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Engage Nova Scotia is a non-profit organization whose focus is a more vibrant, inclusive, and resilient province. This organization is leading the "From Me to You" initiative, which is an invitation for community members to write a note to someone and make a connection in their community.

Interested in becoming engaged in this initiative? Contact sarah@gatewayruralhealth.ca to get a "From Me to You" card today.

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Community Living South Huron supports adults with a developmental disability to live, work and participate in their communities.

Currently looking for volunteers to teach a new skill or share their talent with a group of eager learners over Zoom.

To learn more about this opportunity please contact Katie Fox (Co-Executive Director) @ katie.fox@clsh.ca or 519-237-3637 ext 634.

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Gateway Centre of Excellence in Rural Health is a not-for-profit organization that aims to improve rural health.

Gateway is currently offering the Lonely No More program in Huron County and will be expanding the program into North Perth in March. This program consists of weekly teleconference calls (Elder Circles) between isolated seniors, facilitated by educated community members (volunteers).

To learn more about this opportunity please contact Lonely No More's Program Coordination @ sarah@gatewayruralhealth.ca or call at 519 612 1053.

This program is currently recruiting volunteers and participants.

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South West Self-Management Program, SWLHIN

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South West Self-Management Program, SWLHIN

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SWLHIN works with community members to help them manage their chronic conditions, including but not limited to diabetes, chronic pain, mental health conditions and heart disease as well as provide support to caregivers.

Currently looking for volunteers to deliver healthy living and caregiver support workshops.

To learn more about this opportunity please contact Jackie Alves (Program Outreach Officer) @  jackie.alves@lhins.on.ca or 519-533-8955.

This program is currently recruiting volunteers. Volunteers are provided an honorarium of $25 per session (for a total of $150).

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Victim Services Huron provide emotional support and practical assistance to survivors of crime and tragic circumstance.

Currently looking for volunteers to provide on scene support to victims of crime and tragedy.

To learn more about this opportunity please contact Victim Services Huron @ jenn@victimserviceshuron.ca.

This program is currently recruiting volunteers.

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Huron Respite Network provides respite services to families across Huron County.

Currently looking for host families and respite providers to welcome an individual into their home as an occasional break for the caregiver.

To learn more about this opportunity please contact Huron Respite Network @ respite@clch.ca or call 519 482 3115.

This program is currently recruiting volunteers.

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Add a description about your organization and your volunteer opportunity here

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Gateway Centre of Excellence in Rural Health is helping cultivate resilience in Huron County through offering a series of free educational opportunities through their Connectedness Coaching Project to Huron residents this February.

These educational opportunities are aimed at community members who are interested in learning more about peer support, coaching conversations, and system navigation, skills each individual can use to help strengthen our communities.

Gateway CERH is also inviting local social service agencies and groups to participate and attend these events to complement their invaluable work.

For more information about these events click here:

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Partnering with a peer volunteer may be a great aid in addressing malnutrition in older adults living alone.

To learn more click the image below.

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Older adults living alone are vulnerable to malnutrition, especially when co-morbid loneliness and social isolation are experienced⁽⁻Reference Wylie, Copeman and Kirk ⁴⁾. Malnutrition in later life is associated with undesirable outcomes such as poor quality of life⁽Reference Vetta, Ronzoni and Taglieri ⁵⁾, impaired immune function⁽Reference Chandra and Kumary ⁶⁾, increased risk of higher post-operative complications, mortality, and duration and cost of hospitalisation⁽Reference Correia and Waitzberg ⁷⁾. Living alone is thought to cause malnutrition because of its association with dining alone, as eating with others (and particularly with friends) is associated with increased energy intake⁽Reference Brindal, Wilson and Mohr ⁸,Reference de Castro and Stroebele ⁹⁾, a phenomenon known as the social facilitation effect.

The social facilitation effect can be used to manipulate energy intake among older adults. Dining with others improves food intake specifically among older adults who live alone⁽Reference Locher, Robinson and Roth ¹⁰⁾. Companionship can mitigate the impact of age-related appetite loss on energy intake too⁽Reference McIntosh, Shifflett and Picou ¹¹⁾.

The presence of others may improve social cognitive factors related to diet as well. Social cognitive theory states that individuals guide their own behaviour as informed through interactions with others⁽⁾. Social cognitive theory provides a framework in which individual factors can be targeted with the aim of altering behavioural outcomes. According to this theory, we learn best through watching the actions of others, and watching others can improve our confidence in our own abilities. This confidence is referred to by Bandura as 'self-efficacy', and has been studied in relation to nutritional health behaviours in the past⁽Reference Anderson, Winett and Wojcik ¹³,Reference Hendy, Nelson and Greco ¹⁴⁾. Social cognitive theory predicts that when self-efficacy is high, the individual is most likely to engage in a given health behaviour. Self-efficacy can be improved by providing opportunities for social modelling and vicarious learning (i.e. learning by observing others), combined with provision of educational information⁽Reference Archuleta, VanLeeuwen and Halderson ¹⁵⁻Reference Wunderlich, Bai and Piemonte ¹⁷⁾.

Involving peers in intervention delivery is advised, as social modelling is more likely to occur when one is observing a peer engage in a behaviour, which facilitates improvement of self-efficacy⁽Reference Buman, Giacobbi and Dzierzewski ¹⁸⁾. Peer volunteers have been shown to enhance the gains associated with a physical activity intervention among older adults⁽Reference Buman, Giacobbi and Dzierzewski ¹⁸⁾ as well as those associated with nutrition interventions⁽Reference Perez-Escamilla, Hrorni-Fiedler and Vega-Lopez ¹⁹⁾.

Although nutrition education interventions have used peers in the past to improve nutritional behaviours, little research to date has considered the utility of peers in a more informal setting, such as in an informal mealtime intervention. Mealtime interventions typically constitute a shared mealtime, and have been used effectively for institutionalised older adults in long-term residential care and hospitals to improve energy intake⁽Reference Abbott, Whear and Thompson-Coon ²⁰⁻Reference Nijs, de Graaf and Siebelink ²⁵⁾. Mealtime interventions are often utilised for individuals with dementia, as dementia onset often brings with it the experience of difficulties at mealtimes⁽Reference Aselage and Amella ²⁶,Reference Charras and Fremontier ²⁷⁾, and as such these interventions are often concerned with feeding support and staff interactions. However, little is known about the utility of more informal mealtime interventions in improving outcomes for community-dwelling older adults. Mealtimes as a research topic are becoming prioritised in the literature⁽⁾, as they represent the provision of nutrition and social support, as well as occupational activity when the individual is involved in meal preparation as well⁽Reference Bundgaard ²²⁾. Although many older adults report that they prefer to graze than to sit down for full meals, particularly after life transitions such as children leaving the family home, retirement or widowhood⁽Reference Donkin, Johnson and Lilley ²⁹,Reference Winter Falk, Bisogni and Sobal ³⁰⁾, regular meal preparation is associated with improved nutrition and lower risk of mortality⁽Reference Chen, Lee and Chang ³¹,Reference Hughes, Bennett and Hetherington ³²⁾, and can stimulate appetite and interest in food⁽Reference Bundgaard ²²⁾, thus representing a modifiable factor for improving nutrition.

The present study investigated a mealtime intervention focusing on the improvement of self-efficacy, food enjoyment and energy intake among older adults living alone at risk of social isolation. The research question addresses the impact of this 90-min, once weekly, 8-week intervention programme on these outcomes, compared with individuals in a control condition. A peer volunteer visited the individuals in the treatment condition once weekly to prepare and share a meal with them, aiming to improve their self-efficacy, food enjoyment and energy intake. As we were interested in potential future applications to subsets of the older population, we wanted to investigate outcomes in relation to the conditions of the intervention, as well as sex and extent of social connectedness, as this would tell us whether our intervention is more likely to improve outcomes among males, females, those who are socially isolated and those who are socially connected.

Hypothesis 1: The intervention will lead to an improvement in self-efficacy relative to the control group.

Hypothesis 2: The intervention will lead to an improvement in food enjoyment relative to the control group.

Hypothesis 3: The intervention will lead to an improvement in energy intake relative to the control group.

Methods

Results

Discussion

This study evaluated an intervention designed to improve self-efficacy, food enjoyment and energy intake in older adults living alone. The intervention led to a non-significant trend towards improvement in self-efficacy in those in the treatment condition. Second, individuals in the control group improved more so than those in the treatment group in food enjoyment between baseline and after intervention. However, although individuals in the treatment group continued to improve their levels of food enjoyment at the follow-up point, at this point food enjoyment decreased among participants in the control group. All males engaged in the study increased their energy intake over time, whereas females in the treatment group but not in the control group showed decreases in energy intake (except for females in the treatment group who increased their intake at follow-up). It is important to note that increases in energy intake may represent an improvement in some individuals and a disimprovement in others.

