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Topic 1: Online Counseling and its benefits 

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Topic 1: Online Counseling and its benefits 

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This study is centered around data from ages 11-25 years old and the use of online resources for mental health support. They used the Goal-Based Outcome tool online to measure progress on goals. They set 3 goals and track them throughout the treatment. They also used the Reliable Change Index. Which they based on parent-reported data. The results showed that those who spent more time talking to a counselor felt a more meaningful change in their life and mental health status. The point of this study was to see if an online counseling service would have an impact on mental health amount of meaningful change.

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Jacob, J; Costa da Silva, L; Sefi, A; Edbrooke-Childs, J; (2021) Online counselling and goal achievement: Exploring meaningful change and the types of goals progressed by young people. Counselling and Psychotherapy Research , 21 (3) pp. 502-513. 10.1002/capr.12363.

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Abstract

Background: Young people are increasingly looking towards the internet for mental health support. There has been little research on the impact of online counselling, as captured in routine outcome measures. This research aims to explore an online counselling service, using goal-based data. / Methods: 'Meaningful change' drawing on the principles of the Reliable Change Index, t tests and logistic regression were applied to administration data (n = 4,218) to assess goal progress, and associations between service contact, goal type and meaningful change. / Results: 55.6% of young people reported meaningful goal improvement. Those who meaningfully improved spent significantly more time engaged than those who did not. Goal types most likely to meaningfully improve were 'getting professional help' and 'self-help-self-care'. / Conclusions: Most young people made significant movement towards their collaboratively agreed goals, which is a good indication that the service is helping to address important areas of change. The findings, linked to earlier research, may indicate that those who report improvements in goals may engage with services more. The high proportion of 'getting help' goals may be attributable to the online setting, which young people may use as a first point of contact for help seeking, to gather information to access further support. With the increased uptake of online support services associated with the current global pandemic, future research should consider the present findings as a baseline of goal progress and service utilisation.

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Online counselling and goal achievement: Exploring meaningful change and the types of goals progressed by young people - UCL Discovery

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UCL Discovery is UCL's open access repository, showcasing and providing access to UCL research outputs from all UCL disciplines.

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This study is focused on providing more evidence that online counseling is beneficial and as reliable as face-to-face counseling. They define online counseling as using technology as way of communication between a counselor and patient. Whether this be through online meeting, like zoom or through chat, or email. They used meta-analysis to compare other studies to their research question. Their main method was comparing peer-reviewed references from 1995-2012 that related to online therapy. There were 1, 872 results and 29 extra studies found through searching the references of the main studies. They found that in 6 of the articles that related to chat interventions, that there was a significant positive effect from online counseling. There was quite a bit of limitations with the studies they referred to, as most of the studies only worked with small populations.

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Online counseling and therapy for mental health problems: A systematic review of individual synchronous interventions using chat.

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Online interventions are increasingly seen as having the potential to meet the growing demand for mental health services. However, with the burgeoning of services provided online by psychologists, counselors, and social workers, it is becoming critical to ensure that the interventions provided are supported by research evidence. This article reviews evidence for the effectiveness of individual synchronous online chat counseling and therapy (referred to as “online chat”). Despite using inclusive review criteria, only six relevant studies were found. They showed that although there is emerging evidence supporting the use of online chat, the overall quality of the studies is poor, including few randomized control trials (RCTs). There is an urgent need for further research to support the widespread implementation of this form of mental health service delivery. (PsycINFO Database Record (c) 2016 APA, all rights reserved)

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Comparison study of Online and Face-to-Face Counseling Client Perceptions

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Comparison study of Online and Face-to-Face Counseling Client Perceptions

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This study focuses on the differences and similarities between these two counseling methods. It centers around 3 factors, mental health, social presence, and working alliance. The data set was 37 face-to-face and 13 online counseling participants. They gathered data through a demographic questionnaire, a working alliance inventory which consisted of a short form, Networked Minds Social Presence Measure, and a general health questionnaire. This study showed results that online counseling works well for goal setting, since communication like email and texts puts goals into written form and is easier to refer back to. They also found a higher score of working alliance in online counseling, supporting the hypothesis that you can form this alliance despite not being in the same physical space. Overall, this case supports that online counseling can be just as beneficial as in person counseling.

