22 research outputs found

    A co-production approach guided by the behaviour change wheel to develop an intervention for reducing sedentary behaviour after stroke

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    Background Stroke survivors are highly sedentary; thus, breaking up long uninterrupted bouts of sedentary behaviour could have substantial health benefit. However, there are no intervention strategies specifically aimed at reducing sedentary behaviour tailored for stroke survivors. The purpose of this study was to use co-production approaches to develop an intervention to reduce sedentary behaviour after stroke. Methods A series of five co-production workshops with stroke survivors, their caregivers, stroke service staff, exercise professionals, and researchers were conducted in parallel in two-stroke services (England and Scotland). Workshop format was informed by the behaviour change wheel (BCW) framework for developing interventions and incorporated systematic review and empirical evidence. Taking an iterative approach, data from activities and audio recordings were analysed following each workshop and findings used to inform subsequent workshops, to inform both the activities of the next workshop and ongoing intervention development. Findings Co-production workshop participants (n = 43) included 17 staff, 14 stroke survivors, six caregivers and six researchers. The target behaviour for stroke survivors is to increase standing and moving, and the target behaviour for caregivers and staff is to support and encourage stroke survivors to increase standing and moving. The developed intervention is primarily based on co-produced solutions to barriers to achieving the target behaviour. The developed intervention includes 34 behaviour change techniques. The intervention is to be delivered through stroke services, commencing in the inpatient setting and following through discharge into the community. Participants reported that taking part in intervention development was a positive experience. Conclusions To our knowledge, this is the first study that has combined the use of co-production and the BCW to develop an intervention for use in stroke care. In-depth reporting of how a co-production approach was combined with the BCW framework, including the design of bespoke materials for workshop activities, should prove useful to other researchers and practitioners involved in intervention development in stroke

    Sitting as a moral practice: older adults’ accounts from qualitative interviews on sedentary behaviours

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    Amidst public health campaigns urging people to sit less as well as being more physically active, this paper investigates how older adults make sense of their sedentary behaviour. Using an accounts framework focusing on how people rationalise their sitting practices, we analysed data from 44 qualitative interviews with older adults. All interviewees had received information about sedentary behaviour and health, visual feedback on their own objectively measured sitting over a week and guidance on sitting less. Participants used accounts to position sitting as a moral practice, distinguishing between ‘good’ (active/‘busy’) and ‘bad’ (passive/‘not busy’) sitting. This allowed them to align themselves with acceptable (worthwhile) forms of sitting and distance themselves from other people whose sitting they viewed as less worthwhile. However, some participants also described needing to sit more as they got older. The findings suggest that some public health messaging may lead to stigmatisation around sitting. Future sedentary behaviour guidelines and public health campaigns should consider more relatable guidelines that consider the lived realities of ageing, and the individual and social factors that shape them. They should advocate finding a balance between sitting and moving that is appropriate for each person

    What do older people do when sitting and why? Implications for decreasing sedentary behaviour

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    Background and Objectives: Sitting less can reduce older adults’ risk of ill health and disability. Effective sedentary behavior interventions require greater understanding of what older adults do when sitting (and not sitting), and why. This study compares the types, context, and role of sitting activities in the daily lives of older men and women who sit more or less than average. Research Design and Methods: Semistructured interviews with 44 older men and women of different ages, socioeconomic status, and objectively measured sedentary behavior were analyzed using social practice theory to explore the multifactorial, inter-relational influences on their sedentary behavior. Thematic frameworks facilitated between-group comparisons. Results: Older adults described many different leisure time, household, transport, and occupational sitting and non-sitting activities. Leisure-time sitting in the home (e.g., watching TV) was most common, but many non-sitting activities, including “pottering” doing household chores, also took place at home. Other people and access to leisure facilities were associated with lower sedentary behavior. The distinction between being busy/not busy was more important to most participants than sitting/not sitting, and informed their judgments about high-value “purposeful” (social, cognitively active, restorative) sitting and low-value “passive” sitting. Declining physical function contributed to temporal sitting patterns that did not vary much from day-to-day. Discussion and Implications: Sitting is associated with cognitive, social, and/or restorative benefits, embedded within older adults’ daily routines, and therefore difficult to change. Useful strategies include supporting older adults to engage with other people and local facilities outside the home, and break up periods of passive sitting at home

    Pre-pandemic mental health and disruptions to healthcare, economic and housing outcomes during the COVID-19 pandemic: evidence from 12 UK longitudinal studies

