Does intervention engagement mediate physical activity change in a web-based computer-tailored physical activity intervention?-Secondary outcomes from a randomised controlled trial.

Introduction: The relationship between intervention engagement and behaviour change may vary depending on the specific engagement metric being examined. To counter this composite engagement measures may provide a deeper understanding of the relationship between engagement and behaviour change, though few studies have applied such multidimensional engagement metrics. The aim of this secondary analysis of RCT data was to examine how a composite engagement score mediates the effect of a web-based computer-tailored physical activity intervention. Methods: 501 inactive Australian adults were randomised to a no-treatment control or intervention group. Intervention participants received 8 sessions of web-based personalised physical activity advice over a 12-week intervention period and the ability to complete action plans. Change in physical activity was assessed using Actigraph accelerometers at baseline, 3-months and 9-months. Engagement with the intervention (i.e., a composite score including frequency, intensity, duration and type) was continuously assessed during the intervention period using website tracking software and database metrics. Generalised structural equation models were used to examine how a composite engagement score mediated intervention effects at 3 months and 9 months. Results: At 3 months, mediation analysis revealed that the intervention group had significantly higher engagement scores than the control group [a-path exp(b) = 6.462, 95% CI = 5.121-7.804, p < 0.001]. Further, increased engagement with the intervention platform was associated with an increased time spent in moderate-to-vigorous physical activity [ab-coefficient exp(b) = 1.008, 95% CI = 1.004-1.014, P < 0.001]; however, the magnitude of this effect was small. There were no significant mediation effects at the 9-month time point. Discussion: The findings suggest that a composite intervention engagement score has a small positive influence on physical activity changes and that other factors (e.g., behaviour change techniques) are likely to be more important drivers of behaviour change.

Calibrated to drive: Measuring self-assessed driving ability and perceived workload after prolonged sitting and sleep restriction.

Self-assessed driving ability may differ from actual driving performance, leading to poor calibration (i.e., differences between self-assessed driving ability and actual performance), increased risk of accidents and unsafe driving behaviour. Factors such as sleep restriction and sedentary behaviour can impact driver workload, which influences driver calibration. This study aims to investigate how sleep restriction and prolonged sitting impact driver workload and driver calibration to identify strategies that can lead to safer and better calibrated drivers. Participants (n = 84, mean age = 23.5 ± 4.8, 49 % female) undertook a 7-day laboratory study and were randomly allocated to a condition: sitting 9-h sleep opportunity (Sit9), breaking up sitting 9-h sleep opportunity (Break9), sitting 5-h sleep opportunity (Sit5) and breaking up sitting 5-h sleep opportunity (Break5). Break9 and Break5 conditions completed 3-min of light-intensity walking on a treadmill every 30 min between 09:00-17:00 h, while participants in Sit9 and Sit5 conditions remained seated. Each participant completed a 20-min simulated commute in the morning and afternoon each day and completed subjective assessments of driving ability and perceived workload before and after each commute. Objective driving performance was assessed using a driving simulator measuring speed and lane performance metrics. Driver calibration was analysed using a single component and 3-component Brier Score. Correlational matrices were conducted as an exploratory analysis to understand the strength and direction of the relationship between subjective and objective driving outcomes. Analyses revealed participants in Sit9 and Break9 were significantly better calibrated for lane variability, lane position and safe zone-lane parameters at both time points (p < 0.0001) compared to Sit5 and Break5. Break5 participants were better calibrated for safe zone-speed and combined safe zone parameters (p < 0.0001) and speed variability at both time points (p = 0.005) compared to all other conditions. Analyses revealed lower perceived workload scores at both time points for Sit9 and Break9 participants compared to Sit5 and Break5 (p = <0.001). Breaking up sitting during the day may reduce calibration errors compared to sitting during the day for speed keeping parameters. Future studies should investigate if different physical activity frequency and intensity can reduce calibration errors, and better align a driver's self-assessment with their actual performance.

The moderating effect of social support on the effectiveness of a web-based, computer-tailored physical activity intervention for older adults.