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References

Jacob, J., da Silva, L. C., Sefi, A., & Edbrooke, C. J. (2021). Online counselling and goal achievement: Exploring meaningful change and the types of goals progressed by young people. Counselling & Psychotherapy Research, 21(3), 502–513. https://doi.org/10.1002/capr.12363

Holmes, C., & Foster, V. (2012). A preliminary comparison study of online and face-to-face counseling: Client perceptions of three factors. Journal of Technology in Human Services, 30(1), 14–31. https://doi.org/10.1080/15228835.2012.662848

Dowling, M., & Rickwood, D. (2013). Online counseling and therapy for mental health problems: A systematic review of individual synchronous interventions using chat. Journal of Technology in Human Services, 31(1), 1–21. https://doi.org/10.1080/15228835.2012.728508

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Topic 2: COVID-19 and its effects on Mental Health

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Topic 2: COVID-19 and its effects on Mental Health

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Bremner, J. D., Russo, S. J., Gallagher, R., & Simon, N. M. (2025). Acute and long-term effects of COVID-19 on brain and mental health: A narrative review. Brain, Behavior, and Immunity, 123, 928–945. https://doi.org/10.1016/j.bbi.2024.11.007

Novotný, J. S., Gonzalez-Rivas, J. P., Kunzová, Š., Skladaná, M., Pospíšilová, A., Polcrová, A., … Stokin, G. B. (2024). The long-term effects of consecutive COVID-19 waves on mental health. BJPsych Open, 10(1), e15. doi:10.1192/bjo.2023.620

Wilding, S., O’Connor, D. B., Ferguson, E., Wetherall, K., Cleare, S., O’Carroll, R. E., Robb, K. A., & O’Connor, R. C. (2022). Information seeking, mental health and loneliness: Longitudinal analyses of adults in the UK COVID-19 Mental Health and Wellbeing Study. Psychiatry Research, 317, 1–7. https://doi.org/10.1016/j.psychres.2022.114876

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This study focuses on the long-term effects on mental health and the brain. The main method used was literature review. They reviewed articles from January, 1st 2020 - July, 15th 2023 with keywords such as mental health, anxiety, and depression. They found that someone with the COVID-19 infection had a greater chance of developing a psychiatric disorder. The presence of a psychiatric disorder did not increase your chances of getting COVID-19 but if it was present before getting sick, it had potential to make the disorder worse afterwards. They found that acute COVID-19 has had an increase of anxiety, trauma, and mood disorders. They believe this was because of inflammatory reactions with the breakdown of blood and also social change that came with the pandemic.

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Longitudinal analyses of adults in the UK COVID-19 

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Longitudinal analyses of adults in the UK COVID-19 

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This study focuses on women in the UK and how they reported having an increase of symptoms of anxiety during the COVID-19 pandemic. The main method used in this longitudinal study was the utilization of a survey. An email was sent out through March - November 2020 to women 18 and over, to fill out a survey on health and well-being. 3,077 people were included in the final sample. The first wave was during the first 6 weeks of the lockdown. The next 3 waves occurred over the next 2-3 months. The main question was how often do they seek out information about COVID-19. They found that in the beginning of COVID when things were new, they were many searches, as it went on the searches got less and less. They found that there was more searches when the participants felt that they were feeling more anxious and there well-being was lower. This supports the hypothesis that COVID caused an increase in mental health issues.

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Abstract

Information seeking has generally been seen as an adaptive response to the COVID-19 pandemic. However, it may also result in negative outcomes on mental health. The present study tests whether reporting COVID-related information seeking throughout the pandemic is associated with subsequently poorer mental health outcomes. A quota-based, non-probability-sampling methodology was used to recruit a nationally representative sample. COVID-related information seeking was assessed at six waves along with symptoms of depression, anxiety, mental wellbeing and loneliness (N = 1945). Hierarchical linear modelling was used to assess the relationship between COVID-related information seeking and mental health outcomes. Information seeking was found to reduce over time. Overall, women, older and higher socioeconomic group individuals reported higher levels of information seeking. At waves 1-4 (March-June 2020) the majority of participants reported that they sought information on Covid 1-5 times per day, this decreased to less than once per day in waves 5 and 6 (July-November 2020). Higher levels of information seeking were associated with poorer mental health outcomes, particularly clinically significant levels of anxiety. Use of a non-probability sampling method may have been a study limitation, nevertheless, reducing or managing information seeking behaviour may be one method to reduce anxiety during pandemics and other public health crises.