Results are mixed, and it is difficult to conclusively determine the success of the intervention. The intervention appears to be associated with improvements in food enjoyment and in some individuals' energy intake. Overall, we only partially support our hypotheses, which suggested that the intervention would lead to improvements in social cognitive factors and energy intake in older adults.

For some outcomes, following corrections for multiple comparisons, there was no difference between the control group and the treatment group. It has previously been found that both treatment and control groups improve in social support interventions because of the interactive and social nature of the research, as well as interactions with researchers potentially constituting an intervention of sorts⁽Reference Berkman, Blumenthal and Burg ⁴⁶⁾. As all participants had interactions with assessors a minimum of ten times during their tenure with the project, this explanation likely holds for the current findings. Furthermore, the control group received the guidebook, which may have itself constituted a successful intervention. As both groups received this information, it is unlikely that the information constituted a more significant intervention for the control group unless they attended more to this information than those in the treatment group. We interviewed individuals in the control and treatment groups following the study to explore this possibility and it did not appear to be the case that those individuals in the control group attended to the guidebook more so than those in the intervention group. Future research comparing three groups - one control group receiving no intervention, one guidebook-only group and one group receiving the full social cognitive intervention - would be more informative about the specific effective components of such an intervention.

Our interviews also allowed us to ask whether participants felt that they got along with their volunteer matches, as this would likely affect the success of the intervention. Most participants reported that they felt they got along well with their volunteers, and acknowledged that they had been made aware of the opportunity for re-matching at the study outset.

Social cognitive theory has successfully been applied to nutritional health behaviours and cooking skills in previous studies, and social cognitive determinants are related to good nutritional outcomes⁽Reference Anderson, Winett and Wojcik ¹³,Reference Hendy, Nelson and Greco ¹⁴,Reference Condrasky, Williams and Catalano ⁴⁷⁻Reference Liquori, Koch and Ruth Contento ⁴⁹⁾. Largely, the results corroborate previous findings in the literature. We found that self-efficacy marginally trended towards improvement with the provision of opportunities for social modelling and vicarious learning in combination with education, as delivered by peers, as was previously found⁽Reference Archuleta, VanLeeuwen and Halderson ¹⁵⁻Reference Buman, Giacobbi and Dzierzewski ¹⁸⁾. We found improvements in energy intake for men but not for women, which partially aligns with previous findings that mealtime interventions in institutions can improve energy intake⁽Reference Abbott, Whear and Thompson-Coon ²⁰⁻Reference Nijs, de Graaf and Siebelink ²⁵⁾. We also found that the mealtime intervention led to an improvement in food enjoyment, which is in accordance with previous findings that interventions focusing on meal preparation can stimulate interest in food⁽Reference Bundgaard ²²⁾. The effect of the treatment on food enjoyment appeared to continue after the completion of the visits, which may suggest that the visits stimulated interest in food for the participants, leading to improved food enjoyment. The participants in the control group experienced an initial increase in food enjoyment, followed by decreases at follow-up, which might suggest that, although their initial involvement in and initiation to the study may have been sufficient to stimulate interest in food, it did not provide a long-lasting effect. Future studies are required to further explore the effectiveness of visits in providing long-lasting effects on food enjoyment.

The present study had methodological limitations. After corrections for multiple comparisons were made, only one of the findings remained significant (related to food enjoyment). This may be related to the fact that the study was underpowered, because the sample size was based on a feasibility principle rather than an a priori power calculation. Insufficient sample size is a common problem in health psychology intervention research⁽Reference O'Carroll ⁵⁰⁾, and results should as such be interpreted with caution. Participants were recruited to the study if they self-reported a risk of social isolation. Originally, the study protocol featured an inclusion criterion of being identified as socially isolated using the Lubben Social Network Scale⁽Reference Altman and Bland ³⁷⁾. However, it proved extremely difficult to recruit sufficient number of participants who scored as isolated on this scale, because, as was found in a nationally representative cohort, only 6 % of the older Irish population are classifiable as socially isolated⁽Reference Timonen, Kamiya and Maty ⁵¹⁾, and this small proportion of socially isolated individuals in the population was reflected in attempts to recruit. As such inclusion criteria were relaxed to facilitate timely delivery of the project. In investigating the subset of the treatment group who were socially isolated, then, it appears that further studies focusing exclusively on socially isolated individuals (perhaps in areas with larger populations than that in which the current study was conducted) would find more conclusive evidence of the effectiveness (or otherwise) of the intervention being evaluated. The study results are best evaluated, in our opinion, as a suggestion that interventions may be beneficial for individuals who are at risk of becoming isolated. They also indicate that further evalaution of this intervention with a more definitively vulnerable population, such as individuals with psychosocial or otherwise functional limitations, is merited, in order to explore whether the mechanisms considered in this study have a role in protecting the well-being of these vulnerable individuals.

Participants in the current study were not representative of the overall older population, and thus generalisability of findings is limited to those living alone and who were willing to have a visitor to their home once weekly for 8 weeks. Furthermore, it is possible that the offer of a cost-free meal once a week for 8 weeks skewed interest in the study to those who were potentially more economically deprived than average. It is also a possibility that the intensity of the intervention was not sufficient; perhaps two or three visits per week would have yielded more conclusive results in the current study. We also did not evaluate nutritional knowledge in either the participants or the volunteers before the intervention - it is possible that minimising differences between treatment and control groups for this knowledge may have provided a more fair comparison between groups. This is advised for future similar interventions.

Results of the current trial could inform the design of future interventions. We acknowledge the need for future interventions to define study participants using more rigorous and objective methods than a self-report of social isolation risk, in order to deliver the intervention to those who are most in need and most likely to benefit from inclusion. Future interventions would benefit from considering the interaction between sex and impact of intervention, and potentially design separate interventions for males and females, as in the cohort we studied these individuals faced different challenges with regard to food and social isolation.

Our results have implications for further research and policy. We identify a gap in the current services offered to older adults, which are typically nutritional but not social, and we suggest that combining support for these two areas would be of importance for many older adults living alone. Older adults face challenges in both nutrition and social isolation, and targeting both areas simultaneously could represent an effective and cost-effective means to improve the health status of older adults.

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RelAte: pilot study of the effects of a mealtime intervention on social cognitive factors and energy intake among older adults living alone | British Journal of Nutrition | Cambridge Core

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Older adults living alone are vulnerable to malnutrition, especially when co-morbid loneliness and social isolation are experienced( - Reference Wylie, Copeman and Kirk 4 ). Malnutrition in later life is associated with undesirable outcomes such as poor quality of life( Reference Vetta, Ronzoni and Taglieri 5 ), impaired immune function( Reference Chandra and Kumary 6 ), increased risk of higher post-operative complications, mortality, and duration and cost of hospitalisation( Reference Correia and Waitzberg 7 ).

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Peer support models have shown to improve depression symptoms and encourage social connections.

To learn more click the image below.

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Highlights

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Co-morbidity of depression with diabetes leads to poor outcomes.

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There is lack of interventions that can improve both depression and diabetes.

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Peer support holds promise for the treatment of comorbid diabetes and depression.

Abstract

Aims

Depression in diabetes mellitus (DM) is common and is associated with poor health outcomes. Peer support DM interventions include encouraging interactions that could improve depressive symptoms. We examined intervention effects for those with and without depressive symptoms in a peer support trial.

Methods

The 1-year ENCOURAGE trial included 424 persons with DM living in rural Alabama. Intervention participants worked with community volunteers who encouraged participants to engage in daily self-management; control arm participants received usual care. Outcomes included HbA1c, body mass index (BMI) and quality of life (QoL) with EuroQuol-5D (range 0.0-1.0). Depressive symptoms were assessed with the Patient Health Questionnaire (PHQ-8, range 0-24). Generalized Additive Models (GAM) examined control-intervention differences in changes in HbA1c, BMI, and QoL for those with PHQ-8 ≥ 5 and PHQ-8 < 5.

Results

Of the 424 participants enrolled at baseline, 355 completed follow-up and had data were that could be included into the study; they were aged 60.2 ± 12.1 years, 87% African American, 75% female, and 39% insulin-treated. In an overall GAM adjusting for imbalance across trial arms and time-related covariates, depressive symptoms improved for all, but after 15 months of follow-up intervention, participants experienced greater reduction in PHQ-8 score than control participants (p = 0.01). In stratified analyses, those with PHQ-8 ≥ 5 had unchanged HbA1c, lost weight (p = 0.03) and improved QoL (p = 0.04). Those with PHQ-8 < 5 also had unchanged HbA1c and lost weight, but did not improve QoL (p = 0.06).