This study aimed to assess the moderating effect of social support on the effectiveness of a web-based, computer-tailored physical activity intervention for older adults. In the Active for Life trial, 243 inactive adults aged 65+ years were randomised into: (1) tailoring + Fitbit (n = 78), (2) tailoring-only (n = 96) or (3) control (n = 69). For the current study, participants were categorised as having higher (n = 146) or lower (n = 97) social support based on the Duke Social Support Index (DSSI_10). Moderate-to-vigorous physical activity (MVPA) was measured through accelerometers at baseline and post-intervention. A linear mixed model analysis demonstrated that among participants with lower social support, the tailoring + Fitbit participants, but not the tailoring only participants increased their MVPA more than the control. Among participants with higher social support, no differences in MVPA changes were observed between groups. Web-based computer-tailored interventions with Fitbit integration may be more effective in older adults with lower levels of social support.

A Mobile Health Resistance Training Intervention Using Outdoor Gym Equipment: Process Evaluation of the Ecofit Effectiveness Randomized Controlled Trial.

BACKGROUND: Few mobile health resistance-based physical activity interventions have targeted community-dwelling adults. "Ecofit" is a multicomponent intervention that promotes resistance and aerobic activities using smartphone technology, outdoor gyms, and social support. This study evaluated process evaluation outcomes of the ecofit randomized controlled trial: (1) the acceptability and usability of the ecofit smartphone app and app user workouts; (2) perceptions of factors influencing outdoor gym use; and (3) the fidelity, reach, recruitment, and dose received of the ecofit program. METHODS: Process data were collected through program evaluation surveys at 3 months, and app usage data were collected via the intervention platform for up to 3 months. Data were analyzed using descriptive statistics. RESULTS: The survey was completed by 57% (n = 69) of eligible participants. The majority (93%) believed the app provided them with sufficient information to perform muscle-strengthening activities. Approximately half (51%) agreed that the goal-setting function encouraged them to complete their workouts, and 42% agreed that the self-assessment helped them monitor progress. "Proximity" to outdoor gyms emerged as the most important factor for choosing locations to workout (mean = 5.5, SD = 1.1). Participants logged a median of 5.5 (interquartile range = 19) workouts and 1 (interquartile range = 1) upper- and lower-body muscular fitness self-assessment. CONCLUSIONS: The ecofit app provided participants with sufficient skills to perform unsupervised resistance training exercises using mobile health. Only half of the participants regarded self-assessments and goal setting as useful, suggesting a need for modifications to how these are implemented. Mobile health remains a promising delivery platform to promote unsupervised resistance training, although more research is needed to improve uptake.

Factors relating to sustainability and scalability of the 'Food, Move, Sleep (FOMOS) for Postnatal Mental Health' program: Qualitative perspectives from key stakeholders across Australia.

ISSUE ADDRESSED: Supporting healthy behaviours (quality diet, physical activity, sleep) through home-based interventions is feasible to improve postnatal mental health. Involving stakeholders in developing interventions is essential for maximising accessibility, implementation and scale-up. This study aimed to identify factors affecting the sustainable implementation and scalability of the Food, Move, Sleep (FOMOS) for Postnatal Mental Health program, including strategies to enhance research-practice translation. METHODS: Stakeholders (n = 13) involved in promoting physical activity, healthy eating, postnatal and mental health, public health and/or policy participated in semi-structured interviews. Interviews, based on PRACTIS Guide recommendations for implementation and scale-up, explored perceptions of program design, implementation and scalability. Reflexive thematic analysis was undertaken. Identified implementation and scale-up strategies were mapped against the Expert Recommendations for Implementing Change compendium and PRACTIS Guide. RESULTS: Individual-level: Targeting multiple systems (primary, tertiary, community-based care) and entry points (early, mid-postpartum) for uptake was important. For equity, screening women in public hospitals, engaging with community agencies and targeting most at-risk women, was suggested. Provider-level: Stakeholders identified strategies to enhance future roll-out (organisations assisting with recruitment). Factors impacting sustainability included high demand for the FOMOS program, and governance around screening and funding; online delivery, connecting with partners and providers and integration into existing services may enhance sustainability. Systems-level: Political support and community champions were perceived important for program dissemination. Nine strategies addressing program uptake, reach, implementation, potential scalability and sustainability were identified. CONCLUSIONS: For sustainable implementation and potential scalability of a home-based multi-behaviour postnatal intervention, multi-level implementation and scale-up strategies, aligned with existing health systems, policies and initiatives to support postnatal mental health should be considered. SO WHAT?: This paper provides a comprehensive list of strategies that can be used to enhance sustainable implementation and scalability of healthy behaviour programs targeting postnatal mental health. Further, the interview schedule, systematically developed and aligned with the PRACTIS Guide, may serve as a useful resource for researchers conducting similar studies in future.