Keywords: Coronavirus, Depression, Anxiety, Social media, Public health, Isolation

1. Introduction

The COVID-19 pandemic has involved a huge amount of information being shared by governments and public health agencies in order to keep people informed about health promoting behaviours to reduce the spread of COVID-19 (e.g., social and physical distancing, handwashing), to provide regular updates on government restrictions and lockdowns, and to allow populations to have access to clear and reliable COVID-related news ( Liu, 2020; Naeem and Bhatti, 2020). This information has come from a variety of sources including through television and newspapers, online via search engines such as Google and via social media, as well as in person via friends and family ( Statista, 2020; Tran et al., 2020). Google Trends data also demonstrated a particular spike in COVID-19 information seeking in March 2020 in the United States of America ( Mangono et al., 2021). Moreover, one early study showed that many individuals consumed their COVID-19 information through the internet, online newspapers and social networks (e.g., Tran et al., 2020).

While information seeking has been adaptive in order to keep up to date with the latest information regarding the pandemic and initial data showed that specific up-to-date and accurate health information was related to lower levels of stress, anxiety and depression ( Wang et al., 2020), it does not always result in positive outcomes. It can be difficult for people to evaluate accurate information when trying to deal with the deluge of information. Information seeking can also be a reassurance seeking behaviour aimed at reducing health-related fears and is particularly common where there is uncertainty about information presented in the media related to a specific topic ( Guillaume and Bath, 2004). However, a high-level of information seeking can be associated with higher health anxiety ( McMullan et al., 2019; Jagtap et al., 2021) and it is suggested that it can actually increase anxiety due to negative reinforcement ( Starcevic and Berle, 2013). Relatedly, previous research has also shown that media messaging about infectious diseases can increase perceptions of public risk and anxiety ( Sell et al., 2017). Moreover, extrapolating from work conducted during the Ebola and H1N1 outbreaks suggests that repeated exposure to the crisis (and associated information) during the COVID-19 pandemic may have led to increased anxiety and elevated stress responses that may lead to future negative health effects ( Thompson et al., 2017; Garfin et al., 2020). Indeed, COVID-related information seeking has been found to be associated with obsessive-compulsive symptoms ( Loosen et al., 2021) and other mental health problems ( Gao et al., 2020). Additionally, greater COVID-related information seeking is related to an increase in pandemic-related preventative health behaviours such as hand washing ( Liu, 2020). It is also related to a decline in other health-related searches (e.g., doctors' appointments; Mangono et al., 2021) and associated with increased distress which is subsequently associated with reduced adherence to preventative measures ( Siebenhaar et al., 2020).

In this paper, we report data from the UK COVID-19 Mental Health and Wellbeing study, a longitudinal, national survey that ran from March 2020 to July 2021. The present study focused on information seeking across the six waves of the study and whether it was related to symptoms of depression, anxiety, and wellbeing, as mental health outcomes, together with loneliness.

2. Methods

Participant recruitment was conducted by Taylor McKenzie, a social research company. A non-probability sample of adults (aged 18 years or older) was recruited from across the UK to the UK COVID-19 Mental Health and Wellbeing study (UK COVID-19-MH), with a longitudinal study design. UK COVID-19-MH has been detailed previously ( O'Connor et al., 2021, O'Connor et al., 2022) and the main research questions were preregistered at AsPredicted.org (#41910).

Between 31 st March and November 2020, members of an existing online UK panel (Panelbase.net) were invited by email to take part in an online survey on health and wellbeing. At wave 1, 7471 panel members were invited to take part and 3077 were included in the final sample (target sample was n=3,000). A quota sampling methodology was employed, with quotas based on age (18-24 years: 12%; 25-34: 17%; 35-44: 18%; 45-54: 18%; 55-64: 15%; ≥65: 20%), gender (women: 51%; men: 49%), socioeconomic grouping (SEG; assessed via The National Readership Survey social grade; AB:27%; C1: 28%; C2: 20%; DE: 25%, based on occupation, where A, B and C1 are higher and categories C2, D, E are lower) and region of the UK (12 regions). The panel has approximately 300,000 registered adult members and of those invited, 4394 did not take part in the survey. The majority were screened out as a particular quota was full (n=3527) and the remainder dropped out (n=867).

The first three waves occurred within the first 6 weeks of the UK lockdown, and the subsequent three waves were roughly every 2 to 3 months, with the interval between waves increasing over time. The survey included questions on a wide range of psychological and social measures along with questions about COVID-19. In this paper we test whether reporting COVID-related information seeking is associated with poorer mental health outcomes. As outlined above and in our previous work ( O'Connor et al., 2022), a total of 3077 adults completed the survey at wave 1. Findings for waves 1 (31 March to 9 April 2020) to 6 (1st October to - 4th November 2020) are reported in the current paper. At wave 2, 89% of participants (n = 2742) completed the survey, 85% (n = 2604) completed wave 3, 77.5% (n = 2384) completed wave 4, 69.7% (n = 2144) completed wave 5 and 74.2% (n = 2283) completed wave 6. 1945 (63.2%) participants completed all six waves of the study.

