Based on the trend of global aging, people are paying more and more attention to the health of the elderly and the improvement of green open spaces. However, few studies have focused on strategies to improve green spaces in response to this trend. Especially, with the outbreak of COVID-19, an urgent need to develop a sustainable system strategy to improve the health of the elderly in residential communities in old districts has emerged. Traditional improvement strategies based on current situation evaluation often focus on the most prominent practical problems. Therefore, the objective of this study was to provide theoretical research and practical improvement strategies for green open spaces in old downtown residential communities to improve the health and well-being of the elderly. In response to this problem, this research proposes an alternative method based on causality (FDM-DANP-mV model), by extracting 23 green open space elements that affect the health of the elderly and dividing them into three dimensions, to form a preliminary evaluation framework. On this basis, the more effective and feasible standard elements are screened out, and the influence relationship behind the elements is clarified. Then, the sustainable development strategy is systematically discussed in three practical cases. This allows for the analysis of the present situation to not only identify the current significant problems but also to capture the source of the influence behind the real problems based on the clarification of the dominant influence relationship. The actual value of this study is to provide a key design decision basis for the improvement of the green open spaces in old downtown residential communities, aiming at avoiding waste to the greatest extent under the premise of limited resources and gradually promoting the improvement of the urban built environment to promote the health and well-being of the elderly.

Health-related quality of life (HRQOL) is a comprehensive concept that reflects overall health by measuring their physical, psychological, and social well-being (Testa & Simonson, 1996). It is a va...

Park audits can inform neighbourhood-scale urban design strategies that support health. However, interpreting park audit data is time-consuming and requires specialised expertise. Recent advances in large language models suggest potential for assisting with structured data interpretation, but their application to park audits remains unexplored. This study examined whether a large language model (ChatGPT-5) can assist in interpreting park audit data from public parks in Dhaka City, Bangladesh. Using a modified park audit tool, 59 parks were audited, of which 26 met the predefined completeness threshold and were included in the analysis. ChatGPT-5 and human experts received identical park audit datasets and instructions for interpretation. Outputs were evaluated using content analysis and a pre-defined scoring framework to assess accuracy and comprehensiveness. Paired t-tests compared ChatGPT-5 outputs with the expert benchmark. ChatGPT-5 showed no statistically significant difference from the expert benchmark in overall accuracy in this sample (p = 0.13). The unadjusted analysis showed a higher recommendation-match count for ChatGPT-5 (p < 0.05), but this result should be interpreted as exploratory because multiple criteria were tested. No statistically significant differences were detected across accuracy domains or other comprehensiveness criteria. These findings suggest that ChatGPT-5 may assist with preliminary interpretation of structured park audit data. However, the results do not establish equivalence with expert assessment. Expert review remains necessary to assess feasibility, contextual relevance, and alignment with local planning standards.

BACKGROUND The worldwide rise in the prevalence of noncommunicable diseases has increased the recognition of the need to identify modifiable risk factors for preventing and managing these diseases. The office worker, as a representative group of physically inactive workers, is exposed to risk factors for metabolic syndrome, which is a primary driver of noncommunicable diseases. The use of virtual reality (VR) exergames may offer a potential solution to the problem of increasing noncommunicable disease prevalence, as it can help individuals increase their physical activity levels while providing a more immersive experience. OBJECTIVE This exploratory study aims to examine the interventional efficacy of at-home immersive VR exergames on metabolic syndrome biomarkers among office workers. Additionally, it seeks to investigate the impacts of at-home immersive VR exergames on the active and sedentary behaviors of office workers. METHODS A 3-arm, single-blinded pilot randomized controlled trial will be conducted to examine the therapeutic effects of at-home immersive VR exergames. A total of 120 Chinese office workers, engaging in less than 150 minutes per week of moderate to vigorous intensity physical activity, will be recruited via a convenience sampling method. The participants, who will be tested over a 12-week period, will be randomly assigned to one of three groups: (1) the VR exergame intervention group, (2) the regular physical activity control group, and (3) the nonexercise control group. Throughout the 12-week trial, three categories of variables will be collected across the three groups: clinical risk factors associated with metabolic syndrome, active and sedentary behaviors, and demographics. To analyze variance among the groups, a mixed linear model will be applied to assess the efficacy of each group. Differences in metabolic syndrome clinical risk factors among all groups will be used to evaluate the effects of at-home immersive VR exergames. Changes in active and sedentary behaviors will also be used to determine the impacts of VR exergames on metabolic syndrome. RESULTS The ethics committee of Guangzhou University, China, approved this study on September 25, 2024. Participant recruitment will begin in early 2025 and continue for approximately 3 months. Data will be analyzed after the 12-week trial is completed, with full results expected to be presented in early 2026. CONCLUSIONS This study explores an emerging topic by applying an at-home immersive VR exergame intervention, potentially contributing to understanding the effects of an exergame program on metabolic syndrome risk among office workers. CLINICALTRIAL ClinicalTrials.gov NCT06556784; https://clinicaltrials.gov/study/NCT06556784 INTERNATIONAL REGISTERED REPORT PRR1-10.2196/64560

Background: The worldwide rise in the prevalence of noncommunicable diseases has increased the recognition of the need to identify modifiable risk factors for preventing and managing these diseases. The office worker, as a representative group of physically inactive workers, is exposed to risk factors for metabolic syndrome, which is a primary driver of noncommunicable diseases. The use of virtual reality (VR) exergames may offer a potential solution to the problem of increasing noncommunicable disease prevalence, as it can help individuals increase their physical activity levels while providing a more immersive experience. Objective: This exploratory study aims to examine the interventional efficacy of at-home immersive VR exergames on metabolic syndrome biomarkers among office workers. Additionally, it seeks to investigate the impacts of at-home immersive VR exergames on the active and sedentary behaviors of office workers. Methods: A 3-arm, single-blinded pilot randomized controlled trial will be conducted to examine the therapeutic effects of at-home immersive VR exergames. A total of 120 Chinese office workers, engaging in less than 150 minutes per week of moderate to vigorous intensity physical activity, will be recruited via a convenience sampling method. The participants, who will be tested over a 12-week period, will be randomly assigned to one of three groups: (1) the VR exergame intervention group, (2) the regular physical activity control group, and (3) the nonexercise control group. Throughout the 12-week trial, three categories of variables will be collected across the three groups: clinical risk factors associated with metabolic syndrome, active and sedentary behaviors, and demographics. To analyze variance among the groups, a mixed linear model will be applied to assess the efficacy of each group. Differences in metabolic syndrome clinical risk factors among all groups will be used to evaluate the effects of at-home immersive VR exergames. Changes in active and sedentary behaviors will also be used to determine the impacts of VR exergames on metabolic syndrome. Results: The ethics committee of Guangzhou University, China, approved this study on September 25, 2024. Participant recruitment will begin in early 2025 and continue for approximately 3 months. Data will be analyzed after the 12-week trial is completed, with full results expected to be presented in early 2026. Conclusions: This study explores an emerging topic by applying an at-home immersive VR exergame intervention, potentially contributing to understanding the effects of an exergame program on metabolic syndrome risk among office workers. Trial Registration: ClinicalTrials.gov NCT06556784; https://clinicaltrials.gov/study/NCT06556784 International Registered Report Identifier (IRRID): PRR1-10.2196/64560