Evaluating a multi-behavioural home-based intervention for reducing depressive symptoms in postnatal women : The food, move, sleep (FOMOS) for postnatal mental health randomised controlled trial protocol.

BACKGROUND: Postnatal depression (PND) is a leading cause of illness and death among women following childbirth. Physical inactivity, sedentary behaviour, poor sleep, and sub-optimal diet quality are behavioural risk factors for PND. A feasible, sustainable, and scalable intervention to improve healthy behaviours and reduce PND symptoms among women at postpartum is needed. This study aims to examine the effectiveness of a multi-behavioural home-based program Food, Move, Sleep (FOMOS) for Postnatal Mental Health designed to improve PND symptoms in women at postpartum. METHODS: This randomised clinical trial will recruit 220 Australian women (2-12 months postpartum) experiencing heightened PND symptoms (Edinburgh Postnatal Depression Scale score ≥ 10). Participants will be randomised to FOMOS or wait-list control receiving standard clinical care. FOMOS is a 6-month mobile health (mHealth) intervention targeting diet quality, physical activity, sedentary behaviour, sleep, and mental health. The intervention, informed by the Social Cognitive Theory and incorporating behaviour change techniques defined in the CALO-RE taxonomy and Cognitive Behavioural Treatment of Insomnia, provides exercise equipment, and educational/motivational material and social support via mHealth and social media. Data collection pre-intervention and at 3, 6 and 12 months will assess the primary outcome of PND symptoms and secondary outcomes (diet quality, physical activity, sitting time, sleep quality) using self-report and device measures. Process evaluation will explore acceptability, appropriateness, cost-effectiveness, feasibility, and sustainability via analytic tools, record keeping, interviews, and surveys. DISCUSSION: If effective, FOMOS could be a feasible and potentially scalable management strategy to support improvement of health behaviours and mental health for women with PND symptoms. TRIAL REGISTRATION: https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?ACTRN=12622001079730p.

The impact of action plans on habit and intention strength for physical activity in a web-based intervention: is it the thought that counts?

OBJECTIVE: Action planning is a common approach used in physical activity interventions. The aim of this study was to assess the association of frequency, consistency and content of action planning with physical activity behaviour, intention strength and habit strength. METHODS AND MEASURES: Within a 3-month web-based, computer-tailored physical activity intervention, participants (N = 115; 68.7% female, M age =43.9; range = 22-73 years) could create 6 rounds of action plans for 4 activities each (24 total). RESULTS: Consistency of action planning during the intervention was associated with change in physical activity at 9-months, and intention and habit strength at 3-months and 9-months. Frequency of action planning was negatively associated with intention at 3-months and 9-months. The effect of action planning consistency on physical activity behaviour was no longer significant when accounting for change in intention and habit strength. CONCLUSION: Consistency of how, where, when and with whom people plan their physical activity may translate into stronger physical activity habits. Interventions should avoid encouraging making many distinct action plans, but rather encourage stable contexts through consistent action planning.

Mediating effects of sleep on mental health in older adolescents: Findings from the Burn 2 Learn randomized controlled trial.

