Jin Lee, Ph. D.
Office: BH 467
Dr. Lee’s research focus is primarily on workplace safety, health, and well-being. Specifically, he holds research interests in safety climate assessment and management in high-risk industries, analysis of risk perception styles of temporary workers, work system improvement through the perspectives of macroergonomics and Total Worker Health™, and application of advanced quantitative methodology in multidisciplinary research efforts. Currently, he is a principal investigator for a project about the design of safety climate intervention based on socio-technical systems approach. Also, he is interested in data visualization and application of machine learning approaches to I/O psychology. More information is available at Dr. Lee's laboratory web page.
Principal Investigator (June 2015 – Present) / Project title: Improving Corporate Safety Climate - Review and Recommendations for Interventions Based on a Systems Approach (LMRIS 15-09; Liberty Mutual Research Institute for Safety, Hopkinton, MA, USA)
Dr. Lee supervises and collaborates with graduate students in the industrial and organizational psychology graduate program. Students attend weekly laboratory meetings to develop research ideas and learn knowledge and skills for occupational safety and health research. In his lab, opportunities to learn about management and analysis of data, grant proposal writing, and publication of the research results will be offered. Ultimately, students will be prepared as independent applied psychology researcher. More information about research opportunities in his lab can be obtained by contacting him (email@example.com).
Current Graduate Students
Frank Giordano (since 2016 Fall)
Stacy Stoffregen (since 2016 Fall)
Huang, Y. H., Lee, J., McFadden, A. C., Rineer, J., & Robertson, M. M. (2017). Individual Employee's Perceptions of "Group-Level Safety Climate" (Supervisor Referenced) versus "Organization-Level Safety Climate" (Top Management Referenced): Associations with Safety Outcomes for Lone Workers. Accident Analysis and Prevention.98, 37-45.
Zohar, D. & Lee, J. (2016). Testing the effects of safety climate and disruptive children behavior on school bus drivers performance: A multilevel model. Accident Analysis and Prevention, 95, 116-124.
Huang, Y., Lee, J., McFadden, A. C., Murphy, L. A., Robertson, M. M., Cheung, J. H., & Zohar, D. (2016). Beyond safety outcomes: An investigation of the impact of safety climate on job satisfaction, employee engagement and turnover using social exchange theory as the theoretical framework. Applied Ergonomics, 55, 248-257.
Lee, J., Huang, Y. H., Murphy, L. A., Robertson, M. M., & Garabet, A. (2016). Measurement equivalence of a safety climate scale across multiple trucking companies, Journal of Occupational and Organizational Psychology, 89(2), 352-376.
Zohar, D., Huang, Y. H., Lee, J., & Robertson, M. M. (2015). Testing extrinsic and intrinsic motivation as explanatory variables for the safety climate-safety performance relationship among long-haul truck drivers. Transportation Research Part F: Traffic Psychology and Behavior, 30, 84-96.
Huang, Y. H., Robertson, M. M., Lee, J., Rineer, J., Murphy, L. A., Garabet, A., & Dainoff, M. J. (2014). Supervisory interpretation of safety climate versus employee safety climate perception: Association with safety behavior and outcomes for lone workers. Transportation Research Part F: Traffic Psychology and Behavior, 26, 348-360.
Lee, J., Huang, Y. H., Robertson, M. M., Murphy, L. A., Garabet, A., & Chang, W. R. (2014). External validity of a generic safety climate scale for lone workers across different industries and companies. Accident Analysis and Prevention, 63, 138-145.
Zohar, D., Huang, Y. H., Lee, J., & Robertson, M. M. (2014). A mediation model linking supervisory leadership and work ownership with safety climate as predictors of truck driver safety performance. Accident Analysis and Prevention, 62, 17-25.
Huang, Y. H., Zohar, D., Robertson, M. M., Garabet, A., Murphy, L. A. & Lee, J. (2013). Development and validation of safety climate scales for remote workers using utility/electric workers as exemplar. Accident Analysis and Prevention, 59, 76-86.