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.

Depression and anxiety are prevalent and rising in children and adolescents, prompting interest in exercise as a potential therapeutic intervention. The aim of this systematic umbrella review and meta-meta-analysis (a meta-analysis of meta-analyses) was to evaluate the effects of exercise on depression and anxiety symptoms in children and adolescents and to identify the most promising exercise-based approaches. This systematic umbrella review was preregistered (PROSPERO ID: CRD42024533558) and followed Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) and Preferred Reporting Items for Overviews of Reviews (PRIOR) guidelines. A search of 11 databases identified systematic reviews and meta-analyses of randomized controlled trials (RCTs) evaluating the effects of exercise (aerobic, resistance, mind-body exercise) on depression and anxiety symptoms in children and adolescents. Risk of bias was assessed using the A MeaSurement Tool to Assess systematic Reviews (AMSTAR-2) tool, and certainty of evidence was assessed using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) tool. Meta-analyses were conducted to combine effect sizes, using random effects models. Subgroup analyses were performed to examine participant and intervention characteristics. A total of 21 systematic reviews (n = 375 RCTs, n = 38,117 participants 5-18 years of age) were included. Participants included those with various clinical conditions, including depression, psychosocial disorders, obesity, and cancer, as well as healthy individuals. The pooled analysis found moderate effect sizes favoring exercise for symptoms of depression (standardized mean difference [SMD] = -0.45, 95% CI = -0.59 to -0.31, I² = 71.37%, p < .01, 180 RCTs, n = 34,490 participants) and anxiety (SMD = -0.39, 95% CI = -0.61 to -0.17, I² = 68.1%, p < .01, n = 55 RCTs, n = 24,797 participants). Mixed exercise modes and moderate-intensity exercise had the largest effects on depression, whereas resistance exercise was most effective for symptoms of anxiety. Interventions that were <12 weeks were more effective for depression compared with those that were ≥12 weeks. Benefits were generally consistent across populations. The certainty of evidence was moderate for depression and low to moderate for anxiety. This meta-meta-analysis finds that exercise reduces depression and anxiety symptoms in children and adolescents. These results suggest that structured exercise programs should be considered as part of comprehensive care approaches. This study reviewed evidence from 21 review articles, consisting of 375 randomized controlled trials involving over 38,000 children and adolescents, to examine the effects of exercise on symptoms of anxiety and depression. Results show that exercise significantly reduces symptoms of depression and anxiety, with moderate-intensity and resistance exercises being particularly effective. Shorter interventions (less than 12 weeks) had greater benefits for depression. These results highlight the potential of structured exercise programs as a valuable tool for improving youth mental health. • Clinicians should consider incorporating structured exercise programs, particularly moderate-intensity and resistance training, as part of a comprehensive approach to managing depression and anxiety in children and adolescents. • Shorter exercise interventions (<12 weeks) may provide greater benefits for depression and could be a practical starting point for integrating exercise into treatment plans. • Given the broad effectiveness of exercise across various populations, healthcare providers can recommend physical activity interventions regardless of a child's clinical condition, tailoring programs to individual needs and preferences. Effectiveness of physical activity in improving depression and anxiety in children and adolescents: a systematic umbrella review; https://www.crd.york.ac.uk/PROSPERO/view/CRD42024533558.

