Financial Incentives for Physical Activity and Sports Participation in Young People.

Physical inactivity is a global health problem. Childhood is an opportune time to establish healthy physical activity behaviors, including the participation in organized physical activity, such as sports. We hypothesize that financial incentives can improve young people's participation in physical activity and sports. The design of the incentive and the context in which it operates are crucial to its success.

A Digital Lifestyle Program for Psychological Distress, Wellbeing and Return-to-Work: A Proof-of-Concept Study.

OBJECTIVE: To demonstrate proof-of-concept for a chatbot-led digital lifestyle medicine program in aiding rehabilitation for return-to-work. DESIGN: Retrospective cohort study with pre-post measures. SETTING: Community setting, Australia. PARTICIPANTS: 78 adult participants (mean age 46 years, 32% female) with an active workers' compensation claim (N=78). INTERVENTIONS: A 6-week digital lifestyle medicine program led by an artificially intelligent virtual health coach and weekly telehealth calls with a health coach. MAIN OUTCOME MEASURES: Adherence (% program completions) and engagement (% of daily and weekly sessions completed), changes in depression, anxiety and distress (K10), psychological wellbeing (WHO-5), return-to-work confidence and anxiety and change in work status. RESULTS: Sixty participants completed the program (72%), with improvements in psychological distress (P≤.001, r=.47), depression (P<.001, r=.55), anxiety (P<.001, r=.46) and wellbeing (P<.001, r=.62) were noted, as well as increased confidence about returning to work (P≤.001, r=.51) and improved work status (P≤.001). Anxiety about returning to work remained unchanged. Participants completed an average of 73% of daily virtual coach sessions and 95% of telehealth coaching sessions. CONCLUSIONS: Artificial intelligence technology may be able to provide a practical, supportive, and low-cost intervention to improve psychosocial outcomes among individuals on an active workers' compensation claim. Further, controlled research is needed to confirm these findings.

Hashtag fitspiration: credibility screening and content analysis of Instagram fitness accounts.

BACKGROUND: Fitspiration is a social media phenomenon purported to inspire viewers to lead healthier lifestyles but can result in negative psychological outcomes such as body dissatisfaction. This study aimed to develop a tool to audit Instagram fitspiration accounts and screen for content that could have potentially negative psychological effects. METHODS: This study developed and implemented an audit tool to (1) identify credible fitspiration accounts (i.e., accounts that do not portray potentially harmful or unhealthy content) and (2) describe the content of identified accounts. The most recent 15 posts of 100 leading Instagram fitspiration accounts were audited. Accounts were deemed non-credible and were excluded if they contained fewer than four fitness-related posts or portrayed nudity or inappropriate clothing, sexualisation or objectification, extreme body types, "thinspiration", or negative messages. RESULTS: Many accounts contained fewer than four fitness-related posts (n = 41), sexualisation or objectification (n = 26), nudity or inappropriate clothing (n = 22), and/or extreme body types (n = 15). Three accounts failed on all four criteria, while 13, 10 and 33 failed on three, two, or one criterion, respectively. Therefore, only 41% of accounts were considered credible. Inter-rater reliability (percentage agreement and Brennan and Prediger's coefficient κq) was high (Stage 1: 92% agreement [95% CI 87, 97], κq 0.84 [95% CI 0.73, 0.95]; Stage 2: 93% agreement [95% CI 83, 100], κq 0.85 [95% CI 0.67, 1.00]). Account holders of credible fitspiration accounts were predominantly female (59%), aged 25-34 (54%), Caucasian (62%), and from the United States (79%). Half held a qualification related to physical activity or physical health (e.g., personal trainer, physiotherapy; 54%). Most included accounts included an exercise video (93%) and example workout (76%). CONCLUSION: While many popular Instagram fitspiration accounts offered credible content such as example workouts, many accounts contained sexualisation, objectification or promotion of unhealthy or unrealistic body shapes. The audit tool could be used by Instagram users to ensure the accounts they follow do not portray potentially harmful or unhealthy content. Future research could use the audit tool to identify credible fitspiration accounts and examine whether exposure to these accounts positively influences physical activity.

Physical activity and screen time in outside school hours care services across Australia: current versus best practice.

