Background: With the advancing age of the population, and increasing demands on healthcare services, community participation has become an important consideration for healthy ageing. Low levels of community participation have been linked to increased mortality and social isolation. The extent to which community participation has been measured objectively in older adults remains scarce. This study aims to describe where and how older adults participate in the community and determine the feasibility of measurement methods for community participation. Methods: This observational cross-sectional study obtained data from 46 community dwelling older adults. A combination of Global Positioning Systems (GPS), accelerometry, and self-reported diaries were used over a 7-day monitoring period. Feasibility of methods were determined by calculating the loss of GPS data, questionnaires, and comparison of self-reported locations with GPS co-ordinates. Relationships between community participation, physical activity, social interactions, health related quality of life, sleep quality and loneliness were explored. Results: Older adults took a median (IQR) of 15 (9.25–18.75) trips out of home over the 7-day monitoring period, most frequently visiting commercial and recreational locations. In-home activities were mainly sedentary in nature, with out of home activities dependent on location type. Self-reported and GPS measures of trips out of home and the locations visited were significantly correlated (self-report 15.7 (5.6) GPS 14.4 (5.8) (r = 0.94)). Significant correlations between both the number of trips taken from home, with social interactions (r = 0.62) and the minutes of moderate to vigorous physical activity (MVPA) (r = 0.43) were observed. Daily MVPA was higher in participants who visited local walk/greenspaces (r = 0.48). Conclusion: Participants performed more activities with social interactions out of home and visited commercial locations most frequently. The combination of GPS, accelerometry and self-report methods provided a detailed picture of community participation for older adults. Further research is required with older adults of varying health status to generalise the relationships between community participation, location and physical activity. Trial registration: Ethical approval was gained from the Flinders University Social and Behavioural Research Ethics Committee (protocol no. 8176).

Compared to laboratory equipment inertial sensors are inexpensive and portable, permitting the measurement of postural sway and balance to be conducted in any setting. This systematic review investigated the inter-sensor and test-retest reliability, and concurrent and discriminant validity to measure static and dynamic balance in healthy adults. Medline, PubMed, Embase, Scopus, CINAHL, and Web of Science were searched to January 2021. Nineteen studies met the inclusion criteria. Meta-analysis was possible for reliability studies only and it was found that inertial sensors are reliable to measure static standing eyes open. A synthesis of the included studies shows moderate to good reliability for dynamic balance. Concurrent validity is moderate for both static and dynamic balance. Sensors discriminate old from young adults by amplitude of mediolateral sway, gait velocity, step length, and turn speed. Fallers are discriminated from non-fallers by sensor measures during walking, stepping, and sit to stand. The accuracy of discrimination is unable to be determined conclusively. Using inertial sensors to measure postural sway in healthy adults provides real-time data collected in the natural environment and enables discrimination between fallers and non-fallers. The ability of inertial sensors to identify differences in postural sway components related to altered performance in clinical tests can inform targeted interventions for the prevention of falls and near falls.

Background: With the increasing age of the global population, key components of healthy ageing including community, physical, and social participation continue to gain traction. However, management of the COVID-19 pandemic aimed to protect older adults and reduce the spread of the virus, this restricted community participation and reduced the opportunities for social interaction. Methods: This mixed methods study investigates community dwelling older adults’ community participation; physical activity and social interaction prior to, during, and following the COVID-19 lockdown in Adelaide, Australia. Twenty-six community dwelling older adults were monitored over three time-points between November 2018 and October 2020, with Global Positioning Systems, accelerometry and self-reported diaries. In addition, nineteen participants completed semi-structured interviews. Results: Community participation varied across the three time points, with significant reduction in the number of trips taken out-of-home (p = 0.021), social interactions (p = 0.001) and sleep quality (p = 0.008) during restrictions. Five themes were identified to explain personal experiences of community participation during restrictions: (1) Reframing of meaning, (2) Redefining to maintain activities, (3) Revision of risk, (4) Reflection and renewal and (5) Future planning. Conclusion: During COVID-19 the physical and social activities of community dwelling older adults changed. Services that support older adults to adapt their activities , considering their capacities and preferences, to facilitate community participation are required.

