculosis and HIV infections). Several technologies for diabetes self- and automated monitoring have been developed and can be synced with smartphone devices. These integrated systems may hold similar promise to monitor and improve adherence in diabetes. Electronic pill boxes that are equipped to monitor box openings, wirelessly transmit a signal to servers when a scheduled opening is missed, and then send SMS text messages reminders have been shown to improve adherence.

Tailoring the reminders

Currently, most adherence apps use a simple reminder and are primarily directed to mitigate unintentional nonadherence. These apps are a component of a multipurpose device; therefore, unlike previous reminder systems, patients do not have to be near or carry a separate device that enhances fidelity to the "reminder" device. However, the content of the adherence app messaging is at the nascent stage of development. Although the content of the reminders for the apps evaluated in this report was not formally assessed, few if any appeared to be tailored to patients based on proven theoretical behavioral models. A Cochrane review of randomized trials of adherence interventions showed that less than one-half improve both long-term adherence and clinical outcomes and that the most effective involved complex combinations and multiple strategies to improve adherence. Therefore, adherence apps will likely need to be incorporated into a multimodal strategy to result in sustained improvements in adherence. Because reminders primarily focus on unintentional nonadherence, identifying the reasons for nonadherence and developing a scale that assesses unintentional nonadherence would be a useful starting point toward effectively deploying app-based reminders. Tailoring messages to specific patient needs based on previous adherence behavior and incorporating theoretical behavioral models represent an area of future improvement for app developers. Behavioral models such as the transtheoretical model stages of change or motivational interviewing could be used to develop tailored messages with the potential to decrease unintentional and intentional nonadherence. Studies using smartphones combined with tailored interventions to improve dietary intake of fruits and vegetables are under way, and similar strategies should be tested to improve adherence. The potential for patient response to decrease with repeated reminders delivered by a smartphone (i.e., habituation) is a challenge to improving adherence to chronic therapy. Currently, whether and to what extent habituation will occur is unknown. Therefore, efforts to develop and study the impact of content that is constantly refreshed based on patient attributes, including feedback of their current adherence level, are necessary to determine the impact of these strategies on long-term adherence.

Prescription for apps

During the next decade, providers and payers may be looking to the app market to improve patient care and outcomes, as apps may be "medically prescribed" and paid for by health payers. For example, hospital systems in the New York City area are allowing physicians to prescribe health-oriented apps, and in the foreseeable future, payers may begin covering a diabetes care app that has been proven effective in mitigating nonadherence in a clinical trial setting. Medically prescribed and reimbursed apps will provide the financial incentive for app developers to build products, including adherence apps, that generate empirical evidence of improved patient outcomes. The Food and Drug Administration (FDA) has developed draft guidelines to regulate certain mobile apps that they are defining as "medical mobile apps," and Congress recently cleared the pathway allowing FDA to regulate mobile devices. Although apps that are designated as medical mobile apps or are part of FDA-regulated devices have the most clear guidance, the regulatory framework for stand-alone apps such as adherence apps is less clear and whether payers will consider payment for unregulated apps is unknown.

Conclusion

Despite decades of research, medication nonadherence still represents a fundamental health care challenge. Adherence apps are inexpensive, scalable, accessible to anyone with smartphones, and do not require separate devices or packaging, which allows them to be easily implemented. Despite not being tested in trial settings, they could be considered a possible strategy for pharmacists to recommend to nonadherent patients and to incorporate into their practice. Although none of the evaluated apps possess every desirable attribute, three apps were identified that offer the widest range of features and would be the most appropriate to recommend to patients currently. Research is needed to determine whether and how effectively apps can improve adherence and therapeutic outcomes in acute and chronic conditions.

​

Acknowledgments

Funding: Dr. Martin's work was partly supported by the Translational Research Institute, University of Arkansas for Medical Sciences (grant 1UL1RR029884).

Footnotes

Disclosure: The authors declare no conflicts of interest or financial interests in any product or service mentioned in this article, including grants, employment, gifts, stock holdings, or honoraria.

References

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19. Ajzen I. The theory of planned behavior. Organ Behav Hum Decis Process. 1991;50:179-211.

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Smartphone medication adherence apps: Potential benefits to patients and providers

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Lindsey Dayer, PharmD, Assistant Professor, Seth Heldenbrand, PharmD, Assistant Professor, Paul Anderson, graduate student in pharmaceutical evaluation and policy, Paul O. Gubbins, PharmD, Professor, and Bradley C.

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" I left the clinic and heard the diagnosis and I almost stepped in front of a bus" - Anthony's initial reaction.

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Following advances in the medical field and dealing with discrimination and unsympathetic nature of health care professionals (Green, 1997). A groundbreaking smartphone accessory can also be integrated within the app if the person feels uncomfortable about seeing a doctor and getting tested. The accessory attaches onto the individuals smartphone and then acts as a real lab-based blood test. Detect HIV and syphilis within three minutes. The test reported a sensitivity rating of 92- 100% and was praised both by patients and healthcare professionals. Patients were impressed with the ease of the app and also the interpersonal benefits of testing when convenient.

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News: Columbia Engineering researchers have developed a smartphone accessory that can simultaneously detect HIV and syphilis within minutes.

A team led by professor Samuel K Sia, associate professor of biomedical engineering at Columbia University's engineering school, designed the low-cost smartphone add-on, which has already been tested by healthcare workers in Rwanda.

The device emulates an enzyme-linked immunosorbent assay, or ELISA - a blood test usually carried out in a lab - using the phone's audio jack as a power source.

An app prompts the user to enter a patient ID and then displays instructions to guide them through the process.

Cocoon-like suit helps protect against Ebola by peeling away to minimise contact

Users first disinfect a finger and obtain a finger-prick of blood for testing. This is placed into a plastic collector and then inserted into a special chip.

A disposable cassette containing the chip with the blood sample is then inserted into the dongle. Pressing a bulb activates the testing process, and 15 minutes later the results are displayed on-screen.

The disposable cassettes contain reagents, a substance which normally contains an antibody that will stick to a protein in a blood sample - in this case an HIV or syphillis viral protein.

When mixed with the blood, the reagent creates a chemical reaction that will make the substance change colour if the viral proteins are present. An enzyme is included to help speed up this process. Any change is then detected by shining light on the substance and measuring how much is absorbed. The results of this indicate the presence of the viral protein.

In standard equipment, this mixing is achieved used an electrically-powered pump. In the dongle, this has been replaced with a "one-push vacuum" - a soft plastic button that can be compressed and released to create negative pressure in the testing chamber.

According to the team, the dongle, which can also be connected to a computer, matches the quality of a full laboratory test.

"It performs a triplexed immunoassay not currently available in a single test format: HIV antibody, treponemal-specific antibody for syphilis, and non-treponemal antibody for active syphilis infection," explained a statement from Columbia Engineering.

"The team developed the dongle to be small and light enough to fit into one hand, and to run assays on disposable plastic cassettes with pre-loaded reagents, where disease-specific zones provided an objective read-out."

According to Sia, the dongle could have a manufacturing cost of $34, compared to the $18,450 cost for equipment typically used for these tests.

Although many areas do not have reliable access to electricity, there are now more than 7 billion mobile devices in the world. This led the team to focus on designing a device that could be powered by just a smartphone.

The dongle plugs into the audiojack rather than the phone's power dock; connecting cables for audio equipment have been standardised around the world, so this allows the device to be virtually universal.

"Our dongle presents new capabilities for a broad range of users, from health care providers to consumers," explained professor Samuel K Sia. "By increasing detection of syphilis infections, we might be able to reduce deaths by 10-fold."

"And for large-scale screening where the dongle's high sensitivity with few false negatives is critical, we might be able to scale up HIV testing at the community level with immediate antiretroviral therapy that could nearly stop HIV transmissions and approach elimination of this devastating disease," he said.

During field testing in Rwanda, care workers were given just 30 minutes of training. According to the researchers, patients responded well and said they would recommend the device to others.

Sia collaborated with researchers from Columbia's Mailman School of Public Health; the Institute of HIV Disease Prevention and Control, Rwanda Biomedical Center; Department of Pathology and Cell Biology, Columbia University Medical Center; Centers for Disease Control and Prevention-Laboratory Reference and Research Branch, Atlanta; and OPKO Diagnostics.

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Smartphone-powered dongle tests for HIV in 15 minutes

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News: Columbia Engineering researchers have developed a smartphone accessory that can simultaneously detect HIV and syphilis within minutes. A team led by professor Samuel K Sia, associate professor of biomedical engineering at Columbia University's engineering school, designed the low-cost smartphone add-on, which has already been tested by healthcare workers in Rwanda.

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The next step in medical advancement. Table that lists $202 million is spent on digital medical services in 2016. These are specifically designed to cure/mitigate/ treat/ prevent a specific condition.

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In the latest movie from DC Comics Extended Universe Justice League, we finally get to meet one of the members of the superhero squad - Cyborg. Both in the original comics and in the new film, Victor Stone's mind and body have been advanced against his will to create a better version of a human. By the comic book classic formula, Victor has to learn to control these new powers and overcome the feeling of being a threat to humanity.

Neil Harbisson is a cyborg too, only in real life. His "power" is much more poetic and definitely less resented by its carrier - he can hear colors. An antenna implanted in his skull allows Neil to receive audio signals that he can interpret into colors. As a colorblind person, Neil's natural abilities have been extended thanks to this technology. Now Neil creates art aimed at expanding human senses - he produces paintings and piano concerts to help people see how he perceives the world with his newfound sense.

Neil's modification of his natural senses albeit unconventional is not that farfetched for every other human living now. How? Technology has inserted itself into our lives to the extent to which we delegate some of our functions to it. We use it to store our memories, we rely on it for calculations and information input, we even use it to bend space and time by bringing other continents closer, by making our voices travel miles and reaching people across oceans. Even analogue tools like eyeglasses have been enhancing people's vision for more than 700 years. A digital hearing aid can help 28.8 million American adults to once again experience sound. Prosthetic limbs will soon allow amputees to receive sensory feedback, meaning they will be able to feel the touch.

But what do you do when your desire to enhance your physical abilities isn't affected by your disabilities? Artist and a co-founder of the Cyborg Foundation, Moon Ribas, has a sensor implanted in her elbow that allows her to feel seismic activity all over the world through vibrations. The sensor receives this data online, through an iPhone app, locating earthquakes of different intensity, which Ribas translates into movement.

Harbisson and Ribas call themselves cyborgs. As a concept, cybernetics studies the act of interaction, control, and organization of systems of any kind, be it human, animal, or AI. Enhancing and transforming human preexisting abilities falls under the term transhumanism - the movement that studies the benefits, opportunities, and limitations of enhancing ourselves with the help of technology.

Not everyone, however, finds such possibilities appealing. Science fiction likes to explore these themes in a most morbid way, showing us the decay of humanity, in which human bodies will become hackable like computers. This representation of the human enhancement movement along with the supposed threat it poses to traditional values creates an inaccurate vision in the minds of many.

What if we lose connection with our humaneness? Should we play God and go beyond our natural abilities? What are the societal changes that this progression imposes? Are we ready to see RoboCops patrolling our streets?

The argument against human augmentation

As Elon Musk and Nick Bostrom are raising awareness about the dangers of artificial intelligence, the opponents of human augmentation fear the decay of humanity due to our fusion with technology.

Even before Google Glass hit the stores in 2014, critics concerned about the loss of privacy joining with those concerned with distinguishing digital from human. These leitmotifs are another science fiction exploration, showing us as two-legged computers ripe for hacking.

But is it reasonable to be worried about transhumanism?

Privacy and security

The stop-the-cyborgs campaign that anticipated before the launch of Google Glass was led by the idea that anyone wearing the device would be able to record their surroundings without others knowing. The device was quickly banned at some restaurants, bars, and movie theaters, creating an unspoken social warning: Take it off if you don't want to be creepy.

In 2015, engineer Seth Wahle demonstrated how easy it is to manipulate smartphones or security systems with the use of the almost undetectable NFC chip in his palm.

NFC/RFID chips are usually installed between an index finger and a thumb
Source: BioTeq

The problem with Google Glass and other interfering technology could be solved by creating regulations and policies that users or manufacturers would have to obey. Like every cellphone shipped to Japan is required to have a non-removable shutter sound, there's a way to ensure that such body enhancements can't be used against another person's will. And it's sensible to create these regulations before another questionable technology panics the masses.

Dehumanization

The fear that people will eventually turn into emotionless machines is supported by the media that likes to humanize artificial intelligence and strip cyborgs of empathy and morality. But is it realistic?

We can argue about what it means to be a human. One would say that organic body parts make you a human, but are the people with artificial organs and limbs less human than anyone else? Medical bionics are actively used for patients on waiting lists for human transplants. The artificial organ market is expected to grow by 9 percent each year. They will soon be mass produced and help eliminate waiting lists altogether. How about a brain? We can't yet construct a machine simulating all the complicated processes happening inside our minds though the work is ongoing. Some might argue that changing anything about our bodies or minds is unnatural, but the definition of what is natural is evolving as well.

A recent survey uncovered the correlation between religion and a willingness to accept digital body enhancements. The more religious the person is, the less compelling and ethical they find the idea of transhumanism. However, this thinking doesn't represent all religions. Take Christian Transhumanist Association, for instance. One thing is clear - there's no absolute right or wrong regarding these issues.

Inequality

"Some would express fear that emerging augmentations would create an arms race, that threatens to leave behind those who choose not to be augmented," says transhumanist writer Gennady Stolyarov. "But this assumes everyone will seek to compete with everyone else."

There's an obvious concern that the opportunities to empower ourselves will be initially available only to the privileged, thus adding to the long list of characteristics by which we are already dividing ourselves as human beings. As technology won't be accessible to everyone at the same time, there will inevitably be those who have more information, more power, more cognitive abilities.

The double amputee runner Oscar Pistorius was prohibited from participating in the Olympics in 2008 along with able-bodied athletes due to his greater than 30 percent mechanical advantage. Similar concerns may arise soon for chess and go players who can use deep learning algorithms to win competitions.

However, the technological advancements don't usually come in single tsunami waves that smash everything in their way. The transition will most likely happen gradually, allowing everyone to grab a piece of this transhumanist pie at their own pace. Some will gladly replace one eye with high-quality connected cameras. Others will feel more comfortable wearing magnetic bands around their heads to improve productivity. Just like with smartphone adoption in the US, it will grow steadily.
Smartphone adoption in the US has grown from 4 percent of entire mobile market in 2007 to 54.9 percent only five years later
Source: comScore
It's fair to predict that transhumanist technology will be adopted at a similar pace with the same pervasive result ten years later.

But exactly what technology are we talking about? The transhumanist ideology doesn't just entail enabling people with telepathic powers or having a flash drive implanted in your finger. It also revolves around the idea of reprogramming diseases, improving our sight in the dark, or stimulating neural activity. What technology and tools do we already have and what does it take to merge with machines for good?

Biohacking 101

In a recent study, the consulting and research firm Frost & Sullivan defined three types of transhumanism: evolving body, thought, and behavior. Let's talk about the possibilities of human enhancement in those same ways.

Body enhancement

Regular contact lenses, smart watches, and mind-controlled prosthetics are not the only examples of how humans can evolve and enhance their physical properties. Body hacking can be roughly divided into the following categories.

Wearables. Fitness trackers, health monitors, even smart clothes connected to your phone are the wearables meant to augment the way people experience the world.
Top investment categories in digital health
Source: Rock Health report
The most widely developed applications of wearable technology are in healthcare. They're used to monitor and record health data allowing for faster diagnosing and prompt reaction to disturbances. For example, a wearable patch Fever Scout allows you to monitor a person's temperature in real time via an app. The Go2Sleep ring that will become available in May 2018 monitors your heart rate, pulse, and oxygen levels as an alternative to expensive and complex in-clinic testing. According to a Rock Health report, wearables attract the third-highest amount of investments in all digital health, after big data and genomics.

Besides healthcare, wearable technology has potential in manufacturing as well. North Star BlueScope Steel along with IBM developed smart helmets and wristbands that monitor each worker's individual metrics to safely guide them away from hazardous areas and notify them about unsafe conditions. The agricultural equipment manufacturer John Deere uses VR headsets to help reviewers determine the potential dangers that go into assembling a product.

Among other use cases you can find payments (implemented on Apple Watch and Samsung Gear among others), sports equipment (see smart glasses for cyclists by Solos), insurance, security, planning, and navigation.

Implants. Kevin Warwick is one of the first self-proclaimed cyborgs. Back in 1998, he got a chip implanted in his left arm to automatically access the doors and computers in his laboratory. The radio frequency identification (RFID) technology in his implant is the same technology used for security cards and pet implants, which easily track pets or activate pet doors in our homes.