2.1. Ethical approval

Participants provided written informed consent online. The authors assert that all procedures contributing to this work comply with the ethical standards of the relevant national and institutional committees on human experimentation and with the Helsinki Declaration of 1975, as revised in 2008. All procedures involving human subjects/patients were approved by the University of Glasgow's Medical, Veterinary and Life Sciences Ethics Committee (approval number: 200190146) and participants consented for their data to be used in the research. Participants received £1.50 for the completion of each survey and were entered into prize draws.

3. Measures

Information seeking was assessed using a single item ("How often do you actively seek out information on COVID-19: Less than once a day; 1-5 times a day; 6-10 times a day; 11-20 times a day; 21-50 times a day; 50+times per day). Given the time urgency, this measure was devised by an expert panel of highly experienced researchers and considered to have good face validity. Moreover, similar measures have been used to assess frequency of information seeking in relation to a range of different health behaviours (e.g. Neumark et al., 2013; Jia et al., 2021).

Depressive symptoms were assessed via the nine-item Patient Health Questionnaire (PHQ-9; Löwe et al., 2004; Kroenke and Spitzer, 2002). The 7-item Generalized Anxiety Disorder (GAD-7; Spitzer, Kroenke, Williams and Lowe, 2006) tool was used to assess symptoms of generalised anxiety disorder. Both measures ask how often symptoms have been bothering the respondents in the past 2 weeks on a scale of 0 (not at all) to 3 (nearly every day). Cronbach's alpha for the scales in the current sample ranged from .90 to .93, and .92 to .94, respectively. Scores range from 0-27 on the PHQ-9 and 0-21 on the GAD-7, with higher scores indicating higher levels of depression and anxiety. Scores of≥10 on both measures are thought to indicate clinically significant cut-offs as indicators of at least moderate levels of depression and anxiety ( Kroenke and Spitzer, 2002; Spitzer Kroenke, Williams and Lowe, 2006).

Mental wellbeing was assessed via the 7-item Short Warwick Edinburgh Mental Wellbeing Scale (SWEMWBS; Fat et al., 2017). Participants were asked to respond about their experiences over the last 2 weeks on a 1 (none of the time) to 5 (all the time) scale. Cronbach's alphas for the scale in the current sample ranged from .89 to .92. Scores range from 7-35 with a higher score indicating better mental wellbeing. A score of 19.3 is thought to indicate low levels of mental wellbeing and is used as a clinically significant cut-off (Fat et al., 2016).

Loneliness was measured using the UCLA 3-item loneliness scale ( Hughes et al., 2004). Participants were asked to respond about their experiences over the last 2 weeks on a three-point scale (hardly ever, some of the time, often). Scores ranged from 3-9 where a higher score indicates greater loneliness. Cronbach's alphas for the scale in the current sample ranged from .88 to .90. To our knowledge, there are no published clinically significant cut-offs for this measure, we therefore conducted a median split on the data and treated any scores above the median as indicative of high loneliness.

To assess mental health status, participants were asked to indicate whether they had any mental health conditions, neuro-divergent disorders or alcohol/drug problems. To assess physical health status, participants were asked to indicate whether they had existing physical health conditions (e.g., diabetes, cancer, heart disease).

3.1. Analyses

Analyses were conducted in SPSS v.25 and multilevel models were conducted in HLM 8 ( Raudenbush et al., 2011). We assessed how mental health outcomes and loneliness changed over the waves of the study along with whether information seeking differed by demographic characteristics (age, SEG, gender). Finally, we assessed whether information seeking was associated with mental health outcomes (depression, anxiety, wellbeing) and loneliness. Analyses were performed on the 1945 individuals who completed all six waves of the survey.

