# Development of a police officer stress algorithm to prevent adverse events: A mixed-methods approach

> **NIH ALLCDC K01** · UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON · 2020 · $93,999

## Abstract

PROJECT SUMMARY
 Dr. Katelyn Jetelina is a postdoctoral Research Associate in the Department of Epidemiology at the
University of Texas, School of Public Health. She is seeking three years of funding 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 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 and safety. Dr. Jetelina’s long-term career goals are to become an independent investigator and a mixed-
methods expert, and to develop a system-level intervention to reduce rates of police officer and citizen injury.
 In the current proposal, Dr. Jetelina outlines five short-term goals to be achieved throughout the award
period that are intended to link her quantitative skills to new methodological techniques. These are: 1) to
accumulate a strong knowledge base in qualitative methodology; 2) to gain formal training in mixed-methods
design; 3) to learn the appropriate techniques and processes for stakeholder engagement; 4) to extend her
current knowledge of officer health to community police based training; and 5) to orient herself with the
science of team science. These goals will be achieved through a combination of mentoring by a multi-
disciplinary team of established researchers, attendance at national workshops and conferences, focused
coursework, and the proposed study.
 The proposed research plan seeks 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 will identify
predisposing multi-dimensional factors that converge to create high-stress calls for Dallas Police Department
(DPD) officers using a mixed-methods design. Specifically, the aims are: 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
contribute the greatest to high-stress calls is instrumental to inform a R01 application where Dr. Jetelina will
develop a new computer-assisted dispatch system, which would take into account compound stress of a police
officer’s shift and ...

## Key facts

- **NIH application ID:** 9942345
- **Project number:** 5K01OH011532-03
- **Recipient organization:** UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON
- **Principal Investigator:** Katelyn K Jetelina
- **Activity code:** K01 (R01, R21, SBIR, etc.)
- **Funding institute:** ALLCDC
- **Fiscal year:** 2020
- **Award amount:** $93,999
- **Award type:** 5
- **Project period:** 2018-09-01 → 2021-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9942345

## Citation

> US National Institutes of Health, RePORTER application 9942345, Development of a police officer stress algorithm to prevent adverse events: A mixed-methods approach (5K01OH011532-03). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/9942345. Licensed CC0.

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