Today the number of people implanting similar chips is growing. Dangerous Things, a biohacking supplier, provides hardware, tools, and other implanting equipment for conducting safe and successful procedures. Their products range from NFC (near field communication) chips for data transferring to biomagnets for lifting small metallic objects by touch.

Health risks of such implanting procedures have not been entirely studied. However, proponents argue that they are no more dangerous than getting a piercing or a tattoo. The broad potential of these applications has not yet been put into action. For instance, to be able to make payments with the tap of a finger, you first need permission from a bank and a payment gateway system. But, with growing demand, it's fair to expect gradual adoption of implants.

Reprogramming cells. Changing an organism's DNA to cure diseases and inhibit aging has been one of the most ambitious initiatives of modern science. And it's no longer unrealistic. The most recent genome editing method called CRISPR-Cas9 has already cured two girls of leukemia. The method's simplicity and versatility is promising to deliver impressive results in treating viruses and even passing the improved genomes to future generations.

However, due to ethical concerns, the wide adoption of the technology is questionable. Besides treating HIV and manufacturing revolutionary drugs, CRISPR may improve the general intelligence of an embryo or even design a human with desired features. Such prospects send some alarming signals from moral, religious, and legal standpoints and, therefore, the methodology first must to be studied and probably regulated prior to widespread application.

Thought enhancement

Humans have been unknowingly enhancing their cognitive abilities with the help of technology for decades. We don't need to know all the contact numbers in our phone directory by heart, we don't have to store the information about upcoming meetings in our memory, we easily make and copy notes of all the information we receive. But can we go further?
From the series of futuristic pictures created in 1899, 1900, 1901 and 1910
Source: The Public Domain Review
Any augmentation of information processing in the brain including perception, attention, memory, or ability to learn can be filed under cognitive enhancement.

Today, all of the technology enhancing our abilities is external. It's been more than a century since the creation of the infamous postcards predicting the future in 2000 but we still don't load information directly into our brains.
The tDCS kit by foc.us promises to "excite" brain cells and help them reach their prime activity
The use of current cognitive enhancement pharmaceuticals also known as nootropics is still debated. Nootropics promote the production of neurotransmitters and increase circulation in the brain, thus boosting the efficiency of cognitive functions. Neuroscientists and psychologists are drawing attention to alarming side effects while numerous students are legally taking smart drugs to handle stress and academic performance during exam season. Initially safe, smart drugs can lead to addiction or memory impairment in underdeveloped brains, especially when exceeding recommended dosage and duration of use.

When it comes to technology, the results are even more vague. The US Defense Innovation Unit has recently admitted to the testing neuro-stimulant technologies for elite forces, and mentioned 20-hour peak performance with the help of electrical stimulation. While electrical brain stimulation currently used in therapy is helpful in research on the animal and human brain, the widespread or even commercial benefits of the technology are not only questionable but perhaps even harmful.

Commercial brain stimulating kits like the ones by foc.us promise to increase capability to learn but are highly unreliable. They use Transcranial Direct Current Stimulation (tDCS) - an experimental treatment claiming to enhance social and learning capabilities with the help of electrical jolts directed to your brain. A user can control the intensity and duration of a treatment; however, to achieve the desired effect, they should be able to repeat laboratory conditions at home, or they risk seizures and head burns.

Another non-invasive form of neurostimulating technology is TMS - transcranial magnetic stimulation, an FDA-approved methodology for treating major depression, Alzheimer's disease, or addictions. Calibrated to target specific regions of a brain, magnetic pulses are helping release neurotransmitters thus altering cognitive performance. Beside mental health benefits, scientists report numerous instances of attention and memory improvement associated with TMS. Either way, the research in this area has just started and it's still unclear whether the effect of magnetic stimulation is long-term.

Behavior enhancement

The possibilities of augmenting human empathy, collaborativeness, and decision-making processes are surprisingly poorly explored, especially considering how these features are the objects of concern for the anti-transhumanism movement. If people can become less empathic or even psychopathic due to technology, we should research how to maintain or improve our social skills.

We can ensure human enhancement through improving attention and ability to learn, but we still lack an important component to a fully advanced human - motivation and discipline.

In his recent article, the innovation thought leader and writer Michael Schrage offered the term "selvesware" to define personal assistants of the future - data-driven and personalized tools to augment our cognitive and behavioral attitudes. While Siri and Alexa perform tasks and learn new skills every day, true augmentation, according to Schrage, doesn't come with acquiring more external assistance, but with improving our own selves using analytics.

Selvesware will be able to monitor our physical data like Fitbit, and then predict performance and suggest better options to distribute time at the workplace. Depending on your profession, these assistants will automatically go around your personal weaknesses and elevate your strengths. They will help designers and artists overcome creative blocks by helping them find a new perspective or suggesting effective choices from their previous projects. Along with wearables and sensors, selvesware will use such cognitive improvement practices like mindfulness, mental maps, and deep focus work to replace tons of productivity apps and make us more naturally disciplined.

The key here is "naturally". The robot-like employees moving in perfect rows along the corridors of office buildings is not something anyone wants unless you're a cartoon villain. But in the era where machine intelligence boosts technology performance, it's inevitable that it will soon automate and augment human potential to make us better experts while organically balancing our personal and professional lives.

Are we ready for human enhancement?

James Young won a chance to receive a 3D-printed prosthetic arm inspired by the game Metal Gear Solid. The arm looks futuristic and powerful. It's equipped with a USB port and even a small drone. But it's very heavy. Young admits that he doesn't wear it most of the times. The so-called Phantom Arm is more artistic project exploring the alternative possibilities of a human arm than a product ready for mass production. And that does not even consider the price tag of such custom technology.

If amputees and physically or mentally challenged people are the ones most likely interested in obtaining enhancements, what about those who don't have a strong need to make their lives easier? The demand for microchips is growing but implanting one small sensor in your hand is not the same as replacing a real working arm, even with something that potentially does a better job.

The possibilities for transhumanist applications are varied but not entirely solid. Perhaps, the concept of what it means to augment humans will shift over time as well as how we see the difference between technology and biology. How soon will the enhancements be available not only for the people who need them, but also the ones who want them? We can only follow the current studies and wait for the appearance of science-backed commercial projects.

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Reality Check: Are Cyborgs the Next Step in Human Evolution?

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In the latest movie from DC Comics Extended Universe Justice League, we finally get to meet one of the members of the superhero squad - Cyborg. Both in the original comics and in the new film, Victor Stone's mind and body have been advanced against his will to create a better version of a human.

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Those that have the diagnosis are reluctant to seek help and to adhere to HAART medications due the concerns surrounding fear and discrimination. Through an online intervention this offers   the individual a sense of anonymity about asking for help and managing the illness.  The general population now have widespread access to the internet and most of the population have access to a smart phone, therefore there is a potential to use this popularity to be able to reduce the gaps in adherence through an app. The app would include promotional prevention messages, information surrounding the drug requirements, alerts and reminders to take the medication and information on the importance of adherence. Through recent advances an opportunity to connect a smartphone accessory onto your phone that allows the user to self-test for HIV, this will inevitably avoid you having to go to a clinic which the individual may feel is uncomfortable to do. In addition, creating a community page which would be monitored will allow for individuals to ask a range of questions and offers a sense of personalisation that many other apps fail to have including CHESS.
What the current app will focus on and improve on:
Improving public use- The HIV app icon on the phone will be discreet and the name of it would be simple as it was found that apps that show the word HIV often led to an unwanted conversation and the individual may feel uncomfortable if they was using it on public transport
( Singh et al., 2017).
Some apps are misleading in the titles and the descriptions where it uses the incorrect terminology such as "risk of aids" instead of "risk of hiv". Even such a small mistake as that can affect the individual and may affect how they understand. For my smart phone app there will be a dictionary on the user interface that will hold and store all the acronyms and terms that are important to know.
The app should also be functionally sound with a clean well-designed interface, should also provide a level of security through incorporating password protection (Gkatzidou et al., 2013). Convenience is a key factor in creating a solid smartphone app, they should have the options for notifications through the app or what suits them best such as email or text messages.

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These electronic monitors, use a computer chip in the cap of the medication vial that records the date and time the vial is opened and then presumes that the medication has been taken.
Evaluation:
The advantage to using MEMS caps is that it provides valuable information as to the drug intake behaviours that cannot be usually assessed by medical histories.

One limitation to measuring adherence in this way is that humans are not that honest. To successfully use MEMS cap the individual needs to be honest about when they take the medication. Patients could forget which medication were taken and or over estimate the amount they have taken.
There is currently no direct method to assess adherence and as such any method that tries is often orientated around changing the behavioural and cognitive mechanisms. MEMS caps, provide an accurate index of use of the vial, but they fail to account if the cap is opened but they do not swallow pill.

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Self-efficacy to adhere to antiretroviral therapy 

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Self-efficacy to adhere to antiretroviral therapy 

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Self-efficacy theory suggests that individuals perform behaviours if they believe they are capable of performing them well (Bandura, 1991). The concept of self-efficacy is the perceived ability to regulate a behaviour effectively and consistently. Individuals who regard themselves as being successful in their ability to adhere will set higher goals and thus be more committed in performing them well.

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Through putting in place an intervention such as a computer based support system and or a smart phone app can have substantial benefits in reducing barriers surrounding adherence and overall providing a greater service for those with HIV. CHESS provides an in depth and accurate information date base whenever the individual has access to a computer whether it be at a community centre, library or home use. Having a chronic illness means that the individual is opened to a new world of intense vocabulary that they should be aware of. Often medical terminology is confusing for the everyday individual and if the individual is suffering from symptoms then they may further lack the energy to decipher the text. Having the computer system will break down all of the terminology into an easy relatively understandable context. Deciphering terminology can also be used through my mobile intervention app.

Going to the doctors for some is an uneasy and unpredictable event whereby, due to the stressors of the job clinicians may come across as being unsympathetic and intimidating which thus influences whether the individual will choose to listen. Having a computer system will eliminate this as it is a safe and non-judgemental resource for any queries they may have.
Advantages of CHESS:
- Improves the health status of the individual as CHESS provides a varied range of support and information to help make tough decisions. Having a communication option to talk to other individuals with HIV will reduce the feelings of isolation and depression that are co-morbid symptoms of the disease.
- Improve health behaviour through providing facts and tools to help assist with adherence such as decision analysis and implementation analysis which allows them to maintain the appropriate behaviours.
-Cost effective as the system provides a resources that guide them to what the best services are. Well informed patients will then spend less time asking questions to health care staff, CHESS also allows the patient to document there appointments and medications and symptoms which can help make health care professionals make a diagnosis and a successful treatment plan quicker.

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Important to use interventions that look into the emotional well-being and QOL to give a wider understanding of adherence.
Living with HIV involves many challenges, with greater levels of stress and depression widely reported (Bing et al., 2001). Those who report higher levels of distress are also associated with poorer health behaviours including non-adherence (Bing et al., 2001). HIV patients struggle with a number of social problems that impact their QOL including stigma and discrimination. Health related quality of life can be used to document the patients perceived burden of chronic disease, tracking the changes in health, assessing the effects of treatments.

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Adherence self-efficacy and adherence to antireretroviral medications in those with HIV.
Findings- Positive interactions between health care providers can increase adherence scores.

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Mallory O. Johnson, Ph.D., ¹ Margaret A. Chesney, Ph.D., ¹ Rise B. Goldstein, M.P.H., Ph.D., ² Robert H. Remien, Ph.D., ³ Sheryl Catz, Ph.D., ⁴ Cheryl Gore-Felton, Ph.D., ⁵ Edwin Charlebois, M.P.H., Ph.D., ¹ Stephen F. Morin, Ph.D., ¹ and the NIMH Healthy Living Project Team

Abstract

Adherence to antiretroviral (ARV) therapy for HIV infection is critical for maximum benefit from treatment and for the prevention of HIV-related complications. There is evidence that many factors determine medication adherence, including adherence self-efficacy (confidence in one's ability to adhere) and relations with health care providers. However, there are no studies that examine how these two factors relate to each other and their subsequent influence on HIV medication adherence. The goal of the current analysis was to explore a model of medication adherence in which the relationship between positive provider interactions and adherence is mediated by adherence self-efficacy. Computerized self administered and interviewer administered self reported measures of medication adherence, demographic and treatment variables, provider interactions, and adherence self-efficacy were administered to 2765 HIV infected adults on ARV. Criteria for mediation were met, supporting a model in which adherence self-efficacy is the mechanism for the relationship between positive provider interactions and adherence. The finding was consistent when the sample was stratified by gender, race, injection drug use history, and whether the participant reported receipt of HIV specialty care. Positive provider interactions may foster greater adherence self-efficacy, which is associated with better adherence to medications. Results suggest implications for improving provider interactions in clinical care, and future directions for clarifying inter-relationships among provider interactions, adherence self-efficacy, and medication adherence are supported.

Keywords: HIV/AIDS, Provider Relations, Adherence/Compliance

INTRODUCTION

The importance of adherence to antiretroviral (ARV) medications in the treatment of HIV infection is well documented [ 1, 2]. High levels of adherence are critical for clinical benefit and the prevention of HIV-related complications and opportunistic infections. Multiple issues, including patient factors (e.g., depression, substance use, treatment beliefs), treatment factors (e.g., regimen complexity, side effects), and contextual factors (e.g., access to care) have been identified as predictors of adherence and have, to varying degrees, been the focus of interventions to improve medication adherence [ 3- 6].

One patient factor that is consistently and meaningfully related to ARV medication adherence is adherence self efficacy [ 5, 7- 12], or confidence in one's ability to adhere to a treatment regimen in the face of challenges such as side effects, interference with daily activities, environmental barriers to treatment, depression, and lack of support from others. Self efficacy is a paramount requisite factor for health behavior change [ 13, 14] and, along with perceptions of treatment efficacy, are central to many theories of health behavior, including the Health Belief Model [ 15]. Findings linking adherence to self-efficacy have indicated the potential for interventions to bolster adherence self-efficacy for persons who are struggling with adherence. The determinants of adherence self-efficacy, however, remain unclear.

Another factor that is often linked to ARV adherence is positive provider relations[ 16]. In a wide range of illness contexts, dimensions of patient satisfaction with providers' communication, engagement, and general interaction skills are linked to adherence to care [ 17- 20]. In the context of diabetes treatment, patients' perceptions of provider communication skills are associated with treatment adherence[ 21, 22]. In HIV treatment, treatment plan adherence has been associated with patients' perceived level of engagement and satisfaction with their providers [ 16, 23, 24].

An understanding of the relationship between self-efficacy and provider relations has the potential to inform interventions to improve adherence, but this understanding has not been achieved. Therefore, the purpose of this paper is to evaluate a model of medication adherence in which adherence self-efficacy mediates the association between positive provider interactions and self reported ARV adherence. We hypothesize that positive provider interactions are linked to greater self-efficacy for adherence, which in turn is associated with better ARV adherence; specifically, that higher adherence self-efficacy explains the association between provider interaction and adherence. The rationale for the proposed sequence is that we hypothesize that positive interactions with a provider (such as a greater sense of engagement with the provider and a perception that the provider understands and takes the patient's concerns seriously) lead to greater agreement with treatment recommendations and a greater personal commitment to the treatment plan. This translates to greater adherence self-efficacy, which is linked to adherence as described above. illustrates the mediation model proposed in this paper.

We also explored differences in this relationship along the dimensions of gender, race, injection drug use, and whether the patient reports receiving care at an HIV specialty clinic. We distinguished HIV specialty clinics from other medical care settings in response to debate in the literature regarding relative benefit of specialist training versus generalists in the treatment of HIV disease[ 25- 27]. Likewise, lower adherence rates among IDUs and African Americans have been reported in the literature [ 5] and patient history of IDU has been suggested as influencing provider perceptions about patients' ability to adhere [ 16, 28]. Also, there is recent evidence that non-White patients rate satisfaction with provider interactions differently than White patients, providing rationale for such focus in our analyses [ 29]. Finally, we explored potential effects of gender in response to assertions that gender of patient (and provider) may influence patient-provider interactions [ 30, 31].

METHODS

Study Respondents

A total of 3,818 HIV-positive individuals in four cities (San Francisco, Los Angeles, New York City, and Milwaukee) were screened for recruitment into the Healthy Living Project (HLP). Recruitment and screening of potential respondents were undertaken in community agencies and medical clinics serving HIV-positive clients. Brochures, posters, and project descriptions, as well as direct contact by study staff in clinical and social service agencies were used to recruit respondents. In addition, advertisements were placed in newspapers and magazines serving HIV-positive and gay/bisexual populations, and potential respondents learning of the study by word of mouth were eligible to be screened. Interested persons who provided verbal consent were briefly screened by project personnel to determine their self-reported HIV status as well as basic demographic and contact information, and then, if they wished to participate, scheduled for a baseline interview.