BACKGROUND: Outside school hours care (OSHC) is accessed by millions of children internationally. Recently, physical activity and screen time guidelines in OSHC were developed. This study described the current physical activity and screen time scheduling in Australian OSHC, obtained sector feedback on the guidelines and compared current- with best-practice. METHODS: A cross-sectional online survey was administered to n = 3551 Australian OSHC directors. Participants reported scheduling for physical activity and screen time opportunities in before- and after-school care. Feedback was sought on the new guidelines, including barriers and enablers for implementation. Scheduling data were used to evaluate whether services were currently meeting the new guidelines; that is if time allocated matched with time recommended. RESULTS: Five hundred and sixty-six directors participated (response rate 16%). Physical activity and screen time practices varied widely (e.g., after-school physical activity opportunity ranged from 15 to 150 min, mean 74, SD 28; after-school screen time opportunity ranged from 15 to 195 min, mean 89, SD 43), with state (p = 0.002) and socioeconomic (based on postcode; p < 0.001) differences. Most participants (54-81%) agreed that the guideline's recommended physical activity and screen time durations were appropriate, however, only 40% of participants' OSHC services' programs actually met the guidelines. CONCLUSIONS: Physical activity and screen time scheduling in OSHC is highly variable. Despite support for the guidelines, current scheduling practice in the majority of OSHC services surveyed do not meet best practice guidelines.

Examining social-cognitive theory constructs as mediators of behaviour change in the active team smartphone physical activity program: a mediation analysis.

BACKGROUND: Regular engagement in physical activity has well-established physical and psychological health benefits. Despite this, over a quarter of the global adult population is insufficiently physically active. Physical activity interventions grounded in behaviour change theory, such as the social-cognitive theory, are widely considered to be more effective than non-theoretical approaches. Such interventions set out to intervene on the ultimate outcome (physical activity), but also influence intermediate factors (social-cognitive theory constructs) which in turn, are believed to influence physical activity behaviour. The primary aim of the study was to use mediation analysis to examine whether changes in the social-cognitive theory and related constructs, in particular self-efficacy, outcome expectations, intentions, barriers and goal setting, mediated the effects of a smartphone-based social networking physical activity intervention. METHODS: Mediation analyses were conducted using the PROCESS Macro in SPSS to (i) calculate the regression coefficients for the effect of the independent variable (group allocation) on the hypothesised mediators (social-cognitive theory constructs), (ii) calculate the regression coefficient for the effect of the hypothesised mediators (social-cognitive theory constructs) on the dependent variable (objectively measured physical activity or self-report physical activity), independent of group assignment and (iii) determine the total, direct and indirect intervention effects. RESULTS: Data from 243 participants were included in the mediation analysis. There was no evidence of mediation for change in objectively measured MVPA or self-reported MVPA. CONCLUSIONS: There was no conclusive evidence that any of the social-cognitive theory constructs mediated the relationship between an app-based intervention and change in physical activity. Ongoing efforts to develop and understand components that make physical activity app-based interventions effective are recommended. TRIAL REGISTRATION: This trial was registered with the Australian and New Zealand Clinical Trial Registry ( ACTRN12617000113358 , date of registration 23 January, 2017).

Annual, seasonal, cultural and vacation patterns in sleep, sedentary behaviour and physical activity: a systematic review and meta-analysis.

BACKGROUND: Time spent in daily activities (sleep, sedentary behaviour and physical activity) has important consequences for health and wellbeing. The amount of time spent varies from day to day, yet little is known about the temporal nature of daily activity patterns in adults. The aim of this review is to identify the annual rhythms of daily activity behaviours in healthy adults and explore what temporal factors appear to influence these rhythms. METHODS: Six online databases were searched for cohort studies exploring within-year temporal patterns (e.g. season effects, vacation, cultural festivals) in sleep, sedentary behaviour or physical activity in healthy 18 to 65-year-old adults. Screening, data extraction, and risk of bias scoring were performed in duplicate. Extracted data was presented as mean daily minutes of each activity type, with transformations performed as needed. Where possible, meta-analyses were performed using random effect models to calculate standardised mean differences (SMD). RESULTS: Of the 7009 articles identified, 17 studies were included. Studies were published between 2003 and 2019, representing 14 countries and 1951 participants, addressing variation in daily activities across season (n = 11), Ramadan (n = 4), vacation (n = 1) and daylight savings time transitions (n = 1). Meta-analyses suggested evidence of seasonal variation in activity patterns, with sleep highest in autumn (+ 12 min); sedentary behaviour highest in winter (+ 19 min); light physical activity highest in summer (+ 19 min); and moderate-to-vigorous physical activity highest in summer (+ 2 min) when compared to the yearly mean. These trends were significant for light physical activity in winter (SMD = - 0.03, 95% CI - 0.58 to - 0.01, P = 0.04). Sleep appeared 64 min less during, compared to outside Ramadan (non-significant). Narrative analyses for the impact of vacation and daylight savings suggested that light physical activity is higher during vacation and that sleep increases after the spring daylight savings transition, and decreases after the autumn transition. CONCLUSIONS: Research into temporal patterns in activity behaviours is scarce. Existing evidence suggests that seasonal changes and periodic changes to usual routine, such as observing religious events, may influence activity behaviours across the year. Further research measuring 24-h time use and exploring a wider variety of temporal factors is needed.

