Evidence map›Paper›PMID 28314707›Full record

ArticleJMIR research protocols2017

Biometrics and Policing: A Protocol for Multichannel Sensor Data Collection and Exploratory Analysis of Contextualized Psychophysiological Response During Law Enforcement Operations.

Robert D Furberg, Travis Taniguchi, Brian Aagaard, Alexa M Ortiz, Meghan Hegarty-Craver, Kristin H Gilchrist, Ty A Ridenour

Open access · goldAbstract read
In one paragraph

Article in JMIR research protocols, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
11.3field-weighted citation impact, top 2% 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

4 citing papers in PubMed, 22 citations in OpenAlex.

  1. A computational model for adaptive recording of vital signs through context histories.Journal of ambient intelligence and humanized computing · 2021
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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

7 authors at 1 institution in 1 country.

Robert D FurbergDigital Health & Clinical Informatics, RTI International, Research Triangle Park, NC, United States.ORCID http://orcid.org/0000-0002-3803-1879
Travis TaniguchiPolicing Research Program, RTI International, Research Triangle Park, NC, United States.ORCID http://orcid.org/0000-0003-2040-1330
Brian AagaardPolicing Research Program, RTI International, Research Triangle Park, NC, United States.ORCID http://orcid.org/0000-0001-9290-6165
Alexa M OrtizDigital Health & Clinical Informatics, RTI International, Research Triangle Park, NC, United States.ORCID http://orcid.org/0000-0002-8121-1250
Meghan Hegarty-CraverEngineered Materials, Devices and Systems, RTI International, Research Triangle Park, NC, United States.ORCID http://orcid.org/0000-0002-0919-6906
Kristin H GilchristEngineered Materials, Devices and Systems, RTI International, Research Triangle Park, NC, United States.ORCID http://orcid.org/0000-0003-3584-9832
Ty A RidenourBehavioral & Urban Health Program, RTI International, Research Triangle Park, NC, United States.ORCID http://orcid.org/0000-0002-9709-6808
RTI International · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundStress experienced by law enforcement officers is often extreme and is in many ways unique among professions. Although past research on officer stress is informative, it is limited, and most studies measure stress using self-report questionnaires or observational studies that have limited generalizability. We know of no research studies that have attempted to track direct physiological stress responses in high fidelity, especially within an operational police setting. The outcome of this project will have an impact on both practitioners and policing researchers. To do so, we will establish a capacity to obtain complex, multisensor data; process complex datasets; and establish the methods needed to conduct idiopathic clinical trials on behavioral interventions in similar contexts.

objectiveThe objective of this pilot study is to demonstrate the practicality and utility of wrist-worn biometric sensor-based research in a law enforcement agency.

methodsWe will use nonprobability convenience-based sampling to recruit 2-3 participants from the police department in Durham, North Carolina, USA.

resultsData collection was conducted in 2016. We will analyze data in early 2017 and disseminate our results via peer reviewed publications in late 2017.

conclusionsWe developed the Biometrics & Policing Demonstration project to provide a proof of concept on collecting biometric data in a law enforcement setting. This effort will enable us to (1) address the regulatory approvals needed to collect data, including human participant considerations, (2) demonstrate the ability to use biometric tracking technology in a policing setting, (3) link biometric data to law enforcement data, and (4) explore project results for law enforcement policy and training.

Indexed as

clinical trialdigital healthlaw enforcementpsychophysiologysensor, wearable

Identifiers

PMID28314707
PMCPMC5375974
OpenAlexW2596963603

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.