Respondents were required to be at least 18 years of age, to provide written informed consent and medical documentation of their HIV infection, to be free of severe neuropsychological impairment or psychosis, and not be currently involved in another behavioral intervention study related to HIV. Severe neuropsychological impairment and psychosis were assessed on a case-by-case basis by senior project personnel in collaboration with the clinical supervisor at the involved institution.

Overview of assessment procedures

All procedures and forms were reviewed and approved by the sites' Institutional Review Boards (IRB). Assessment interviews were conducted in private settings in research offices, community-based organizations, and clinics in the four cities. Written informed consent to participate in the study was obtained from each respondent prior to the administration of the baseline interview. The interview was then conducted over a period of two to four hours with regular breaks allowed to minimize respondent fatigue.

Procedures involved a combination of Audio Computer Assisted Self-Interviewing (ACASI) and Computer Assisted Personal Interviewing (CAPI) using Questionnaire Development System (QDS), Nova Research Company. ACASI allows the respondent to listen to an item via headphones while reading the item on a computer monitor. The respondent then enters his or her response directly into the computer. This approach has been proposed as an effective method of decreasing social desirability and thereby enhancing veracity of self-report of sensitive behaviors and attitudes [ 32, 33]. With CAPI, an interviewer reads items from a computer and the respondent verbally gives responses that the interviewer enters directly into the computer.

Respondents were compensated US$50 for completing the baseline interview and those needing child care were also eligible to receive US$10 to defray child care costs.

Interview training and quality assurance

Interviewers were trained centrally with the use of a detailed assessment manual, practice with the computer programs, participation in an intensive 3-day training program, and review and certification of audio-taped mock interviews based on standardized criteria. All interviews were audio-taped and each tape labeled with the respondent's study identification number, date of the interview, and the interviewer's identification number. A systematic sample of all tapes was reviewed for protocol adherence and feedback was provided to all interviewers on a regular basis; however, sites were notified immediately if raters identified significant violations of the assessment protocol by particular interviewers.

Measures

Demographics / Background

Detailed background and demographic data included items such as respondent age, race/ethnicity, gender, sexual orientation, relationship status, educational level, employment status, self-reported most recent CD4 count, and injection drug use (IDU) in the past 12 months.

Depression

Depression was assessed with the 21-item Beck Depression Inventory (BDI) [ 34, 35] (α = .85) which has been widely used in studies with HIV-infected patients to evaluate the severity of depressive symptoms [ 36].

Social support

A global score on the Social Provisions Scale (SPS) [ 37, 38] was used to assess level, type, and perceived satisfaction with social supports from one's social network. This score was derived by averaging scores on the 6 SPS subscales: guidance, reliable alliance, reassurance of worth, attachment, social integration, and opportunity for nurturance (α for total score is .82).

Positive Patient-Provider Interactions

Adapted from previous studies[ 39], we administered an 8 item scale to assess patients' perceptions of positive interactions with their providers. Respondents were asked how often certain things occurred during recent contacts with health care providers, such as discussing side effects and other medication problems, getting providers to really listen to concerns, and feeling helped by their providers. Sample item "How often during your recent interactions with your providers did you get help in solving any problems in taking your medications or dealing with symptoms or side effects?" Response choices are never (0), some of the time (1), most of the time (2), and every time (3). For these analyses, scores on each item are averaged for each respondent with higher scores indicating more positive provider interactions. Cronbach's alpha for this administration = 0.81.

Adherence Self-Efficacy

A 12-item scale was used to assess patient confidence to carry out important treatment-related behaviors related to adhering to treatment plans, especially medication regimen adherence, in the face of barriers. Reponses range from 1 (cannot do it at all) to 10 (certain you can do it). Sample item "How confident are you that you can stick to your treatment plan when side effects interfere with daily activities?" Scores on each item were averaged for each respondent with higher scores indicating higher adherence self efficacy. Cronbach's alpha equals 0.91 for this scale, which has been used in other adherence reports[ 5].

Medication Adherence

Recent self-reported antiretroviral medication adherence was assessed over a three-day period using an adherence survey developed for use in AIDS Clinical Trials [ 7]. The measure was computerized for ACASI administration allowing respondents to indicate how many antiretroviral pills they had skipped during each of the previous three days. This measure has been used widely with diverse samples and the short term recall period has been associated with long term clinical outcomes. Adherence was assessed only for those ARV medications that were reported in the adherence section of the interview. For the present study, we calculated percent adherence based on number of pills taken divided by the number of pills respondents reported being expected to take. Respondents were classified as having achieved less than 90% adherence versus 90% or higher adherence, consistent with current literature on minimum levels of adherence to achieve HIV viral suppression and clinical benefit [ 2, 40].

Statistical analysis

We followed established procedures to test for mediation in our analyses[ 41]. Specifically, each of the three variables must be bivariately associated with the other two variables. In the current application, this would mean that provider interactions must be associated with self-efficacy and adherence. Given these associations, the association between positive provider relations and adherence must become smaller (for partial mediation) or eliminated (for full mediation) if self-efficacy mediates the relationship between positive provider interactions and adherence. We conducted separate univariate logistic regression analyses in which positive provider interactions and adherence self-efficacy each were regressed onto dichotomous adherence outcomes. We then entered the provider and self-efficacy variables into the same model with adherence as the outcome. Control variables include gender, age, education, ethnicity, IDU in the past 12 months, depression, social support, usual source of HIV care, and most recent CD4 count. Comparing the results from these analyses allows the determination if mediation is supported. Among those with complete adherence data, an acceptable number (less than 4%) of cases were excluded from multivariate analyses due to missing data[ 42].

We then conducted post hoc analyses to determine if the pattern of results was the same when stratified by gender (male vs. females), ethnicity (African American vs. White vs. Latino), IDU status (past 12 months), and usual source of HIV care (HIV specialty clinic vs. other).

RESULTS

Sample description and treatment variables

Of the 3818 individuals interviewed, 75% were currently taking ARVs. Findings presented in the paper are based on the 2765 participants for whom adherence data are available. Sample characteristics, including demographics, treatment variables, and mean adherence self-efficacy and positive provider interaction scores are presented in . The sample was 74% male, 49% African American/Black, 18% Latino/a, and 26% White. The mean age was 42 years (SD = 7.6) and the median was 41. Twenty-five percent reported less than high school graduation, and 12% were born outside of the U.S. Forty-three percent identified as heterosexual, 43% as homosexual, and 12% identified as bisexual. With regard to clinical status, the mean CD4 count reported was 431 (SD=292) and 46% reported an undetectable viral load at last testing. The median length of time on regimen was 127 weeks (2.4 years).

Table 1

Adherence rates

Overall, 31.75% (878/2,765) of persons taking antiretroviral medications indicated that they had skipped enough pills in the prior three days to result in less than 90% adherence for the reporting period. There were no differences in adherence rates by site or gender. For a complete report of the differences between adherers and nonadherers in this sample, see Johnson, et al.[ 5]

Test of Mediation

The Pearson correlation between positive provider interactions and adherence self efficacy is 0.260 (p<.001). Bivariate odds ratios of each of these two variables relationships with adherence are presented in , indicating that either higher positive provider interactions or higher adherence self-efficacy is related to reporting 90% or higher medication adherence. When both are entered into the same multivariate logistic regression analysis in which adherence is the dependent variable, self-efficacy's odds ratio remains largely unchanged, whereas the provider interactions variable is no longer significant, indicating mediation as per criteria described above. reports these results for the entire sample and illustrates the mediation model tested in these analyses. In this figure, the direct line (dotted) between provider interactions and adherence is not significant once the path through adherence self-efficacy is taken into account.

Table 2

There were some differences between groups in adherence, adherence self-efficacy and provider interactions scores. Specifically, illustrates that women and those reporting HIV specialty care had higher positive provider interactions scores, and African American respondents reported lower adherence self efficacy scores than White respondents. African Americans' adherence rates were lower than White and Latino respondents and IDUs had lower adherence than non-IDUs. However, moderation analyses revealed that the pattern of results was the same for men vs. women, African American vs. White vs. Latino, IDU vs. non-IDU, and HIV specialty care recipient vs. not, indicating that these variables did not change the mediation model described above. The final odds ratios presented in are after controlling for multiple demographic and treatment variables.

Table 3

DISCUSSION

In this study, adherence self-efficacy mediated the relationship between positive provider interactions and medication adherence. This indicates that, statistically, the relationship of provider interactions and adherence can be explained by adherence self-efficacy, suggesting that self-efficacy may be the mechanism of the relationship between the other two variables. The pattern of this relationship was the same regardless of gender, race/ethnicity, injection drug use, and site of usual HIV care, suggesting substantial support for this model of adherence. Further, this relationship is maintained when controlling for important demographic variables (age, gender, education), treatment variables (CD4 count, usual source of care), and other factors often linked to adherence (depression, social support, IDU).

These findings have implications for improving adherence self-efficacy such that fostering positive interactions between providers and patients may lead to better medication adherence [ 43]. Effective interventions to improve provider relations may target the patient, the provider, or both. For example, helping providers create an environment in which the patient feels respected and understood may lead to greater confidence in the patient's ability to stick to a treatment regimen. This may involve structural changes within clinical settings or provider training in which interpersonal skills are addressed. Greater time per patient visit in which the provider has the opportunity to sit and talk with the patient, although challenging to implement given current healthcare delivery systems, is one example of a structural change that may result in more positive interactions [ 44]. Physician training to increase collaborative negotiation in setting treatment goals and strategies is also likely to bolster adherence self-efficacy. For example, greater patient-physician agreement about top priority treatment strategies has been shown to predict greater self-efficacy for diabetes self-management ⁴⁰. Because patient perceptions of stress may undermine self-efficacy for antiretroviral adherence ⁴¹, it may also be beneficial to improve patient-physician communication about managing stressful life circumstances that influence medication adherence. Likewise, patient-focused interventions that enhance skills may improve provider/patient visits [ 45] and lead to greater self-efficacy for medication adherence. For example, assertive communication skills, in which the patient is able to respectfully make specific requests of the provider, may facilitate positive interactions. Other strategies by which the patient can influence the interaction with the provider, e.g., making lists of questions for the provider, may have a beneficial impact on the patient-provider interaction and thereby improve adherence self-efficacy. Such a focus has implications for preventive medicine in that complications from HIV infection may be avoided if adherence can be supported through positive provider interactions.

Limitations

The mediation model we have tested and presented in this paper is based on cross sectional data. For this reason, we cannot be certain of causality in the relationships among the variables and cannot rule out competing models that may fit the data. For example, it may be that better adherence leads to more positive provider interactions and to higher self-efficacy. It is also likely that reciprocity exists, in which there is a dynamic influence of provider and patient behavior that affects adherence outcomes, as suggested by some researchers[ 31]. Second, we do not have information on provider gender, training, or ethnicity, nor do we have providers' assessments of the interactions with the patients. Having both patient and provider perspectives would enhance our understanding of the model presented.

The use of self-reported adherence data has been questioned in HIV research. Currently, there is no gold standard for measuring adherence to antiretroviral medications. Self-reported levels of adherence are suspected of being inflated because of recall, social desirability, and other biases. To minimize the biases inherent in self-reported data, we employed several techniques. First, we used a validated measure of adherence that has demonstrated meaningful relationships with important outcomes, such as viral load, in other studies. Second, we used ACASI interviewing for the adherence portion of the interview, thereby removing the interviewer's presence and minimizing social desirability bias. Finally, we included instructions that contained recall cues, which asked the respondent to carefully think back through events in the past three days and the computer referred to each day by name. Such approaches to computerized adherence assessment have shown favorable effects in other studies [ 46, 47].

Finally, because it is impossible to obtain a comprehensive list of HIV-positive persons from which to randomly sample and because we were recruiting for a randomized behavioral intervention trial, we interviewed a convenience sample from multiple sources in each city (e.g., infectious disease clinics, AIDS service organizations, bars, advertisements in periodicals). Nevertheless, by using a large number and range of recruitment sites, we were able to obtain a sample demographically representative of the HIV epidemic in each subgroup in the US [ 48]. In comparison to another large, multi-city sample of HIV-infected adults, the HIV Cost and Services Utilization Study (HCSUS) cohort [ 49], our study included more members of ethnic minority and low socioeconomic status groups, and included individuals who were not receiving treatment, and may thus more closely approximate the HIV-infected population in the US.

This study represents an important step in elucidating the role of provider relations in determining adherence to medications. Longitudinal studies are needed in which programs to enhance patient-provider interactions are evaluated in their effect on adherence self-efficacy and medication taking behaviors. Such investigations have the potential to maximize preventive medicine efforts in the treatment of HIV disease.

ACKNOWLEDGMENTS

This research was funded by National Institute of Mental Health grants U10-MH57636, U10- MH57631, U10-MH57616, and U10-MH57615. We also acknowledge the support of NIMH center grants P30-MH058107 (Mary Jane Rotheram-Borus, Ph.D., PI), P30-MH57226 (Jeffrey A. Kelly, Ph.D., PI), P30-MH43520 (Anke A. Ehrhardt, Ph.D., PI), P30-MH062246 (Thomas J. Coates, Ph.D., PI), and NIMH grant K08-MH01995 (Mallory O. Johnson, Ph.D., PI). The authors thank Ellen Stover, Ph.D, and Willo Pequegnat, Ph.D., at NIMH for their technical assistance in developing the study and Christopher M. Gordon, Ph.D., and Dianne Rausch, Ph.D., at NIMH for their support of this research. Thanks to the Psychosexual Core of the HIV Center for Clinical and Behavioral Studies at New York State Psychiatric Institute and Columbia University, especially Heino Meyer-Bahlburg, Terry Dugan, and Theresa Exner, for collaborating with us in developing the sexual behavior interview, to the assessors in each city who conducted the interviews, to our clinic and community based organization collaborators, to all other support staff involved in the project, and to the men and women who participated in the interviews.

REFERENCES

13. Bandura A. Self-efficacy mechanism in physiological activation and health-promoting behavior. In: Madden IJ, editor. Neurobiology of learning, emotion and affect. Raven; New York: 1991. pp. 229-270.

14. Bandura A. Social foundations of thought and action: A social cognitive theory. xiii. Prentice-Hall, Inc; Englewood Cliffs, NJ, US: 1986. p. 617.

35. Beck AT. Depression: Causes and Treatment. University of Pennsylvania Press; Philadelphia, PA: 1967.

36. Griffin KW, Rabkin JG. Psychological distress in people with HIV/AIDS: Prevalence rates and methodological issues. AIDS & Behavior. 1997;1(1):29-42.

38. Cutrona CE, Russell DW. Type of social support and specific stress: Toward a theory of optimal matching. In: Sarason BR, Sarason IG, editors. Social support: An interactional view. New York, NY: 1990. pp. 319-366.

42. Roth PL. Missing data: A conceptual review for applied psychologists. Personnel Psychology. 1994;47(3)

46. Stewart KE. ICAAC. San Diego, CA: 1998. Patterns of self-reported adherence to ART in a prospective clinical cohort.

48. CDC HIV/AIDS surveillance report: Midyear 2001 edition. MMWR CDC Surveillance Summaries. 2001;13(1)

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Positive provider interactions, adherence self-efficacy, and adherence to antiretroviral medications among HIV infected adults: A mediation model

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Mallory O. Johnson, Ph.D., 1 Margaret A. Chesney, Ph.D., 1 Rise B. Goldstein, M.P.H., Ph.D., 2 Robert H. Remien, Ph.D., 3 Sheryl Catz, Ph.D., 4 Cheryl Gore-Felton, Ph.D., 5 Edwin Charlebois, M.P.H., Ph.D., 1 Stephen F.

# data[].attributes.body
HIV positive individuals experience numerous uncontrollable stressors. On top of the challenges of dealing with a chronic illness they also have to deal with stigma and the discrimination of being homosexual, drug user or sexual promiscuous.
Cognitive- behavioural interventions are one of the most effective approaches to improve mental health- focuses on the interactions of thoughts feelings and behaviours ( Beck, 1976).

- study by Safren  et al., (2010) found that treatment using CBT let to significantly better outcomes in both adherence and depression than an enhanced-care comparison group.