Annual rhythms in adults' lifestyle and health (ARIA): protocol for a 12-month longitudinal study examining temporal patterns in weight, activity, diet, and wellbeing in Australian adults.

BACKGROUND: Almost one in three Australian adults are now obese, and the rate continues to rise. The causes of obesity are multifaceted and include environmental, cultural and lifestyle factors. Emerging evidence suggests there may be temporal patterns in weight gain related, for example, to season and major festivals such as Christmas, potentially due to changes in diet, daily activity patterns or both. The aim of this study is to track the annual rhythm in body weight, 24 h activity patterns, dietary patterns, and wellbeing in a cohort of Australian adults. In addition, through data linkage with a concurrent children's cohort study, we aim to examine whether changes in children's body mass index, activity and diet are related to those of their parents. METHODS: A community-based sample of 375 parents aged 18 to 65 years old, residing in or near Adelaide, Australia, and who have access to a Bluetooth-enabled mobile device or a computer and home internet, will be recruited. Across a full year, daily activities (minutes of moderate to vigorous physical activity, light physical activity, sedentary behaviour and sleep) will be measured using wrist-worn accelerometry (Fitbit Charge 3). Body weight will be measured daily using Fitbit wifi scales. Self-reported dietary intake (Dietary Questionnaire for Epidemiological Studies V3.2), and psychological wellbeing (WHOQOL-BREF and DASS-21) will be assessed eight times throughout the 12-month period. Annual patterns in weight will be examined using Lowess curves. Associations between changes in weight and changes in activity and diet compositions will be examined using repeated measures multi-level models. The associations between parent's and children's weight, activity and diet will be investigated using multi-level models. DISCUSSION: Temporal factors, such as day type (weekday or weekend day), cultural celebrations and season, may play a key role in weight gain. The aim is to identify critical opportunities for intervention to assist the prevention of weight gain. Family-based interventions may be an important intervention strategy. TRIAL REGISTRATION: Australia New Zealand Clinical Trials Registry, identifier ACTRN12619001430123 . Prospectively registered on 16 October 2019.

Improving User Experience of Virtual Health Assistants: Scoping Review.

BACKGROUND: Virtual assistants can be used to deliver innovative health programs that provide appealing, personalized, and convenient health advice and support at scale and low cost. Design characteristics that influence the look and feel of the virtual assistant, such as visual appearance or language features, may significantly influence users' experience and engagement with the assistant. OBJECTIVE: This scoping review aims to provide an overview of the experimental research examining how design characteristics of virtual health assistants affect user experience, summarize research findings of experimental research examining how design characteristics of virtual health assistants affect user experience, and provide recommendations for the design of virtual health assistants if sufficient evidence exists. METHODS: We searched 5 electronic databases (Web of Science, MEDLINE, Embase, PsycINFO, and ACM Digital Library) to identify the studies that used an experimental design to compare the effects of design characteristics between 2 or more versions of an interactive virtual health assistant on user experience among adults. Data were synthesized descriptively. Health domains, design characteristics, and outcomes were categorized, and descriptive statistics were used to summarize the body of research. Results for each study were categorized as positive, negative, or no effect, and a matrix of the design characteristics and outcome categories was constructed to summarize the findings. RESULTS: The database searches identified 6879 articles after the removal of duplicates. We included 48 articles representing 45 unique studies in the review. The most common health domains were mental health and physical activity. Studies most commonly examined design characteristics in the categories of visual design or conversational style and relational behavior and assessed outcomes in the categories of personality, satisfaction, relationship, or use intention. Over half of the design characteristics were examined by only 1 study. Results suggest that empathy and relational behavior and self-disclosure are related to more positive user experience. Results also suggest that if a human-like avatar is used, realistic rendering and medical attire may potentially be related to more positive user experience; however, more research is needed to confirm this. CONCLUSIONS: There is a growing body of scientific evidence examining the impact of virtual health assistants' design characteristics on user experience. Taken together, data suggest that the look and feel of a virtual health assistant does affect user experience. Virtual health assistants that show empathy, display nonverbal relational behaviors, and disclose personal information about themselves achieve better user experience. At present, the evidence base is broad, and the studies are typically small in scale and highly heterogeneous. Further research, particularly using longitudinal research designs with repeated user interactions, is needed to inform the optimal design of virtual health assistants.

Can Instagram be used to deliver an evidence-based exercise program for young women? A process evaluation.

