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Updated: Mar 31, 2026

Methodology for Establishing a Community-Wide Life Laboratory for Capturing Unobtrusive and Continuous Remote Activity and Health Data
Published on: July 27, 2018
Mapping health behaviors: Constructing and validating a common-sense taxonomy of health behaviors
Gabriel Nudelman1, Shoshana Shiloh1
1The School of Psychological Sciences, Tel Aviv University, P.O. Box 39040, Tel Aviv 6997801, Israel.
Objective:
Health behaviors (HBs) are major determinants of health, illness, and mortality. Theoretical efforts aimed at understanding their nature and the processes involved in their initiation and maintenance have largely ignored differences among them. Therefore, the objective of this research was to establish a reliable and valid common-sense taxonomy of HBs.
Methods:
The first study created a comprehensive list of 66 HBs based on the views of laypeople (N = 70), health professionals (N = 30), and a literature review. In the second study, a sample of laypeople (N = 268) selected the most important HBs. In the third study, a similarity card-sorting technique was administered to a representative sample (N = 450) in an effort to uncover the structure of HBs. The fourth study replicated the structure (N = 627) and assessed its stability and generalizability.
Results:
A complete list of 66 HBs was developed, of which 45 were judged as most important. Classifications of HBs identified two main categories: psychosocial, including psychological, social, and work issues; and physical, composed of risk avoidance, nutritional habits, and prevention. The hierarchical classification further separated each category into distinguishable clusters and subclusters. The results were replicated, and additional analyses revealed a high level of stability of the taxonomy across different demographic sub-groups.
Conclusions:
The taxonomy can provide a framework for research and a map for program developers looking for meaningful links between specific groups of HBs and particular behavior change techniques. This should optimize the cost-effectiveness of promotion and intervention programs, and thus increase health and decrease health-care burden.
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