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CHESS intervention- comprehensive health enhancement support system 

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CHESS intervention- comprehensive health enhancement support system 

# data[].attributes.body
CHESS provides crucial information for those who have HIV. There are a range of categories that the individual can search through such as: Questions and Answers which consists of over 400 questions related to medical, financial, legal, and social/sexual issues of AIDS/HIV, Instant library, Ask an expert as well other categories such as support services which allow for discussion between those and personal stories. The problem solving services include programs to help people understand their lifestyle risks and patterns, decision aid and guided program that is titled action.

Due to the wide ranges of services that CHESS provides, they allow the individual to use only what the need anonymously any time of the day, furthermore CHESS is designed to be used for both the patient as well as any queries the family may have.
Gustafson et al., (1994) concluded that those with HIV who used CHESS had an improved level of QOL.
Limitation of Chess as an intervention-
Each component of the system is individualised and not personal to the individual. All of the patients receive the same information, so if you had something personal that needs answering you will just receive a basic response. For my intervention this community page offers a sense of personalisation whereby, the answers can be tailored to that specific individual.

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Intervention Research

We investigated the utility and the pattern of use of the Comprehensive Health Enhancement Support System (CHESS), an Internet based consumer health informatics system for people living with HIV/AIDS. Eight patients utilized CHESS for 4 months. The total number of log-ins ranged between 1 and 93 (median 21), with a median of 4.6 per month (0.2-21.8). Discussions Group was the service most frequently accessed; the Referral Directory and Fat Assessment services were requested the least. The barriers to using CHESS were difficulty in using the laptop, being too busy, and the discussion group size being too small. Most participants agreed that CHESS was easy to use and helped them cope with and understand more about their disease. They also felt comfortable asking questions and felt more involved in their health care.

KEY WORDS:

Comprehensive health enhancement support system (CHESS) consumer health informatics system patient empowerment HIV infection

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REFERENCES

1. Coplan, P., Cormier, K., Japour, A., Maradit-Kremers, H., Nikas, A., and Lewis, R. (2000). Myocardial infarction incidence in clinical trials of 4 protease inhibitors. In Seventh Conference on Retroviruses and Opportunistic Infections (Abstract 34). San Francisco.

2. Gustafson, D. H., Bosworth, K., Hawkins, R. P., Boberg, E. W., and Bricker, E. (1992). CHESS: A computer-based system for providing information referrals, decision support and social support to people facing medical and other health-related crisis. In Presented at the Proceedings --- The Annual Symposium on Computer Applications in Medical Care, 161-165.

© Springer Science+Business Media, Inc. 2005

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Comprehensive Health Enhancement Support System (CHESS) for People with HIV Infection

# data[].attributes.attachment_link.description
Intervention Research We investigated the utility and the pattern of use of the Comprehensive Health Enhancement Support System (CHESS), an Internet based consumer health informatics system for people living with HIV/AIDS. Eight patients utilized CHESS for 4 months. The total number of log-ins ranged between 1 and 93 (median 21), with a median of 4.6 per month (0.2-21.8).

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Patients beliefs about the specific medication prescribed for them could be grouped under two core themes. These were their beliefs about the necessity of the prescribed medication for maintaining health now and in the future, and concerns about the potential adverse effects of taking the medication.  These beliefs might influence patients decisions about being prescribed the medication- these adherence decisions are influenced by a cost-benefit assessment in which personal beliefs about the necessity of the medication for improving health.
Positive illness beliefs are associated with positive physiological changes. People who have a positive sense of self-worth, believe in their own control and optimism were more likely to have better health habits.

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Adherence to prescribed treatments has been found to be predicted by patients beliefs about the treatment itself. This is known as the necessity-concerns framework.
It is a multidimensional theory that provides a relationship between patients necessity beliefs and concerns regarding medication- this then forms the outcome of adherence.
The patients weigh up the costs against the benefits of taking a medication.

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Theories that can help us understand adherence 

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Theories that can help us understand adherence 

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Health Belief Model-  Motivation for people to take action to promote or prevent disease is based on:
- How strongly they believe that they are susceptible to the disease
-Whether the disease would have serious effects on their lives
-Suggested health intervention is of value
-Whether the effectiveness of the treatment is worth the cost ( you develop co-morbid symptoms which are not otherwise developed from HIV alone).
Model is dived into three components:
- The individuals perceptions
-Modifying factors (stigma and discrimination)
- Benefits

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The importance of measuring QOL is to be aware of how the patient is experiencing their health condition and thus offers the ability to improve and refine pre-existing methods. Sprangers and Schwartz, (1999) proposed a theoretical model to clarify the changes over time in the perceived QOL, as a result of the interaction of catalysts, antecedents, mechanisms and response shift.
Response shift which was added in the revised stages in which is the shift in ones self evaluation Richard and Folkman, (2000).

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The necessity- concerns- framework: a multidimensional theory.
Findings- Individuals that had strong necessity beliefs and weak concerns was positively
associated with greater adherence scores.

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Abstract

Background

Patients' medication-related concerns and necessity-beliefs predict adherence. Evaluation of the potentially complex interplay of these two dimensions has been limited because of methods that reduce them to a single dimension (difference scores).

Purpose

We use polynomial regression to assess the multidimensional effect of stroke-event survivors' medication-related concerns and necessity-beliefs on their adherence to stroke-prevention medication.

Methods

Survivors (n=600) rated their concerns, necessity-beliefs, and adherence to medication. Confirmatory and exploratory polynomial regression determined the best-fitting multidimensional model.

Results

As posited by the Necessity-Concerns Framework (NCF), the greatest and lowest adherence was reported by those with strong necessity-beliefs/weak concerns and strong concerns/weak necessity-beliefs, respectively. However, as could not be assessed using a difference-score model, patients with ambivalent beliefs were less adherent than those exhibiting indifference.

Conclusions

Polynomial regression allows for assessment of the multidimensional nature of the NCF. Clinicians/Researchers should be aware that concerns and necessity dimensions are not polar opposites.

Keywords: Polynomial Regression, Necessity-Concerns Framework (NCF) and the Beliefs about Medicines Questionnaire (BMQ), Medication Adherence, Stroke Survivors, Bivariate Evaluation Plane

Patient adherence to prescribed treatments, which has been called the 'the key mediator between medical practice and patient outcomes' ( 1), is known to be predicted by patients' beliefs, particularly those regarding the treatment itself (i.e., beliefs in the necessity of and concerns regarding the treatment; 2, 3). The effects of patients' treatment-related beliefs on their adherence are delineated in the Necessity-Concerns Framework (NCF; 3), which is a multidimensional theory in that it posits relationships between two separate dimensions-patients' necessity beliefs and concerns regarding medication-and between these two predictors and an outcome (medication adherence). The NCF states that patients implicitly weigh the costs against the benefits of taking a medication when deciding whether or not to adhere to it and that medication adherence will be greater the more patients' beliefs in the necessity of the medication exceed their concerns. Researchers have found support for the NCF in many illness domains, including asthma ( 4), HIV ( 5, 6), cystic fibrosis ( 7), hemophilia ( 8), renal disease ( 9), hypertension ( 10), depression ( 11), diabetes, cardiac illnesses, and cancer ( 3), and recently, among stroke survivors ( 12). Patients' treatment-related beliefs predict their adherence more strongly than do socio-demographic variables (education, gender, age), clinical variables (type of illness, number of medications), and other beliefs (e.g., illness perceptions; 4, 6).

Given the importance of patients' treatment-related beliefs for their adherence behaviors, the NCF holds great promise for interventions that aim to improve medication adherence. While the NCF enjoys wide support, its optimal application would benefit from further advancement in the methods used to evaluate the NCF. Currently, researchers in the field are using suboptimal methods to assess the NCF that threaten the validity of their conclusions and constrain the theoretical hypotheses they can test. Simply put, researchers are collapsing the separate concerns and necessity-belief dimensions into one dimension (necessity beliefs minus concerns) to analyze the multidimensional theoretical relationships posited by the NCF (as depicted in ).

The purpose of the current paper is twofold: 1) to demonstrate the usefulness of polynomial regression for studying the NCF and patient adherence; and 2) to use polynomial regression to extend the evidence regarding the importance of the NCF in a stroke-survivor population, for whom adherence to stroke-prevention medications is of utmost importance to prevent stroke recurrence ( 12, 13).

The Necessity Concerns Framework is a multidimensional theory

The 'necessity beliefs' and 'concerns' subscales of the Beliefs about Medicines Questionnaire (BMQ; 14) were designed to assess the NCF. These positive and negative evaluations of medications, respectively, are separate theoretical dimensions. Not only are they measured on separate subscales, but they have also been shown to be orthogonal to each other in predicting adherence. For example, Aikens et al. ( 11) found that patients' necessity beliefs and concerns regarding their maintenance-phase antidepressants were unrelated to each other (i.e., did not correlate) and that they independently predicted adherence.

The separate dimensionality of positive and negative evaluations can be traced to earlier social psychological theorists. Cacioppo and colleagues ( 15, 16) took issue with the fact that positive and negative evaluations were being assessed on unidimensional, bipolar scales (e.g., semantic differentials; if a subject had a positive attitude towards a behavior or object, then he/she was thought to necessarily not have a negative attitude towards the behavior or object), and proposed the 'bivariate evaluation plane'. The bivariate evaluation plane theory maintains that individuals' behavior may be determined by reciprocal (when one is high, the other is necessarily low), non-reciprocal (also called 'co-activated', meaning a person can be ambivalent about a behavior, having both strong positive and strong negative evaluations of it or can be indifferent about a behavior, having weak positive and weak negative evaluations of it), or uncoupled positive and negative evaluations. For example, Cacioppo and Gardner ( 17) demonstrated that blood donation among multi-gallon blood donors was greater when donors' attitudes towards blood donation were ambivalent rather than indifferent, but greatest when attitudes were reciprocal-positive (strongly positive and weakly negative) and least when attitudes were reciprocal-negative (strongly negative and weakly positive). Similar 'attitude groups' have been created from the BMQ necessity beliefs and concerns subscales (i.e., ambivalence, indifference, skepticism, acceptance; 11).

With positive and negative evaluations existing on two separate dimensions, their relationships to an outcome variable exist in three dimensions. The NCF is, therefore, inherently a multidimensional model, which may be represented with a graph such as , which represents patient adherence (the Z-axis) as predicted by different combinations of patients' necessity beliefs (the X-axis) and concerns (the Y-axis).

Methods to assess the NCF have been constrained to two-dimensions

The methods thus far used to test the bivariate evaluation plane and the NCF are 'two-dimensional', because they function to place the separate dimensions of positive and negative evaluations back onto a single dimension. Researchers have either constructed a difference score (necessity beliefs minus concerns; e.g. 6, 11) or artificially categorized patients into attitude groups, which then function as the predictor on a single dimension. See for a graph of a two-dimensional version of the three-dimensional plane in ; likewise, see for a two-dimensional representation of artificial 'attitude groups' and their differing mean levels of an outcome.

Examples of these constrained analyses include the following: Horne and Weinman ( 3) constructed a difference score between patients' necessity beliefs and concerns about their medications for asthma-, renal-, cardiac-, or oncology-related conditions, and found that the difference score significantly predicted patient adherence; they also split the patients into those for whom concerns scores exceeded necessity scores and those for whom necessity scores exceeded concerns scores, finding that the latter group reported significantly lower adherence to medication than the former. Horne et al. ( 6) similarly calculated a 'necessity-concerns differential (NCD)' to represent the relative value of patients' necessity beliefs to their concerns regarding their medication and compared the average necessity belief score, concerns score, and NCD between artificially dichotomized low and high adherence groups. The authors concluded from a significantly higher NCD in the high adherence group, that their necessity beliefs were more likely to outweigh their concerns than would be the case for the low adherence group.

A final example is the methods used by Cacioppo and Gardner ( 17) to test the bivariate evaluation plane theory: they categorized participants into groups defined by their high versus low scores on positive and negative evaluations of blood donation (high/high, high/low, low/high, low/low); they then tested the mean differences in donated blood (gallons) between the groups. Researchers assessing the NCF for predicting adherence in different illness domains have used this method, splitting their sample into attitude groups based on median splits of the data ( 18, 19) or on scale-center splits of the data ( 20, 21). While this categorization recognizes the separate dimensionality of the positive and negative evaluations, it functionally and statistically places them on a single dimension.

Some researchers may analyze the effect of necessity beliefs separately from the effect of concerns on adherence (using them as separate predictors in a multiple regression; e.g., 6, 12), but these analyses do not test the fundamental theory of the NCF, which regards the combined effect of the two types of beliefs on adherence, such as what the effect on adherence is when the two types of beliefs are similar in strength or one is relatively stronger than the other; instead, these analyses look at which type of belief accounts for more variance in adherence in the entire sample.

Methods that collapse dimensions provide suboptimal tests of multidimensional theories

Using difference scores and artificial categorization of participants, thereby collapsing two separate predictor dimensions, decreases statistical power (increasing Type II error risk) and confounds the effect of each predictor on the outcome (increasing Type I error risk; e.g., a significant relationship of the difference score to the outcome may be entirely explained by the relationship between only one of the predictors and the outcome, leading a researcher to falsely conclude that the coupled effect of the two predictors is important for the outcome; 22, 23).

These sub-optimal methods also constrain the theoretical relationships between variables. Of primary importance for the NCF, the algebraic difference score constrains (inherently assumes) patients with ambivalent attitudes to be equal in adherence to patients with indifferent attitudes. This can be seen by considering the regression model tested when a researcher uses a difference score to predict an outcome: Z = b ₀ + b ₁(X-Y); when X = Y, Z = b ₀, regardless of the absolute level of X and Y (whether high or low).

Using artificial 'attitude groups' is not a solution to this problem, because, as mentioned, these group-based methods condense the separate predictor dimensions to one (as in ). They also decrease statistical power, regardless of how the data is split; further, those who use median splits or other sample-dependent thresholds compromise the generalizability of the results and can lead to false statistical significance ( 24). See Edwards ( 22, 25) or Phillips ( 23) for a more comprehensive review of the problems associated with difference scores and artificial categorizations.

Polynomial regression is a 'multidimensional method'

Polynomial regression is a 'multidimensional method' that utilizes unconstrained predictors in order to test the difference score model as posited in theories or to determine the three-dimensional relationships as yet un-theorized. Polynomial regression avoids a majority of the statistical problems associated with 'two-dimensional methods' and further allows researchers to test more complex theoretical hypotheses. The analysis is ideal for testing hypotheses posited by the NCF and the bivariate evaluation plane theory: it is used when two related, continuous predictors (e.g., two individuals' perspectives on the same issue, such as positive and negative evaluations of a behavior; or expected and experienced levels of the same construct, such as expected and experienced satisfaction) are used to predict a continuous outcome, such as adherence ( 26).

Before providing specific hypotheses, we provide here a brief explanation of polynomial regression and how it can be used to study the theorized relationships between individuals' positive and negative evaluations and a target behavior. Polynomial regression is a 'multidimensional method' in that it maintains the positive and negative evaluations on separate dimensions, as they are theorized to be, in their prediction of the outcome. There are two approaches: a confirmatory approach and an exploratory approach.

The confirmatory approach compares an a priori hypothesized, constrained model (e.g., the algebraic difference score) with the unconstrained version of the regression model to test whether the constraints are accurate. Figures 1b and 1d illustrate the constrained and unconstrained difference score models that would be compared with the confirmatory approach. When researchers test the algebraic difference score as a single predictor, they are testing the following regression equation, which is graphed in : Z = b ₀ + b ₁(X-Y); the graph is made as a simple line graph, with b ₀ as the intercept and b ₁ as the slope of the line. is a three-dimensional version of -both adhere to the constraint on the regression coefficients of the two predictors. illustrates the polynomial regression equivalent to testing a difference score-X and Y are not combined in a single predictor through subtraction but are constrained in the same way. The constrained regression equation tested as the difference score model in polynomial regression is Z = b ₀ + b ₁X - b ₁Y (). is a graph of a plane in which the regression coefficients on X and Y are not constrained to be equal and opposite in magnitude. The 'unconstrained' regression equation of this graph is the following: Z = b ₀ + b ₁X + b ₂ Y. Comparing the results of this 'unconstrained' regression model with those of the constrained polynomial regression model (illustrated in ), a researcher can statistically infer whether the constraint imposed by the difference score is accurate or not.