BACKGROUND: Instagram provides an opportunity to deliver low cost, accessible and appealing physical activity content. This study evaluated the feasibility of delivering an exercise program for young women using Instagram. METHODS: A single-group pre- and post-intervention trial examined the feasibility and preliminary efficacy of a 12-week Instagram-delivered program with young inactive women (n = 16; M = 23 years), which prescribed running and body weight exercises to complete three times per week. Daily Instagram posts delivered the exercises, video demonstrations and motivational content. Feasibility was evaluated by examining exposure (Instagram posts viewed per week), engagement (likes, comments and tags on Instagram posts; number of exercise sessions completed per week; retention, defined as completion of the online survey at weeks 6 and 12), and acceptability [whether the program increased participants' motivation to exercise (1 = strongly disagree-5 = strongly agree); satisfaction with the program (1 = not satisfied-5 = very satisfied)]. Preliminary efficacy was evaluated by comparing baseline and 12-week self-reported physical activity (IPAQ short-form) and fitness (cardiorespiratory and muscle strength; 1 = very poor-5 = very good, International Fitness Scale) using the Exact sign test. RESULTS: On average, participants reported seeing six posts in their Instagram feed per week. Posts received an average of five likes (IQR = 3-6). A total of four comments and one tag were observed across all posts. On average, participants reported completing two exercise sessions per week. Retention was 88% at 6 weeks but dropped to 56% at 12 weeks. Participants reported increased motivation to exercise (Mdn = 4, IQR = 3-4) and were satisfied with the program (Mdn = 4, IQR = 3-4). Only self-reported cardiorespiratory fitness showed a meaningful, though nonsignificant, improvement (MdnΔ = 1, IQR = 0-1, p = .06). CONCLUSIONS: Although Instagram has the potential to deliver a low cost, convenient exercise program for young women, additional research is needed to identify methods of improving engagement (interaction with the Instagram content, exercise sessions completed, and retention in the program). Future research could examine the use of behaviour change theory and provide information that enables participants to tailor the exercises to their interests and needs. Additionally, the use of objective assessments of physical activity and fitness among a larger participants sample is needed.

The Effectiveness of a Web-Based Computer-Tailored Physical Activity Intervention Using Fitbit Activity Trackers: Randomized Trial.

BACKGROUND: Web-based interventions that provide personalized physical activity advice have demonstrated good effectiveness but rely on self-reported measures of physical activity, which are prone to overreporting, potentially reducing the accuracy and effectiveness of the advice provided. OBJECTIVE: This study aimed to examine whether the effectiveness of a Web-based computer-tailored intervention could be improved by integrating Fitbit activity trackers. METHODS: Participants received the 3-month TaylorActive intervention, which included 8 modules of theory-based, personally tailored physical activity advice and action planning. Participants were randomized to receive the same intervention either with or without Fitbit tracker integration. All intervention materials were delivered on the Web, and there was no face-to-face contact at any time point. Changes in physical activity (Active Australia Survey), sitting time (Workforce Sitting Questionnaire), and body mass index (BMI) were assessed 1 and 3 months post baseline. Advice acceptability, website usability, and module completion were also assessed. RESULTS: A total of 243 Australian adults participated. Linear mixed model analyses showed a significant increase in total weekly physical activity (adjusted mean increase=163.2; 95% CI 52.0-274.5; P=.004) and moderate-to-vigorous physical activity (adjusted mean increase=78.6; 95% CI 24.4-131.9; P=.004) in the Fitbit group compared with the non-Fitbit group at the 3-month follow-up. The sitting time and BMI decreased more in the Fitbit group, but no significant group × time interaction effects were found. The physical activity advice acceptability and the website usability were consistently rated higher by participants in the Fitbit group. Non-Fitbit group participants completed 2.9 (SD 2.5) modules, and Fitbit group participants completed 4.4 (SD 3.1) modules. CONCLUSIONS: Integrating physical activity trackers into a Web-based computer-tailored intervention significantly increased intervention effectiveness. TRIAL REGISTRATION: Australian New Zealand Clinical Trials Registry ACTRN12616001555448; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=371793 (Archived by WebCite at http://www.webcitation.org/73ioTxQX2).

Physical Activity, Sedentary Behavior, and Diet-Related eHealth and mHealth Research: Bibliometric Analysis.