Conclusions

Peer support improved depressive symptoms for all, but resulted in greater weight loss and gains in QoL for those with baseline depressive symptoms compared to those without.

View Abstract

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Volunteer peer support, diabetes, and depressive symptoms: Results from the ENCOURAGE trial

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Co-morbidity of depression with diabetes leads to poor outcomes. * There is lack of interventions that can improve both depression and diabetes. * Peer support holds promise for the treatment of comorbid diabetes and depression. Depression in diabetes mellitus (DM) is common and is associated with poor health outcomes.

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Peer support can encourage healthy living. This type of support has shown to encourage action steps to improve overall health.

To learn more click the image below.

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American Public Health Association (APHA) publications

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The American Journal of Public Health (AJPH) from the American Public Health Association (APHA) publications

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The American Journal of Public Health (AJPH) from the American Public Health Association (APHA)

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Through using the gifts and assets of community members you can foster community development and engagement.

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This Gallery was created as a virtual space where you can get inspired, inspire others and explore ways to engage in your community.

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To see more entries try scrolling using the dark blue bar on the upper right hand corner of the columns

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Have an idea you would like to share? Feel free to add your own entry in our last column (far right of the screen). Feel free to comment on other entries as well using the comment box below each entry.

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Improvements in participant's wellbeing was found using a peer-to-peer support model in vulnerable, low-income older adults in Cape Town, South Africa.

To learn more click the image below.

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Peer Review reports

Background

Aging among the world populations defies borders, including developed, developing and underdeveloped regions. The dramatic increase in aging worldwide calls for health care providers and others to prepare and intervene now to best position older adults for high quality of life while providing an efficient and economical model of care to support them. For instance, the United Nations Population Division has estimated that the number of people over the age of 60 will rise from 800 million (11% of the world's population) in 2011 to over 2 billion (22% of the world's population) in 2050 [ 1]. The number of people aged 80+ is estimated to increase by 270% over the same period [ 1], with the greatest increase of older persons expected in low and middle income countries. In Africa, the population over age 60 will increase from 46 million in 2015 to an estimated 147 million in 2050 [ 2]. The South African Medical Research Council estimates that the absolute size of growth of the population over 60 in South Africa will increase by 112%, from 2.47 million in 1985 to 5.23 million in 2025 [ 3]. This growth presents significant challenges to resource-constrained economies with other significant competing health and social challenges [ 3, 4, 5, 6].

Although few studies have been conducted, there is general agreement in the literature that access to care and health system responsiveness in developing countries is poor, and that health systems frequently fail to meet the needs of older people [ 4, 7]. Addressing the issue of aging within this context, the purpose of this project was to implement a peer-to-peer support model among a group of vulnerable older adults and to examine the program's effect on the wellbeing, social engagement and physical activity of community dwelling older adults living in a community situated in a developing country (South Africa).

With advancing age comes increases in chronic conditions such as dementia, stroke, chronic obstructive pulmonary disease and diabetes mellitus [ 8]. Increased survival with chronic disease will account for greater disability as the population ages [ 8]. Even in the absence of chronic illness, lack of proactive strategies will accelerate declining physical ability as adults age. Physical limitations may lead to functional decline and the inability to care for oneself in addition to increasing risk for falls, physical activity decline, depression, loneliness and hospitalization.

For example, loneliness, defined as a subjectively experienced aversive emotional state, is related to the perception of unfulfilled, intimate and social needs [ 9]. Social loneliness occurs through isolation and physical loss, while emotional loneliness can occur through the absence of a reliable attachment figure such as a partner and may result in feelings of depression [ 9]. Studies among the 65+ age group in Britain report a prevalence of 5-16% [ 9]. Amongst South African adults participating in the Study of Global Ageing and Adults Health (SAGE), loneliness has been estimated to affect between 9.9, and 12.5% of those over 70 [ 10]. Prevalence of loneliness increases with age, due to changes in health, functional capacity and social networks [ 11]. Loneliness and physical loss have been associated with an increased risk of poor prognosis in late life depression [ 12], metabolic syndrome [ 13], elevated systolic blood pressure [ 14], mortality in men [ 15], and emergency hospitalisation [ 16].

Social wellbeing is a person's subjective perception that life is good [ 17]. High social wellbeing has been shown to lower the odds of mortality and onset of disability [ 17, 18]. Health, physical activity, social integration, connection, relationships and social support have been frequently cited as some of the most important factors influencing self-reported wellbeing in the elderly [ 17, 19, 20]. A review of loneliness and social wellbeing literature reveals a paucity of information pertaining to older persons in Africa in general, and South Africa specifically. Furthermore, no intervention studies have been reported to address issues of loneliness and wellbeing.

Studies have shown that peer-to-peer programs are effective ways to provide emotional, informational and appraisal support and help alleviate transitional, chronic or acute life stressors in numerous populations [ 21]. Among Western populations, as well as some Asian countries [ 22, 23, 24], use of peer support with older adult programming has demonstrated effectiveness. A series of evidence-based programs were developed in the US to address some common geriatric syndromes. These programs address issues such as falls [ 25], chronic disease self-management [ 26, 27], chronic lower back pain [ 28, 29], and depression [ 30]. In all instances, these programs are delivered using trained older adult peers and peer volunteers who experience the same problem or threat. In Korea, Kim [ 22] matched trained peer supporters with community-dwelling, low-income older adults living alone. Findings showed improvements in mental health, social functioning, depression, and physical health status.

Peers have also been used to target physical activity outcomes. Dorgo, Robinson and Bader [ 31] found use of peer mentors produced higher retention rate in a fitness regimen that included resistance training and cardiovascular activities when compared with kinesiology student mentors. Others have found phone calls and home visits by peers improved physical activity among elders [ 32]. The encouragement and support from peers results in greater physical activity improvement among elders when compared with a community group intervention [ 33]. A study by Buman et al. revealed that peer volunteers enhanced the long term maintenance of physical activity when examined 18 months following a 16 week intervention [ 33].

Peer support programs present a low-cost way of supporting healthy ageing, yet few such programs have been piloted in low and middle-income countries. To address the needs of an expanding older adult population in Cape Town, South Africa, the AgeWell program was piloted in the community of Khayelitsha, a township of Cape Town in 2014. This paper reports on selected longitudinal change outcomes at the five-month follow-up.

Methods

Programme description

AgeWell - a community-based peer-to-peer support program - was designed as an adaptation of the successful Mothers2Mothers (M2M) program [ 34] for HIV positive mothers. M2M empowers and employs HIV-positive Mother Mentors to work in local communities to ensure that women and their families get the health and support they need.1 The AgeWell model drew on this mentor or peer supporter concept, engaging older people to provide companionship to less-able older persons living in their communities. Peer supporters or "AgeWells", worked in pairs conducting home visits comprised of both social and wellness content. The social content was related to companionship, social support, and community engagement. Through scheduled contact, AgeWells built friendships, encouraged social engagement, provided emotional and informational support, and promoted healthy living. In addition, these peer service providers were trained to use smartphone technology, programmed with research-driven screening tools and referral algorithms to identify evolving health problems and make referrals to primary care providers and social workers. AgeWells collaborated with clients to draw up a "Wellness Plan" and then followed up with clients through subsequent home visits and phone calls to encourage compliance with referral recommendations and wellness plan strategies for goal achievement.

A pre-post, pilot design was used to test the feasibility of the program and evaluate targeted outcomes.

Sample

A non-random, convenience sample of 212 persons, aged 60+ years and living independently, were recruited from Khayelitsha, a peri-urban suburb of Cape Town, and specifically, the geographic area of Mandela Park. The sample size was based on the number of people participating in older persons clubs in the area who opted into and qualified to participate in the study. Khayelitsha is a high density area with a total population of 391,749, approximately 30 km from Cape Town [ 35]. The population is predominantly disadvantaged black, isiXhosa speaking South Africans with limited resources and limited access to formal healthcare services. Unemployment in the area is extremely high and exceeds 38% and a quarter of the households have incomes of less than USD337. Living standards are low - over 35% of dwellings are informal shelters and many people have no piped water to their homes (65%), no flush toilets (28%), or electricity for lighting (19%) [ 35].

Key statistics are summarised in Table 1.

Recruitment and enrolment procedures

Programme staff and volunteers shared programme information with older persons visiting the sites of local care providers, community centers and community organizations. Word of mouth was also used to disseminate information about the program in each of the study areas. Potential clients were then contacted by a member of the study team by telephone for the purposes of pre-screening. Each potential client was asked:

1. 1)
"Are you under the age of 60"

2. 2)
"Do you live outside the designated geographical area?"

3. 3)
"Do you require 24 hour professional care?"