Objective: Virtual reality (VR) technologies are increasingly used in physical rehabilitation; however, it is unclear how VR interventions are being delivered, and, in particular, the role of the therapist remains unknown. The purpose of this study was to systematically evaluate how commercially available VR technologies are being implemented in gait, posture, and balance rehabilitation, including justification, content, procedures, and dosage of the intervention and details of the therapist role. Methods: Five databases were searched between 2008 and 2018. Supervised interventional trials with >10 adult participants using commercially available VR technologies to address mobility limitations were independently selected by 2 authors. One author extracted reported intervention characteristics into a predesigned table and assessed methodological quality, which was independently verified by a second author. A total of 29 studies were included. Results: Generally, minimal clinical reasoning was provided to justify technology or activity selection, with recreational systems and games used most commonly (n = 25). All but 1 study used a single interventional technology. When explicitly described, the intervention was delivered by a physical therapist (n = 14), a therapist assistant (n = 2), both (n = 1), or an occupational therapist (n = 1). Most studies reported supervision (n = 12) and safeguarding (n = 8) as key therapist roles, with detail of therapist feedback less frequently reported (n = 4). Therapist involvement in program selection, tailoring, and progression was poorly described. Conclusion: Intervention protocols of VR rehabilitation studies are incompletely described and generally lack detail on clinical rationale for technology and activity selection and on the therapist role in intervention design and delivery, hindering replication and translation of research into clinical practice. Future studies utilizing commercially available VR technologies should report all aspects of intervention design and delivery and consider protocols that allow therapists to exercise clinical autonomy in intervention delivery. Impact Statement: The findings of this systematic review have highlighted that VR rehabilitation interventions targeting gait, posture, and balance are primarily delivered by physical therapists, whose most reported role was supervision and safeguarding. There was an absence of detail regarding complex clinical skills, such as tailoring of the intervention and reasoning for the choice of technology and activity. This uncertainty around the role of the therapist as an active ingredient in VR-based rehabilitation hinders the development of implementation guidelines. To inform the optimal involvement of therapists in VR rehabilitation, it is essential that future studies report on all aspects of VR intervention design and delivery.

Benefits of community participation and physical activity for the health and wellbeing of older adults are well documented. This review aims to answer the question; “How is community participation ...

Background: eHealth and mobile health (mHealth) interventions are promising in promoting healthy behaviors among children and adolescents. Objective: This systematic umbrella review and meta–meta-analysis aimed to evaluate the effectiveness of eHealth and mHealth interventions in promoting healthy behaviors among children and adolescents. Methods: Nine databases were searched for systematic reviews and meta-analyses of randomized controlled trials of eHealth and mHealth interventions targeting physical activity, sedentary behavior, sleep, and dietary outcomes in children and adolescents aged below 18 years. Screening, data extraction, and all assessments were completed by 2 reviewers. Study quality was assessed using the AMSTAR-2 (A Measurement Tool to Assess Systematic Reviews-2) checklist, and meta-analyses were conducted to combine effect sizes using random effects models. Subgroup analyses examined participant and intervention characteristics. Results: A total of 25 systematic reviews comprising 440 randomized controlled trials and 133,501 participants, mostly involving healthy children and adolescents (n=18, 72%) or those who were overweight or with obesity (n=4, 16%), were included. Interventions mostly included active video games or serious games (n=8, 32%), various mHealth interventions (n=6, 24%), various eHealth interventions (n=5, 20%), combined eHealth and mHealth interventions (n=4, 16%), wearables (n=1, 4%), and computer-based interventions (n=1, 4%). Most studies (n=18, 72%) had critically low AMSTAR-2 scores. Meta-analyses based on standardized mean difference (SMD) showed significant effects (all P<.05) for moderate to vigorous physical activity (SMD 0.18, 95% CI 0.09-0.27), total physical activity (SMD 0.24, 95% CI 0.13-0.35), fat intake (SMD 0.10, 95% CI 0.02-0.18), fruit and vegetable intake (SMD 0.11, 95% CI 0.00-0.22), BMI (SMD 0.19, 95% CI 0.11-0.27), and body weight (SMD 0.15, 95% CI 0.01-0.30). No effects were found for sedentary behavior (SMD 0.12, 95% CI –0.11 to 0.35) or sleep (SMD 0.27, 95% CI –0.09 to 0.63). Shorter interventions (lasting <8 weeks) had a greater effect on moderate to vigorous physical activity than longer interventions (lasting ≥8 weeks), while longer interventions (lasting ≥12 weeks) had a greater effect on BMI compared with shorter interventions. Conclusions: eHealth and mHealth interventions offer modest but meaningful improvements in physical activity, diet, and weight management in children and adolescents, with important implications for integrating digital tools into health promotion strategies. Trial Registration: PROSPERO CRD42024537019; https://www.crd.york.ac.uk/PROSPERO/view/CRD42024537019