BACKGROUND: Electronic health (eHealth) and mobile health (mHealth) approaches to address low physical activity levels, sedentary behavior, and unhealthy diets have received significant research attention. However, attempts to systematically map the entirety of the research field are lacking. This gap can be filled with a bibliometric study, where publication-specific data such as citations, journals, authors, and keywords are used to provide a systematic overview of a specific field. Such analyses will help researchers better position their work. OBJECTIVE: The objective of this review was to use bibliometric data to provide an overview of the eHealth and mHealth research field related to physical activity, sedentary behavior, and diet. METHODS: The Web of Science (WoS) Core Collection was searched to retrieve all existing and highly cited (as defined by WoS) physical activity, sedentary behavior, and diet related eHealth and mHealth research papers published in English between January 1, 2000 and December 31, 2016. Retrieved titles were screened for eligibility, using the abstract and full-text where needed. We described publication trends over time, which included journals, authors, and countries of eligible papers, as well as their keywords and subject categories. Citations of eligible papers were compared with those expected based on published data. Additionally, we described highly-cited papers of the field (ie, top ranked 1%). RESULTS: The search identified 4805 hits, of which 1712 (including 42 highly-cited papers) were included in the analyses. Publication output increased on an average of 26% per year since 2000, with 49.00% (839/1712) of papers being published between 2014 and 2016. Overall and throughout the years, eHealth and mHealth papers related to physical activity, sedentary behavior, and diet received more citations than expected compared with papers in the same WoS subject categories. The Journal of Medical Internet Research published most papers in the field (9.58%, 164/1712). Most papers originated from high-income countries (96.90%, 1659/1717), in particular the United States (48.83%, 836/1712). Most papers were trials and studied physical activity. Beginning in 2013, research on Generation 2 technologies (eg, smartphones, wearables) sharply increased, while research on Generation 1 (eg, text messages) technologies increased at a reduced pace. Reviews accounted for 20 of the 42 highly-cited papers (n=19 systematic reviews). Social media, smartphone apps, and wearable activity trackers used to encourage physical activity, less sedentary behavior, and/or healthy eating were the focus of 14 highly-cited papers. CONCLUSIONS: This study highlighted the rapid growth of the eHealth and mHealth physical activity, sedentary behavior, and diet research field, emphasized the sizeable contribution of research from high-income countries, and pointed to the increased research interest in Generation 2 technologies. It is expected that the field will grow and diversify further and that reviews and research on most recent technologies will continue to strongly impact the field.

Are health behavior change interventions that use online social networks effective? A systematic review.

BACKGROUND: The dramatic growth of Web 2.0 technologies and online social networks offers immense potential for the delivery of health behavior change campaigns. However, it is currently unclear how online social networks may best be harnessed to achieve health behavior change. OBJECTIVE: The intent of the study was to systematically review the current level of evidence regarding the effectiveness of online social network health behavior interventions. METHODS: Eight databases (Scopus, CINAHL, Medline, ProQuest, EMBASE, PsycINFO, Cochrane, Web of Science and Communication & Mass Media Complete) were searched from 2000 to present using a comprehensive search strategy. Study eligibility criteria were based on the PICOS format, where "population" included child or adult populations, including healthy and disease populations; "intervention" involved behavior change interventions targeting key modifiable health behaviors (tobacco and alcohol consumption, dietary intake, physical activity, and sedentary behavior) delivered either wholly or in part using online social networks; "comparator" was either a control group or within subject in the case of pre-post study designs; "outcomes" included health behavior change and closely related variables (such as theorized mediators of health behavior change, eg, self-efficacy); and "study design" included experimental studies reported in full-length peer-reviewed sources. Reports of intervention effectiveness were summarized and effect sizes (Cohen's d and 95% confidence intervals) were calculated wherever possible. Attrition (percentage of people who completed the study), engagement (actual usage), and fidelity (actual usage/intended usage) with the social networking component of the interventions were scrutinized. RESULTS: A total of 2040 studies were identified from the database searches following removal of duplicates, of which 10 met inclusion criteria. The studies involved a total of 113,988 participants (ranging from n=10 to n=107,907). Interventions included commercial online health social network websites (n=2), research health social network websites (n=3), and multi-component interventions delivered in part via pre-existing popular online social network websites (Facebook n=4 and Twitter n=1). Nine of the 10 included studies reported significant improvements in some aspect of health behavior change or outcomes related to behavior change. Effect sizes for behavior change ranged widely from -0.05 (95% CI 0.45-0.35) to 0.84 (95% CI 0.49-1.19), but in general were small in magnitude and statistically non-significant. Participant attrition ranged from 0-84%. Engagement and fidelity were relatively low, with most studies achieving 5-15% fidelity (with one exception, which achieved 105% fidelity). CONCLUSIONS: To date there is very modest evidence that interventions incorporating online social networks may be effective; however, this field of research is in its infancy. Further research is needed to determine how to maximize retention and engagement, whether behavior change can be sustained in the longer term, and to determine how to exploit online social networks to achieve mass dissemination. Specific recommendations for future research are provided.