If any question was answered "Yes", then the potential client was declined further assessment and participation in the program. The purpose of Question 3 was to exclude the most dependent older persons from the outset. The preliminary telephone screening yielded a sample of 245 for the second phase, the baseline assessment. If a client was deemed to be suitable for the program, then an appointment was scheduled for a trained assessor to visit them in their own home to determine eligibility.

The recruitment goal was a cohort of older adults who were not too frail or not too well, and thus best suited to benefit from this type of program. Those excluded for being "too frail" included those residing in an assisted living or frail care facility or requiring 24 h professional care, greater than mild cognitive impairment as calculated by the interRAI Cognitive Performance Scale > 1 [ 36], or functional impairment as calculated by the interRAI Functional Hierarchy Scale > 6 [ 37], or having an unstable medical condition plus fatigue. In addition, subjects deemed "too well" to benefit from the AgeWell program also were also excluded. This determination was based upon having less than 2 of the following physical or psychosocial conditions: unstable gait, mood problems, loneliness, daily pain of less than moderate or severe intensity, infrequently or never leaves home, incontinence, dyspnea, or fatigue. If the client was deemed to be too well for the program, they were encouraged to continue with their normal activities and the interview was terminated.

This secondary screening assessment was conducted by a trained assessor in the prospective client's home using the interRAI Check-Up instrument - a comprehensive assessment tool derived from interRAI's Health and Social Check-up and Wellness tools [ 38]. interRAI CheckUp is a geriatric assessment instrument designed to be used by non-healthcare professionals to identify losses in intrinsic capacity at the primary care level. This instrument belongs to the interRAI suite of assessment instruments, a set of third-generation comprehensive multi-dimensional instruments for use in a number of vulnerable populations (including older adults), developed by a network of health researchers from over 30 countries [ 39]. All instruments are built on a common set of items, as well as specialised items relevant to particular contexts and patient groups and are designed to track patients longitudinally over time and across multiple care settings. These instruments have been continuously improved and validated against other commonly used instruments for use in long-term care, acute and post-acute care, home care, palliative and community settings [ 40, 41, 42, 43, 44]. The item domains of these instruments have been shown to have good inter-rater reliability and have been adopted in across the world [ 45].

Two assessors, fluent in English & isiXhosa, with tertiary education, but no formal health care qualification, were given 40 h of training to use the interRAI Check-Up instrument. Training consisted of workshops, supervised assessments and mock assessments.

Data was captured onto tablet devices. Custom-written software for the Check-Up instrument allowed capture of information directly to the device, allowing inherent scales and algorithms designed by interRAI for the Check-Up to be calculated in real time. The Check-Up instrument was administered as a 3 part questionnaire.

A total of 245 assessments were completed during this second phase. Six were deemed too frail to participate and 27 deemed too well to participate, yielding a final sample of 212 adults.

Intervention

Once a client was deemed to be eligible for the program, the remaining items of the Check-Up assessment, as well as the World Health Organisation Wellbeing Index (WHO-5) and Medical Outcomes Study Social Support Survey (MOS-SS) assessments were completed. The intent was to highlight health and social welfare conditions that could trigger the need for further investigations, improve wellbeing and reduce loneliness.

At the conclusion of the full assessment, the older adult and the assessor collaborated to develop a "Wellness Plan". Incorporating results from the assessment, the "Wellness Plan" contained primary goals for the elder and a set of action plans or activities to pursue and support achievement of articulated goals. The plan was viewed as an individualised roadmap for each older adult, guiding them towards a higher level of wellness.

A secondary aim of this project (and primary focus of this paper) was to evaluate whether peer-to-peer companionship by Agewell visitors to other older adults could improve wellbeing and social support. Twenty-eight active and able persons, aged 60 years and older, living in the study area and belonging to a partner community-based organisation were recruited after an interview and selection process. These AgeWell Visitors (AgeWells) were given 4 weeks of training on topics such as older persons' health, wellbeing, friendship development, smart phone operation, use of a proprietary screening instrument developed by AgeWell and referrals to social or health services according to algorithms devised by AgeWell. All 28 trainees performed well during training and were all offered positions as AgeWells. AgeWells were paid a stipend for 20 h of weekly engagement.2 AgeWells were paired up and allocated between 13 and 17 clients to visit according to a predefined visit schedule.

AgeWell program participants were assigned a pair of AgeWell visitors who would visit them at weekly, twice monthly or monthly intervals. The frequency of intervals was determined by the outcome of the embedded scale scores and risk indices of the InterRAI Check-Up screening instrument. Those assessed as having higher levels of disability received more frequent visits. Contact with the clients was made at more frequent intervals via telephone calls.

During visits, AgeWells administered a short 20-question wellness assessment using a smartphone. Depending on the responses, algorithms might trigger referral recommendations to medical professionals and social services providers, which were facilitated via the provision of a printed letter containing the relevant information. AgeWells then follow-up with clients through subsequent home visits and phone calls to encourage compliance with referral recommendations. Other aspects of the visits included building friendships, encouraging social engagement, providing emotional and informational support and promoting healthy living.

Enrollment to the program commenced on 20 March 2014 and completed on 7 August 2014. Services were provided from April 2014 - December 2014, thus allowing for at least 4-5 months of client exposure to the program.

Study outcome variables

The main study outcomes, subjective wellbeing and levels of emotional and informational support were measured using the WHO-5 Wellbeing Index, the Medical Outcomes Study Social Support Survey (MOS-SS) and variables from the interRAI CheckUp instrument related to mood, loneliness and levels of social and physical activity. The CheckUp instrument was administered prior to enrolment (as part of the recruitment screening procedures described above) and at the end of the study. The WHO-5 and MOS-SS instruments were administered by an assessor at the beginning of the study.

The WHO-5 is a 5 question assessment which has been validated in a number of studies [ 46, 47, 48] in various populations across the world [ 48, 49] including numerous geriatric populations [ 48, 50, 51]. The total score range is 0-25, with 25 representing the highest state of wellbeing. Total scores are multiplied by 4 to obtain a percentage score. A 10% shift in score indicates a significant change in wellbeing. The Medical Outcomes Study Social Support Survey (MOS-SS) is a 19-item, self- administered social support survey [ 52]. The scale is considered useful for assessing changes in the levels of social support available to those who have been identified as being socially isolated. It can be used as a measure for the outcome of services or areas of work focused on reducing social isolation or increasing levels of social support [ 53]. Each of the scale's four domains can be used in isolation and, for the purposes of this study, the 8-question subscale (MOS-SS 8) on emotional/ informational support was used as this best fit the profile of the AgeWell intervention. This scale has been demonstrated to be psychometrically sound, is considered universally applicable and has been used in various populations over more than two decades [ 53, 54].

Specific outcome variables related to psychological wellbeing, as well as physical activity and falls were measured via interRAI's Check-up instrument. While the interRAI CheckUp includes items related to health and function, these were not the main focus of the intervention and are therefore not reported on below.

The selected outcome measures for all three instruments are summarised in Table 2 below.

Program monitoring and evaluation

The AgeWell visitors used smartphones, allowing for paperless data collection, real-time performance management, and automatic and immediate referral triggers. An mHealth system was designed to monitor program activities and gather outcome data. Activity data was monitored to assess for timeliness and adherence to visit schedules and social/physical health screenings completed. The benefit of using e-technology to monitor much of the program implementation meant that necessary adjustments and problem solving could be expedited to ensure operational success. At the end of the programme, 3 focus groups were held with 25 AgeWells. The intention was to explore the effects of the AgeWell peer-support health model on improved wellbeing amongst AgeWells and their peer-companions and to elicit feedback on their programmatic improvement.

Ethics approval

Ethics approval for the study was obtained from the Foundation for Professional Development-Research Ethics Committee (FPD-REC) in Johannesburg, South Africa. The trained assessors were responsible for obtaining informed written consent from all participants.

Statistical methods

STATA was used to analyse the cleaned quantitative data collected from the WHO-5 and MOS-SS 8 instruments. Paired t-tests were used to analyse differences in wellbeing and social support scores at baselines and end-line.

SPSS was used to analyse data collected via the interRAI CheckUp instrument. For the CheckUp outcome variables, in each case the delta was established between the baseline and follow-up scores, and this value was tested with the chi-square statistic.

Results

The mean age of participants was 69. The sample population is described in Table 3 below:

Few lived alone (7%), and 38% identified as a primary caregiver. Multi-generational households are very common in the African population and, given high unemployment and the AIDS epidemic, older people, particularly women, often take on primary care and financial care of their grandchildren using their state pensions. Despite most living with family, 58% were at high risk for loneliness, with 52% reporting that they cannot count on friends for companionship and 61% not having left the house in the past 3 days.

Most had access to healthcare and 73% had visited a primary care provider less than a month ago. This high rate of access to primary healthcare is common as primary healthcare is free in South Africa and people with chronic illnesses attend dedicated treatment clubs for regular check-ups and to receive their medication.

