BACKGROUND: Effective policy implementation is essential for a healthy workplace. The Ryan-Kossek 2008 model for work-life policy adoption suggests that supervisors as gatekeepers between employer and employee need to know how to support and communicate benefit regulations. This article describes a workplace intervention on a national employee benefit, Family and Medical Leave Act (FMLA), and evaluates the effectiveness of the intervention on supervisor knowledge, awareness, and experience with FMLA. METHODS: The intervention consisted of computer-based training (CBT) and a survey measuring awareness and experience with FMLA. The training was administered to 793 county government supervisors in the state of Oregon, USA. RESULTS: More than 35% of supervisors reported no previous training on FMLA and the training pre-test revealed a lack of knowledge regarding benefit coverage and employer responsibilities. The CBT achieved: (1) a significant learning effect and large effect size of d = 2.0, (2) a positive reaction to the training and its design, and (3) evidence of increased knowledge and awareness regarding FMLA. CONCLUSION: CBT is an effective strategy to increase supervisors' knowledge and awareness to support policy implementation. The lack of supervisor training and knowledge of an important but complex employee benefit exposes a serious impediment to effective policy implementation and may lead to negative outcomes for the organization and the employee, supporting the Ryan-Kossek model. The results further demonstrate that long-time employees need supplementary training on complex workplace policies such as FMLA.
Humans ; Learning ; Local Government ; Oregon ; Social Control, Formal

BACKGROUND: In a cluster-randomized trial, the Safety and Health Involvement For Truck drivers intervention produced statistically significant and medically meaningful weight loss at 6 months (−3.31 kg between-group difference). The current manuscript evaluates the relative impact of intervention components on study outcomes among participants in the intervention condition who reported for a postintervention health assessment (n = 134) to encourage the adoption of effective tactics and inform future replications, tailoring, and enhancements. METHODS: The Safety and Health Involvement For Truck drivers intervention was implemented in a Web-based computer and smartphone-accessible format and included a group weight loss competition and body weight and behavioral self-monitoring with feedback, computer-based training, and motivational interviewing. Indices were calculated to reflect engagement patterns for these components, and generalized linear models quantified predictive relationships between participation in intervention components and outcomes. RESULTS: Participants who completed the full program-defined dose of the intervention had significantly greater weight loss than those who did not. Behavioral self-monitoring, computer-based training, and health coaching were significant predictors of dietary changes, whereas behavioral and body weight self-monitoring was the only significant predictor of changes in physical activity. Behavioral and body weight self-monitoring was the strongest predictor of weight loss. CONCLUSION: Web-based self-monitoring of body weight and health behaviors was a particularly impactful tactic in our mobile health intervention. Findings advance the science of behavior change in mobile health intervention delivery and inform the development of health programs for dispersed populations.
Body Weight ; Health Behavior ; Linear Models ; Motivational Interviewing ; Motor Activity ; Motor Vehicles ; Occupational Health ; Telemedicine ; Weight Loss