Evaluation of the "15 Minute Challenge": A Workplace Health and Wellbeing Program.

The 15 Minute Challenge is an mHealth workplace wellness initiative, employing gamification to promote physical activity, aiming to enhance health outcomes and overall well-being. This retrospective cohort study evaluated the effectiveness of the program among employees at various Australian, New Zealand, and UK workplaces. Real-world data from 11,575 participants across 73 companies were analyzed. The program encouraged daily 15 min physical activity sessions over six weeks. Participants self-reported their physical activity and fitness, energy, overall health, sleep quality, and mood at baseline and 6 weeks. Program satisfaction, engagement rates, and adherence to the program were also assessed. Effectiveness was evaluated using multi-level mixed-effects linear regression analyses. The intervention showed significant increases in physical activity, with 95% of participants meeting or exceeding international physical activity guidelines, up from 57% at baseline (p < 0.05). Self-reported fitness, energy, overall health, sleep quality, and mood significantly improved (between 7.1 and 14.0% improvement; all p < 0.05). High satisfaction was reported, with 92% of participants recommending the program. The 15 Minute Challenge effectively increased physical activity levels and improved self-reported health outcomes among participating employees. The high satisfaction rates and significant health improvements highlight the potential of workplace wellness programs to combat sedentary behavior and promote a healthier, more active lifestyle.

Annual and Seasonal Patterns of Dietary Intake in Australian Adults: A Prospective Cohort Study.

Poor diet is a major risk factor for non-communicable disease. The aims of this study were to describe temporal patterns and seasonal changes in diet across the year in Australian adults. A total of 375 adults from a prospective cohort study conducted between 1 December 2019 and 31 December 2021 in Adelaide, Australia, were asked to complete the Dietary Questionnaire for Epidemiological Studies at eight timepoints over a year. Average intakes over the previous month of total energy, macronutrients, healthy food groups, and discretionary foods and beverages were derived. Temporal patterns in diet were analysed descriptively. Multilevel linear regression modelling was used to assess seasonal differences in diet. Of the 375 participants recruited, 358 provided sufficient data for analysis. Intake of total energy, all macronutrients, and most discretionary foods and beverages peaked in December. Total energy intake was higher in summer than in autumn, winter, and spring. Fruit intake was higher in summer than in winter. Consumption of alcoholic beverages was higher in summer than in autumn, winter, and spring. Consumption of non-alcoholic beverages was higher in summer than in autumn and winter. This study identified temporal differences in dietary intake among Australian adults. Seasonal effects appear to be driven largely by increases in consumption of foods and beverages over the December (summer) holiday period. These findings can inform the design and timing of dietary interventions.

A systematic umbrella review and meta-meta-analysis of eHealth and mHealth interventions for improving lifestyle behaviours.

The aim of this meta-meta-analysis was to systematically review randomised controlled trial (RCT) evidence examining the effectiveness of e- and m-Health interventions designed to improve physical activity, sedentary behaviour, healthy eating and sleep. Nine electronic databases were searched for eligible studies published from inception to 1 June 2023. Systematic reviews with meta-analyses of RCTs that evaluate e- and m-Health interventions designed to improve physical activity, sedentary behaviour, sleep and healthy eating in any adult population were included. Forty-seven meta-analyses were included, comprising of 507 RCTs and 206,873 participants. Interventions involved mobile apps, web-based and SMS interventions, with 14 focused on physical activity, 3 for diet, 4 for sleep and 26 evaluating multiple behaviours. Meta-meta-analyses showed that e- and m-Health interventions resulted in improvements in steps/day (mean difference, MD = 1329 [95% CI = 593.9, 2065.7] steps/day), moderate-to-vigorous physical activity (MD = 55.1 [95% CI = 13.8, 96.4] min/week), total physical activity (MD = 44.8 [95% CI = 21.6, 67.9] min/week), sedentary behaviour (MD = -426.3 [95% CI = -850.2, -2.3] min/week), fruit and vegetable consumption (MD = 0.57 [95% CI = 0.11, 1.02] servings/day), energy intake (MD = -102.9 kcals/day), saturated fat consumption (MD = -5.5 grams/day), and bodyweight (MD = -1.89 [95% CI = -2.42, -1.36] kg). Analyses based on standardised mean differences (SMD) showed improvements in sleep quality (SMD = 0.56, 95% CI = 0.40, 0.72) and insomnia severity (SMD = -0.90, 95% CI = -1.14, -0.65). Most subgroup analyses were not significant, suggesting that a variety of e- and m-Health interventions are effective across diverse age and health populations. These interventions offer scalable and accessible approaches to help individuals adopt and sustain healthier behaviours, with implications for broader public health and healthcare challenges.

