ArticleBMJ open sport & exercise medicine2024
Exploring individual, social and environmental factors related to physical activity: a network analysis.
Article in BMJ open sport & exercise medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
4 citing papers in PubMed.
- Exploring Response Patterns to Motivational Messages Supporting Physical Activity: Latent Class Analysis.JMIR human factors · 2026Article
- Examining the Factor Structure of Objective Health Literacy and Numeracy Scales: Large-Scale Cross-Sectional Study.JMIR public health and surveillance · 2026Article
- The impact of neighborhood environment on physical activity among older adults: chain mediating roles of self-efficacy and outcome expectations.Frontiers in aging neuroscience · 2025Article
- Evaluating the performance of personality-based profiling in predicting physical activity.BMC psychology · 2024Article
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objectives: Insufficient physical activity (PA) has long been a global health issue, and a number of studies have explored correlates of PA to identify the mechanisms underlying inactive lifestyles. In the literature, dozens of correlates have been identified at different (eg, individual, environmental) levels, but there is little or no direct evidence for the mutual associations of these correlates. This study analysed 44 variables identified as theoretically and empirically relevant for PA to clarify the factors directly and indirectly associated with PA. Methods: A cross-sectional survey dataset of 19 005 Japanese-speaking adults (mean age=53.50 years, SD=17.40; 9706 women) was analysed. The data encompassed demographic and anthropometric variables; self-reported PA levels; perceived social support and environments (eg, awareness of urban facilities for PA); psychological traits and health-behaviour characteristics (eg, personality, motivation, self-efficacy, decisional balance, process of change strategies); and technology use (eg, mobile health apps). Results: Network analyses were performed to select meaningful associations (partial correlations) among variables, which identified nine variables directly positively associated with PA: job/employment status, self-efficacy, perceived social support, intrinsic motivation, stage of change, counter conditioning, self-reevaluation, environment and technology use. Indirect associations (two-step neighbourhood) were identified for 40 (out of 44) variables, implying that most of the known PA-correlates are associated with PA-at least indirectly. Conclusion: These identified associations echo the importance of the multilevel perspective in understanding how people maintain (in)active lifestyles. Interventions for PA could have mixed-level targets, including intraindividual characteristics, social support and physical and digital environments.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.