Workplace Well-Being Factors That Predict Employee Participation, Health and Medical Cost Impact, and Perceived Support

Purpose: This study tested relationships between health and well-being best practices and 3 types of outcomes. Design: A cross-sectional design used data from the HERO Scorecard Benchmark Database. Setting: Data were voluntarily provided by employers who submitted web-based survey responses. Sample:...

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Bibliographic Details
Published in:American journal of health promotion 2020-05, Vol.34 (4), p.349-358
Main Authors: Grossmeier, Jessica, Castle, Patricia H., Pitts, Jennifer S., Saringer, Colleen, Jenkins, Kristi Rahrig, Imboden, Mary T., Mangen, David J., Johnson, Sara S., Noeldner, Steven P., Mason, Shawn T.
Format: Article
Language:English
Subjects:
Age Factors
Best practice
Cross-Sectional Studies
Employee involvement
Health promotion
Health Promotion - organization & administration
Health technology assessment
Humans
Incentives
Internet
Leadership
Medical screening
Motivation
Occupational Health
Organizational support
Patient Participation
Perceptions
Residence Characteristics
Sex Factors
Structural equation modeling
Well being
Workplace
Workplaces
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Summary:Purpose: This study tested relationships between health and well-being best practices and 3 types of outcomes. Design: A cross-sectional design used data from the HERO Scorecard Benchmark Database. Setting: Data were voluntarily provided by employers who submitted web-based survey responses. Sample: Analyses were limited to 812 organizations that completed the HERO Scorecard between January 12, 2015 and October 2, 2017. Measures: Independent variables included organizational and leadership support, program comprehensiveness, program integration, and incentives. Dependent variables included participation rates, health and medical cost impact, and perceptions of organizational support. Analysis: Three structural equation models were developed to investigate the relationships among study variables. Results: Model sample size varied based on organizationally reported outcomes. All models fit the data well (comparative fit index > 0.96). Organizational and leadership support was the strongest predictor (P < .05) of participation (n = 276 organizations), impact (n = 160 organizations), and perceived organizational support (n = 143 organizations). Incentives predicted participation in health assessment and biometric screening (P < .05). Program comprehensiveness and program integration were not significant predictors (P > .05) in any of the models. Conclusion: Organizational and leadership support practices are essential to produce participation, health and medical cost impact, and perceptions of organizational support. While incentives influence participation, they are likely insufficient to yield downstream outcomes. The overall study design limits the ability to make causal inferences from the data.
ISSN:0890-1171
2168-6602
DOI:10.1177/0890117119898613