A systematic review and meta-analysis of tertiary interventions in clinical burnout

Clinical burnout is one of the leading causes of work absenteeism in high- and middle-income countries. There is hence a great need for the identificationof effective intervention strategies to increase return-to-work (RTW) in this population. This review aimed to assess the effectiveness of tertiary interventions for individuals with clinically significant burnout on RTW and psychological symptoms of exhaustion, depression and anxiety. Four electronic databases (Ovid MEDLINE, PsychINFO, PubMed and CINAHL Plus) were searched in April 2016 for randomized and non-randomized controlled trials of tertiary interventions in clinical burnout. Article screening and data extraction were conducted independently by two reviewers. Pooled odds ratios (ORs) and hazard ratios (HRs) were estimated with random-effects meta-analyses. Eight articles met the inclusion criteria. There was some evidence of publication bias. Included trials were of variable methodological quality. A significant effect of tertiary interventions compared with treatment as usual or wait-list controls on time until RTW was found, HR = 4.5, 95% confidence interval (CI) = 2.15–9.45; however, considerable heterogeneity was detected. The effect of tertiary interventions on full RTW was not significant, OR = 1.33, 95% CI = 0.59–2.98. No significant effects on psychological symptoms of exhaustion, depression or anxiety were observed. In conclusion, tertiary interventions for individuals with clinically significant burnout may be effective in facilitating RTW. Successful interventions incorporated advice from labor experts and enabled patients to initiate a workplace dialogue with their employers

Personality typologies of smokers and excessive drinkers: a cross-sectional survey of respondents in the BBC Lab UK Study

Background: Several personality traits have been linked to addictive behaviours, including smoking and excessive drinking. We hypothesised that the combination of low conscientiousness, high extraversion and high neuroticism would be synergistically associated with smoking, excessive drinking and both behaviours combined. Methods: Respondents aged 16+ years (N=363,454) were surveyed between 2009-2013 as part of the BBC Lab UK Study, with no restrictions on geographical location. Respondents provided information about sociodemographic characteristics, personality traits, and smoking and alcohol consumption. A series of multivariable logistic regression analyses were conducted. Results: No significant three-way but significant two-way interactive effects were observed. The association of high extraversion with smoking was more pronounced in those with high (vs. low) conscientiousness (ORadj=1.51, 95% CI=1.46, 1.56, p<.001; ORadj=1.38, 95% CI=1.35, 1.42, p<.001). The association of high extraversion with excessive drinking was more pronounced in those with low (vs. high) conscientiousness (ORadj=1.70, 95% CI=1.67, 1.74, p<.001; ORadj=1.60, 95% CI=1.56, 1.63, p<.001). The association of high extraversion with both behaviours combined was more pronounced in those with high (vs. low) conscientiousness (ORadj=1.74, 95% CI=1.65, 1.83, p<.001; ORadj=1.62, 95% CI= 1.56, 1.68, p<.001). Results remained largely robust in sensitivity analyses. Conclusions: In a large international survey, we identified two-way ‘personality typologies’ that are associated with greater odds of smoking, excessive drinking and both behaviours combined. The results may be useful for the tailoring of behaviour change interventions to at-risk individuals

Smokers’ and drinkers’ choice of smartphone applications and expectations of engagement: a think aloud and interview study

BACKGROUND: Public health organisations such as the National Health Service in the United Kingdom and the National Institutes of Health in the United States provide access to online libraries of publicly endorsed smartphone applications (apps); however, there is little evidence that users rely on this guidance. Rather, one of the most common methods of finding new apps is to search an online store. As hundreds of smoking cessation and alcohol-related apps are currently available on the market, smokers and drinkers must actively choose which app to download prior to engaging with it. The influences on this choice are yet to be identified. This study aimed to investigate 1) design features that shape users’ choice of smoking cessation or alcohol reduction apps, and 2) design features judged to be important for engagement. METHODS: Adult smokers (n = 10) and drinkers (n = 10) interested in using an app to quit/cut down were asked to search an online store to identify and explore a smoking cessation or alcohol reduction app of their choice whilst thinking aloud. Semi-structured interview techniques were used to allow participants to elaborate on their statements. An interpretivist theoretical framework informed the analysis. Verbal reports were audio recorded, transcribed verbatim and analysed using inductive thematic analysis. RESULTS: Participants chose apps based on their immediate look and feel, quality as judged by others’ ratings and brand recognition (‘social proof’), and titles judged to be realistic and relevant. Monitoring and feedback, goal setting, rewards and prompts were identified as important for engagement, fostering motivation and autonomy. Tailoring of content, a non-judgmental communication style, privacy and accuracy were viewed as important for engagement, fostering a sense of personal relevance and trust. Sharing progress on social media and the use of craving management techniques in social settings were judged not to be engaging because of concerns about others’ negative reactions. CONCLUSIONS: Choice of a smoking cessation or alcohol reduction app may be influenced by its immediate look and feel, ‘social proof’ and titles that appear realistic. Design features that enhance motivation, autonomy, personal relevance and credibility may be important for engagement

