When Workplace Wellness Programs Work: Lessons Learned from a Large Employer in Texas

ABSTRACT

Background: Workplace wellness programs have been widely implemented to promote employee health outcomes and reduce health costs. However, little is known about how designs of wellness programs matter for best promoting positive employee health outcomes. Purpose: This research aims to identify the most effective designs of workplace wellness programs resulting in positive employee health outcomes. Methods: We conducted endogenous treatment analyses to compare the effectiveness of three wellness programs (diabetes prevention, hypertension prevention, and nutrition classes) on employees’ health outcomes. Data were analyzed from 24,117 full-time employees who received the pre- and post-intervention biometric screening in 2012–2016 at a large employer in Texas, U.S. Results: Unlike the mixed effects in diabetes and hypertension prevention programs, the nutrition program, which exhibited a high level of topic relevance, impact, and intensity, significantly decreases all four biometric indicators: decreasing systolic blood pressure (4%), diastolic blood pressure (10%), glucose (2%), and cholesterol (26%), which improves health outcomes. Discussion: This study prompts health educators to consider comparative effectiveness of workplace wellness programs for maximized impact on employees’ health outcomes. Translation to Health Education Practice: Designing wellness programs with high topic relevance, impact, and intensity should be emphasized in implementing workplace wellness programs.

Acknowledgments

The authors wish to acknowledge the Research Coordinator, Melissa Shaffer, for administrative assistance for conducting this research, and the Senior Research Assistant, Jacob Kolman, for technical assistance on manuscript formatting and clarity.

Disclosure statement

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Additional information

Funding

This material is based upon work supported by the National Science Foundation under Grant No. IIP - 1361509. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.