Changes in use of time, activity patterns, and health and wellbeing across retirement: design and methods of the life after work study.

BACKGROUND: Retirement is a major life transition during which people restructure everyday activities; however little is known about this. The primary aim of the Life After Work study is to comprehensively measure changes in time use and patterns of physical activity and sedentary behaviour, and its associations with health and wellbeing, across the retirement transition. METHODS/DESIGN: A target sample of 120 participants aged 50 years and over will be recruited in two Australian state capital cities, Adelaide and Brisbane. Participants will undertake a battery of assessments approximately 3 months prior to retirement, and 3, 6 and 12 months post-retirement. Measures will include self-reported use of time (using the Multimedia Activity Recall for Children and Adults), objectively assessed physical activity and sedentary behaviour (using Actigraph GT3X+ accelerometers), self-reported health and well-being (using a battery of questionnaires including the Short-Form Health Survey (SF-36), Australian Unity Personal Well-being Index (AUPWI), Depression Anxiety Stress Scales 21 (DASS21), Short Warwick-Edinburgh Mental Well-being Scale, UCLA Loneliness Scale, Rosenberg Self-Esteem Scale), retirement circumstances and socio-demographic characteristics, objectively assessed anthropometric measures (height, weight and waist circumference), and resting blood pressure. Multivariate mixed models will be used to examine changes in use of time, health and well-being across retirement. DISCUSSION: The results will provide important new information that will inform the development of lifestyle and policy interventions to address and improve health and well-being in retirement.

Trends in Well-Being Among Youth in Australia, 2017-2022.

Importance: Little is known about temporal trends in children's well-being and how the COVID-19 pandemic may have influenced the well-being of young Australians. Certain demographic groups may be more vulnerable to experiencing declines in well-being. Objective: To examine well-being trends over 6 consecutive years among South Australian students and explore the influence of sociodemographic characteristics. Design, Setting, and Participants: Longitudinal analyses of annual (2017 to 2022) cross-sectional data of students in grades 4 through 9 (n = 40 392 to 56 897 per year) attending South Australian government schools from the Well-being and Engagement Collection (WEC) census. Exposures: Calendar year (2017-2022) and sociodemographic characteristics (sex, school grade, parental education, language spoken at home, residential region) from school enrollment records. Main Outcomes and Measures: Students self-reported life satisfaction, optimism, happiness, cognitive engagement, emotional regulation, perseverance, worry, and sadness. Results: Over 6 years (2017 to 2022), a total of 119 033 students (mean [SD] age, 12.1 y; 51.4% male) participated in this study. Most well-being measures declined over time, with consistent worsening of well-being from 2020 onward. For example, compared with 2017, sadness was 0.26 (95% CI, 0.25-0.27) points higher in 2020 (standardized mean difference [SMD], 0.27) and remained elevated by more than 0.26 points (SMD, 0.27) in 2021 and 2022. At almost every time point, greatest well-being was reported by students of male sex (except cognitive engagement and perseverance), in earlier school grades, with highest parental education, speaking a language other than English at home, and residing in outer regional and remote settings (for satisfaction, optimism, and emotional regulation). Sociodemographic differences in well-being were generally consistent over time; however, sex differences widened from 2020 for all indicators except cognitive engagement and perseverance. For example, between 2017 and 2022, sadness increased by 0.27 (95% CI, 0.25-0.29) more points among females than males (SMD, 0.28). Conclusions and Relevance: In this longitudinal analysis of annual census data, there were downward trends in students' well-being, especially since 2020. The largest sociodemographic disparities were observed for students of female sex, those in later school grades, and those with lowest parental education. Urgent and equitable support for the well-being of all young people, particularly those facing disparity, is imperative.

Uptake of a Universal Sports Subsidy Program for School-Aged Children: A Population Data Analysis.

BACKGROUND: Around 40% of Australian children do not participate in sport. Cost is a major barrier to participation, particularly for children from low socioeconomic backgrounds. This study aimed to evaluate the uptake of a population-level children's sports subsidy scheme, including sociodemographic differences in uptake. METHODS: A state-wide cross-sectional analysis comparing sports voucher claimants (primary school-aged children with a valid Medicare or Australian visa number) from the 2019 financial year with population census data from South Australia. Chi-square was used to examine whether the percentage of eligible children who claimed a voucher differed based on age, sex, socioeconomic status (SES), and geographical remoteness. Subgroup analyses were conducted for the lowest 2 socioeconomic disadvantage deciles, split by gender. Scatterplots were used to compare sports between high and low SES children. RESULTS: A total of 74,668 children claimed sports vouchers (45.5% of eligible children). Children who were relatively younger, female, from low socioeconomic backgrounds, and from major cities were least likely to claim the voucher. The 5 most common sports were Australian rules football (30.2%), netball (13.6%), soccer (13.1%), gymnastics (10.4%), and basketball (5.7%), with the popular sports similar for high and low SES children. CONCLUSIONS: Future work is needed to understand how Sports Voucher, and sport participation rates have changed over time, and to improve voucher uptake among girls, city dwellers, and low SES children.