PURPOSE: Our study explored the mediating effect of sleep-related variables on older adolescents' mental health in the context of a school-based physical activity intervention. METHODS: We evaluated the Burn 2 Learn (B2L) intervention using a cluster randomized controlled trial, which included two cohorts. Participants for this sub-study were from the second cohort, which included 292 older adolescents (16.0 ± 0.5 years) from 10 secondary schools in New South Wales, Australia. Teachers at intervention schools delivered two high-intensity activity breaks (approximately 10 mins) per week to students during academic lessons. Participants completed measures of mental health (i.e., perceived stress and internalizing problems) and hypothesized mediators (i.e., sleep duration, sleep latency, awakenings, and daytime sleepiness) at baseline (February-April 2019) and post-intervention (August-September 2019). Single mediation analyses were conducted to explore the potential mediating effects of sleep variables on mental health outcomes using a product-of-coefficient test. RESULTS: We observed a small statistically significant effect for perceived stress (ß = -0.11, SE = 0.034, p = 0.002), but not for internalizing problems (ß = 0.02, SE = 0.051, p = 0.760). There were no significant intervention effects for sleep-related variables. Several sleep-related variables were associated with mental health outcomes but no mediated effects were found. CONCLUSION: The B2L intervention had a small beneficial effect on perceived stress, however our mediation analyses suggest this was not explained by changes in sleep-related variables. Markers of sleep were associated with mental health constructs, highlighting the importance of sleep for good psychological health. However, in the context of a physical activity intervention, effects on mental health may be driven by other behavioral, neurobiological, or psychosocial mechanisms.

Rehabilitation Support via Postcard (RSVP): A Randomised Controlled Trial of a Postcard to Promote Uptake of Cardiac Rehabilitation.

PURPOSE: The aim was to increase cardiac rehabilitation (CR) uptake using a novel intervention, Rehabilitation Support Via Postcard (RSVP), among patients with acute myocardial infarction discharged from two major hospitals in Hunter New England Local Health District (HNELHD), New South Wales, Australia. METHODS: The RSVP trial was evaluated using a two-armed randomised controlled trial design. Participants (N=430) were recruited from the two main hospitals in HNELHD, and enrolled and randomised to either the intervention (n=216) or control (n=214) group over a six-month period. All participants received usual care; however, the intervention group received postcards promoting CR attendance between January and July 2020. The postcard was ostensibly written as an invitation from the patient's admitting medical officer to promote timely and early uptake of CR. The primary outcome was CR attendance at outpatient HNELHD CR services in the 30-days post-discharge. RESULTS: Fifty-four percent (54%) of participants who received RSVP attended CR, compared to 46% in the control group; however this difference was not statistically significant (odds ratio [OR]=1.4, 95% confidence interval [CI]=0.9-2.0, p=0.11). Exploratory post-hoc analysis among four sub-groups (i.e., Indigeneity, gender, age and rurality), found that the intervention significantly increased attendance in males (OR=1.6, 95%CI=1.0-2.6, p=0.03) but had no significant impact on attendance for other sub-groups. CONCLUSIONS: While not statistically significant, postcards increased overall CR attendance by 8%. This strategy may be useful to increase attendance, particularly in men. Alternative strategies are necessary to increase CR uptake among women, Indigenous people, older people and people from regional and remote locations.

The Efficacy and Feasibility of a High Intensity Interval Training Program to Improve Cardiorespiratory Fitness in Truck Drivers: The Fit 2 Drive Cluster Controlled Pilot Study.

OBJECTIVE: This cluster-controlled pilot study assessed the efficacy and feasibility of "Fit 2 Drive," a depot-delivered, high-intensity interval training (HIIT) program to improve the cardiorespiratory fitness (CRF) of truck drivers. METHODS: Companies of local delivery drivers (44 men; mean [SD] age = 50.5 [9.8] years; Brisbane, Australia) were assigned to "Fit 2 Drive" (4 clusters; 27 drivers; 1 × 4 minutes supervised to self-managed HIIT, 3 times a week, 12 weeks) or a control (5 clusters; 17 drivers). Analyses assessed between group changes in CRF (VO 2peak ), HIIT session attendance, and delivery costs. RESULTS: Driver clusters allocated to "Fit 2 Drive" significantly improved CRF compared to a control (mean difference of 3.6 mL·kg -1 ·min -1 ; P < 0.019; 95% confidence interval = 0.7-6.5 mL·kg -1 ·min -1 ). Drivers who completed the program attended 70% of sessions (25/36) with delivery costs averaging $710 AUD per driver. CONCLUSIONS: The findings support the efficacy and feasibility of Fit 2 Drive but also highlight challenges for in-person delivery at scale.