AgeWell clients showed improvements in wellbeing with a baseline average client WHO-5 Wellbeing score of 50% rising significantly to 79%, ( p < 0.000), an overall improvement of 58% (See Fig. 1 below). There was no association noted between changes in wellbeing score and frequency of AgeWell visits.

Similarly, there was a significant 50% ( p < 0.000) increase in mean client social support scores as measured with MOS-SS 8 from baseline to endline with baseline mean score of 21 with improvement of 10 points to 31 at endline (see Fig. 2 below). Using the categorization of satisfactory social support, only 8.7% of clients scored 32 or above on the scale at baseline. By the end of the project this increased to 61.4%.

Completing a pre-post comparison using the interRAI CheckUp, all of the outcomes with the exception of falls improved significantly over the five-month observation period. Persons were less anxious, less depressed, less withdrawn, less lonely and more physically and socially active.

As indicated in Fig. 3 below, only 23% of the sample reported never feeling lonely and at the end of this project, this increased to 39.2%.

This reduction in loneliness may have been associated with a decreased in the percentage of persons reporting reduced social interactions - from 41% at first assessment to 3.5% at follow-up ( p < 0.000), possibly because of the regular visits by AgeWells. There was also a 31% increase in people reporting participation in social activities of long-standing interest over the past 30 days (Fig. 4).

Overall, the group experienced improved mood and, as Table 4 indicates, there was a significant drop in the number of people experiencing daily anxiety; feelings of sadness, depression or hopelessness; a lack of interest or pleasure in their activities; or withdrawal from activities of interest.

Physical activity levels were initially low, with 49% reporting no exercise or physical activity. At follow-up, there was a significant improvement with 66.4% doing some exercise or physical activity in the last 3 days. This is shown in Fig. 5 below.

While findings were not statistically significant, at follow-up 7% fewer people had experienced falls in the past 90 days ( p = .063). There was also an increase in stamina, with the number of people experiencing no fatigue increasing from 45.5 to 54.5%. However, this finding was only significant at the .034 level.

Programme effects on AgeWell visitors

The AgeWell programme not only benefitted those older persons visited, but also had notable empowerment effects on the AgeWell visitors themselves. Focus groups conducted with AgeWells as part of monitoring and evaluation efforts indicated that the program had an effect on their subjective psycho-social, emotional and physical wellbeing. Focus group participants indicated that since commencing the program they felt more connected to each other and their community and reported feeling less alone or isolated. The group structure and schedule of the program contributed to building authentic relationships amongst AgeWells.

AgeWells also reported improved self-esteem, and feeling a renewed sense of purpose. They were also excited to be able to learn about new technology and to make use of it and felt empowered by their new skills. AgeWells also became more aware of and more motivated to take responsibility for their own health and wellbeing and reported becoming more physically active.

Receiving a small salary for their work gave both monetary value to their work and allowed them to become economically active. This had a considerable effect on the welfare of their family and their self-esteem and alleviated some of the disempowering effects of poverty.

Discussion

The results from the pilot study demonstrated that a simple, low-cost intervention of visiting older persons, identified as lonely, can significantly increase self-reported wellbeing, levels of emotional and informational support, levels of social interaction, reduce loneliness, improve mood scores and increase levels of physical activity.

Home visitations and telephone calls created opportunities for social contact critical for reducing social loneliness. Given their shared experience of ageing, AgeWells were able to genuinely understand and empathise with the challenges faced by clients. This helped peer supporters to genuinely connect with clients and build trust. These relationships also acted as a motivating factor that provided participants with a common activity to look forward to. In some cases, genuine friendships emerged between AgeWell visitors and their clients, reducing emotional loneliness.

Given the well-established relationship between loneliness, psycho-social wellbeing and morbidity and mortality [ 18], peer supporters are well-positioned to effect preventive and promotive health in this population, alleviating downstream costs incurred from hospitalization and institutionalization.

Peer supporters such as AgeWells also have the potential to form an important link between community-dwelling older persons and health and social services.

While the study did not demonstrate improved health status, it is likely that continued intervention with sustained improvements in quality of life, mood and physical activity and reduction in loneliness may have long-term positive effects on general health and physical function.

In terms of project implementation, there was high demand for the intervention from clients, driven in part by the close-knit community, involvement of community leaders (some of whom were AgeWell visitors), the desire for social engagement and no reluctance to accept safety net services. Although client refusals were not tracked, overall client attrition from the programme was 10%, with relocation accounting for 35% of programme dropout. Challenges faced included political unrest, which could interfere with enrolment and visits and linking clients to health and social services given the overburdened and under-resourced health and social systems and difficulty in tracking referrals. While AgeWell visitors were enthusiastic, training older persons on administering the AgeWell wellness screening tool was challenging and their struggles using the tool could distract from the social visit.

Limitations of the study and generalizability

It is possible that some of the improvements seen in the study population were due to initial excitement and expectations at being included in a program that values a largely neglected and marginalized group of people. It would be important to see if these gains could be meaningfully sustained over longer periods of time through further study. Furthermore, the study is based on a small sample of participants and, given that there was no control intervention, it is not possible to establish whether it was peer-to-peer support produced the improvements in psychosocial outcomes observed in the results or other factors internal or external to the programme. The CheckUp, MOS-SS and WHO-5 instruments are all self-report instruments, which may introduce biases in terms of social desirability and may be affected by participant feelings at the time of the assessment or issues around recall. However, the study does indicate that social interventions to improve the wellbeing of older persons in LMICs are worth investigating through further longer-term and more rigorous studies, such as a randomized control trial that engages with both psychosocial and health outcomes should be undertaken.

Conclusions and implications

Innovative and effective strategies need to be developed to address the impending health and social welfare burden of ageing in resource poor settings. The AgeWell program has demonstrated improvement in client wellbeing and social support in a low-income community. Older persons, familiar with the challenges faced by the elderly are well-suited to identifying and responding the needs of older persons and providing social support to prevent loneliness and depression.

Policymakers should consider integrating peer support models into existing health programs to better address the needs of the elderly population and promote healthy ageing in community settings. Peer interaction can reduce social and possibly also emotional loneliness, promote health and wellbeing, and allow older persons to remain at home longer. As Steptoe et al. [ 55] argue, "health-care systems should be concerned not only with illness and disability, but also with supporting methods to improve positive psychological states. Through prevention measures for early intervention and disease management, this type of intervention also has the potential to positively affect health outcomes for the elderly.

Availability of data and materials

The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.

Notes

1. 1.

M2M provided technical, infrastructural, legal and human resource support for all administrative aspects of the project.

2. 2.

Given high rates of unemployment and poverty in South Africa, stipend-paid volunteering is very common.

Abbreviations

M2M:

Mothers2Mothers

MOS-SS:

Medical Outcomes Study Social Support Survey

WHO-5:

World Health Organisation Well-being Index

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Acknowledgements

We would like to acknowledge Dr. Mitch Besser and the AgeWell Global team who initially carried out the pilot study, as well as community partners Neighbourhood Old Age Homes, Cape Jewish Seniors Association, Cape Peninsula Organisation for the Aged and Ikamva Labantu.

Funding

The pilot study, including programme design, operational costs, data collection and analysis was funded by Mothers2Mothers. The work of researchers at the Samson Institute of For Ageing Research, who interpreted the data and wrote the manuscript, was provided by Eric and Sheila Samson Foundation.

Author information

Affiliations

1. Samson Institute for Ageing Research, 234 Upper Buitenkant Street, Cape Town, 8001, South Africa

Leon N. Geffen & Gabrielle Kelly

2. Marcus Institute for Aging Research, Boston, MA, USA

John N. Morris

3. Connell School of Nursing, Boston College, Newton, MA, USA

Elizabeth P. Howard

Contributions

Study concept and design: LG, EPH, JM. Acquisition of data: LG. Analysis and interpretation of data: GK, LG, EPH, JM. Drafting of the manuscript: GK, EPH. Critical revision of the manuscript for intellectual content: LG, EPH, JM. Revisions of the manuscript after peer review: GK. All authors reviewed read and approved the final version of the manuscript.

Corresponding author

Correspondence to Gabrielle Kelly.

Ethics declarations

Ethics approval and consent to participate

Ethics approval for the study was obtained from the Foundation for Professional Development-Research Ethics Committee (FPD-REC) in Johannesburg, South Africa. The trained assessors were responsible for obtaining informed written consent from all participants.

Consent for publication

Not applicable

Competing interests

Authors declare no financial conflicts of interest. Dr. Leon Geffen was the medical director of AgeWell Global during the pilot study, but is no longer involved in the organisation. He has full permission to use the data collected for this paper. All authors have consented to the publication of this manuscript.