Hierarchical linear modelling was used to assess the relationship between COVID-related information seeking and mental health (depression, anxiety and wellbeing) and loneliness scores. The data were considered to have a two-level hierarchical structure. Level 1 variables (COVID-related information seeking, levels of depression, anxiety, mental wellbeing and loneliness at each wave) were group mean centred. Level 2 variables (gender (female, male), age (under and equal to 30, over 30), physical and mental health status (any mental health conditions reported: no/yes; any physical health conditions reported: no/yes), socioeconomic group (SEG): high (A + B + C1) vs. low (C2 + D + E)) were uncentred as they were dichotomous variables. The level 1 variables were modelled as random as we assumed that each of the within-person variables would vary from wave to wave. The level 2 variables were assumed to be fixed. For all the models tested here, an unrestricted level 1 variance-covariance structure was assumed. The main analyses were conducted in two blocks. First, we examined whether COVID-related information seeking was associated with each of the mental health and wellbeing outcomes (over the past 2 weeks) across the 6 waves. In these analyses, gender, age, SEG, whether participants had an existing mental health or physical health condition, and whether they lived alone or not were entered as covariates. Wave was also entered as a control variable in all analyses. Second, we explored whether the effects of COVID-related information seeking on mental health and loneliness were moderated by mental health status. Third, these analyses were repeated using the clinical cut-off to indicate high levels of depression, anxiety and loneliness and low levels of wellbeing using hierarchical Bernoulli models. Depression, anxiety and wellbeing scores were converted into a binary categorization based on previously published clinically meaningful cut-offs (scores of 10+ on the PHQ and GAD indicate moderate or severe levels of depression and anxiety; scores of 19.3 or less on the SWEMWBS indicate low wellbeing).

4. Results

4.1. Covid-related information seeking and mental health outcomes

4.1.1. Information seeking over time

From waves 1-4, the majority of participants reported that they sought information on Covid 1-5 times per day (see Fig. 1 & Table 1 ). During waves 5-6, the majority of participants reported that they sought information less than once per day, suggesting that information seeking reduced over time. The proportions of participants reporting information seeking more than 6 times per day also reduced over time, with the highest at wave 1 and lowest at wave 5.

Fig. 1.

Information seeking over the six study waves (N=1945).

4.1.2. Information seeking by participant characteristics

Chi squared analyses were conducted to assess the relationship between age, gender and SEG on information seeking over the six waves. There was a significant relationship between SEG and information seeking at waves 1, 2, 3, 5, and 6 (all p<.02) where people with high SEG occupations were more likely to report greater information seeking compared to people with low SEG occupations. There was a significant relationship between gender and information seeking at waves 3-6 (all p<.001), with women reporting greater information seeking than men. Finally, there was a significant relationship between age and information seeking at waves 2, 3, 4 and 6, with older individuals (aged over 30) reporting greater information seeking compared to participants under 30 (all p<.02).

4.1.3. Is Covid-related information seeking associated with mental health outcomes across the six waves?

The results of the hierarchical linear models found that there were significant positive associations between COVID-related information seeking and depression ( Table 2 ; unadjusted, β = .25, p = .001; adjusted, β = 0.25, p = .001) and anxiety (unadjusted, β = .22, p<.001; adjusted, β = .22, p < .001) and a negative association between COVID-related information seeking and wellbeing (unadjusted, β = -.26, p<.001; adjusted, β = -.26, p < .001) and a positive association with loneliness (unadjusted, β = .05, p=.026; adjusted, β = .05, p = .026). The results showed that higher levels of COVID-related information seeking were associated with higher levels of depression, anxiety and loneliness and lower wellbeing across the 6 waves

4.1.4. Is Covid-related information seeking associated with clinically meaningful mental health outcomes?

The results of the hierarchical Bernoulli models found that there were significant positive associations between COVID-related information seeking and clinically meaningful levels of depression (unadjusted, Odds Ratio = 1.14, 95% CI 1.014,1.280; adjusted, Odds Ratio = 1.09, 95% CI 1.014,1.280), anxiety (unadjusted, Odds Ratio = 1.21, 95% CI 1.066,1.375; adjusted, Odds Ratio = 1.17, 95% CI 1.066,1.375) and wellbeing (unadjusted, Odds Ratio = 1.12, 95% CI 1.003,1.248; adjusted, Odds Ratio = 1.12, 95% CI 1.003,1.248). The association between COVID-related information seeking and clinically meaningful levels of loneliness were not statistically significant ( Table 3 ).

4.1.5. Are the effects of COVID-related information seeking moderated by current mental health status?

Mental health status did not significantly moderate the relationship between COVID-related information seeking and any of the mental health outcomes or loneliness (See Supplementary Table 1).

5. Discussion

The general trend in the data was that information seeking declined over time, peaking at the earliest stages of the pandemic (waves 1 and 2; March- April 2020) with the majority of participants reporting they sought information between one and five times per day. By wave 5 (July-August 2020), the majority of participants reported that they sought information less than once a day. Nevertheless, information seeking was found to be related to all three mental health outcomes where higher levels of information seeking were associated with greater depression and anxiety scores and lower wellbeing.