Safety, Feasibility and Efficacy of Lokomat® and Armeo®Spring Training in Deconditioned Paediatric, Adolescent and Young Adult Cancer Patients.

BACKGROUND: Rehabilitation robotics is a field of study which aims to understand and augment rehabilitation through the use of robotics devices. OBJECTIVE: This proof of concept study aimed to test the safety (no. adverse events, incidence of infection), feasibility (program demand, adherence, participant satisfaction) and efficacy (Peak Oxygen uptake (VO2peak), 6-min walk test, gait speeds, Canadian Occupational Performance Measure, quality of life) of Lokomat® and Armeo®Spring training in children and adolescents and young adults (AYAs) during or soon after cancer treatment. METHOD: This was a 6-week single arm pre-post study. Cancer patients with significant musculoskeletal, neurological, gait and/or upper limb deficiency aged 5 to 25 years were recruited. The rehabilitation program included access to two robotic orthoses: the Lokomat® and/or Armeo®Spring. Robotic devices utilised real-time biofeedback and computer games to engage and guide participants through a repetitive functional range of movement aimed at improving functional deficiencies. Progressive increases in exercise intensity and duration were encouraged. RESULTS: Twentey-eight participants were approached for study; twenty-one consented. Seventy-six percent completed the six-week intervention with an overall adherence of 83%. The mean participant satisfaction score was 8.8/10. Forty-nine adverse events were recorded throughout the course of the study, forty-five grade 1, three grade 2 and one grade 3. No adverse events led to withdrawal from the study. Preliminary efficacy results indicate large beneficial effects on VO2peak (r = 0.63), 10 m comfortable pace walk (r = 0.51) and maximal pace walk (r = 0.60), 6-min walk test (r = 0.60), maximal back and leg strength (r = 0.71), trunk flexibility (r = 0.60), The European Organization for the Research and Treatment of Cancer Quality of Life Questionnaire (EORTC QLQ C30) (r = 0.61), Functional Assessment of Chronic Illness Therapy-Fatigue (FACIT F) r = 0.53 and the Canadian Occupational Performance Measure, satisfaction (r = 0.88) and performance scores (r = 0.83), and moderate beneficial effects on Leisure Score Index (LSI) (r = 0.30). CONCLUSION: Our results suggest that Lokomat® and Armeo®Spring training is safe and feasible for use in children and AYAs who are currently undergoing or have recently completed cancer therapy. A larger controlled trial investigating the efficacy of robotics rehabilitation in this cohort is warranted.

Gamification in a Physical Activity App: What Gamification Features Are Being Used, by Whom, and Does It Make a Difference?

Background: Gamification is purported to enhance engagement with health behavior apps, ultimately improving their effectiveness. This study aimed to examine (1) whether the inclusion of gamification features in a physical activity smartphone app was associated with improved app usage and goal adherence, describe (2) use of the gamification features, and (3) by whom, and determine (4) whether engagement was associated with increased physical activity. Methods: Data from community-dwelling adult participants (mean age 42.1 years, standard deviation [SD 11.9], 74% female) in the gamified (n = 134) and nongamified (n = 155) conditions from a three-group randomized controlled trial were analyzed. Physical activity was assessed at baseline and 9 months using a survey and accelerometers. App usage (number of days steps were logged), goal adherence (number of days step count was ≥10,000), and behavioral engagement with gamification features were obtained from server logs. Multilevel modeling was used to examine the study aims. Results: Participants who received the gamified app showed more days of usage than those who received the nongamified app (M = 113 days [SD 88] vs. M = 81 days [SD 54], P = 0.006), whereas goal adherence did not differ between groups. The leaderboard and "status" gamification features were the most frequently used gamification features (M = 83 [SD 114] and M = 50 [SD 67] views, respectively). Older age (P = 0.008) and lower body mass index (P = 0.004) were associated with more status views. Participants who reported higher stress symptoms sent more gifts (P = 0.04). The use of gamification features was associated with increased physical activity (P = 0.04). Conclusion: The gamified app was used substantially longer than the nongamified app. Use of gamification features was positively associated with change in physical activity. Leaderboards promoting social comparison may be a promising form of gamification. Research on different forms of gamification is warranted.