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# data[].attributes.attachment_link.title
Peer-to-peer support model to improve quality of life among highly vulnerable, low-income older adults in Cape Town, South Africa

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Background Developing countries are experiencing rapid population ageing. Many do not have the resources or formal structures available to support the health and wellbeing of people as they age. In other contexts, the use of peer support programmes have shown favourable outcomes in terms of reducing loneliness, increasing physical activity and managing chronic disease.

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Peer volunteering has shown to promote active aging in socially isolated, inactive older adults.

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Abstract

Few older people achieve the recommended 150 min of moderate-to-vigorous-intensity physical activity (MVPA) each week ( Keadle, McKinnon, Graubard, & Troiano, 2016). The greatest gains in life expectancy and life quality are likely to occur by moving from the current very low levels of PA to some activity. Lee and coworkers (2012) reported that inactive people would gain 1.3-3.7 years from age 50 years by becoming active.

The validity of the simple "just get out of the door!" active ageing message ( Simonsick, Guralnik, Volpato, Balfour, and Fried, 2005) is supported by the Older People and Active Living (OPAL) observational and longitudinal studies ( Fox et al., 2011, 2015; Simmonds et al., 2014). These studies demonstrated that number of daily trips and steps, done for any reason, using any form of transport or walking, were associated with positive physical and mental health profiles in people aged 70 and older ( Davis et al., 2011; Withall et al., 2014). The importance of getting out and about is further supported by the strong association between lower life-space mobility (defined as the size of the spatial area in which a person moves in everyday life, the frequency of going out, and the need for assistance) and cognitive impairment ( James, Boyle, Buchman, Barnes, & Bennett, 2011), frailty, poor physical functional health, disability, and mortality ( Kennedy et al., 2017).

Social connectedness is as influential on survival as recognized health risks such as smoking and obesity ( Holt-Lunstad, Smith, Baker, Harris, & Stephenson, 2015). The Scottish longitudinal cohort study identified social connectedness and health status as independent predictors of change in PA in community-dwelling people aged 65 years and older ( Clarke et al., 2017). In addition to physical gains, getting out and about on a daily basis generates more opportunities to engage with meaningful pursuits and connect socially, and boost perceptions of autonomy and competence, enhancing social, emotional, and physical well-being ( Polku et al., 2015).

Several personal, social, and environmental barriers discourage older people from leaving their home regularly ( de Koning, Stathi, & Fox, 2015). Perceptions of poor health, not having "a reason to leave home" and 'no-one to go out with," have been identified as high-impact barriers ( Stathi et al., 2012). As people get older they are at increasing risk of a downward spiral of reduced activity and less social engagement, resulting in decreased physical capacity and compromised health ( Shankar, McMunn, Demakakos, Hamer, & Steptoe, 2017). Finding ways to break this downward spiral of inactivity and disengagement is a major public health challenge.

Enlisting peer volunteering support has potential to be an effective strategy for increasing PA in older adults, particularly those who are very inactive and socially disengaged. Volunteering is growing in popularity among older people and tends to remain a prominent behavior until at least middle-old age (mid-70s) ( McMunn, Nazroo, Wahrendorf, Breeze, & Zaninotto, 2009). Evidence supports the contribution of volunteering to social connectedness ( Parkinson, Warburton, Sibbritt, & Byles, 2010), mental well-being, quality of life, self-esteem, active lifestyle, and delayed mortality ( Cattan, Hogg, & Hardill, 2011; McDonnall, 2011; McMunn et al., 2009; Wahrendorf & Siegrist, 2010). Peer volunteers act as positive role models who support and empower older people, and peer-led approaches have potential to be cost-effective and sustainable ( Allen et al., 2016; Peel & Warburton, 2009).

We hypothesized that the recipients of the ACE intervention would report more out-of-house activities and better motivation to adopt an active lifestyle in the long term. In this paper, we report the design of the ACE intervention and describe the findings of the feasibility trial. The specific aims of ACE were to:

1. Assess the feasibility of recruitment and retention of activators and participants to a peer volunteering active ageing intervention.

2. Estimate the potential effect of the intervention on engagement in activities outside the home, PA, and physical function.

3. Assess the applicability of the theoretical framework adopted for this intervention.

4. Examine the acceptability of the intervention and trial methods to participants and activators.

Methods

A two-arm randomized control feasibility trial was used to evaluate the ACE intervention.

Recruitment

Participants were recruited from two wards in Bristol, United Kingdom chosen from a range of 14 neighborhood partnerships. These wards were selected to provide diversity based on several criteria including percentage of older residents, level of deprivation, and extent of provision of leisure facilities for older adults. This information was gathered via: (a) statistical profiles from Bristol City Council ( http://www.bristol.gov.uk/page/council-and-democracy/neighbourhood-partnership-statistical-profiles) and (b) the Mosaic Public Sector system which provides details of U.K. citizens' location, demographics, lifestyles, and behaviors ( http://www.experian.co.uk/public-sector/index.html). The study was approved by the University of Bath REACH ethics committee (EP 11/1298). Participants were informed about the study in writing and in person, and provided written informed consent.

Participants included: (a) the ACEs: These were sedentary retired adults aged 65 and older who reported spending less than 20 min per week in the past month in MVPA, were capable of walking at least 200 m, and did not have a diagnosis of dementia. Inclusivity was emphasized but we excluded people with disease or disability that seriously precluded participation in out-of-house activities, people who were already meeting current PA recommendations, and people who were regularly engaging with local groups and activities; (b) the activators (the volunteers). Using established communication channels within the two neighborhood partnerships and via the recruitment mailing described below, we recruited adults aged 60 and older to act as peer volunteers supporting intervention participants (ACEs-I); and (c) two part-time coordinators. One part-time (0.2FTE) coordinator in each ward was employed by the University of Bath but had no research role. Their tasks were to form working relationships with community groups, coordinate activator training sessions, support activators in the intervention delivery, and represent ACE locally.

Participants were recruited via a letter of invitation. Based on our formative research ( Stathi, Fox, Withall, Bentley, & Thompson, 2014; Withall et al., 2018), the recruitment materials focused on provision of assistance with getting out and about and engaging within communities. A commercial mailing list of residents in the relevant postcodes who were 65 and older was purchased (£510), and approximately 2,000 invitation letters and reply slips were mailed (£1,100). An A5 flyer (148 mm × 210 mm) highlighting key messages was also delivered to 1,000 homes in one of the intervention areas (£420). Posters were displayed in local health centers, libraries, and community centers, and local community groups and professionals were asked to refer potential participants. People interested in taking part were sent an information pack, a reply form requesting basic demographic information, and a reply-paid envelope (£55). Once screened and deemed eligible, ACEs were randomized to either the intervention [ACEs-I] or the control [ACEs-C] arm by choosing an envelope containing random allocation information. ACEs-I were then paired with an activator based on shared interests and geographical proximity of their residences. Given the gender imbalance between activators and ACEs-I, some pairings were necessarily a gender discordant match. No pairings were actively rejected by either party for this reason.

The invitation letters included an option for people to express an interest in the activator role. Those who did were invited for interview and if deemed eligible, were invited to the baseline assessments where they could meet the ACEs-I. Eligibility criteria were being 60 years old or over, physically capable of getting out and about locally, good communication skills, two references, and a successful Criminal Records Bureau (CRB) check.

Intervention Development and Delivery

The development of the ACE intervention was one of the outcomes of a collaborative network, AVONet, which used a range of approaches to identify best bet active ageing promotion strategies ( Stathi et al., 2014).

Description of Intervention and Control Groups

ACEs-I were invited to attend a 6-month program. This included two one-to-one initial meetings with their activators to support motivation (Motivation stage - first 2 weeks), to enable ACEs-I and activators to get to know each other, to review potential local activities, and to consider and address any barriers to participation. At least three joint visits to local initiatives of the ACEs-I's choice followed (Action stage - month 1-3). Further support to continue attending local activities was provided by telephone and at least two further joint visits, with the aim of ACEs-I beginning to attend these activities independently during the maintenance stage (month 3-6). ACEs-I engaged with a wide range of activities, physical and non-physical, at both Action and Maintenance stage. These included bowling, ballroom dancing, lunch clubs, tai-chi, walking groups, art classes, yoga, skittles (a game similar to bowling), and special events such as festivals and charity fairs. Two ACE social events were scheduled for all ACEs-I and activators to support exchange of information about local opportunities, celebration of achievements, and facilitation of within-group support for more local engagement. Other than written materials about local initiatives, ACEs-C received no additional input during the period of the intervention, but were offered the intervention after study completion.

