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Development of a Police Officer Stress Algorithm to Prevent Adverse Events: A Mixed-Methods Approach



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  • Personal Author:
  • Description:
    During this award, Dr. Katelyn Jetelina was an Assistant Professor in the Department of Epidemiology at the University of Texas Health Science Center, School of Public Health. She had three years of funding (with one additional no cost extension year) through the Mentored Research Scientist Development Award (K01). Dr. Jetelina conducts research in examining the acute and chronic stresses of law enforcement by evaluating the effects of reactive outcomes, like coping mechanisms and excessive use-of-force, on officer health and safety. This area of study is significant due to the recent, highly visible concern that has largely framed reactive outcomes as police mismanagement rather than occupational health. Dr. Jetelina's long-term career goals are to become an independent investigator and mixed methods expert, and to develop a system-level intervention to reduce rates of police officer and citizen injury. Dr. Jetelina accomplished five short-term goals throughout the award period that linked her quantitative skills to new methodological techniques. These were: 1) Accumulated a strong knowledge base in qualitative methodology; 2) Gained formal training in mixed-methods design; 3) Learned the appropriate techniques and processes for stakeholder engagement; 4) Extended her current knowledge of officer health to community police based training; and 5) Oriented herself with the science of team science. These goals were achieved through a combination of mentoring by a multi-disciplinary team of established researchers, attendance at national workshops and conferences, focused coursework, and the awarded study. The research plan sought to contribute to the NORA Sector: Public Safety, Cross-sector: Traumatic Injury Prevention, and Strategic Goal 5: Evaluate information sources collected by stakeholders that may be enhanced to conduct effective occupational health and safety surveillance among law enforcement workers. This study identified predisposing multi-dimensional factors that converged to create high-stress calls for Dallas Police Department (DPD) officers using a mixed-methods design. Specifically, her completed aims were: 1) To identify themes associated with consecutive high-stress calls and current stress decompression techniques through structured observations, focus groups, and distributing a stress survey among DPD officers; 2) To build a multi-level database that will classify calls for service on a stress continuum scale by triangulating new and pre-existing data from multiple DPD sources; and 3) To test the predictive capability of the integrated database, by evaluating statistical relationships between multi-level factors and adverse events (e.g. injury). Identifying predictors that contributed the greatest to high-stress calls was instrumental to inform a R01 application where Dr. Jetelina proposed to improve the mental illness of officers, which would consider compound stress of a police officer's shift and evaluate whether it reduces the likelihood of officer (and citizen) injury. [Description provided by NIOSH]
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  • Pages in Document:
    1-26
  • NIOSHTIC Number:
    nn:20066913
  • Citation:
    Atlanta, GA: U.S. Department of Health and Human Services, Public Health Service, Centers for Disease Control and Prevention, National Institute for Occupational Safety and Health, K01-OH-011532, 2022 Sep; :1-26
  • Contact Point Address:
    Katelyn Jetelina, MPH PhD, Principal Investigator, The University of Texas Health Science Center at Houston (UTHealth), PO Box 20036, Houston, Texas 77225-0036
  • Email:
    Katelyn.k.jetelina@uth.tmc.edu
  • Federal Fiscal Year:
    2022
  • NORA Priority Area:
  • Performing Organization:
    University of Texas Health Science Center, Houston
  • Peer Reviewed:
    False
  • Start Date:
    20180901
  • Source Full Name:
    National Institute for Occupational Safety and Health
  • End Date:
    20210831
  • Collection(s):
  • Main Document Checksum:
    urn:sha-512:fbefac4c7636c1fdd36e1f07e05b66f21d0505c801cce19bc36a7454658eb42c8c22b90450835c12d87d9edebbd9211b0615c8ea350ac4d8ec34b86525671c10
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  • File Type:
    Filetype[PDF - 4.33 MB ]
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