Evidence map›Paper›PMID 41537090›Full record

ArticleJournal of experimental criminology2025

Does automated feedback impact the acceptability of AI-generated police body worn camera review? An implementation science natural experiment.

Seth Watts, Brandon Del Pozo, Michael D White, Aili Malm

Abstract read
In one paragraph

Article in Journal of experimental criminology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

4 authors.

Seth WattsSchool of Criminal Justice and Criminology, Texas State University, San Marcos, TX, USA.ORCID 0000-0002-5108-9055
Brandon Del PozoThe Warren Alpert Medical School of Brown University Health, Providence, RI, USA.ORCID 0000-0001-6481-2196
Michael D WhiteSchool of Criminology and Criminal Justice, Arizona State University, Phoenix, AZ, USA.
Aili MalmSchool of Criminal Justice and Emergency Management, California State University, Long Beach, Long Beach, CA, USA.ORCID 0000-0001-6059-0258

Funding

Police Diversion to Treatment for Opioid Use Disorder: A Mixed Methods StudyK01DA056654 · NIDA · RHODE ISLAND HOSPITAL · PI Brandon del Pozo · 2022 to 2026
$878k
NIDA NIH HHS K01 DA056654
6 · The paper itself

Abstract

The diffusion of innovations in policing has often been hindered by barriers to implementation and officer acceptance, which can derail an innovation regardless of its validity or effectiveness. Implementation Science (IS) is a useful lens for addressing such concerns because IS empirically examines the way a new technology or strategy is deployed, and it offers insights on barriers, facilitators, and fidelity. The present study uses an IS framework to investigate one of the latest innovations in policing: Artificial Intelligence (AI). In early 2024, two Arizona police departments deployed Truleo, an AI-driven body-worn camera review platform, via randomized controlled trials, but only one of those departments used a feature of Truleo that sends automated positive feedback emails to officers when they engage in behaviors assessed as "highly professional" by the AI algorithm. Using cross-sectional survey data from line-level officers (

Identifiers

PMID41537090
PMCPMC12798756

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.