Baseline and Follow-up Measures

As this was a feasibility trial, the main measures of interest were recruitment rate, study completion rate (the proportion of participants providing data at 6 months), and acceptability of the intervention (explored via interviews and focus groups). Intervention attendance (mean number of the sessions attended from the seven sessions scheduled for ACEs-I and their activators) was also measured.

Process evaluation was conducted to determine the relative usefulness of different intervention components and identify ways to refine/improve the intervention ( Moore et al., 2015). This included:

a) Quantitative process evaluation via a self-administered questionnaire which assessed changes in the motivation variables targeted by the PMLBC model (importance, self-efficacy, social support) and the three basic needs (autonomy, competence, relatedness) identified within Self-Determination Theory and measured by the Basic Needs Satisfaction-General Scale (BNS-GS) ( Gagné, 2003).

b) Qualitative process evaluation via semi-structured exit interviews and focus groups with a selection of 20 ACEs-I, 13 activators, and 2 coordinators, to evaluate which elements of the intervention worked well and which could be improved. Due to space constraints, a brief overview of key areas for improvement is presented in the "Results" section and in Supplementary Appendix A.

Several outcome measures were also included in the assessment protocol to identify those most appropriate for inclusion in a future definitive trial together with demographic data (i.e., age, gender, marital status, ethnicity, education level reached, type of residence, house ownership status, and years at current address).

Physical activity

Lower limb function

ACEs' lower limb function was assessed using the Short Physical Performance Battery (SPPB). The SPPB measures lower extremity function using activities that mimic tasks key to maintaining independent living: static balance (three balances), gait speed (4-m walk), and leg strength (getting up and down from chair) ( Guralnik et al., 1994).

Well-being

Activity barriers

Fourteen items assessing perceived personal, social, and environmental barriers to neighborhood activity ( European Commission-Pan-EU Survey, 1999) were included. All baseline assessments took place after screening and before randomization. Participants were asked to complete the questionnaires, perform the SPPB tests, and were administered the accelerometer with a manual of how to use it for the next 7 days. After completion of the intervention, all participants were asked to repeat the same protocol.

Baseline and 6-month data, described above, were collected in a 1.5- to 2.5-hr session either at the activator's or participant's home or a local community center. Accelerometers and the PA logs were returned after 7 days in a reply-paid envelope.

Data Analysis

Descriptive statistics (frequencies, percentages, means, SDs, 95% confidence intervals [CIs]) were generated to describe the recruitment and attendance data. To test for pre-post changes in PA variables between baseline and 6 months, paired samples t-tests were conducted separately for the control, intervention, and activator groups. As this was a feasibility trial, the sample size was not powered to detect differences either within or between groups. Hence, 95% CIs around estimates of mean differences are presented, rather than p-values are presented for ACEs-I, ACEs-C, and activators. Principles of framework analyses were employed to analyze focus groups and individual interviews ( Ritchie and Lewis, 2003).

Results

Participants

Fifty-four older adults were recruited as ACE participants ( n = 39) or activators ( n = 15). Table 1 presents the sample characteristics; 82% (95% CI: 70-94) of ACE participants provided quantitative data at both baseline and 6 months.

Aim 1. Feasibility of Recruitment and Retention

Two thousand mailed invitations and 1,000 flyers were delivered in the target areas resulting in 230 responses from potential participants and activators (response rate 11.5% [95% CI: 10.1-12.8]). Limited response rate data are available from similar studies for comparison purposes. The Groningen Active Living Model study completed baseline measures on 315 older adults having mailed 8,504 people (3.7%). Recruitment rates were supported by reminders and home visits for potential participants. Retention figures were not reported ( Stevens, de Jong, & Lemmink, 2008).

ACE participant

We received 154 requests for information packs. Sixty-five people returned reply forms. Twelve people were screened out due to high activity levels. Three people did not respond to further phone calls and messages. Forty people consented to take part. One person died prior to baseline measures; therefore, the baseline sample includes 39 people. Seven people dropped out prior to final measures due to ill-health ( n = 3), carer commitments ( n = 2), lack of time ( n = 1), and moving to a different city ( n = 1). The ACE participants were represented similarly across gender and marital status with a mean age ( SD) of 73.8 (7.3) years (see Table 1).

Activators

We received 76 requests for information packs. Twenty people returned their reply forms. One person was screened out for being in full-time (F/T) employment and another went back to F/T employment prior to baseline measures. One person dropped out prior to training (going back to F/T employment) and two people dropped out during/after training (one going back to part-time [P/T] employment, one unwilling to commit to the program schedule). Activators were two men and 13 women, with a mean age ( SD) of 68.7 (4.4) years. All 15 of the remaining activators completed the ACE program and all provided data at both baseline and 6 months. Eight activators supported one ACEs-I participant each. Seven activators agreed to support two ACEs-I participants each. These activators delivered the intervention with each of their allocated ACEs-I participants separately.

Aim 2. Changes in Activity, Physical Function, and Well-being

Activity and physical function

ACEs-I reported more activities outside the home at (6-month) follow-up ( M = 6.34; SD = 4.15) than at baseline ( M = 4.39; SD = 3.75). ACEs-C did not report changes in the number of activities outside home at follow-up. Both ACEs-I and ACEs-C increased the number of activities done at home.

The baseline characteristics of the sample are reported in Table 1. At baseline, ACEs-I were substantially less active than ACEs-C for minutes of lifestyle activity per day, MVPA, and steps per day and spent more time (55 min per day) being sedentary. Changes in PA from baseline to follow-up for ACEs are presented in Table 2. ACEs-I increased lifestyle PA, MVPA, sedentary time but decreased light activity. ACEs-C increased their light and lifestyle activity, MVPA, and step counts while reducing their sedentary time over the intervention period ( Table 2). However, only 8 out of 17 ACEs-C provided us with valid accelerometry data, so their results should be treated with caution as they might not be representative of the group as a whole.

Activators increased their light and lifestyle activity, MVPA, and step counts while reducing their sedentary time over the intervention period ( Table 2).

A mean difference of 0.98 points in physical function (95% CI: −0.38 to 2.3) between ACEs-I and ACEs-C groups was reported post-intervention. A difference in change scores of 0.5 is deemed to be a clinically significant difference therefore it is plausible that a definitive trial might find a clinically meaningful difference between the two groups ( Table 3).

Well-being

ACEs reported higher levels of vitality at follow-up ( Table 4). ACEs-I reported increased life satisfaction and resilience and better perceptions of physical, mental, and social well-being. ACEs-C reported small increases in mental and social well-being and lower levels of physical well-being and vitality.

Aim 3. Motivational Processes

The importance of getting out and about was high for ACE participants at baseline and it further increased at follow-up ( Table 4). The confidence to get out and about, a key target of change in ACE, increased for ACEs-I as well at their planning ability over the 6 months of intervention. ACEs-C reported lower levels of importance and confidence. Perceptions of social support were higher at follow-up for the ACEs-I but not for ACEs-C ( Table 5).

Perceptions of competence and autonomy to get out and about at 6 months were higher at follow-up in the ACEs-I and there was also a decrease in the importance of barriers to get out and about. The lower rating of barriers' importance and the higher levels of confidence and resilience draw a favorable motivational picture for ACEs-I at 6 months. These changes were evident at follow-up, even though the face-to-face support provided by the activators was reduced gradually in the final 3 months (maintenance stage).

Aim 4. Acceptability of the Intervention and Trial Methods to ACEs and Intervention Providers

Fourteen semi-structured exit interviews and seven focus groups examining issues related to acceptability of the ACE intervention and trial methods were conducted with 20 ACEs-I, 13 activators, and the two coordinators.

Acceptability of ACE intervention

Attendance.

All ACEs-I who completed the intervention engaged with their activator at least seven times as planned during the motivation, action, and maintenance stages. However, most ACEs-I engaged more often, especially in the maintenance stage. Of the three ACEs-I who dropped out, two met their activator less than five times but were contacted regularly by phone. Their reasons for drop out (ill-health, carer responsibilities) had already affected their engagement with the program in the early motivation stage.

Activators and activities.

ACEs-I rated highly the role of the activators in informing them about local initiatives and facilitating their re-engagement with their community:

It got me back into things, as I said, like painting and...the singing, I probably wouldn't have thought about that, but I really enjoy it. It's a fun thing. I certainly wouldn't have done it if I didn't get in touch and start coming to ACE. (ACEs-I, Group 1)

The ACE days were well received. All ACEs-I were invited to these two events which included interactive sessions, information sharing and opportunities for socializing:

I think what it did, it made all of the participants realize there were other people like them, and they enjoyed chatting with each other. I think that was part of making them feel like they were part of a group.(Activator, Group 2)

Coordinators' support.

All activators praised the coordinators, highlighting the benefits of the support they provided:

She [the coordinator] was brilliant, she'd ring up regular and say "How did you get on?" she was really nice. (Activator, Group 1)

Supplementary Appendix A provides a list of specific areas for improvement for intervention delivery and research design, including illustrative quotes.