Background: Weather is a potentially important influence on how time is allocated to sleep, sedentary behaviour and physical activity across the 24-h day. Extremes of weather (very hot, cold, windy or wet) can create undesirable, unsafe outdoor environments for exercise or active transport, impact the comfort of sleeping environments, and increase time indoors. This 13-month prospective cohort study explored associations between weather and 24-h movement behaviour patterns. Methods: Three hundred sixty-eight adults (mean age 40.2 years, SD 5.9, 56.8% female) from Adelaide, Australia, wore Fitbit Charge 3 activity trackers 24 h a day for 13 months with minute-by-minute data on sleep, sedentary behaviour, light physical activity (LPA), and moderate-to-vigorous physical activity (MVPA) collected remotely. Daily weather data included temperature, rainfall, wind, cloud and sunshine. Multi-level mixed-effects linear regression analyses (one model per outcome) were used. Results: Ninety thousand eight hundred one days of data were analysed. Sleep was negatively associated with minimum temperature (-12 min/day change across minimum temperature range of 31.2 °C, p = 0.001). Sedentary behaviour was positively associated with minimum temperature (+ 12 min/day, range = 31.2 oC, p = 0.006) and wind speed (+ 10 min/day, range = 36.7 km/h, p< 0.001), and negatively associated with sunshine (-17 min/day, range = 13.9 h, p < 0.001). LPA was positively associated with minimum temperature (+ 11 min/day, range = 31.2 °C, p = 0.002), cloud cover (+ 4 min/day, range = 8 eighths, p = 0.008) and sunshine (+ 17 min/day, range = 13.9 h, p < 0.001), and negatively associated with wind speed (-8 min/day, range = 36.7 km/h, p < 0.001). MVPA was positively associated with sunshine (+ 3 min/day, range = 13.9 h, p < 0.001) and negatively associated with minimum temperature (-13 min/day, range = 31.2 oC, p < 0.001), rainfall (-3 min/day, range = 33.2 mm, p = 0.006) and wind speed (-4 min/day, range = 36.7 km/h, p < 0.001). For maximum temperature, a significant (p < 0.05) curvilinear association was observed with sleep (half-U) and physical activity (inverted-U), where the decrease in sleep duration appeared to slow around 23 °C, LPA peaked at 31 oC and MVPA at 27 °C. Conclusions: Generally, adults tended to be less active and more sedentary during extremes of weather and sleep less as temperatures rise. These findings have the potential to inform the timing and content of positive movement behaviour messaging and interventions. Trial registration: The study was prospectively registered on the Australian New Zealand Clinical Trial Registry (Trial ID: ACTRN12619001430123).

The COVID-19 pandemic has dramatically impacted lifestyle behaviour as public health initiatives aim to “flatten the curve”. This study examined changes in activity patterns (physical activity, sedentary time, sleep), recreational physical activities, diet, weight and wellbeing from before to during COVID-19 restrictions in Adelaide, Australia. This study used data from a prospective cohort of Australian adults (parents of primary school-aged children; n = 61, 66% female, aged 41±6 years). Participants wore a Fitbit Charge 3 activity monitor and weighed themselves daily using Wi-Fi scales. Activity and weight data were extracted for 14 days before (February 2020) and 14 days during (April 2020) COVID-19 restrictions. Participants reported their recreational physical activity, diet and wellbeing during these periods. Linear mixed effects models were used to examine change over time. Participants slept 27 minutes longer (95% CI 9–51), got up 38 minutes later (95% CI 25–50), and did 50 fewer minutes (95% CI -69–-29) of light physical activity during COVID-19 restrictions. Additionally, participants engaged in more cycling but less swimming, team sports and boating or sailing. Participants consumed a lower percentage of energy from protein (-0.8, 95% CI -1.5–-0.1) and a greater percentage of energy from alcohol (0.9, 95% CI 0.2–1.7). There were no changes in weight or wellbeing. Overall, the effects of COVID-19 restrictions on lifestyle were small; however, their impact on health and wellbeing may accumulate over time. Further research examining the effects of ongoing social distancing restrictions are needed as the pandemic continues.