Polynomial regression is fundamentally a model-fitting process; in the confirmatory approach, a researcher tests the relative model fit of the constrained to the unconstrained polynomial regression models by evaluating four criteria, regarding the accuracy of the constraints implied by the difference-score (or other a priori hypothesized model); see the Analysis Overview for an explanation of these criteria for assessing the fit of the algebraic difference score model, which is the model posited by the NCF (versus an absolute value difference score model, |X-Y|, e.g.). If a researcher wanted to test the relative fit of two constrained models (e.g., an algebraic versus an absolute-value difference score model), then the four criteria for good fit would be evaluated for each of the constrained models, through comparing them to their unconstrained versions; only one model could meet all criteria. Since only the algebraic difference score model is relevant to the NCF, the reader is referred to the general polynomial regression literature for more information regarding comparison of constrained models ( 22, 25).

Exploratory polynomial regression is used if the confirmatory approach results in rejection of the constrained model; it is used to test unconstrained models of increasing order (linear, quadratic, cubic, etc.) to find the best fitting polynomial model. The best-fitting model is the last model to explain significant incremental variance in the outcome; for example, if the linear and quadratic models (entered as separate steps in the hierarchical linear regression) both explain significant variance in the outcome but the cubic model does not, then the researcher concludes that the quadratic model is the best-fitting model ( 22). The regression coefficients of the final model can be graphed in three dimensions and statistically analyzed for hypothesized relationships, such as those posited by the bivariate evaluation plane theory. Confirmatory regression can then be used in a separate sample to test the accuracy of the final model of the exploratory polynomial regression (the same process used for factor analysis of a construct or constructs).

Polynomial regression not only allows for appropriate analysis of linear differences in ambivalent, indifferent, skeptical, and accepting evaluations of medications and adherence (as in ) but nonlinear effects as well. For example, see the hypothetical cubic surface in , in which the effect of reciprocal evaluations (adherence along line of incongruence, Y=-X) is exponential at the extremes of the necessity-beliefs and concerns scales (adherence increases exponentially as necessity beliefs increase and concerns decrease in equal units and decreases exponentially as concerns increase and necessity beliefs decrease in equal units), with a flat (equivalent) effect of co-activated evaluations (adherence is the same for high X, high Y as for low X, low Y).

The exact process used in the current study for testing the NCF is described in the next section and in the overview of the analyses in the Method section. See Phillips ( 23) for a more comprehensive review and explanation of polynomial regression for studying three-dimensional (congruence) relationships among health psychological constructs.

The current study: Assessing the NCF in a stroke-survivor population using polynomial regression

In the current study, we assess whether stroke (or transient ischemic attack, TIA) survivors' beliefs regarding their stroke-prevention medications predict their self-reported adherence to those medications as posited by the NCF. Unlike previous research in this area ( 12), however, we utilize polynomial regression to test hypotheses of the NCF: first, we use confirmatory polynomial regression to explicitly test the constraints of the algebraic difference score model-that is, we use an unconstrained regression model to test whether the constrained models used by other researchers (who use difference scores) are accurate (i.e., represent true relationships among variables in the population), at least within the current sample. Second, since the strict algebraic difference score model is rarely accurate ( 22, 27), we use exploratory polynomial regression to determine the best-fitting multidimensional model to explain the effects of patients' necessity beliefs and concerns on their adherence. We specifically test the possible differing effects on adherence of patients' ambivalent, indifferent, skeptical, and accepting attitudes towards their stroke-prevention medications, as posited by the NCF (note: these attitude domains are theoretically relevant to a multidimensional, linear model, and would not be relevant categories if the final model is found to be quadratic or cubic, for example).

Method

Participants and Procedure

Participants (n=600) were recruited into a stroke-prevention intervention trial targeted at stroke and transient ischemic attack (TIA) survivors in underserved communities in New York City (inclusion criteria: age ≥ 40 years, had at least one stroke or TIA in the past 5 years) (see 28, for a report of the larger intervention trial methods). After obtaining informed consent (read aloud when necessary), trained research staff conducted baseline, in-person interviews in English or Spanish at community venues and a large urban teaching hospital. Interviews, conducted prior to the intervention, included demographic variables. The Mount Sinai School of Medicine Human Research Protection Program approved all consent documents and procedures.

Measures

In addition to demographic variables, comorbidities, health utilization and health behaviors, we collected data on necessity beliefs and concerns, and detailed information on medication adherence. The specific necessity beliefs and specific concerns subscales of the Beliefs about Medicines Questionnaire (BMQ; 14) have been shown by many researchers in varied patient populations, including stroke survivors ( 12), to predict patients' medication adherence.

With respect to the concerns subscale, three items ask participants to rate the degree to which they worry about 'having to take your medicines', 'long-term effects of your medicines', and 'becoming too dependent on your medicines.' The fourth item asks how much 'medicines disrupt your life' and the fifth asks how much 'medicines are a mystery to you'. Based on the results of piloting the BMQ with representatives of our study population, we modified questions from the original instrument to make them more understandable to our study population which had low health literacy. Specifically, instead of asking participants to read each item and then rate their agreement with it, participants were directly asked each question by the interviewer. In addition, the response scale for the included items was reduced from the usual five options ('strongly disagree' to 'strongly agree') to four options (1-'not at all', 2-'a little bit', 3-'somewhat' and 4-'very much'). We were concerned that participants had difficulty understanding the fifth item. This item had a zero corrected item-total correlation with the other concern items, substantially negatively affecting the internal consistency of the scale; it was therefore not included in the composite of the concern items that was used in the statistical analyses.

The necessity subscale asks participants to rate how much 'your health depends on your medications', they would be 'ill without your medications', 'your health in the future depends on your medications', 'your life would be impossible without your medications', and 'your medicines protect you from becoming worse.' We adapted the necessity subscale in the same manner as the concerns subscale and participants were given the same response options as for the concerns items. Therefore, the concerns scale was an average of 4 items with higher scores indicating greater concerns regarding the medicines, and the necessity beliefs scale was an average of 5 items with higher scores indicating greater necessity beliefs regarding the medicines.

Medication adherence was measured using the 8-item Morisky Medication Adherence Scale (MMAS; 29), which is an 8-item measure with 7 yes/no items (e.g., 'Have you ever stopped taking your medication without telling your doctor because you felt worse when you took it? Yes/No') and one 5-option item ('How often do you have difficulty remembering to take all your medicines?'). Conventional scoring was used but reversed so that higher scores represent greater/better adherence.

For all three of the above scales, the interviewer did not ask patients to respond about a specific medication, as the patient may have been taking multiple medications within multiple categories with proven efficacy to prevent strokes. Therefore, patients could have answered the items with regards to one or more medicines they were currently taking for prevention of future stroke (for blood pressure control, cholesterol control, and/or blood thinners).

Analysis Overview

All analyses were conducted separately for patients who had suffered only a TIA, since suffering a stroke is more serious and could theoretically affect patients' beliefs and/or adherence. None of the results differed for TIA-only (n=284) compared to stroke-survivors (n=316), and so the results from combined analyses are reported below.

Confirmatory Polynomial Regression

There are four criteria that must be met using confirmatory polynomial regression in order to find support for the algebraic difference score model ( 22): first, the model (the unconstrained regression equation: Z = b ₀ + b ₁X + b ₂Y) must explain significant variance in the outcome, Z (adherence); second, the regression coefficients for the concerns and necessity subscales must be significant and in the expected direction (i.e., necessity beliefs should significantly, positively predict adherence; concerns should significantly, negatively predict adherence); third, the constraint imposed on the regression coefficients by the two-dimensional model (i.e. that b ₁=-b ₂ in order for Z = b ₀ + b ₁(X-Y)) should be accurate; this is equivalent to showing that the constrained/two-dimensional model should not significantly decrease explained variance in adherence from the unconstrained/three-dimensional model; lastly, the potential of more complex relationships should be ruled out-higher-order models should not explain significant variance beyond that explained by the linear terms of the unconstrained (and constrained) difference score model. If these criteria are met, then the strict hypotheses as tested by other researchers with regards to the NCF in other patient populations ( 3, 4, 6, 11) will be supported.

Exploratory Polynomial Regression

In exploratory polynomial regression, polynomial models of increasing order (unconstrained linear, quadratic, and cubic models) are tested for fit to the data, in a hierarchical regression, with the terms of each order model entered together as a step in the regression. The variance in adherence explained by each model is calculated, and the final, best-fitting model is the highest-order model that explains significant incremental variance in adherence from the preceding lower-order model. The regression coefficients of the final model are used to graph the results in three-dimensions; inference tests may be done to test specific relationships of interest (resources exist online for conducting these tests: see 23, 26). If the final model is linear, these tests will include calculating and testing the significance of the slope of the surface when patients' necessity beliefs and concerns are equal in magnitude; if the final model is quadratic or cubic, these tests will assess slopes and curvatures of the surface to assess how adherence is influenced by different combinations of necessity beliefs and concerns. All analyses were conducted in the current study using SPSS, version 17 (SPSS, Inc.).

Results

Demographics and descriptive statistics of study variables are presented in . Similar to previous studies, we found that patients' stroke-prevention necessity beliefs and concerns were not related as would be expected if they were opposite ends of the same conceptual dimension (for which they would have a correlation close to −1.0); in fact, the two subscales correlated positively with each other, although weakly (Pearson r(558) = 0.13, 95% CI = 0.05,0.21). If patients were to be grouped into categories by their attitudes towards medications (using a scale-centered split on necessity beliefs and on concerns), approximately 24% would be considered ambivalent, 13% indifferent, 4% skeptical, and 59% accepting.

Table 1

Variable/Characteristic

Possible or Observed Range

Mean (SD) or Percentage

Confirmatory Polynomial Regression of the algebraic difference score model

The necessity beliefs and concerns variables were scale-centered in order to reduce multicollinearity between the predictors and their higher order terms and to ease interpretation of the polynomial regression results ( 23, 30). Standardized values for each variable were calculated to identify univariate outliers; 6 patients had necessity-beliefs scores lower than 3 SD from the mean. Analyses were conducted with and without these cases included in the dataset, and results did not differ with their exclusion; therefore, the results reported below are with the 6 cases included in the dataset. Mahalanobis' distance values were calculated to identify potential multivariate outliers, of which there were none.

The results relevant to the four criteria required to support the strict algebraic difference score model, as inherently implied by previous tests of the NCF that used difference scores, are the following: 1.) The unconstrained model ((Adherence) = b ₀ + b ₁(necessity beliefs) + b ₂(concerns)) explained significant variance in patient adherence ( = 0.17, F(2,552)=55.58, p<0.001), meaning there are non-zero effects of the predictors on the outcome (the first necessary but not sufficient condition for demonstrating congruence effects that adhere to a difference score model); 2.) The regression coefficients for necessity beliefs and concerns were in the expected directions and had the expected significance (=0.25, p<0.01, 95%CI = 0.07,0.42, and = −0.81, p<0.001, 95%CI = −0.96, −0.66, respectively), which is also a necessary but not sufficient condition for confirming the difference score model; 3.) However, the unconstrained model predicted significant incremental variance to the constrained model ( F(1,552)=25.70, p<0.001), which means that the constraint, , was found to be inaccurate (rather than being equal in magnitude, the regression coefficient on the concerns subscale, −0.81, was greater in magnitude than that on the necessity-beliefs subscale, 0.25, so constraining the combined effect of necessity beliefs and concerns on adherence to be necessity beliefs minus concerns is not accurate); 4.) The higher-order terms did not predict significant incremental variance to the unconstrained model ( F(3,549)=2.04, p=0.11); since the third criterion was not met to confirm the difference score model, this fourth criterion did not strictly need to be assessed.

Exploratory Polynomial Regression

Because the confirmatory analysis resulted in rejection of the strict algebraic difference score model, exploratory polynomial regression was conducted to determine the best-fitting three-dimensional model of the data. The linear terms (X and Y for the scale-centered necessity-beliefs and concerns, respectively) were entered in the first step of the hierarchical regression, the quadratic terms (X ², Y ², XY) in the second step, and the cubic terms (X ³, X ²Y, XY ², Y ³) in the third step. Only the linear unconstrained model was significant. While the interaction term (XY) was significant in the quadratic model ( b=0.29, p=0.014), the overall quadratic step was not significant ( change < 0.01, F(3,549)=2.04, p=0.11); therefore, the final polynomial model that best fits the data is the linear model, which was graphed using the regression coefficients on necessity beliefs and concerns (see ). As explained in detail elsewhere ( 25), since the overall quadratic model was not significant, it would be inappropriate to keep and interpret only the interaction term in the final model. Briefly, there are two reasons why one would not test the interaction term separately from the other quadratic terms: first, the purpose of exploratory polynomial regression is to determine the best fitting shape/order polynomial model (i.e., to determine whether the data are best-fitted by a linear, quadratic, cubic, etc, model) and not to merely maximize variance explained in the outcome with variously-ordered terms. Second, testing the higher-order terms as a set after controlling for the lower-order terms is an omnibus test; similarly to other omnibus tests (e.g. ANOVA), testing or interpreting the individual terms of a model instead of as a set would inflate Type I error.

The graphs of the polynomial regression coefficients can be interpreted by evaluating the outcome and change in the outcome for different combinations of the predictors. For example, to answer the question, 'what happens to adherence as concerns increase and necessity beliefs decrease in equal units', one would look at the changes in the outcome along the line in the XY-plane called the line of incongruence (when X = -Y). As illustrated in , adherence was highest when necessity beliefs were high and when concerns were low and lowest when necessity beliefs were low and concerns were high (intuitive, reciprocal effects). Equivalently, in congruence terms, adherence was most positively affected along the line of incongruence-i.e., when concerns decreased and necessity beliefs increased in equal measure. A statistical inference test can be conducted to see if the observed change in adherence along this line of incongruence is significant ( 23, 26). Here the test is whether the slope of the surface (i.e., changes in adherence) when X=-Y is significantly different from zero; this slope was significantly positive (slope = 1.06, t(549) = 5.70, p < 0.001), meaning adherence increased as necessity beliefs increased and concern decreased (in equal units: e.g., from X,Y = 0,0 to 1, −1 to 2, −2). Formulas for calculating relevant slopes and curvatures of surfaces are available in existing publications and online ( 23, 26).

Co-activated, or non-reciprocal effects are also evident and would not have been identified using 'two-dimensional' analysis of the difference score (Necessity Beliefs - Concerns), which constrains adherence to be the same for all values of X-Y (to be equal when both X and Y are high and when both X and Y are low, e.g.): specifically, adherence was greater when both concerns and necessity beliefs were low than when both concerns and necessity beliefs were high. This can be seen in by following the surface from the front corner (when X and Y are both low) diagonally to the back corner (when X and Y are both high). This can be seen statistically from the slope of the surface along the line of congruence or co-activated effects (when X=Y); this slope was −0.56 ( t(549) = −3.01, p = 0.003), meaning adherence decreased as X and Y both increased (e.g., from X,Y = 0,0 to 1,1 to 2,2). The differences between the difference score model and the final model can be seen in the differences between Figures 1b and 1d : the three-dimensional representation of the algebraic difference score model () constrains the adherence levels for when X = Y (whether both are high or low) to be equal, whereas the adherence levels seen in differ when attitudes are ambivalent (X and Y, or necessity beliefs and concerns, are both high) from when they are indifferent (X and Y are both low).

Discussion

In the current study, we used polynomial regression to analyze the coupled effects of stroke survivors' medication-related concerns and necessity beliefs on their self-reported adherence. O'Carroll et al. ( 12) were the first, to our knowledge, to test the influence of patients' concerns and necessity beliefs on adherence to stroke-prevention medication; they tested the separate/independent effects of necessity beliefs and concerns on adherence and did not test the effect of their difference score, finding that only the concerns were significantly related to patient-reported adherence.

The current results extend this research by using polynomial regression to assess the combined effects of necessity beliefs and concerns on adherence as posited by the NCF. The results show that while the general premise of the NCF may be correct-that patients are less adherent when concerns outweigh necessity beliefs and are more adherent when necessity beliefs outweigh concerns-the effect of these positive and negative evaluations on adherence is more complex. The confirmatory polynomial regression ruled out a strict difference score model as the best-fitting model-the model that is typically implied by tests of the NCF (i.e., difference-score analyses; e.g., 14). The exploratory polynomial regression found that patients with ambivalent attitudes towards their medications (strong concerns and strong necessity beliefs) had lower reported adherence than did patients with indifferent attitudes (weak concerns and weak necessity beliefs). This is the opposite finding to Cacioppo and Gardner's ( 17) study on blood donation, in which more blood was donated by those who were ambivalent rather than indifferent towards blood donation. The more negative association of ambivalent attitudes with adherence compared to indifferent attitudes in the current study is due to the stronger bivariate effect of patients' concerns on adherence compared to the bivariate effect of patients' necessity beliefs on adherence. It may be that necessity beliefs are more important for blood donation, a singular low-risk event. In contrast, concerns are more important for stroke-prevention medication adherence, requiring daily medication use with known side effects to avoid a high risk, previously experienced event. For a definite interpretation, the blood donation findings would need to be replicated with polynomial regression rather than artificial patient categories.