Information seeking was also found to differ by participant demographics, with older participants, women and those from higher socioeconomic groups reporting greater information seeking. In addition, individuals reporting higher levels of information seeking were more likely to also report mental health outcomes that were at or above the clinically meaningful thresholds. In particular, high levels of information seeking were associated with the clinical threshold for moderate or severe anxiety on the GAD.

The current findings are consistent with other work that has explored the adverse effects of information seeking and exposure to media messaging during public health crises ( Thompson et al., 2017; Garfin et al., 2020). Previously reported negative effects have included increased psychological distress which may have widespread impacts, including future mental health problems (e.g., Starcevic and Berle, 2013; Gao et al., 2020; Loosen et al., 2021) as well as potentially reducing compliance with preventative health behaviours ( Siebenhaar et al., 2020). Moreover, these current findings are in line with other studies conducted during the COVID-19 pandemic and have important implications for future pandemics. For example, Loosen et al. (2021) found evidence that COVID-related information seeking was associated with increases in obsessive-compulsive symptoms and underlined the importance of closely monitoring the public's mental health during public health crises ( Loosen et al., 2021). Similarly, Gao et al. (2020) found high prevalence of mental health problems, in particular, anxiety and depression, to be associated with high social media usage in individuals during the COVID-19 outbreak. Wang et al. (2021), in a large study of seven middle-income countries in Asia, also found that spending less time on health information was a protective factor for mental health. Taken together, there is a clear need for governments and health agencies to consider strategies to help mitigate the negative effects of the "infodemic" which often arises during public health emergencies.

How might high levels of information seeking about COVID-19 lead to adverse mental health outcomes? Evidence from other public health crises and traumatic events show that in cases of uncertainly, where information is unknown or badly communicated, exposure to this information can trigger heightened appraisals of threat, which lead to feelings of uncontrollability and increased levels of anxiety ( Garfin et al., 2020; Taha et al., 2014). This is likely to be the case during the COVID-19 pandemic, particularly during the early stages before a vaccine had become viable and the future remained entirely uncertain ( O'Connor et al., 2020, 2022). In another earlier example, during the Ebola outbreak in 2014, a study in the United States (where risk levels were low) found that higher levels of exposure to Ebola-related stories were associated with increased worry, distress and impaired functioning ( Thompson et al., 2017).

It has also been shown that the amount and type of media exposure can negatively affect psychological distress following publicly traumatic events. For example, following the Boston Marathon bombings, individuals who had spent a large amount of time exposed to bombing-related media reported greater acute stress symptoms, with future exposure to these kind of events creating a cycle of distress ( Garfin et al., 2020; Holman et al., 2014). Moreover, the same research team found that exposure to particular types of media also made a difference, such that exposure to graphic images (i.e., that included blood) was associated with elevated posttraumatic stress and fear 6 months after the bombings. Therefore, it is likely that the amount, type and often-graphic nature of media exposure will have contributed to the associations between COVID-19 information-seeking and psychological distress observed in the current study. Unfortunately, given the time urgent nature of setting up studies early in the pandemic together with the need to reduce participant burden, it was not possible to collect information on the different sources of information sought by participants. However, as outlined above, badly communicated, uncertain and graphic information may have had a particularly adverse effect on mental health outcomes during COVID-19 pandemic.

This study also found that COVID related information seeking was associated with higher levels of loneliness (while controlling for whether participants lived alone or not), although the association was small and did not translate into a meaningful clinical cut-off for loneliness. It is clear from recent meta-analytical findings that there were small, but robust increases in loneliness during the pandemic ( Ernst et al., 2022). However, less is known about the psychological and behavioural factors that are associated with changes in loneliness levels. Therefore, the current finding is important as it suggests that information seeking may play a role in helping improving our understanding of individual differences in loneliness during times of uncertainty and risk.

Overall, the present research demonstrates that information seeking is associated with poorer mental health outcomes. Implications of this work suggest that management of information seeking behaviour may be one method to reduce anxiety and improve wellbeing during situations that involve large amounts of information sharing. Another method might be to target repetitive thinking such as worry and rumination likely triggered by information seeking. A recent meta-analysis has identified a number of useful interventions that can reliably reduce worry and rumination. For example, techniques that encourage individuals to challenge their thinking style, to disengage from the emotional responses brought on by worry or rumination as well as mindfulness-based approaches should be considered ( McCarrick et al., 2021, see also Prudenzi et al., 2022). Additionally, due to the sheer amount of information from differing sources, of varying validity, that is available, it is difficult for people to know what sources of information to rely on or trust. It is also important that health authorities and governmental organisations provide clear information during these situations in order to reduce potential uncertainty that can stem from the varying quality of information available online. However, the current findings suggest that public health agencies should encourage members of the public to limit their information seeking and to have regular breaks from media and messaging. Future research might also usefully investigate the extent to which high levels of information seeking may contribute to 'pandemic fatigue' and emerging work on COVID-19 burnout and burnout more broadly ( Al-Ghunaim et al., 2021; Wang et al., 2021).

