Abstract
Objectives: This study adopts the International Classification of Functioning, Disability and Health (ICF) model to determine extent to which the clustered patterns of long-term care (LTC) environment and activity participation are associated with older residents’ mental health.
Method: This study enrolled a stratified equal probability sample of 634 older residents in 155 LTC institutions in Taiwan. Latent profile analysis and latent class analysis were conducted to explore the profiles for environment and activity participation. Multilevel modeling was performed to elucidate the hypothesized relationships.
Results: Three environment profiles (Low-, Moderate-, and High-Support Environment) based on physical, social, and attitudinal environment domains and two activity profiles (Low- and High-Activity Participation) across seven activity domains were identified. Compared to the Low-Support class, older adults in the Moderate- and High-Support Environment classes had better mental health. Older residents in those two classes were more likely to be in the “High Activity Participation” class, which in turn, exhibited better mental health.
Conclusion: Environment and activity participation directly relate to older residents’ mental health. Activity participation also mediates the link between environment and mental health. A combination of enhanced physical, social, and attitudinal environments, and continual engagement in various activities may optimize older LTC residents’ mental health.
Acknowledgement
The authors would like to like to thank the Ministry of Science and Technology, Taiwan for supporting this research under contract No. MOST 101-2410-H-002-215-SS2. The authors would also like to thank three anonymous reviewers for their valuable comments in the earlier draft.
Disclosure statement
No potential conflict of interest was reported by the authors.
Funding
This work was supported by the Ministry of Science and Technology, Taiwan for supporting this research under Grant No. MOST 101-2410-H-002-215-SS2.