Changes in Cigarette Smoking and Vaping in Response to the COVID-19 Pandemic in the UK: Findings from Baseline and 12-Month Follow up of HEBECO Study

This study investigated UK adults’ changes in cigarette smoking and vaping during the COVID-19 pandemic and factors associated with any changes. Data were from an online longitudinal study. A self-selected sample (n = 332) of 228 smokers and 155 vapers (51 participants were both smokers and vapers) completed 5 surveys between April 2020 and June 2021. Participants self-reported data on sociodemographics, COVID-19-related, and smoking/vaping characteristics. During the 12 months of observations, among smokers, 45% self-reported a quit attempt (27.5% due to COVID-19-related reasons) since the onset of COVID-19 pandemic and the quit rate was 17.5%. At 12 months, 35.1% of continuing smokers (n = 174) reported smoking less and 37.9% the same, while 27.0% reported an increase in the number of cigarettes smoked/day. Among vapers, 25.0% self-reported a quit attempt (16.1% due to COVID-19-related reasons) and the quit rate was 18.1%. At 12 months, 47.7% of continuing vapers (n = 109) reported no change in the frequency of vaping/hour, while a similar proportion reported vaping less (27.5%) and more (24.8%). Motivation to quit smoking and being younger were associated with making a smoking quit attempt and smoking cessation. Being a cigarette smoker was associated with vaping cessation. Among a self-selected sample, COVID-19 stimulated more interest in reducing or quitting cigarette smoking than vaping

Seven Lessons for interdisciplinary research on interactive digital health

Research and development for interactive digital health interventions requires multi-disciplinary expertise in identifying user needs, and developing and evaluating each intervention. Two of the central areas of expertise required are Health (broadly defined) and Human–Computer Interaction. Although these share some research methods and values, they traditionally have deep differences that can catch people unawares, and make interdisciplinary collaborations challenging, resulting in sub-optimal project outcomes. The most widely discussed is the contrast between formative evaluation (emphasised in Human–Computer Interaction) and summative evaluation (emphasised in Health research). However, the differences extend well beyond this, from the nature of accepted evidence to the culture of reporting. In this paper, we present and discuss seven lessons that we have learned about the contrasting cultures, values, assumptions and practices of Health and Human–Computer Interaction. The lessons are structured according to a research lifecycle, from establishing the state of the art for a given digital intervention, moving through the various (iterative) stages of development, evaluation and deployment, through to reporting research results. Although our focus is on enabling people from different disciplinary backgrounds to work together with better mutual understanding, we also highlight ways in which future research in this interdisciplinary space could be better supported

Perceptions of factors influencing engagement with health and wellbeing apps: a qualitative study using the COM-B model and Theoretical Domains Framework

Objectives. User engagement with health and wellbeing apps is typically poor. Understanding factors that influence engagement can inform the design of more engaging apps. This study explored users’ experiences of and reasons for engaging and not engaging with health and wellbeing apps. / Methods. UK-based adults (N=17) interested in using a health or wellbeing app took part in a semi-structured interview to explore experiences of engaging with these apps. Data were analysed with the framework approach, informed by the Capability, Opportunity, Motivation – Behaviour (COM-B) model and the Theoretical Domains Framework, two widely used frameworks that incorporate a comprehensive set of behavioural influences. / Results. Factors to influence capability included accessible information (e.g. user guidance, statistical and health information), reduced cognitive load, well-designed reminders, self-monitoring features, features that help to establish a routine, features that offer safety netting and stepping-stone app characteristics. Tailoring, peer support and embedded professional support were identified as important factors that enhance users’ opportunities for engagement. Feedback, rewards, encouragement, goal setting, action planning, self-confidence and commitment were judged to be motivation factors that affect engagement. / Conclusion. Multiple factors were identified across all components of the COM-B model that may be valuable for the development of more engaging health and wellbeing apps. Engagement appears to be influenced primarily by features that provide user guidance, promote minimal cognitive load and support self-monitoring (capability), provide embedded social support (opportunity), and goal setting with action planning (motivation)

Associations between vaping and Covid-19: Cross-sectional findings from the HEBECO study

