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.

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.

Interventions Using Wearable Activity Trackers to Improve Patient Physical Activity and Other Outcomes in Adults Who Are Hospitalized: A Systematic Review and Meta-analysis.

Importance: Low levels of physical activity during hospitalization are thought to contribute to a range of poor outcomes for patients. Using wearable activity trackers during hospitalization may help improve patient activity, sedentary behavior, and other outcomes. Objective: To evaluate the association of interventions that use wearable activity trackers during hospitalization with patient physical activity, sedentary behavior, clinical outcomes, and hospital efficiency outcomes. Data Sources: OVID MEDLINE, CINAHL, Embase, EmCare, PEDro, SportDiscuss, and Scopus databases were searched from inception to March 2022. The Cochrane Central Register for Controlled trials, ClinicalTrials.gov, and World Health Organization Clinical Trials Registry were also searched for registered protocols. No language restrictions were imposed. Study Selection: Randomized clinical trials and nonrandomized clinical trials of interventions that used wearable activity trackers to increase physical activity or reduce sedentary behavior in adults (aged 18 years or older) who were hospitalized were included. Data Extraction and Synthesis: Study selection, data extraction, and critical appraisal were conducted in duplicate. Data were pooled for meta-analysis using random-effects models. The Preferred Reporting Items for Systematic Reviews and Meta-analyses guideline was followed. Main Outcomes and Measures: The primary outcomes were objectively measured physical activity or sedentary behavior. Secondary outcomes included clinical outcomes (eg, physical function, pain, mental health), and hospital efficiency outcomes (eg, length of stay, readmission). Results: Fifteen studies with a total of 1911 participants were included, representing various surgical cohorts (4 studies), stroke rehabilitation (3 studies), orthopedic rehabilitation (3 studies), mixed rehabilitation (3 studies), and mixed medical (2 studies). All studies were included in meta-analyses. There was a significant association between wearable activity tracker interventions with higher overall physical activity (standardized mean difference, 0.35; 95% CI, 0.15 to 0.54; I2 = 72%; P < .002) and less sedentary behavior (mean difference, -35.46 min/d; 95% CI, -57.43 to -13.48 min/d; I2 = 0; P = .002), and a significant association between wearable activity tracker interventions with improvements in physical function (standardized mean difference, 0.27; 95% CI, 0.08 to 0.46; I2 = 0; P = .006) compared with usual care. There was no significant association between wearable activity tracker interventions with pain, mental health, length of stay, or readmission risk. Conclusions and Relevance: In this systematic review and meta-analysis, interventions that used wearable activity trackers with patients who are hospitalized were associated with higher physical activity levels, less sedentary behavior, and better physical functioning compared with usual care.

Systematic review and meta-analysis of the effectiveness of chatbots on lifestyle behaviours.

Chatbots (also known as conversational agents and virtual assistants) offer the potential to deliver healthcare in an efficient, appealing and personalised manner. The purpose of this systematic review and meta-analysis was to evaluate the efficacy of chatbot interventions designed to improve physical activity, diet and sleep. Electronic databases were searched for randomised and non-randomised controlled trials, and pre-post trials that evaluated chatbot interventions targeting physical activity, diet and/or sleep, published before 1 September 2022. Outcomes were total physical activity, steps, moderate-to-vigorous physical activity (MVPA), fruit and vegetable consumption, sleep quality and sleep duration. Standardised mean differences (SMD) were calculated to compare intervention effects. Subgroup analyses were conducted to assess chatbot type, intervention type, duration, output and use of artificial intelligence. Risk of bias was assessed using the Effective Public Health Practice Project Quality Assessment tool. Nineteen trials were included. Sample sizes ranged between 25-958, and mean participant age ranged between 9-71 years. Most interventions (n = 15, 79%) targeted physical activity, and most trials had a low-quality rating (n = 14, 74%). Meta-analysis results showed significant effects (all p < 0.05) of chatbots for increasing total physical activity (SMD = 0.28 [95% CI = 0.16, 0.40]), daily steps (SMD = 0.28 [95% CI = 0.17, 0.39]), MVPA (SMD = 0.53 [95% CI = 0.24, 0.83]), fruit and vegetable consumption (SMD = 0.59 [95% CI = 0.25, 0.93]), sleep duration (SMD = 0.44 [95% CI = 0.32, 0.55]) and sleep quality (SMD = 0.50 [95% CI = 0.09, 0.90]). Subgroup analyses showed that text-based, and artificial intelligence chatbots were more efficacious than speech/voice chatbots for fruit and vegetable consumption, and multicomponent interventions were more efficacious than chatbot-only interventions for sleep duration and sleep quality (all p < 0.05). Findings from this systematic review and meta-analysis indicate that chatbot interventions are efficacious for increasing physical activity, fruit and vegetable consumption, sleep duration and sleep quality. Chatbot interventions were efficacious across a range of populations and age groups, with both short- and longer-term interventions, and chatbot only and multicomponent interventions being efficacious.

Early mobilisation in critically ill children: Does routine patient screening reduce time to commencing mobilisation?

OBJECTIVE: The objective of this study was to investigate the impact of daily screening for medical readiness to participate in early mobilisation in the paediatric intensive care unit (PICU), on reducing time to mobilisation and to explore the safety-, feasibility-, and patient-level barriers to the practice. METHODS: An interventional study with a historical control group was conducted in a PICU in a tertiary teaching hospital in Australia. The Early Mobilisation Screening Checklist was applied at 24-48 h of PICU stay with the aim to reduce time to commencing mobilisation. All patients aged term to 18 years admitted to the PICU for >48 h were included in this study. Data on time to mobilisation and patient characteristics were collected by an unblinded case note audit of children admitted to the PICU over 5 months in 2018 for the baseline group and over a corresponding period in 2019 for the intervention group. MEASUREMENTS AND MAIN RESULTS: A total of 71 children were enrolled. Survival analysis was used to compare time to mobilisation between groups, and a cox regression model found that children in the intervention group were 1.26 times more likely to participate in mobility, but this was not statistically significant (P = 0.391, log rank test for equality of survival functions). Early mobilisation was safe, with no adverse events reported in 177 participant mobilisation days. Feasibility was demonstrated by 62% of participants mobilising within 72 h of admission. Mechanical ventilation during stay (P = 0.043) and days receiving sedation infusion (% of days) (P = 0.042) were associated with a decreased likelihood of participating in mobility. CONCLUSIONS: Implementation of routine screening alone does not significantly reduce time to commencing mobility in the PICU. Early mobilisation in the PICU is safe and feasible and resulted in no adverse events during mobilisation. Patient characteristics influencing participation in mobility warrant further exploration.