Finally, we recognise that strengths and limitations of the present study include that the study is likely to have under-recruited individuals with particularly poor mental health outcomes and the use of a non-probability, quota-based sampling method is a shortcoming as not all members of the population had a chance to participate, and this may limit the generalisability of the findings. Nevertheless, it is important to note that utilisation of this sampling approach allowed us to ensure we recruited a nationally representative sample. The study also relies on self-reported outcomes including a single item measure of information seeking, though, it is worth noting that this measure was devised by a panel of experts, is similar to other measures and has good face validity. Additionally, we do not know the direction of causality and whether poorer mental health causes greater information seeking, or information seeking causes poorer mental health. Despite this, the study recruited a relatively large, quota-based sample and is able to report the relationship between the key variables over a substantial period of time.

In conclusion, the results of the current study show that information seeking during the COVID-19 pandemic was related to poorer mental health outcomes. The results were particularly pronounced for anxiety. Reducing or managing information seeking behaviour may be one method to reduce anxiety during situations involving large amounts of information sharing, such as pandemics and future public health crises.

Funding

This work was supported by the University of Glasgow, Samaritans, Scottish Association for Mental Health and the Mindstep Foundation.

Author contributions

S.W. and D.O'C. led the statistical analyses and led the drafting of the manuscript but all authors contributed to further drafting, revising and approved the final manuscript for submission.

Declaration of Competing Interest

None of the authors have any conflict of interest to declare.

Footnotes

Appendix. Supplementary materials

References

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Supplementary Materials

Articles from Psychiatry Research are provided here courtesy of Elsevier

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Information seeking, mental health and loneliness: Longitudinal analyses of adults in the UK COVID-19 mental health and wellbeing study

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Information seeking has generally been seen as an adaptive response to the COVID-19 pandemic. However, it may also result in negative outcomes on mental health. The present study tests whether reporting COVID-related information seeking throughout ...

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Effects of consecutive COVID-19 waves on mental health

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Effects of consecutive COVID-19 waves on mental health

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The main point of this study was to examine longitudinal changes with COVID-19 and mental health. They did this through a probability sample. This consisted of an online survey that was completed by participants from the COVID-19 add-on study. They had them do this study at four different time points, pre-covid, first wave, second wave, and third wave. (The specific months are listed in the paper) They found that during the waves, stress and depressive levels were higher than pre-covid. There were many stressors on-top of just covid. They called them secondary stressors, which included loneliness, a lack of resilience, and a negative emotions regarding COVID.

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The long-term effects of consecutive COVID-19 waves on mental health.

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Background: Although several studies have documented the impact of the COVID-19 pandemic on mental health, the long-term effects remain unclear. Aims: To examine longitudinal changes in mental health before and during the consecutive COVID-19 waves in a well-established probability sample. Method: An online survey was completed by the participants of the COVID-19 add-on study at four time points: pre-COVID-19 period (2014–2015, n = 1823), first COVID-19 wave (April to May 2020, n = 788), second COVID-19 wave (August to October 2020, n = 532) and third COVID-19 wave (March to April 2021, n = 383). Data were collected via a set of validated instruments, and analysed with latent growth models. Results: During the pandemic, we observed a significant increase in stress levels (standardised β = 0.473, P < 0.001) and depressive symptoms (standardised β = 1.284, P < 0.001). The rate of increase in depressive symptoms (std. covariance = 0.784, P = 0.014), but not in stress levels (std. covariance = 0.057, P = 0.743), was associated with the pre-pandemic mental health status of the participants. Further analysis showed that secondary stressors played a predominant role in the increase in mental health difficulties. The main secondary stressors were loneliness, negative emotionality associated with the perception of COVID-19 disease, lack of resilience, female gender and younger age. Conclusions: The surge in stress levels and depressive symptoms persisted across all three consecutive COVID-19 waves. This persistence is attributable to the effects of secondary stressors, and particularly to the status of mental health before the COVID-19 pandemic. Our findings reveal mechanisms underlying the surge in mental health difficulties during the COVID-19 waves, with direct implications for strategies promoting mental health during pandemics. (PsycInfo Database Record (c) 2024 APA, all rights reserved)