Background: Wearable activity trackers, including fitness bands and smartwatches, offer the potential for disease detection by monitoring physiological parameters. However, their accuracy as specific disease diagnostic tools remains uncertain. Objective: This systematic review and meta-analysis aims to evaluate whether wearable activity trackers can be used to detect disease and medical events. Methods: Ten electronic databases were searched for studies published from inception to April 1, 2023. Studies were eligible if they used a wearable activity tracker to diagnose or detect a medical condition or event (eg, falls) in free-living conditions in adults. Meta-analyses were performed to assess the overall area under the curve (%), accuracy (%), sensitivity (%), specificity (%), and positive predictive value (%). Subgroup analyses were performed to assess device type (Fitbit, Oura ring, and mixed). The risk of bias was assessed using the Joanna Briggs Institute Critical Appraisal Checklist for Diagnostic Test Accuracy Studies. Results: A total of 28 studies were included, involving a total of 1,226,801 participants (age range 28.6-78.3). In total, 16 (57%) studies used wearables for diagnosis of COVID-19, 5 (18%) studies for atrial fibrillation, 3 (11%) studies for arrhythmia or abnormal pulse, 3 (11%) studies for falls, and 1 (4%) study for viral symptoms. The devices used were Fitbit (n=6), Apple watch (n=6), Oura ring (n=3), a combination of devices (n=7), Empatica E4 (n=1), Dynaport MoveMonitor (n=2), Samsung Galaxy Watch (n=1), and other or not specified (n=2). For COVID-19 detection, meta-analyses showed a pooled area under the curve of 80.2% (95% CI 71.0%-89.3%), an accuracy of 87.5% (95% CI 81.6%-93.5%), a sensitivity of 79.5% (95% CI 67.7%-91.3%), and specificity of 76.8% (95% CI 69.4%-84.1%). For atrial fibrillation detection, pooled positive predictive value was 87.4% (95% CI 75.7%-99.1%), sensitivity was 94.2% (95% CI 88.7%-99.7%), and specificity was 95.3% (95% CI 91.8%-98.8%). For fall detection, pooled sensitivity was 81.9% (95% CI 75.1%-88.1%) and specificity was 62.5% (95% CI 14.4%-100%). Conclusions: Wearable activity trackers show promise in disease detection, with notable accuracy in identifying atrial fibrillation and COVID-19. While these findings are encouraging, further research and improvements are required to enhance their diagnostic precision and applicability. Trial Registration: Prospero CRD42023407867; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=407867

Background: There is a growing body of robust evidence to show that lifestyle behaviors influence mental health outcomes. Technology offers an accessible and cost-effective implementation method for interventions, yet the study of the effectiveness of interventions to date has been specific to the mode of delivery, population, or behavior. Objective: The primary aim of this review was to comprehensively evaluate the effectiveness of digital lifestyle interventions for improving symptoms of depression, anxiety, stress, and well-being as coprimary outcomes in adults. The secondary aim was to explore the technological, methodological, intervention-specific, and population-specific characteristics that were associated with major changes in mental health outcomes. Methods: A systematic search was conducted across the MEDLINE, CINAHL, Embase, Emcare, PsycINFO, and Scopus databases to identify studies published between January 2013 and January 2023. Randomized controlled trials of lifestyle interventions (physical activity, sleep, and diet) that were delivered digitally; reported changes in symptoms of depression, anxiety, stress, or well-being in adults (aged ≥18 years); and were published in English were included. Multiple authors independently extracted data, which was evaluated using the 2011 Levels of Evidence from the Oxford Centre for Evidence-Based Medicine. Inverse-variance random-effects meta-analyses were used for data analysis. The primary outcome was the change in symptoms of depression, anxiety, stress, and well-being as measured by validated self-report of clinician-administered outcomes from pre- to postintervention. Subgroup analyses were conducted to determine whether results differed based on the target lifestyle behavior, delivery method, digital features, design features, or population characteristics. Results: Of the 14,356 studies identified, 61 (0.42%) were included. Digital lifestyle interventions had a significant small-to-medium effect on depression (standardized mean difference [SMD] −0.37; P<.001), a small effect on anxiety (SMD −0.29; P<.001) and stress (SMD −0.17; P=.04), and no effect on well-being (SMD 0.14; P=.15). Subgroup analyses generally suggested that effects were similar regardless of the delivery method or features used, the duration and frequency of the intervention, the population, or the lifestyle behavior targeted. Conclusions: Overall, these results indicate that delivering lifestyle interventions via a range of digital methods can have significant positive effects on depression (P<.001), anxiety (P<.001), and stress (P=.04) for a broad range of populations, while effects on well-being are inconclusive. Future research should explore how these interventions can be effectively implemented and embedded within health care with a concerted focus on addressing digital health equity. Trial Registration: PROSPERO CRD42023428908; https://www.crd.york.ac.uk/PROSPERO/view/CRD42023428908