Changes in physical activity, diet, sleep, and mental well-being when starting university: A qualitative exploration of Australian student experiences.

Objective: To explore young adult's experiences of how starting university influenced their physical activity, diet, sleep, and mental well-being, and barriers and enablers to health behavior change. Participants: University students aged 18-25 years. Methods: Three focus groups were conducted in November 2019. Inductive thematic approach was utilized to identify themes. Results: Students (female: n = 13, male: n = 2, other gender identity: n = 1, 21.2 (1.6) years) reported mental well-being, physical activity levels, diet quality and sleep health were negatively affected. Stress, study demands, university timetabling, not prioritizing physical activity, cost and availability of healthy foods, and difficulty falling asleep were key barriers. Health behavior change interventions aiming to support mental well-being need to include both information and support features. Conclusions: There is a significant opportunity to improve the transition to university for young adults. Findings highlight areas to target in future interventions to improve physical activity, diet, and sleep of university students.

Are health behaviors associated with mental health among tertiary education students? A systematic review of cohort studies.

OBJECTIVE: To evaluate the association between health behaviors with mental health among tertiary education students. METHODS: Six databases were searched until September 2021 for prospective cohort studies evaluating the association between health behavior(s) (dietary intake, physical activity, sedentary behavior, alcohol intake, sleep, smoking or illicit drug use) and mental health. Two independent reviewers screened records for inclusion, extracted data and completed risk of bias assessments. RESULTS: 33 studies were included (14 assessed sleep, 14 alcohol intake, 13 physical activity, 8 smoking, 6 sedentary behavior, 4 diet, 1 illicit drug use). A consistent association between poor sleep, and physical inactivity with increased risk of poor psychological wellbeing, and between poor sleep and increased mental ill-health related outcomes was demonstrated. CONCLUSION: Findings suggest interventions to address poor sleep and physical inactivity among students may positively impact mental health. Further research of other health behaviors, and their association with mental health, is required.

Engagement, acceptability, usability and satisfaction with Active for Life, a computer-tailored web-based physical activity intervention using Fitbits in older adults.

BACKGROUND: Preliminary evidence suggests that web-based physical activity interventions with tailored advice and Fitbit integration are effective and may be well suited to older adults. Therefore, this study aimed to examine the engagement, acceptability, usability, and satisfaction with 'Active for Life,' a web-based physical activity intervention providing computer-tailored physical activity advice to older adults. METHODS: Inactive older adults (n = 243) were randomly assigned into 3 groups: 1) tailoring + Fitbit, 2) tailoring only, or 3) a wait-list control. The tailoring + Fitbit group and the tailoring-only group received 6 modules of computer-tailored physical activity advice over 12 weeks. The advice was informed by objective Fitbit data in the tailoring + Fitbit group and self-reported physical activity in the tailoring-only group. This study examined the engagement, acceptability, usability, and satisfaction of Active for Life in intervention participants (tailoring + Fitbit n = 78, tailoring only n = 96). Wait-list participants were not included. Engagement (Module completion, time on site) were objectively recorded through the intervention website. Acceptability (7-point Likert scale), usability (System Usability Scale), and satisfaction (open-ended questions) were assessed using an online survey at post intervention. ANOVA and Chi square analyses were conducted to compare outcomes between intervention groups and content analysis was used to analyse program satisfaction. RESULTS: At post-intervention (week 12), study attrition was 28% (22/78) in the Fitbit + tailoring group and 39% (37/96) in the tailoring-only group. Engagement and acceptability were good in both groups, however there were no group differences (module completions: tailoring + Fitbit: 4.72 ± 2.04, Tailoring-only: 4.23 ± 2.25 out of 6 modules, p = .14, time on site: tailoring + Fitbit: 103.46 ± 70.63, Tailoring-only: 96.90 ± 76.37 min in total, p = .56, and acceptability of the advice: tailoring + Fitbit: 5.62 ± 0.89, Tailoring-only: 5.75 ± 0.75 out of 7, p = .41). Intervention usability was modest but significantly higher in the tailoring + Fitbit group (tailoring + Fitbit: 64.55 ± 13.59, Tailoring-only: 57.04 ± 2.58 out of 100, p = .003). Participants reported that Active for Life helped motivate them, held them accountable, improved their awareness of how active they were and helped them to become more active. Conversely, many participants felt as though they would prefer personal contact, more detailed tailoring and more survey response options. CONCLUSIONS: This study supports web-based physical activity interventions with computer-tailored advice and Fitbit integration as engaging and acceptable in older adults. TRIAL REGISTRATION: Australian and New Zealand Clinical Trials Registry: ACTRN12618000646246. Registered April 23 2018, https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=374901.