Discussion

This study examined the feasibility and acceptability of a theory-informed, pragmatic intervention using peer volunteering support to promote active ageing. The ACE intervention was the outcome of a rigorous developmental process during which a range of stakeholders co-produced a program designed to be acceptable, feasible, and make a positive contribution to older people's health and well-being. The extensive patient and public involvement (PPI) throughout development may have helped produce a community intervention which was well accepted and easy to administer ( Stathi et al., 2014; Withall et al., 2018). The importance of extensive PPI is now widely acknowledged, and is an established goal of science policy and a requirement of research funders in the UK ( http://www.rds.nihr.ac.uk/wp-content/uploads/RDS-PPI-Handbook-2014-v8-FINAL.pdf).

ACEs included similar numbers of men and women. This is significant as older men are less likely to become involved in activity interventions ( Waters, Galichet, Owen, & Eakin, 2010). The majority of activators were female and as might be expected were younger, fitter, and healthier than the ACE participants.

The qualitative process evaluation indicated that the ACE intervention was well accepted by all parties. ACEs-I adhered to the program, attended the planned sessions with their activators, and in many cases met more often than originally planned. The completion rate was high and only serious health problems and/or family issues prevented some participants from continuing.

This feasibility trial was not powered for statistical significance. However, we observed a positive increase in ACEs-I' reported activities outside the home. The objective accelerometry data indicated increases in some components of PA for ACEs-C, highlighting the potential for some behavior changes among randomized control trial control group members. However, the low number of follow-up accelerometry data for this group is not sufficient to allow any firm conclusions about PA changes. Activators, although sufficiently active at baseline, also increased their PA supporting the association of volunteering with positive physical health profiles ( Anderson et al., 2014). The highest percentage of increased activity for all groups was for lifestyle intensity PA, MVPA, and step counts which points to an increase in out-of-home activity. Although limited, these data support the recent focus on light and lifestyle intensity PA and its importance for older people ( Hamer, de Oliveira, & Demakakos, 2014).

Objectively measured physical function increased in 50% of ACEs-I. Similarly, in the LIFE study, the PA intervention group had significantly higher total SPPB scores at 6 months than the control group ( Santanasto et al., 2017). This improvement is particularly important as it goes against the expected decline observed in large longitudinal studies. In a sample of 3,070 older adults (mean age = 69), gait speed declined significantly over a 6-year period; evidence of a downward spiral of inactivity and compromised physical function ( Shankar et al., 2017). Unlike the LIFE study, ACE was not an intensive exercise intervention, rather indirectly supporting increased PA, but still it produced positive results in terms of physical function. These results also support the supposition that the functional ability of inactive older adults can be very low, and getting out and about for any reason might offer sufficient stimulation for improvement in physical function ( Davis et al., 2014; Guzman-Castillo et al., 2017). Combined with these findings, the high prevalence of mobility difficulties in 93% of frail and 58% of non-frail older adults in the UK ( Gale, Cooper, & Sayer, 2015), highlight the importance of physical function as a target for public health interventions. Although this study was not powered to detect changes in physical function, it demonstrated the sensitivity of the SPPB measurement tool ( Guralnik et al., 1994) in detecting changes in physical function with the target population. The ease of its administration and its objective nature further support its use in future ACE and other active ageing trials.

The quantitative process evaluation supports the applicability of the PMLBC and its usefulness as a theoretical framework for rigorous development and evaluation of such interventions ( Gillison et al., 2015). Evidence emerged that focusing on specific behavioral processes in the motivation, action, and maintenance stages and employing strategies aimed at boosting autonomy, competence, and relatedness had been effective. Confidence and social support to get out and about, key determinants of PA participation in older people ( Stathi et al., 2012; Stathi, McKenna, & Fox, 2010), increased at follow-up, while the severity of perceived barriers decreased. Together with an increase in resilience, this indicates the potential of the ACE intervention to facilitate lifestyle changes in older people, as these constructs have been shown to promote healthy lifestyles ( Manning, Carr, & Kail, 2014; Perna et al., 2012). The positive changes in perceptions of well-being and life satisfaction suggest that the ACE intervention helped participants to improve their quality of life, highlighting the impact of activity on mental health and subjective well-being ( Whitehead & Blaxton, 2017).

Any future intervention attempting to build upon this feasibility trial will need to address some specific issues. Recruitment was challenging. This is not surprising, as ACE targeted community-dwelling older adults who were relatively isolated. As such, they are likely to lack the confidence to respond to advertisements regarding new initiatives. Furthermore, we were asking them to pioneer an unfamiliar program that was not yet established in the community. We drew on a wide range of recruitment strategies. Targeted mail/invitations using a commercial database and distribution of flyers locally were the most effective approaches. The response rate was 13% with an overall cost of £2,030 (£9 per response). This rate is comparable to those reported by other community programs such as the Groningen Active Living Model which reported a response rate of 12.5% ($84 per response) ( Stevens et al., 2008).

An avenue which was not explored in this feasibility trial was recruitment via primary care ( McMurdo et al., 2011). General Practitioners and Practice Nurses have regular contact with older patients and are well placed to identify physical frailty and signs of loneliness or isolation. Social prescribing initiatives could be a promising recruitment strategy for the ACE intervention, offering an opportunity to prescribe non-medical services and holistically support patients with interrelated health and social problems ( Kimberlee, 2013). Working closely with community providers of social care, pharmacists and occupational therapists could also assist recruitment. The power of word-of-mouth should also not be underestimated. Further studies of the ACE intervention need to include an internal pilot stage where the feasibility of these recruitment strategies can be established.

A rolling approach to recruitment, providing sufficient time for participants recruited in the early phase to embed themselves in the program, and subsequently share their positive experience with their peers should be tested. This approach is difficult to incorporate within the constraints of a funded research study timeline, as it would extend the duration and hence the costs of a trial. However, research funders have realized the importance and challenges of effective recruitment and given a well-justified rationale, they should be supportive of innovative recruitment models and research designs to enhance trial success. Furthermore, this approach provides a more realistic and pragmatic strategy when implementing and rolling out the program in real world settings.

Participants, particularly in the control group, did not comply well with the instructions about wear time of the waist-worn accelerometers. In a trial with repeated measures, wearing these devices can become a burden. For future trials, we suggest the use of wrist-worn accelerometers which improve compliance rates, as most devices can be continuously worn ( Huberty, Ehlers, Kurka, Ainsworth, & Buman, 2015).

The ACE intervention included two social events to which all ACEs-I, activators, and coordinators were invited. These sessions were well received and well attended, and offered further opportunities for meeting new people and exchanging information about local activities. Future studies could facilitate group cohesion in this way and identity other opportunities for interaction among participants. Apart from potentially contributing to improved adherence rates and perceptions of well-being, these events may also support long-term maintenance of positive outcomes for the trial participants.

There was also evidence of organic unplanned growth. Several of the ACEs-I who met during these events formed their own "After ACE" groups, meeting regularly and organizing outings. A future ACE trial will actively support the empowerment of participants to create their own network and become "ambassadors" for the ACE intervention while monitoring the impact of this approach through comprehensive process evaluation. This should contribute to the long-term sustainability and cost-effectiveness of the ACE program.

ACE is a simple and affordable intervention and its potential has been recognized by Public Health England which identified ACE as promising practice in the UK ( Public Health England, 2014). It has been adopted by one of the community partners involved in its development and is currently being delivered in the city of Bristol. A full effectiveness and cost-effectiveness pragmatic trial will determine the cost-benefit of delivering ACE.

Conclusion

This feasibility trial has provided evidence that the ACE intervention is acceptable to all groups of contributors and participants. It is feasible to operate, as costs and labor requirements are relatively low. We have provided preliminary support for the effectiveness of the program in helping isolated and inactive older people to get out and about more, improve their confidence, and engage more with their community. A pragmatic trial employing diverse recruitment strategies, including physical function as one of the key outcomes, promoting the active engagement of participants as ACE Ambassadors and assessing PA with wrist-worn accelerometers will provide definitive evidence about the effectiveness and cost-effectiveness of this promising intervention.

Funding

This study was supported by Medical Research Council - Lifelong Health and Wellbeing (grant/award number: G1001864).

Conflict of Interest

None reported.

References

This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.

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Feasibility Trial Evaluation of a Peer Volunteering Active Aging Intervention: ACE (Active, Connected, Engaged)

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Few older people achieve the recommended 150 min of moderate-to-vigorous-intensity physical activity (MVPA) each week ( Keadle, McKinnon, Graubard, & Troiano, 2016). The greatest gains in life expectancy and life quality are likely to occur by moving from the current very low levels of PA to some activity.

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