Identifying Restorative Environments for Employees’ Recovery

An Interdisciplinary Mixed Methods Approach

Bibliographic Data

ID7993259
AuthorsMicha Hilbert (0000-0003-2214-0349, University of Münster, corresponding author), Carmen Binnewies (0000-0001-7687-6410, University of Münster), Laura Berkemeyer (0000-0002-9619-7148, University of Münster)
Year2023
Volume47
Issue6
Pages1198-1217
Publication date2023-04-17
Peer ReviewedYes
Open AccessNo
TypeARTICLE
VenueLeisure Sciences (JOURNAL)
Journal identifiersISSN: 0149-0400 • E-ISSN: 1521-0588
PublisherTaylor & Francis (PUBLISHER • GB)
DOI10.1080/01490400.2023.2201243
OpenAlexW4366223023
LanguageEN
References cited63

In this paper, we developed an environmental demands-resources (ED-R) model to explain which environments are restorative for employees during leisure based on the job demands-resources model. We used a mixed methods approach combining semi-structured interviews built upon the critical incident technique and psychometric questionnaires. In total, we gathered 100 different incidents in restorative and stressful environments from 29 participants. Following Mayring's qualitative content analysis, we identified natural, residential, and attractive artificial environments as restorative. Logistic multilevel modeling and Fisher's exact tests revealed that restorative environments contain fewer environmental demands (e.g., noise) and more environmental resources (e.g., water elements) than stressful environments. In addition, restorative environments were related to higher psychological detachment from work and relaxation compared to stressful environments. The results support our ED-R model and have practical implications for spatial design at the public, organizational, and individual level. Further theoretical extensions of our ED-R model were discussed

Work (physics · Applied Psychology · Computer Science · Engineering · Place Attachment and Urban Studies · Psychology · Urban Green Space and Health · Urban Heat Island Mitigation

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