AIMS: To explore i) associations between vaping and self-reported diagnosed/suspected Covid-19; ii) changes in vaping since Covid-19 and factors associated with these changes; iii) whether Covid-19 motivated current or recent ex-vapers to quit. METHODS: Cross-sectional online survey of 2791 UK adults recruited 30/04/2020-14/06/2020. Participants self-reported data on sociodemographic characteristics, diagnosed/suspected Covid-19, vaping status, changes in vaping and motivation to quit vaping since Covid-19. RESULTS: There were no differences in diagnosed/suspected Covid-19 between never, current and ex-vapers. Bayes factors indicated there was sufficient evidence to rule out small negative (protective) associations between vaping status and diagnosed/suspected Covid-19. Among current vapers (n = 397), 9.7 % (95 % CI 6.8-12.6 %) self-reported vaping less than usual since Covid-19, 42.0 % (37.2-46.9 %) self-reported vaping more, and 48.3 % (43.4-53.2 %) self-reported no change. In adjusted analyses, vaping less was associated with being female (aOR = 3.40, 95 % CI 1.73-6.71), not living with children (aOR = 4.93, 1.15-21.08) and concurrent smoking (aOR = 8.77, 3.04-25.64), while vaping more was associated with being younger (aOR = 5.26, 1.37-20.0), living alone (aOR = 2.08, 1.14-3.85), and diagnosed/suspected Covid-19 (aOR = 4.72, 2.60-8.62). Of current vapers, 32.2 % (95 % CI 27.5-36.8 %) were motivated to quit vaping since Covid-19, partly motivated by Covid-19, and 21.0 %, (10.5-31.4 %) of recent ex-vapers quit vaping due to Covid-19. CONCLUSIONS: Among UK adults, self-reported diagnosed/suspected Covid-19 was not associated with vaping status. Half of current vapers changed their vaping consumption since Covid-19, with the majority reporting an increase, and a minority was motivated to quit due to Covid-19. REGISTRATION: The analysis plan was pre-registered, and it is available at https://osf.io/6j8z3/

Influences on the uptake of health and wellbeing apps and curated app portals: a think aloud and interview study

Background: Health and wellbeing smartphone apps can be identified through different routes, including via curated health app portals, but little is known about people’s experiences of this. Objective: This study explored how people select health apps online and their views on curated portals. Methods: Eighteen UK-based adults were recruited and asked to verbalise their thoughts whilst searching for a health or wellbeing app online, including on two curated health app portals. This was followed by semi-structured interviews. Data were analysed using Framework Analysis, informed by the COM-B model and the Theoretical Domains Framework. Results: Searching for health and wellbeing apps online was described as a ‘minefield’. App uptake appeared to be influenced by i) capabilities (e.g. app literacy skills, health and app awareness), ii) opportunities (e.g. app aesthetics, cost and social influences) and iii) motivation (e.g. the perceived utility and accuracy of the app, and transparency about data protection). Social influences and the percieved utility of an app, in particular, were important. People were not previously aware of curated portals but found the concept appealing and likely to engender trust and address data protection concerns. While apps listed on these were perceived as more trustworthy, their presentation was considered disappointing. Conclusions: The uptake of health and wellbeing apps appear primarily influenced by social influences and the perceived utility of the app. With curated health app portals perceived as credible, app uptake via such portals may mitigate concerns related to data protection and accuracy, but their implementation must better meet user needs. Clinical Trial: N

Perceptions of factors influencing engagement with health and wellbeing apps: a qualitative study using the COM-B model and Theoretical Domains Framework as an analytical framework

Background: Digital health media, such as health and wellbeing smartphone apps, could offer an accessible and cost-effective way to deliver health and wellbeing interventions. A key component of the effectiveness of these apps is user engagement. However, engagement with health and wellbeing apps is typically sub-optimal. Previous studies have identified multiple factors that influence engagement, however, most of these studies were conducted on specific populations or focused on apps targeting a particular behaviour. Understanding factors that influence engagement with a wide range of health and wellbeing apps can help inform the design and development of more engaging apps. Objective: The aim of this study was to explore users’ experiences of and reasons for engaging and not engaging with a wide range of health and wellbeing apps. Methods: A sample of adults in the UK (N=17) interested in using a health or wellbeing app took part in a semi-structured interview to explore experiences of engaging and reasons for not engaging with these apps. Participants were recruited via social media platforms. Data were analysed with the framework approach, informed by the Capability, Opportunity, Motivation – Behaviour (COM-B) model and the Theoretical Domains Framework, two widely used frameworks that incorporate a comprehensive set of behavioural influences. Results: Factors appearing to influence the capability of participants to engage with health and wellbeing apps included available user guidance, statistical and health information, reduced cognitive load, well-designed reminders, self-monitoring features, features that help to establish a routine, features that allow retaining the app for a potential precipitating event in the future (‘safety netting’) and features that offer a first step in the behaviour change process (‘stepping stone’). Tailoring, peer support and embedded professional support were identified as important factors that appeared to enhance users’ opportunity for engagement with health and wellbeing apps. Feedback, rewards, encouragement, goal setting, action planning, self-confidence and commitment were judged to be motivation factors affecting engagement with health and wellbeing apps. Conclusions: Multiple factors were identified across all components of the COM-B model that may be valuable for enhancing the engagement of health and wellbeing apps. Engagement appears to be influenced primarily by features that provide user guidance, promote minimal cognitive load and support self-monitoring (capability), provide embedded social support (opportunity), and goal setting with action planning (motivation). We provide recommendations for policy makers, industry, health care providers and app developers on how to increase engagement. Clinical Trial: Not applicable