ArticleFrontiers in public health2026
Predictors of user satisfaction with forest healing services differ by health status.
Article in Frontiers in public health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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3 authors.
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Abstract
Objective: Forest healing is increasingly recognized as a public health resource; however, empirical evidence remains limited on how the predictors of service satisfaction vary across users with different health profiles. This study investigated health-status-specific predictors of satisfaction with forest healing services across Korea's national Healing Forest sites. Methods: A cross-sectional survey was conducted among participants from 20 Healing Forest sites. Respondents were categorized into no-disease, single-disease, and multimorbidity groups based on self-reported chronic conditions. Multiple regression analyses were performed to examine factors associated with overall satisfaction within each health status group. Results: Program structure, perceived usefulness of activities, and instructor expertise significantly predicted satisfaction across all groups, with relative contributions varying by health status: program structure was most influential for those without disease, activity usefulness for those with a single disease, and instructor expertise for participants with multimorbidity. The forest environment received uniformly high ratings across all groups, suggesting environmental comfort functions as a necessary but non-differentiating condition. Overall satisfaction and most service-specific domains did not differ significantly across health status groups; information sufficiency and equipment appropriateness were the only domains showing statistically significant group differences, though effect sizes were negligible, reflecting different informational needs and perceived burdens across groups. Conclusion: The predictors of overall satisfaction with forest healing services differ by health status, highlighting the importance of differentiated, health-status-sensitive service models tailored to users' functional capacities and diverse disease burdens.
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