mHealth to Support Outdoor Gym Resistance Training: The ecofit Effectiveness RCT.

INTRODUCTION: In Australia, 45% of adults meet the aerobic recommendations, and only 9%-30% meet the resistance training guidelines. Given the lack of at-scale community-based interventions promoting resistance training, the aim of this study was to assess the impact of an innovative mHealth intervention on upper- and lower-body muscular fitness, cardiorespiratory fitness, physical activity, and social-cognitive mediators among a sample of community-dwelling adults. STUDY DESIGN: Researchers evaluated the community-based ecofit intervention using a cluster RCT from September 2019 to March 2022 in 2 regional municipalities of New South Wales, Australia. SETTING/PARTICIPANTS: Researchers recruited a sample of 245 participants (72% female, aged 53.4±13.9 years) who were randomized to the ecofit intervention group (n=122) or waitlist control (n=123) group. INTERVENTION: The intervention group received access to a smartphone application with standardized workouts tailored to 12 outdoor gym locations and an introductory session. Participants were encouraged to perform at least 2 ecofit workouts per week. MAIN OUTCOME MEASURES: Primary and secondary outcomes were assessed at baseline, 3 months, and 9 months. The coprimary muscular fitness outcomes were evaluated using the 90-degree push-up and the 60-second sit-to-stand test. Intervention effects were estimated using linear mixed models accounting for group-level clustering (participants could enroll in groups of up to 4). Statistical analysis was conducted in April 2022. RESULTS: Statistically significant improvements were observed in upper (1.4 repetitions, 95% CI=0.3, 2.6, p=0.018) and lower (2.6 repetitions, 95% CI=0.4, 4.8, p=0.020) body muscular fitness at 9 months but not at 3 months. Increases in self-reported resistance training, resistance training self-efficacy, and implementation intention for resistance training were statistically significant at 3 and 9 months. CONCLUSIONS: This study has shown that a mHealth intervention promoting resistance training using the built environment can improve muscular fitness, physical activity behavior, and related cognitions in a community sample of adults. TRIAL REGISTRATION: This trial was preregistered with the Australian and New Zealand Clinical Trial Registry (ACTRN12619000868189).

Experience and Satisfaction with a Family-Based Physical Activity Intervention Using Activity Trackers and Apps: A Qualitative Study.

Wearable activity trackers and smartphone apps have been shown to increase physical activity in children and adults. However, interventions using activity trackers and apps have rarely been tested in whole families. This study examined the experience and satisfaction with an activity tracker and app intervention (Step it Up Family) to increase physical activity in whole families. Telephone interviews were conducted with Queensland-based families (n = 19) who participated in the Step it Up Family intervention (N = 40, single-arm, pre/post feasibility study) in 2017/2018. Using commercial activity trackers combined with apps, the intervention included an introductory session, individual and family-level goal setting, self-monitoring, family step challenges, and weekly motivational text messages. Qualitative content analysis was conducted to identify themes, categories and sub-categories. In summary, parents reported that children were engaged with the activity tracker and app features to reach their daily step goals. Some technical difficulties were experienced with app navigation, syncing of activity tracker data, and tracker band discomfort. Although families liked that the weekly text messages reminded them to be active, they did not find them very motivating. Using text messages for physical activity motivation in families requires further testing. Overall, the intervention was well-received by families for increasing physical activity motivation.