Polynomial regression is an analysis tool best used in research (rather than practice) to provide the best possible picture of the relationships between patients' beliefs and behavior that can then be translated to use in practice by clinicians. The current results, for example, could be translated into the following guidelines for clinicians: when discussing patients' necessity beliefs and concerns regarding their stroke-prevention medications, a clinician should note not only their relative difference (whether concerns seem to be greater than beliefs in the medication's necessity) but take into account their absolute levels as well (whether both are relatively high or low). Clinicians working with stroke or TIA survivors should be aware that probing for concerns and for necessity beliefs is important but that a conversation with patients may be more helpful to clinicians in assessing the combined effects of these two types of beliefs on the patients' adherence to stroke-prevention treatment and in optimizing patient satisfaction, understanding, and subsequent adherence to the medications. Assessing concerns and necessity beliefs as discrete constructs may not be sufficient to understand the interplay of the positive and negative attitudes towards the medications on the patients' likeliness to adhere to those medications. More research would be required to test the feasibility and the effectiveness of addressing patients' concerns and necessity beliefs for increasing adherence to stroke-prevention medications; it is possible that addressing these beliefs (or only one type) is not feasible (interventions might not change these beliefs), or it is possible that even if belief-change is possible, these changes might not result in adherence changes (see 31 for an example of a successful intervention in asthma patients).

The exploratory approach to polynomial regression, like any other exploratory analysis (e.g. exploratory factor analysis), is a model-fitting approach that requires replication or cross-validation before hypotheses are built and tested from the results (see, e.g., 32). Therefore, replication of the current study results is required before any implicated practice changes are implemented.

Some limitations of the current study may have affected the relationships assessed. Regarding use of polynomial regression for assessment of the NCF: the necessity beliefs and concerns of patients regarding their medications are not merely positive and negative attitudes-they are specific to certain aspects or consequences of the medications, which may qualitatively differ from each other (e.g., concerns include the effect of the medication on non-health related issues whereas necessity beliefs focus on benefits of medication for illness). Polynomial regression is used for predictors that can be qualitatively matched on commensurate scales ( 25). However, the BMQ necessity-beliefs and concerns subscales are designed to be composites that overall represent patients' positive and negative beliefs, or evaluations, towards a treatment. This is not the first paper to discuss necessity beliefs and concerns as positive and negative evaluations that may be coupled as in the bivariate evaluation plane theory: for example, Aikens et al. ( 11) specified couplings of concerns and necessity beliefs as attitudes representing patient ambivalence, indifference, skepticism, and acceptance-but they used 'two-dimensional' methods to assess differences in these groups on adherence.

A limitation of the data was that patients were asked to report their beliefs about and adherence to medications in general, not for each specific medication; we were unable to parcel evaluations for different medications from each other and for predicting adherence. Patients have been shown to be differentially adherent to medications and concerns and necessity beliefs may be different for different medications; it is therefore possible that different relationships between patients' necessity beliefs, concerns, and adherence could exist for different medications. However, the medications that the patients named were all relevant for stroke prevention (antithrombotics/blood-thinners, blood pressure medications, and cholesterol lowering medications). Therefore, the grouping of medications does have the advantage of relevancy for this population and health concern, which is why the questions were asked in the way they were.

It is important to note that major changes were made to the BMQ specific items and response frame. Although the changes were discussed and agreed upon with the scales' originator due to findings of the pilot testing, the alterations to the items limit synthesizing of the current results with other studies that have used the original form of the BMQ. Further, it is possible that subsequent research in this population that uses the original response options may provide different results.

Lastly, the concurrent assessment of the patients' beliefs and adherence reports limits conclusions regarding how these beliefs may affect future adherence. It is possible that patients' reports of their beliefs were affected by their reflections on their recent adherence, for example. Therefore, subsequent research will need to utilize a prospective design to test (using a confirmatory polynomial regression approach) the linear model implied by the current results.

The analytic method of polynomial regression holds great promise for future tests of the NCF in varied patient and illness populations, in addition to other theoretical models that are used to assess congruence, or three-dimensional relationships between two predictors and an outcome. The current study's results, the overall known issues of difference scores and other methods that collapse separate dimensions, and the multidimensional nature of the NCF all strongly indicate that polynomial regression should be used in future studies of patients' medication-related evaluations and their medication adherence. Although a linear plane was found to be the best-fitting model to the data, other types of surfaces are possible, such as curvilinear or exponential effects (such as the hypothetical cubic surface in ). Also, one might hypothesize different surfaces/relationships for those who experience side effects compared to those who do not. For example, if concerns are more serious, then they would have a greater effect on adherence and the combined effect of concerns and necessity beliefs on adherence might change.

In general, future studies could utilize polynomial regression to investigate the three-dimensional relationships posited by the bivariate evaluation plane theory, between positive and negative evaluations of various treatments for various chronic illnesses. Researchers could test whether negative evaluations are more predictive of behavior than positive evaluations for health behaviors in general, or alternatively, if the effects of positive and negative evaluations are illness- and/or treatment-dependent, which would suggest differing approaches by medical providers to promote adherence for different illnesses and/or treatments.

Acknowledgments

Funding: National Institute on Minority Health and Health Disparities [#5P60MD000270] and the National Center for Advancing Translational Sciences [UL1TR000067].

Footnotes

Conflict of Interest Statement: The authors have no conflict of interest to disclose.

References

2. Haynes RB, Ackloo E, Sahota N, McDonald HP, Yao X. Interventions for enhancing medication adherence. Cochrane Database of Systematic Reviews. 2008:CD000011. doi: 10.1002/14651858.CD000011.pub3.

11. Aikens JE, Nease DE, Nau DP, Klinkman MS, Schwenk TL. Adherence to maintenance-phase antidepressant medication as a function of patient beliefs about medication. [ PMC free article]

22. Edwards JR. Alternatives to difference scores: Polynomial regression analysis and response surface methodology. In: Drasgow F, Schmitt NW, editors. Advances in Measurement and Data Analysis. San Francisco, CA: Jossey-Bass; 2002. pp. 350-400.

23. Phillips LA. Congruence research in behavioral medicine: Methodological review and demonstration of an alternative methodology. J Beh Med. 2013;36(1):61-74. doi: 10.1007/s10865-012-9401-9.

28. Peer education for secondary stroke prevention in inner-city minorities: Design and methods of the Prevent Recurrence of All Inner-city Strokes through Education randomized controlled trial. Contemp Clin Trials. 2012 Jun; In press. [ PMC free article]

29. Morisky DE, Ang A, Krousel-Wood M, Ward H. Predictive Validity of a Medication Adherence Measure for Hypertension Control. J Clin Hypertens. 2008;10(5):348-54. [ PMC free article]

30. Aiken LS, West SG. Multiple regression: Testing and interpreting interactions. Newbury Park, London: Sage; 1991.

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Patients' medication-related concerns and necessity-beliefs predict adherence. Evaluation of the potentially complex interplay of these two dimensions has been limited because of methods that reduce them to a single dimension (difference scores). We use polynomial regression to assess the multidimensional effect of stroke-event survivors' medication-related concerns and necessity-beliefs on their adherence to stroke-prevention medication.

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As the connected medication adherence space matures, companies that have led the space for the past few years are fine-tuning their technology platforms, business models, and approaches to efficacy.

At the Partners Connected Health Symposium in Boston today, representatives from Abiogenix, AdhereTech, AiCure, and Medisafe shared updates on their shared mission to combat the $290 billion medication adherence problem in the country.

Among the most interesting of those updates was from Medisafe EVP of Marketing and Business Development Jon Michaeli, who shared the news, originally announced a few months ago, that the company is moving into hardware via a partnership with TimerRx.

"In about a month we will be shipping Bluetooth-connected pill bottle caps that retrofit on 95 percent of amber vials, that when opened will communicate to Medisafe that a patient has taken their medication," Michaeli said. "Because the infrastructure is in the cloud, we are gathering all of these insights, all of this data within that platform that can then be shared appropriately, sometimes in a deidentified fashion, sometimes with patient opt-in, actual patient data can flow through to doctors, nurses, specialty pharmacists, etc."

The devices, called Medisafe iConnect, will be sold in two form factors: a smart cap and a smart pillbox with multiple compartments. They will be available direct to consumer for $20 and $50 respectively.

"We wanted something that could be available to the mass market," he said. "We didn't have to question affordability or who's going to reimburse."

The partnership seems to bring Medisafe into a closer space with AdhereTech and Abiogenix, which both make connected pill containers. Both those companies have refined their approach and their business models.

AdhereTech CEO Josh Stein said that his company is increasingly distributing its smart pillboxes via relationships with specialty pharmacies, such as Avella, their main distribution partner in the United States. He says they're also just starting to work with payers.

"Most of our customers are not payers, it's typically pharma or specialty pharmacies, but we do work with a few payers," he said. "In our experience they've been a little bit slower to invest time and resources in medication adherence technologies. The one area we've seen adoption with payers is in the Hepatitis C space. Some Hep C medications are incredibly expensive. It requires a lot of upfront payment to pay for this medication, but if the patient doesn't take the medication that leads to even more in treatment costs. That's where we've seen adoption."

Abiogenix, whose uBox smart pillbox can be locked, has found its niche with mental health and addiction recovery and is working with rehab centers as some of its initial partners, according to CEO Sara Cinnamon. She said one of the biggest learnings has been to make the device helpful but unobtrusive.

"If you make the interaction as natural as possible, you're going to get the most authentic data," she said. "But if you make it so annoying that people turn the handle just to turn off the alarm, we don't want that. So we make it very easy to snooze or dismiss an alarm, and the noise itself is customizable to how loud do you want it. Maybe it goes off once every two minutes, realizing we all have real lives and maybe we can't get to it whenever we want to."

Finally, all the panelists talked about the importance of establishing robust efficacy data for their various devices. Adam Hanina, CEO of AiCure, which uses visual AI to confirm that a patient has taken a medication dose, said they're careful about their outcome measures.

"You need to have an accurate validation system," he said. "We don't believe that validation through self-reporting is really a reliable means to confirm that someone's doing something correctly. It's like asking someone to self-report their driving speed down the highway. If you have an accurate mechanism - at AiCure we use drug concentration levels in the blood - it's critical to show that evidence. Because then people begin to trust your technology."

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Medication adherence startups talk hardware, reimbursement, efficacy

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As the connected medication adherence space matures, companies that have led the space for the past few years are fine-tuning their technology platforms, business models, and approaches to efficacy. At the Partners Connected Health Symposium in Boston today, representatives from Abiogenix, AdhereTech, AiCure, and Medisafe shared updates on their shared mission to combat the $290 billion medication adherence problem in the country.

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Multiple factors that can impact the individuals quality of life:

Ø  Combined ART has changed the way people live with the chronic disease- this has increased survival and has improved the patients quality of life.

Ø  Psychosocial aspects of HIV- positive status shows that living with HIV is associated with a large measure of stress and depression. It is widely evidenced that those with HIV have greater rates of depression. Warren, (1984) reported that 20% of LGBT teenagers had either contemplated or even attempted suicide because of the issues they face surrounding their sexual orientation.  The prevalence of depression in HIV has ranged from 22-38% (Kelly, 1999).

Ø  Individuals who confronted stress with a problem-solving attitude were found to have a significant better QOL than those who were not using a coping mechanism.

Ø  A new issue that people face is that they have to balance medication and employment- patients with the HIV infection must frequently adapt to the nature of the illness.

Ø  Various psychological problems, such as stigma, poverty, depression which can affect their QOL. Income, emotional, social support and problem and perception orientated coping were related to QOL.

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The term is now widely used in many research journals, however the actual definition is one that is fairly inconsistent. The term is used to convey an overall sense of well-being such as happiness and how satisfied you are with the life that you are living. As HIV/AIDS has gone from a disease in which you were “dying from” to one where that is “living with” through the development of successful treatments such as Highly Active Antiretroviral Therapy, the survival of these patients has increased then it can be subjectively assumed that so has the QOL.  Those who have been diagnosed with HIV often have to cope with a range of HIV -related symptoms for extended period of times.  Symptoms may be related to the infection itself, comorbid illnesses or toxicities from HIV-related medications. Further to this, many HIV patients struggle with numerous social problems such as stigma, poverty depression which can affect their QOL.

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According to the UNAIDS there are approximately 36.7 million people worldwide that have are living with HIV/AIDS. It was further reported that an estimated 1.8 million people were diagnosed with HIV in the year of 2016 Of that number, 160,000 children were infected by their HIV+ positive mothers through child birth or breastfeeding. Most of these cases were reported in Sub-Saharan Africa whereby, many people in impoverish communities have no or very little access to antiretroviral medication. As of July, 2017 20.9 million have access to the appropriate medication.

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Electronic medication- description and evaluations

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> Leads to reductions in viral load,
>greater immune system function
> less likelihood of clinical immune deficiency in patients with the HIV diagnosis
Almost perfect adherence to HIV medication is critical for a successful outcome. HAART medication often requires the patient to take pills for a long duration, often the dosage levels change with some requirements changing in terms of food intake patterns such as on an empty stomach, taken with meals, some with fatty and non fatty good and some storage requirements. Inevitably this confusion for the correct procedure often causes individuals to fail to adhere.
HAART also requires the patient to take the medication even if they show no visible signs of symptoms, therefore side effects may emerge from taking the medication.

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High adherence to HAART is a key determinant of the degree and durability of viral suppression,  findings have reported that it has been positively associated with lower rates of disease progression, hospitalization and mortality (Press, 2002). For those that fail to adhere to the medication, this is correlated with treatment failure and can limit options for future antiretroviral therapies due to cross- resistance between HIV drugs. Complicated HIV regimens, medication side effects and toxicities, high pill burdens and psychosocial factors all contribute to non-adherence (Singh, 1999; Ferguson, 2002).

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Patient factors: demographic factors- African Americans and other ethnic minorities may have lower adherence- seem to be a correlation between high adherence  and the patients perceived importance of taking all doses as prescribed, and perceived social support.
Lower adherence seems associated with fear of toxicity.
Health care services and communication
Good institutional services were almost uniformly associated with adherence
Majority of physicians report that they counsel patients on adherence at most or all of follow- up visits. In a questionaire however, physicians have identified lack of time, resources and education as important barriers to their communication with HIV+ patients about adherence.

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Previous studies have demonstrates that the rates of non-adherence for medications within the general population can range from 15% to 93% (Haynes, 1979). Whilst HIV adherence is one of the highest amounts for general adherence to medication, the results are still not 100%, in a study of HIV treatment, only 30% of patients within the study were able to attain this level of 95% (Paterson, 2000).

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Nurses were found to be dedicated and the way they communicated with patients encouraged them to feel cared for.

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Health & social care for HIV | Topics, HIV, Long term conditions, People's Experiences | healthtalk.org

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Make collections of pages and videos that interest you.

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Illness behaviour and the numerous stages people go through including the sick role.

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Cognitive behavioural stress management- is a short therapeutic approach that is used to focus on how people's thoughts affect their emotions. Overall CBSM has been found to improve the quality of life for clients.
CBSM can improve the HIV+ person's quality of life by decreasing the distress and depressive thoughts that are associated  with having a chronic disease.
CBSM also uses a technique whereby they encourage the individual to be more accepting and positive towards themselves which has been found to lead to increased social support.
May lead to stress reduction as the individual is encouraged to talk about their emotions and what they are going through- through getting the negatives out their they can being to focus on life and how to eradicate these negative thoughts.

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Most people experience a short flu like illness which only lasts a couple of weeks- the individual will presumably just wait this out, may take some antibiotics to try and eliminate the discomfort.
These symptoms may disappear and the HIV virus may not cause any other symptoms for many years, however internally the virus is continually replicating and damaging the immune system. At this stage, no action will be carried out as they are unaware, the individual will still be living a normal sex life.
HIV will now produce many symptoms- they may visit the doctor who will let them know they have HIV. The individual will then begin to take antiretroviral therapy.