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    Background: The COVID-19 pandemic has disrupted lives and livelihoods, and people already experiencing mental ill health may have been especially vulnerable. Aims: Quantify mental health inequalities in disruptions to healthcare, economic activity and housing. Method: We examined data from 59 482 participants in 12 UK longitudinal studies with data collected before and during the COVID-19 pandemic. Within each study, we estimated the association between psychological distress assessed pre-pandemic and disruptions since the start of the pandemic to healthcare (medication access, procedures or appointments), economic activity (employment, income or working hours) and housing (change of address or household composition). Estimates were pooled across studies. Results: Across the analysed data-sets, 28% to 77% of participants experienced at least one disruption, with 2.3–33.2% experiencing disruptions in two or more domains. We found 1 s.d. higher pre-pandemic psychological distress was associated with (a) increased odds of any healthcare disruptions (odds ratio (OR) 1.30, 95% CI 1.20–1.40), with fully adjusted odds ratios ranging from 1.24 (95% CI 1.09–1.41) for disruption to procedures to 1.33 (95% CI 1.20–1.49) for disruptions to prescriptions or medication access; (b) loss of employment (odds ratio 1.13, 95% CI 1.06–1.21) and income (OR 1.12, 95% CI 1.06 –1.19), and reductions in working hours/furlough (odds ratio 1.05, 95% CI 1.00–1.09) and (c) increased likelihood of experiencing a disruption in at least two domains (OR 1.25, 95% CI 1.18–1.32) or in one domain (OR 1.11, 95% CI 1.07–1.16), relative to no disruption. There were no associations with housing disruptions (OR 1.00, 95% CI 0.97–1.03). Conclusions: People experiencing psychological distress pre-pandemic were more likely to experience healthcare and economic disruptions, and clusters of disruptions across multiple domains during the pandemic. Failing to address these disruptions risks further widening mental health inequalities

    Psychological Distress Before and During the COVID-19 Pandemic Among Adults in the United Kingdom Based on Coordinated Analyses of 11 Longitudinal Studies

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    Importance: How population mental health has evolved across the COVID-19 pandemic under varied lockdown measures is poorly understood, and the consequences for health inequalities are unclear. Objective: To investigate changes in mental health and sociodemographic inequalities from before and across the first year of the COVID-19 pandemic in 11 longitudinal studies. Design, Setting, and Participants: This cohort study included adult participants from 11 UK longitudinal population-based studies with prepandemic measures of psychological distress. Analyses were coordinated across these studies, and estimates were pooled. Data were collected from 2006 to 2021. Exposures: Trends in the prevalence of poor mental health were assessed in the prepandemic period (time period 0 [TP 0]) and at 3 pandemic TPs: 1, initial lockdown (March to June 2020); 2, easing of restrictions (July to October 2020); and 3, a subsequent lockdown (November 2020 to March 2021). Analyses were stratified by sex, race and ethnicity, education, age, and UK country. Main Outcomes and Measures: Multilevel regression was used to examine changes in psychological distress from the prepandemic period across the first year of the COVID-19 pandemic. Psychological distress was assessed using the 12-item General Health Questionnaire, the Kessler 6, the 9-item Malaise Inventory, the Short Mood and Feelings Questionnaire, the 8-item or 9-item Patient Health Questionnaire, the Hospital Anxiety and Depression Scale, and the Centre for Epidemiological Studies–Depression across different studies. Results: In total, 49 993 adult participants (12 323 [24.6%] aged 55-64 years; 32 741 [61.2%] women; 4960 [8.7%] racial and ethnic minority) were analyzed. Across the 11 studies, mental health deteriorated from prepandemic scores across all 3 pandemic periods, but there was considerable heterogeneity across the study-specific estimated effect sizes (pooled estimate for TP 1: standardized mean difference [SMD], 0.15; 95% CI, 0.06-0.25; TP 2: SMD, 0.18; 95% CI, 0.09-0.27; TP 3: SMD, 0.21; 95% CI, 0.10-0.32). Changes in psychological distress across the pandemic were higher in women (TP 3: SMD, 0.23; 95% CI, 0.11, 0.35) than men (TP 3: SMD, 0.16; 95% CI, 0.06-0.26) and lower in individuals with below–degree level education at TP 3 (SMD, 0.18; 95% CI, 0.06-0.30) compared with those who held degrees (SMD, 0.26; 95% CI, 0.14-0.38). Increased psychological distress was most prominent among adults aged 25 to 34 years (SMD, 0.49; 95% CI, 0.14-0.84) and 35 to 44 years (SMD, 0.35; 95% CI, 0.10-0.60) compared with other age groups. No evidence of changes in distress differing by race and ethnicity or UK country were observed. Conclusions and Relevance: In this study, the substantial deterioration in mental health seen in the UK during the first lockdown did not reverse when lockdown lifted, and a sustained worsening was observed across the pandemic period. Mental health declines have been unequal across the population, with women, those with higher degrees, and those aged 25 to 44 years more affected than other groups

    Characteristics of a protocol to collect objective physical activity/sedentary behaviour data in a large study : seniors USP (understanding sedentary patterns)

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    The Seniors USP study measured sedentary behaviour (activPAL3, 9 day wear) in older adults. The measurement protocol had three key characteristics: enabling 24-hour wear (monitor location, waterproofing); minimising data loss (reducing monitor failure, staff training, communication); and quality assurance (removal by researcher, confidence about wear). Two monitors were not returned; 91% (n=700) of returned monitors had 7 valid days of data. Sources of data loss included monitor failure (n=11), exclusion after quality assurance (n=5), early removal for skin irritation (n=8) or procedural errors (n=10). Objective measurement of physical activity and sedentary behaviour in large studies requires decisional trade-offs between data quantity (collecting representative data) and utility (derived outcomes that reflect actual behaviour). Keywords: methodology; accelerometer; adherence; data loss; activPAL; postur
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