Prospective associations between joint categories of physical activity and insomnia symptoms with onset of poor mental health in a population-based cohort.

BACKGROUND: Physical inactivity and insomnia symptoms are independently associated with increased risk of depression and anxiety; however, few studies jointly examine these risk factors. This study aimed to prospectively examine the joint association of physical activity (PA) and insomnia symptoms with onset of poor mental health in adults. METHODS: Participants from the 2013 to 2018 annual waves of the Household Income and Labour Dynamics in Australia panel study who had good mental health (Mental Health Inventory-5 >54) in 2013, and who completed at least 1 follow-up survey (2014-2018), were included (n = 10,977). Poor mental health (Mental Health Inventory-5 ≤ 54) was assessed annually. Baseline (2013) PA was classified as high/moderate/low, and insomnia symptoms (i.e., trouble sleeping) were classified as no insomnia symptoms/insomnia symptoms, with 6 mutually exclusive PA-insomnia symptom groups derived. Associations of PA-insomnia symptom groups with onset of poor mental health were examined using discrete-time proportional-hazards logit-hazard models. RESULTS: There were 2322 new cases of poor mental health (21.2%). Relative to the high PA/no insomnia symptoms group, there were higher odds (odds ratio and 95% confidence interval (95%CI)) of poor mental health among the high PA/insomnia symptoms (OR = 1.87, 95%CI: 1.57-2.23), moderate PA/insomnia symptoms (OR = 1.93, 95%CI: 1.61-2.31), low PA/insomnia symptoms (OR = 2.33, 95%CI: 1.96-2.78), and low PA/no insomnia symptoms (OR = 1.14, 95%CI: 1.01-1.29) groups. Any level of PA combined with insomnia symptoms was associated with increased odds of poor mental health, with the odds increasing as PA decreased. CONCLUSION: These findings highlight the potential benefit of interventions targeting both PA and insomnia symptoms for promoting mental health.

Exploring the Interplay Between Message Format, Need for Cognition and Personal Relevance on Processing Messages About Physical Activity: a Two-Arm Randomized Experimental Trial.

BACKGROUND: According to the Elaboration Likelihood Model, persuasion can occur via two different routes (the central route and peripheral route), with the route utilized dependent on factors associated with motivation and ability. This study aimed to explore the moderating role of need for cognition (NFC) and perceived relevance on the processing of physical activity messages designed to persuade via either the central route or the peripheral route. METHOD: Participants (N = 50) were randomized to receive messages optimized for central route processing or messages optimized for peripheral route processing. Eye-tracking devices were used to assess attention, which was the primary outcome. Message perceptions and the extent of persuasion (changes in physical activity determinants) were also assessed via self-report as secondary outcomes. Moderator effects were examined using interaction terms within mixed effects models and linear regression models. RESULTS: There were no detected interactions between condition and NFC for any of the study outcomes (all ps > .05). Main effects of personal relevance were observed for some self-report outcomes, with increased relevance associated with better processing outcomes. An interaction between need for cognition and personal relevance was observed for perceived behavioral control (p = 0.002); greater relevance was associated with greater perceived behavioral control for those with a higher need for cognition. CONCLUSION: Matching physical activity messages based on NFC may not increase intervention efficacy. Relevance of materials is associated with greater change in physical activity determinants and may be more so among those with a higher NFC.

Effectiveness and reporting of nutrition interventions in cardiac rehabilitation programmes: a systematic review.