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Correlation analysis of self-compassion, life balance, and burnout in counselors

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Correlation analysis of self-compassion, life balance, and burnout in counselors

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This study is a quantitative study that focuses on the relationship between counselor burnout, life-balance and self-compassion. The methods used were Life Balance Inventory, Counselor Burnout Inventory, and Self-Compassion Scale. They found a few different correlations in their results. These included counselors who experience burnout have poor work–life balance, counselors enjoy their job as counselors but do not pay attention to their personal life, counselors enjoy their work but do not pay attention to the quality of their relationships, counselors perceive themselves as being competent but do not like their work environment, and professional counselors who engage in self-compassion practices do not experience burnout.

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A canonical correlation analysis of self‐compassion, life balance, and burnout in counselors.

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This quantitative study explored the relationship between counselor burnout (Counselor Burnout Inventory, CBI), life balance (Life Balance Inventory, LBI), and self‐compassion (Self‐Compassion Scale, SCS) among 331 fully licensed and provisionally licensed counselors throughout the United States with at least 2 years of experience in various clinical settings and providing direct clinical services. Results of two canonical correlation analyses (CCAs) explored the relationship between (a) the subscales of the LBI and the CBI and (b) the subscales of the SCS and the CBI. Both CCAs indicated a statistically significant relationship demonstrating that: (a) increased life balance was associated with lower burnout and (b) increased self‐compassion was associated with lower burnout. Counselors experiencing burnout may turn to increasing their life balance or increasing self‐compassion practices to increase their quality of life. (PsycInfo Database Record (c) 2024 APA, all rights reserved)

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Silva, S. V., Dean, C. J., & Balkin, R. S. (2024). A canonical correlation analysis of self‐compassion, life balance, and burnout in counselors. Journal of Counseling & Development. Advance online publication. https://doi.org/10.1002/jcad.12527

Davies, S. M., Sriskandarajah, S., Staneva, A. S., Boulton, H. C. M., Roberts, C., Shaw, S. H., & Silverio, S. A. (2022). Factors influencing ‘burn‐out’ in newly qualified counsellors and psychotherapists: A cross‐cultural, critical review of the literature. Counselling & Psychotherapy Research, 22(1), 64–73. https://doi.org/10.1002/capr.12485

Silva, S. V., Dean, C. J., & Balkin, R. S. (2024). A canonical correlation analysis of self‐compassion, life balance, and burnout in counselors. Journal of Counseling & Development. Advance online publication. https://doi.org/10.1002/jcad.12527

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Factors influencing ‘burn‐out’ in newly qualified counsellors

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Factors influencing ‘burn‐out’ in newly qualified counsellors

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This study uses cross-cultural literature to explore the experiences of burn-out of new counselors. They discuss the increase of mental health disorders globally and the lack of resources on the counseling side of things. This causes more stress to be put on the current counselors and the ones who are new to the career. They are often giving a heavy caseload. They mention that another cause of burn out can be working with trauma victims, it can often be too much for the counselor to handle if they are not taking care of their own mental health. They also noted that new counselors often feel like their life perspective is changing, which can add another level of stress as well.

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This study focuses novice professional counselors and their experience with working in professional counseling and their self-reported symptoms of burn out. They used surveys and content analysis to complete their research. They did this so they could get an insight of both qualitative and quantitative factors. They analyzed open-ended questions, using the steps of content analysis. They had 1,205 self-reported symptoms of burnout. They noted fatigue, no longer feeling joy at work, physical symptoms, an unhealthy work environment, negative personal relationships, bad coping strategies, and more.

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Self-reported symptoms of burnout in novice professional counselors: A content analysis.

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This study explored the self-reported symptoms of burnout in a sample of 246 novice professional counselors. The authors inductively analyzed 1,205 discrete units using content analysis, yielding 12 categories and related subcategories. Many emergent categories aligned with existing conceptualizations of burnout, while other categories offered new insights into how burnout manifested for novice professional counselors. Informed by these findings, the authors implore counseling scholars to consider, in their conceptualization of counselor burnout, a wide range of burnout symptoms, including those that were frequently endorsed symptoms (e.g., negative emotional experience, fatigue and tiredness, unfulfilled in counseling work) as well as less commonly endorsed symptoms (e.g., negative coping strategies, questions of one’s career choice, psychological distress). Implications for novice professional counselors and supervisors are offered, including a discussion about counselors’ experiences of burnout to ensure they are providing ethical services to their clients. (PsycInfo Database Record (c) 2022 APA, all rights reserved)