Evidence map›Paper›PMID 34991537›Full record

ArticleBMC public health2022

Acceptability of a real-time notification of stress and access to self-help therapies among law enforcement officers.

Katelyn K Jetelina, Rebecca Molsberry, Lauren Malthaner, Alaina Beauchamp, M Brad Cannell, Trina Hall, Ed Fowler, Lonzo Anderson

Open access · goldAbstract read
In one paragraph

Article in BMC public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed, 1 pooled it
0.8field-weighted citation impact, top 27% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed, 1 synthesis or guideline pooled it, 7 citations in OpenAlex.

  1. Pooled it
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors at 1 institution in 1 country.

Katelyn K JetelinaDepartment of Epidemiology, Human Genetics, and Environmental Sciences, University of Texas Health Science Center at Houston, School of Public Health, 6011 Harry Hines Blvd, Dallas, TX, USA. Katelyn.k.jetelina@uth.tmc.edu.
Rebecca MolsberryDepartment of Epidemiology, Human Genetics, and Environmental Sciences, University of Texas Health Science Center at Houston, School of Public Health, 6011 Harry Hines Blvd, Dallas, TX, USA.
Lauren MalthanerDepartment of Epidemiology, Human Genetics, and Environmental Sciences, University of Texas Health Science Center at Houston, School of Public Health, 6011 Harry Hines Blvd, Dallas, TX, USA.
Alaina BeauchampDepartment of Epidemiology, Human Genetics, and Environmental Sciences, University of Texas Health Science Center at Houston, School of Public Health, 6011 Harry Hines Blvd, Dallas, TX, USA.
M Brad CannellDepartment of Epidemiology, Human Genetics, and Environmental Sciences, University of Texas Health Science Center at Houston, School of Public Health, 6011 Harry Hines Blvd, Dallas, TX, USA.
Trina HallDallas Police Department, Dallas, TX, USA.
Ed FowlerRockwall Police Department, Rockwall, TX, USA.
Lonzo AndersonDallas Police Department, Dallas, TX, USA.
The University of Texas Health Science Center at Houston · US

Funding

Southwest Center for Occupational and Environmental HealthT42OH008421 · OH · UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON · PI FELKNOR, SARAH A. · 2005 to 2024
$24.1M
NIOSH CDC HHS T42 OH008421
6 · The paper itself

Abstract

backgroundLaw enforcement officers (LEOs) are exposed to chronic stress throughout the course of their shift, which increases the risk of adverse events. Although there have been studies targeting LEO safety through enhanced training or expanded equipment provisions, there has been little attempt to leverage personal technology in the field to provide real-time notification of LEO stress. This study tests the acceptability of implementing of a brief, smart watch intervention to alleviate stress among LEOs.

methodsWe assigned smart watches to 22 patrol LEOs across two police departments: one suburban department and one large, urban department. At baseline, we measured participants' resting heart rates (RHR), activated their watches, and educated them on brief wellness interventions in the field. LEOs were instructed to wear the watch during the entirety of their shift for 30 calendar days. When LEO's heart rate or stress continuum reached the predetermined threshold for more than 10 min, the watch notified LEOs, in real time, of two stress reduction interventions: [1] a 1-min, guided breathing exercise; and [2] A Calm app, which provided a mix of guided meditations and mindfulness exercises for LEOs needing a longer decompression period. After the study period, participants were invited for semi-structured interviews to elucidate intervention components. Qualitative data were analyzed using an immersion-crystallization approach.

resultsLEOs reported three particularly useful intervention components: 1) a vibration notification when hearts rates remained high, although receipt of a notification was highly variable; 2) visualization of their heart rate and stress continuum in real time; and, 3) breathing exercises. The most frequently reported type of call for service when the watch vibrated was when a weapon was involved or when a LEO was in pursuit of a murder suspect/hostage. LEOs also recollected that their watch vibrated while reading dispatch notes or while on their way to work.

conclusionsA smart watch can deliver access to brief wellness interventions in the field in a manner that is both feasible and acceptable to LEOs.

Indexed as

ExercisePoliceHumansLaw EnforcementMental healthPoliceSmart watchStressTechnology

Identifiers

PMID34991537
PMCPMC8740346
OpenAlexW4225302839

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.