AIMS: Dietary modification is essential for the secondary prevention of cardiovascular disease. However, there are limited published evidence syntheses to guide practice in the cardiac rehabilitation (CR) setting. This systematic review's objective was to assess effectiveness and reporting of nutrition interventions to optimize dietary intake in adults attending CR. METHODS AND RESULTS: Randomized controlled trials (RCTs) of nutrition interventions within CR were eligible for inclusion and had to have measured change in dietary intake. MEDLINE, Embase, Emcare, PsycINFO, CINAHL, Scopus, and The Cochrane Library were searched from 2000 to June 2020, limited to publications in English. Evidence from included RCTs was synthesized descriptively. The risk of bias was assessed using the Cochrane Risk of Bias 2 tool. This review is registered on PROSPERO; CRD42020188723. Of 13 048 unique articles identified, 11 were eligible. Randomized controlled trials were conducted in 10 different countries, included 1542 participants, and evaluated 29 distinct dietary intake outcomes. Five studies reported statistically significant changes in diet across 13 outcomes. Most nutrition interventions were not reported in a manner that allowed replication in clinical practice or future research. CONCLUSION: There is a gap in research testing high-quality nutrition interventions in CR settings. Findings should be interpreted in the light of limitations, given the overall body of evidence was heterogenous across outcomes and study quality; 6 of 11 studies were conducted more than 10 years old. Future research should investigate strategies to optimize and maintain nutrition improvements for patients attending CR. REGISTRATION: PROSPERO; CRD42020188723.

Does matching a personally tailored physical activity intervention to participants' learning style improve intervention effectiveness and engagement?

This study aims to compare the effectiveness, engagement, usability, and acceptability of a web-based, computer-tailored physical activity intervention (provided as video or text) between participants who were matched or mismatched to their self-reported learning style (visual and auditory delivery through video or text-based information). Generalised linear mixed models were conducted to compare time (baseline, 3 months) by group (matched, mismatched) on ActiGraph-GT3X+measured moderate-to-vigorous physical activity (MVPA) and steps. Generalised linear models were used to compare group (matched and mismatched) on session completion, time-on-site, usability, and acceptability. MVPA and steps improved from baseline to 3-months, however this did not differ between participants whose learning styles were matched or mismatched to the intervention they received. Session completion, time-on-site, usability, and acceptability did not differ between matched and mismatched participants. Therefore, aligning intervention delivery format to learning style is unlikely to influence intervention effectiveness or engagement.

Bidirectional associations of sleep and discretionary screen time in adults: Longitudinal analysis of the UK biobank.

The direction of the association between discretionary screen time (DST) and sleep in the adult population is largely unknown. We examined the bidirectional associations of DST and sleep patterns in a longitudinal sample of adults in the general population. A total of 31,361 UK Biobank study participants (52% female, 56.1 ± 7.5 years) had two repeated measurements of discretionary screen time (TV viewing and leisure-time computer use) and self-reported sleep patterns (five sleep health characteristics) between 2012 and 2018 (follow-up period of 6.9 ± 2.2 years). We categorised daily DST into three groups (low, <3 h/day; medium, 3-4 h/day; and high, >4 h/day), and calculated a sleep pattern composite score comprising morning chronotype, adequate sleep duration (7-8 h/day), never or rare insomnia, never or rare snoring, and infrequent daytime sleepiness. The overall sleep pattern was categorised into three groups (healthy: ≥ 4; intermediate: 2-3; and poor: ≤ 1 healthy sleep characteristic). Multiple logistic regression analyses were applied to assess associations between DST and sleep with adjustments for potential confounders. Participants with either an intermediate (OR: 1.40; 95% CI: 1.15, 1.71) or a poor (OR: 1.16; 95% CI: 1.10, 1.24) sleep pattern at baseline showed higher odds for high DST at follow-up, compared with those with a healthy baseline sleep pattern. Participants with medium (OR: 1.40; 95% CI: 1.14, 1.71) or high DST (OR: 1.62; 95% CI: 1.30, 2.00) at baseline showed higher odds for poor sleep at follow-up, compared with participants with a low DST. In conclusion, our findings provide consistent evidence that a high DST at baseline is associated with poor sleep over a nearly 7 year follow-up period, and vice versa.