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Health/ Illness behaviours that characterise HIV

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Health/ Illness behaviours that characterise HIV

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Suchman, (1965) devised an approach for studying illness behaviour which can be subjectively translated to HIV.
Stage 1: Symptom experience: The illness experience is intitiated when the individual senses that something is wrong. For those with HIV this will be the flu- like symptoms at the beginning of the virus.
Assess the illness through perceived seriousness- the individual may believe that they just have flu like symptoms and nothing more.
Stage 2: They accept that they are not well and transition to the " sick role" which is the new role- those with HIV may begin to feel sluggish and deflated from the flu.
Stage 3: Medical Care Contact/ Self-care- at this stage those with HIV may seemingly forget that they had this period of unrest and show no further symptoms. However, once the symptoms return they make seek help from the GP who will then subsequently diagnose them. Due to the male stereotype they may be reluctant to see a physician especially if they have a viewpoint of being "tough" and may be embarrassed to discuss sexual matters to a healthcare professional.
Stage 4: Recovery and Rehabilitation
By this stage those with HIV have began the treatment for HIV- HAART and will have to adhere to the oral medication.

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Interventions to increase antiretroviral adherence 

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Interventions to increase antiretroviral adherence 

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The success of antiretroviral treatment for dealing with HIV infection is primarily determined by adherence. In a recent systematic review of evidence of Sub-Sharan Africa- directly observed therapy, mobile phone text messages, diary cards and food rations can increase adherence.

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africa south of the sahara;hiv infections;humans;medication adherence;outcome assessment (health care)

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Interventions to increase antiretroviral adherence in sub-Saharan Africa: a systematic review of evaluation studies. - PubMed - NCBI

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Self- Efficacy- Lazarus and Folkman, (1984) suggested that self- efficacy was an important factor for mediating stress response- refers to an individuals feeling of confidence that they can perform the desired action. Self- efficacy in those with HIV can also be related back to the concepts of literacy and the availability of education. Wolf et al.,(2007) found that one third of patients in the sample were less than 100% adherent to their HAART regime and patient literacy levels was associated with more than a three fold likelihood of missed doses. This provides the general support that the lack of support and self efficacy was linked to improper adherence to antiretroviral regimens.

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Intervention- Focusing on education and persuasion in terms of making sure that the individual is aware of how important adherence to the drugs are and the damage if they miss the optimal rate of adherence. Peer education interventions have been a frequent strategy for preventing HIV. The prevention is based on the premise that peers have a strong influence on individual behaviour, as they have a certain level of trust and comfort when discussing topics like HIV. Medley, Kennedy, O'Reilly and Sweat, 2009) found that peer education interventions were associated with increased HIV knowledge and increased condom use.
Education programs and the adherence to antiretroviral therapy- Increasing attention to improve adherence Goujard et al., 2003- patients were given therapeutic planning cards, and took part in one hour sessions over 12 months. Findings: Benefit of the intervention was found at 6 months- consistent impact on knowledge and CD4 cell count. The majority of the patients showed 100% adherence to the number of pills taken.

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Health Belief Model in relation to the different concepts and the importance of them in relation to HIV prevention

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Application of the Health Belief Model (HBM) in HIV Prevention: A Literature Review :: Science Publishing Group

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As part of a study that explored the factors associated with consistent condom use among senior secondary school female learners in Mbonge subdivision of rural Cameroon, the Health Belief Model (HBM) was used as the framework.

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HIV-related stigma and discrimination refers to prejudice, negative attitudes and abuse directed at people living with HIV and AIDS. In 35% of countries with available data, over 50% of people report having discriminatory attitudes towards people living with HIV. 1

Stigma and discrimination also makes people vulnerable to HIV. Those most at risk to HIV (key affected populations) continue to face stigma and discrimination based on their actual or perceived health status, race, socioeconomic status, age, sex, sexual orientation or gender identity or other grounds. 2

Stigma and discrimination manifests itself in many ways. Discrimination and other human rights violations may occur in health care settings, barring people from accessing health services or enjoying quality health care. 3 Some people living with HIV and other key affected populations are shunned by family, peers and the wider community, while others face poor treatment in educational and work settings, erosion of their rights, and psychological damage. These all limit access to HIV testing, treatment and other HIV services. 4 5

The People Living with HIV Stigma Index documents the experiences of people living with HIV. As of 2015, more than 70 countries were using the HIV Stigma Index, more than 1,400 people living with HIV had been trained as interviewers, and over 70,000 people with HIV have been interviewed. 6 Findings from 50 countries, indicate that roughly one in every eight people living with HIV is being denied health services because of stigma and discrimination. 7

Whenever AIDS has won, stigma, shame, distrust, discrimination and apathy was on its side. Every time AIDS has been defeated, it has been because of trust, openness, dialogue between individuals and communities, family support, human solidarity, and the human perseverance to find new paths and solutions.
- Michel Sidibé, Executive Director of UNAIDS 8
The fear surrounding the emerging HIV epidemic in the 1980s largely persists today. At that time, very little was known about how HIV is transmitted, which made people scared of those infected due to fear of contagion.

This fear, coupled with many other reasons, means that lots of people falsely believe:

HIV and AIDS are always associated with death

HIV is associated with behaviours that some people disapprove of (such as homosexuality, drug use, sex work or infidelity)

HIV is only transmitted through sex, which is a taboo subject in some cultures

HIV infection is the result of personal irresponsibility or moral fault (such as infidelity) that deserves to be punished

inaccurate information about how HIV is transmitted, which creates irrational behaviour and misperceptions of personal risk.

- Patience Eshun from Ghana, who lost her daughter to an AIDS-related illness 10
My daughter refused to go hospital to receive medicines. My daughter died because of the fear of stigmatization and discrimination

HIV-related stigma and discrimination exists worldwide, although it manifests itself differently across countries, communities, religious groups and individuals. In sub-Saharan Africa, for example, heterosexual sex is the main route of infection, which means that HIV-related stigma in this region is mainly focused on infidelity and sex work. 11

Research by the International Centre for Research on Women (ICRW) outlines the possible consequences of HIV-related stigma as:

loss of income and livelihood

loss of marriage and childbearing options

poor care within the health sector

withdrawal of caregiving in the home

loss of hope and feelings of worthlessness

loss of reputation.

Stigma and discrimination is often directed towards key affected populations such as men who have sex with men (sometimes referred to as MSM), people who inject drugs and sex workers.

These people are increasingly marginalised, not only from society, but from the services they need to protect themselves from HIV. For example, in 2016, 60% of countries in the European Economic Area reported that health care professionals' negative and discriminatory attitudes towards men who have sex with men and people who inject drugs hampered the provision of adequate HIV prevention services for these groups. 13

More than 90% of new HIV infections in Central Asia, Europe, North America, the Middle East and North Africa in 2014 were among people from key populations and their sexual partners, who accounted for 45% of new HIV infections worldwide in 2015. 14 Recent studies suggest that, globally, people who inject drugs are 24 times more likely to acquire HIV than the general population, sex workers are 10 times more likely and men who have sex with men are 24 times more likely. Moreover, transgender people are 49 times more likely and prisoners are five times more likely to be living with HIV than adults in the general population. 15

UNAIDS and the World Health Organization (WHO) cites fear of stigma and discrimination as the main reason why people are reluctant to get tested, disclose their HIV status and take antiretroviral drugs (ARVs). 16

One study found that participants who reported high levels of stigma were over four times more likely to report poor access to care. 17 This contributes to the expansion of the global HIV epidemic and a higher number of AIDS-related deaths.

An unwillingness to take an HIV test means that more people are diagnosed late, when the virus may have already progressed to AIDS. This makes treatment less effective, increasing the likelihood of transmitting HIV to others, and causing early death.

For example, in the United Kingdom (UK), many people who are diagnosed with HIV are diagnosed at a late stage of infection, defined as a CD4 count under 350 within three months of diagnosis. Although late diagnosis of HIV has declined in the UK in the last decade, from 56% in 2005 to 39% in 2015, this figure remains unacceptably high. 18

In South Africa, stigma stopped many young women involved in a trial on HIV prevention from using vaginal gels and pills that would help them stay HIV free. Many reported being afraid that using these products would lead them to being mistakenly identified as having HIV, and so the fear of the isolation and discrimination that being identified as living with HIV would bring led them to adapt behaviours that put them more at risk of acquiring the virus. 19

The epidemic of fear, stigmatization and discrimination has undermined the ability of individuals, families and societies to protect themselves and provide support and reassurance to those affected. This hinders, in no small way, efforts at stemming the epidemic. It complicates decisions about testing, disclosure of status, and ability to negotiate prevention behaviours, including use of family planning services. 20

In 2015, WHO released new treatment guidelines that reflect the need to address stigma and discrimination as a barrier to accessing HIV treatment. 21

HIV and AIDS-related stigma can lead to discrimination, for example, when people living with HIV are prohibited from travelling, using healthcare facilities or seeking employment.

Self-stigma/internalised stigma

Self-stigma, or internalised stigma, has an equally damaging effect on the mental wellbeing of people living with HIV or from key affected populations. This fear of discrimination breaks down confidence to seek help and medical care. 22

Self-stigma and fear of a negative community reaction can hinder efforts to address the HIV epidemic by continuing the wall of silence and shame surrounding the virus. Negative self-judgement resulting in shame, worthlessness and blame represents an important but neglected aspect of living with HIV. Self-stigma affected a person's ability to live positively, limits meaningful self agency, quality of life, adherence to treatment and access to health services. 23

In Zimbabwe, Trócaire and ZNNP+ designed, implemented and evaluated a 12-week pilot programme to support people living with HIV to work through self-stigmatising beliefs. After the 12 weeks, participants reported profound shifts in their lives. The majority of participants (61%) reported a reduction in self-stigma, depression (78%) and fears around disclosure (52%), and increased feelings of satisfaction (52%) and daily activity (70%). 24

Evidence suggests people from key affected populations are also disproportionally affected by self-stigma. For example, a study of men in China who have sex with men found that depression experienced by participants due to feelings of self stigma around homosexuality directly affected HIV testing uptake. 25

Similarly, a study of men in Tijuana, Mexico who have sex with men found that self-stigma was strongly associated with never having tested for HIV, while testing for HIV was associated with identifying as being homosexual or gay and being more 'out' about having sex with men. 26

In countries that are hostile to men who have sex with men and other key populations, innovative strategies are needed to engage individuals in HIV testing and care programmes without exacerbating experiences of stigma and discrimination.

I am afraid of giving my disease to my family members-especially my youngest brother who is so small. It would be so pitiful if he got the disease. I am aware that I have the disease so I do not touch him. I talk with him only. I don't hold him in my arms now.

Governmental stigma

A country's discriminatory laws, rules and policies regarding HIV can alienate and exclude people living with HIV, reinforcing the stigma surrounding HIV and AIDS.

In 2014, 64% of countries reporting to UNAIDS had some form of legislation in place to protect people living with HIV from discrimination. 28 While, conversely, 72 countries have HIV-specific laws that prosecute people living with HIV for a range of offences. 29
Case study: Ending criminalisation of HIV transmission in Australia
Criminalisation of key affected populations remains widespread with 60% of countries reporting laws, regulations or policies that present obstacles to providing effective HIV prevention, treatment, care and support. 30 As of 2016, 73 countries criminalised same sex activity, 31 and injecting drugs use is widely criminalised, leading to high incarceration levels among people who use drugs. 32

More than 100 countries criminalise sex work or aspects of sex work. 33 Even in countries where sex work is at least partially legal the law rarely protects sex workers and many are at risk of discrimination, abuse and violence from both state and non-state actors such as law enforcement, partners, family members and their clients. 34 For example, some 15,000 sex workers in China were detained in so-called custody and education centres in 2013. 35

Laws that criminalise HIV non-disclosure, exposure and transmission perpetuate stigma and deter people from HIV testing and puts the responsibility of HIV prevention solely on the partner living with HIV.

In May 2015, the Australian state of Victoria repealed the country's only HIV-specific law criminalising the intentional transmission of HIV. The repealed law - Section 19A of the Crimes Act 1958 - carried a maximum penalty of 25 years imprisonment, even more than the maximum for manslaughter (which is 20 years).

The legislation to repeal the law was developed through the collaboration of several stakeholders, including legal, public health and human rights experts and representatives of people living with HIV. It was seen as a major step forward for the rights of people living with HIV.

Restrictions on entry, travel and stay

As of September 2015, 35 countries have laws that restrict the entry, stay and residence of people living with HIV. In 2015, Lithuania became the most recent country to remove such restrictions. 39

As of 2015, 17 countries will deport individuals once their HIV positive status is discovered, five have a complete entry ban on people living with HIV and four require a person to be able to prove they are HIV negative before being granted entry. 40

Deportation of people living with HIV has potentially life-threatening consequences if they have been taking HIV treatment and are deported to a country that has limited treatment provision. Alternatively, people living with HIV may face deportation to a country where they would be subject to even further discrimination - a practice that could contravene international human rights law. 41

Healthcare stigma

Healthcare professionals can medically assist someone infected or affected by HIV, and also provide life-saving information on how to prevent it. 42However, HIV-related discrimination in healthcare remains an issue and is particularly prevalent in some countries. It can take many forms, including mandatory HIV testing without consent or appropriate counselling. Health providers may minimise contact with, or care of, patients living with HIV, delay or deny treatment, demand additional payment for services and isolate people living with HIV from other patients. 43

For women living with HIV, denial of sexual and reproductive health and rights services can be devastating. For example, 37.7% of women living with HIV surveyed in 2012 in a six-country study in the Asia-Pacific region reported being subjected to involuntary sterilisation. 44
Case study: Reducing stigma and discrimination among healthcare workers in Thailand
Healthcare workers may violate a patient's privacy and confidentiality, including disclosure of a person's HIV status to family members or hospital employees without authorisation. 45 Studies by WHO in India, Indonesia, the Philippines and Thailand found that 34% of respondents reported breaches of confidentiality by health workers. 46

People from key affected populations may face additional discrimination in healthcare settings. Discriminatory attitudes held by health providers may also lead them to make judgements about a person's HIV status, behaviour, sexual orientation or gender identity, leading individuals to be treated without respect or dignity. These views are often fuelled by ignorance about HIV transmission routes among healthcare professionals. 47

In 2012, half of all people living with HIV in Thailand were starting treatment very late and had CD4 counts under 100. HIV stigma was identified as a major barrier to service uptake so health authorities set a target to cut HIV-related stigma and discrimination by 50% by 2016.

The Ministry of Public Health found that over 80% of healthcare workers had at least one negative attitude to HIV, while roughly 20% knew colleagues who were unwilling to provide services to people living with HIV or provided them substandard services.

More than half of respondents reported using unnecessary personal protection measures such as wearing gloves when interacting with people living with HIV. 25% of people living with HIV surveyed said that they avoided seeking healthcare for fear of disclosure or poor treatment, while a third had their status disclosed without their consent.

In response to these findings, the Ministry of Public Health, in collaboration with civil society and international partners developed initiatives to sensitise healthcare workers in both clinical and non-clinical settings.

Early results in 2014 indicated that improving the attitude of healthcare workers doesn't just improve care for people living with HIV but has wider societal benefits as they are seen as role models.

As of 2017, Thailand had collected data from 22 provinces. The Thai Ministry of Public Health is rolling out an accelerated system-wide stigma reduction programme, in collaboration with civil society and concerned communities.

A study of health providers in urban health facilities in India found 55-80% of providers displayed a willingness to prohibit women living with HIV from having children, endorsed mandatory testing for female sex workers (94-97%) and stated that people who acquired HIV through sex or drugs "got what they deserved" (50-83%). 54

These experiences may leave people living with HIV and people from key affected populations too afraid to seek out healthcare services, or be prevented from accessing them - for instance, if a nurse refuses to treat a sex worker after finding out about their occupation. It also prevents many people from key affected populations being honest with healthcare workers if they're a sex worker, have same-sex relations, or inject drugs, meaning they are less likely to get services that could help them. 55

When I visited a VCT [voluntary counseling and testing] clinic, health personnel were not polite and immediately asked me if I was a sex worker. A doctor asked me outright, 'Are you HIV positive?' This discouraged me from going to the clinics.

Employment stigma

In the workplace, people living with HIV may suffer stigma from their co-workers and employers, such as social isolation and ridicule, or experience discriminatory practices, such as termination or refusal of employment. 57

Evidence from the People Living with HIV Stigma Index suggests that, in many countries, HIV-related stigma and discrimination are as frequently or more frequently a cause of unemployment or a denial of work opportunity as ill health. 58
- HIV-positive woman, UK 60
Key findings from people living with HIV in nine countries across four regions in 2012 found that, as a result of their HIV status, between between 8% (Estonia) and 45% (Nigeria) of respondents had lost their job or source of income; between 5% (Mexico) and 27% (Nigeria) were refused the opportunity to work, and between 4% (Estonia) and 28% (Kenya) had the nature of their work changed or had been refused promotion. In addition, 8% of respondents in Estonia to 54% in Malaysia reported discriminatory reactions from employers once they were aware of the employee's HIV status. Similarly, 5% in Estonia to 54% in Malaysia reported discriminatory reactions from co-workers who became aware of their colleague's HIV status. 59

It is always in the back of your mind, if I get a job, should I tell my employer about my HIV status? There is a fear of how they will react to it. It may cost you your job, it may make you so uncomfortable it changes relationships. Yet you would want to be able to explain about why you are absent, and going to the doctors.

By reducing stigma in the workplace (via HIV and AIDS education, offering HIV testing, and contributing towards the cost of ARVs) employees are less likely to take days off work, and be more productive in their jobs. This ensures people living with HIV are able to continue working. 61

Community and household level stigma

Community-level stigma and discrimination towards people living with HIV can force people to leave their home and change their daily activities.
- Shana Cozad from Tulsa, USA, on her family's reaction after she tested positive for HIV. 64
In many contexts, women and girls often fear stigma and rejection from their families, not only because they stand to lose their social place of belonging, but also because they could lose their shelter, their children, and their ability to survive. The isolation that social rejection brings can lead to low self-esteem, depression, and even thoughts or acts of suicide. 62

The International Center for Research on Women (ICRW) reports that in Bangladesh more than half of women living with HIV have experienced stigma from a friend or neighbour and one in five feel suicidal. In the Dominican Republic, six out of ten women living with HIV fear being the subject of gossip, while in Ethiopia, more than half of all women living with HIV report having low self-esteem. 63

They [my family] were embarrassed and didn't want to talk to me. My mother essentially said, 'Good luck, you're on your own.'

A survey of married HIV-positive women (15-29 years) in India found 88% of respondents experienced stigma and discrimination from their family and community. Women with older husbands and from household's with lower economic status were significantly more likely to experience stigma and discrimination from their husbands' family as well as from friends and neighbours. 65

Stigma and discrimination can also take particular forms within community groups such as key affected populations.

For example, studies have shown that within some lesbian, gay, bisexual, transgender and intersex (LGBTI) communities there is segregation between HIV-positive and HIV-negative people, where people associate predominately with those of the same status. 66 67

The use of specific programmes that emphasise the rights of people living with HIV is a well-documented way of eradicating stigma. As well as being made aware of their rights, people living with HIV can be empowered in order to take action if these rights are violated. 68
Case study: Strengthening the rights of people living with HIV in Ghana
Ultimately, adopting a human rights approach to HIV and AIDS is in the public's interest. Stigma blocks access to HIV testing and treatment services, making onwards transmission more likely. The removal of barriers to these services is key to ending the global HIV epidemic. 69

In March 2016, UNAIDS and WHO's Global Health Workforce Alliance launched the Agenda for Zero Discrimination in Healthcare. This works towards a world where everyone, everywhere, is able to receive the healthcare they need with no discrimination, in line with The UN Political Declaration on Ending AIDS. 70 Zero discrimination is also at the heart of the UNAIDS vision, and one of the targets of its Fast-Track response. This focuses on addressing discrimination in healthcare, workplace and education settings. 71

As part of this work:

A virtual community of practice, Equal Health for All, has been created to facilitate the sharing of communication, collaboration and experiences in implementing the action plan. Over the year, its membership grew to more than 160 members from more than 70 organisations.

In Malawi, the National Association of People Living With and Affected by AIDS, in partnership with Airtel Malawi and UNAIDS, is using an SMS-based reporting system to provide real-time monitoring of experiences of stigma and discrimination faced by people living with HIV in the healthcare sector.

In Argentina, 21 service centres friendly to LGBTI people aim to increase the accessibility and acceptability of health services for key affected populations. Healthcare professionals have been trained on the specific healthcare needs of LGBTI people as well as on non-discrimination, accessible opening hours, and the active involvement of LGBTI people in the design and functioning of services.

In 2016, Kenya reaffirmed its commitment to end HIV-related stigma and discrimination by embarking on a national 'Kick out HIV stigma' campaign. This aims to leverage the power of football to mobilise young people to end HIV stigma and link them to stigma-free HIV testing, treatment and care.

Although Ghana's Constitution protects all citizens from discrimination in employment, education and housing and ensures their right to privacy, there is ambiguity in the way these provisions apply to people living with HIV and to key affected populations.
Photo credit: ©iStock/Stefan_Redel
The Patients' Charter protects people living with HIV from discrimination within the healthcare system, but they are difficult to enforce outside of public health facilities. In addition, consensual sex between adult males and sex work is criminalised, deterring sex workers and men who have sex with men from seeking healthcare services.

To overcome these obstacles, a web-based reporting mechanism was launched in December 2013. People living with HIV can directly report to the Commission by SMS or through the reporting system's website, and they can choose to remain anonymous. This triggers an investigation involving human rights organisations and lawyers.

By September 2015, 32 cases of discrimination had been recorded, and 13 of them have been resolved. Complaints have included violence, blackmail and denial of employment, healthcare and education.

However, a study of the implementation of the Charter at a sample of clinics found that, while healthcare staff were aware of the existence of the patients' Charter and also knew some of its contents, the majority of patients had no knowledge of either the existence or the contents of the Charter and were therefore unable to utilise it to tackle experiences of stigma and discrimination in healthcare settings.

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HIV-related stigma and discrimination refers to prejudice, negative attitudes and abuse directed at people living with HIV and AIDS. In 35% of countries with available data, over 50% of people report having discriminatory attitudes towards people living with HIV. 1 Stigma and discrimination also makes people vulnerable to HIV.

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- level of education can impact the way you think about the illness- for example those where English is not their first language may experience problems in not understanding HIV preventative measures. NICE guidelines found that African American and Mexicans who's language is not English have issues in undestanding the steps in preventing HIV especially in the population that have sex with other men.
Healthcare professionals- HIV related stigma in a healthcare setting discourages the individual to seek medical help if they have recently received unwelcoming judgement. Socially marginalised groups such as men who have sex with me face additional stigma by their healthcare professional. Perceptions of occupational risk- Green, (1997) found that the main source of negative attitudes was due to the perceived risk of contagion. When healthcare professionals are unfamiliar with the procedures, incidences of discrimination are higher.
Health providers may limit the amount of contact they have with the person with HIV or may delay or deny further treatment.
UNAIDs found that healthcare workers may also violate confidentiality and disclose the patients diagnosis without consent.

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Effects of HIV- ( uses a diagram by which when mouse is dragged across body shows the issues)
Once the human immunodeficiency virus (HIV) enters your body, it launches a direct attack on your immune system. How quickly the virus progresses will vary by your age, overall health, and how quickly you’re diagnosed. Receiving treatment at the quickest time will make a huge difference to the symptoms.
HIV virus attacks the white blood cell known as CD4+ , once they are invaded by the virus they replicate and damage the CD4+ count, this then produces more infected CD4+ cells. If the individual goes without treatment, this cycle will be continuous until your immune system is badly compromised leaving you at risk of serious illnesses and infections.

Acquired immunodeficiency syndrome ( AIDS) is the final stage of HIV. At this stage, immune system has practically broke down and the risk of catching infections is much greater.

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You're likely familiar with HIV, but you may not know how it can affect your body. Technically known as the human immunodeficiency virus, HIV destroys CD4+ cells, which are critical to your immune system. They're responsible for keeping you healthy from common diseases and infections.

As HIV gradually weakens your natural defenses, signs and symptoms will occur. Find out what happens when the virus enters your body and interrupts its systems.

Once the human immunodeficiency virus (HIV) enters your body, it launches a direct attack on your immune system. How quickly the virus progresses will vary by your age, overall health, and how quickly you're diagnosed. The timing of your treatment can make a huge difference.

HIV targets the type of cells that would normally fight off an invader like HIV. As the virus replicates, it damages or destroys the infected CD4+ cell and produces more virus to infect more CD4+ cells. Without treatment, this cycle can continue until your immune system is badly compromised, leaving you at risk for serious illnesses and infections.

Acquired immunodeficiency syndrome (AIDS) is the final stage of HIV. At this stage, the immune system is severely weakened, and the risk of contracting opportunistic infections is much greater. However, not everyone with HIV will go on to develop AIDS. The earlier you receive treatment, the better your outcome will be.

Many of the effects described here are related to the failure of the immune system in HIV and AIDS that is progressing. Many of these effects are preventable with early antiretroviral treatment, which can preserve the immune system.

Your immune system prevents your body from acquiring the diseases and infections that come your way. White blood cells defend you against viruses, bacteria, and other organisms that can make you sick.

Early on, symptoms may be mild enough to be dismissed, but after a few months, you may experience a flu-like sickness that lasts a few weeks. This is often associated with the first stage of HIV, which is called the acute infection stage. You may not have many serious symptoms, but there are usually large quantities of virus in your blood as the virus reproduces rapidly.

Acute symptoms can include:

The next stage is called the clinical latent infection state. On average, it lasts 8 to 10 years. In some cases, it lasts much longer than that. You may or may not show signs or have symptoms during this stage.

As the virus advances, your CD4+ count decreases more drastically. This can lead to symptoms such as:

If the HIV infection advances to AIDS, the body becomes prone to opportunistic infections. This puts you at an increased risk of many infections, including a herpes virus called cytomegalovirus. It can cause problems with your eyes, lungs, and digestive tract.

Kaposi sarcoma, another possible infection, is a cancer of the blood vessel walls. It's rare among the general population, but common in people who are HIV-positive. Symptoms include red or dark purple lesions on the mouth and skin. It can also cause problems in the lungs, digestive tract, and other internal organs.

HIV and AIDS also puts you at higher risk of developing lymphomas. An early sign of lymphoma is swollen lymph nodes.

HIV increases the risk of colds, influenza, and pneumonia. Without preventive treatment for HIV, advanced treatment puts you at an even greater risk for complications like tuberculosis, pneumonia, and a disease called pneumocystis carinii pneumonia (PCP). PCP causes:

Your risk for lung cancer also increases with HIV. This is caused by weakened lungs from numerous respiratory issues related to a weakened immune system. According to National AIDS Manual (NAM), lung cancer is more prevalent among people with HIV compared to people without it.

HIV raises the risk of pulmonary arterial hypertension (PAH). PAH is a type of high blood pressure in the arteries that supply blood to the lungs. Over time, PAH will strain your heart.

If you have HIV and have become immunocompromised (have a low T cell count), you're also more susceptible to tuberculosis (TB), a leading cause of death in people who have AIDS. TB is an airborne bacterium that affects the lungs. Symptoms include chest pain and a bad cough that may contain blood or phlegm, which can linger for months.

Since HIV affects your immune system, it also makes your body more susceptible to infections that can affect your digestive system. Problems with your digestive tract can also decrease your appetite and make it difficult to eat properly. As a result, weight loss is a common side effect.

A common infection related to HIV is oral thrush, which includes inflammation and a white film on the tongue. It can also cause inflammation of the esophagus, which can make it difficult to eat. Another viral infection that affects the mouth is oral hairy leukoplakia, which causes white lesions on the tongue.

Salmonella infection is spread through contaminated food or water, and causes diarrhea, abdominal pain, and vomiting. Anyone can get it, but if you have HIV, you're at higher risk of serious complications from this infection.

Consuming contaminated food or water can also result in a parasitic intestinal infection called cryptosporidiosis. This infection affects the bile ducts and intestines and can be particularly severe. For people with AIDS, it can cause chronic diarrhea.

HIV-associated nephropathy (HIVAN) is when the filters in your kidneys become inflamed, making it harder to remove waste products from your bloodstream.

While HIV doesn't generally directly infect nerve cells, it does infect the cells that support and surround nerves in the brain and throughout the body.

While the link between HIV and neurologic damage isn't completely understood, it's likely that infected support cells contribute to nerve injury. Advanced HIV infection can damage nerves (neuropathy). Small holes in the conducting sheaths of peripheral nerve fibers (vacuolar myelopathy) can cause pain, weakness, and difficulty walking.

There are significant neurological complications of AIDS. HIV and AIDS can cause HIV- associated dementia or AIDS dementia complex, two conditions that seriously affect cognitive function.

Toxoplasma encephalitis, caused by a parasite commonly found in cat feces, is another possible complication of AIDS. With a weakened immune system, having AIDS puts you at an increased risk of inflammation of the brain and spinal cord due to this parasite. Symptoms include confusion, headaches, and seizures.

Some common complications of AIDS include:

In very advanced cases, hallucinations and frank psychosis can occur. You may also experience headaches, balance issues, and vision problems.

One of the more visible signs of HIV and AIDS can be seen on the skin. A weakened immune response leaves you more vulnerable to viruses like herpes. Herpes can cause you to develop sores around your mouth or genitals.

HIV also increases your risk for rashes and shingles. Shingles are caused by herpes zoster, the virus that gives you chickenpox. Shingles causes a painful rash, often with blisters.

A viral skin infection called molluscum contagiosum involves an outbreak of bumps on the skin. Another condition is called prurigo nodularis. It causes crusted lumps on the skin, as well as severe itching.

HIV can also make you prone to other skin conditions, such as:

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You're likely familiar with HIV, but you may not know how it can affect your body. Technically known as the human immunodeficiency virus, HIV destroys CD4+ cells, which are critical to your immune system. They're responsible for keeping you healthy from common diseases and infections.

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Stress and coping model- Lazarus and Folkman, (1984) explained the process of adjustment to HIV/ Aids.
Based on the premise that adjustment can be determined by three types of components: cognitive appraisal, coping strategies and coping resources.
Cognitive appraisal- defined as the evaluative process that reflects the persons interpretation of the event, for example if they appraise the event as threatening then they are likely to negatively adjust to HIV and therefore generate more stressors.
Stess may be caused by:

managing the HIV drug regimen

issues with disclosure

poor coping skills

social isolation

discrimination

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Many individuals that have been diagnosed wit HIV have reported that they often view themselves as something negative due to the stigma surrounding the disease- this stigma may even cause internalised homophobia which has been found in some to be a barricade in receiving HIV prevention as they fail to learn about the risks and where they can go for help due to this negative view they have.

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Antiretroviral therapy ( ART) requires lifelong daily oral intake. Whilst advances in ART have significantly improved the quality of life of people living with HIV infection. The success of ART still hinder on the appropriate adherence and daily persistence of taking the medication.
Issues regarding maintaining the correct adherence scores can cause virological failure, drug resistant strains and transmission of the virus.
Virologic  adherence- full viral suppression aims to maximise immune fuction and minimize the virus- often needed to be near perfect adherence to achieve full suppression.
Managing treatments may also be a challenge in regards to those that begin to show signs of internalised homophobia- by which they fail to hear about treatments.
Antiretroviral medication therapy typically involves three or more medications, which may require 30 to 60 pills per day.

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Preserving relationships:
studies have found when people are faced with a choice of either taking their medication and risking discovery of HIV or preserving their social relationships they favour social relationships.
The preserving of their relationships show just how important it is, to try and sort the issue of this- could be linked to that of societal norms and how having HIV is often something that is highly scrutinised and they don't want to disclose their identity in fear.

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Adaptation: Preserving a satisfactory self- image 

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Adaptation: Preserving a satisfactory self- image 

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Being diagnosed with HIV- and being homosexual the individual has to deal with two levels of discrimination and stigma.
Herek, 1999- gave reason for why HIV/Aids is such a stigmatized disease-

often it is perceived as the bearers responsibility as there behaviours are seen as voluntary and avoidable

Conditions that are contagious always have a greater stigma attached to them.

HIV stigma is heightened by its layers upon the stigma associated with homosexuality, drug use and sexual promiscuity.

Often these stigmas could lead the individual to have internalised thoughts especially if the person is homosexual the individual may realise that societal view of homosexuality is wrong and therefore they internalise these thoughts- this can affect hearing about HIV centers  and help groups.
This stigma may lead to direct stressors and greater risk of discrimination.

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HIV can be passed from one person to another through sexual contact- HIV can be transmitted through heterosexual or homosexual sex.
HIV is transmitted from one person to another when bodily fluids from an infected person enters the body of an uninfected body: bodily fluids include blood, semen, pre- ejaculation, vaginal and anal fluids can be passed by:
Having unprotected sex
Sharing sex toys
Using a needle which has already been used by someone who is infected with HIV.

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Help- Seeking Behaviour - Health belief model

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Help- Seeking Behaviour - Health belief model

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Theory-  The health belief model- health behaviour are established by a person's appreciation of the potentially harmful health condition and they learn that the adverse effects can be minimised. A further concept of HBM is the perceived severity of the illness. Those with HIV/AIDS should understand that the disease is a serious infection that can affect many aspects of their lives. Furthermore, the individual should understand the benefits of the advised action such as drug adherence and condom use. This aspect gives the person that by taking the drugs and wearing the condom, will help stop or prevent the problem.