Evidence map›Paper›PMID 42495218›Full record

ArticleFrontiers in psychology2026

AI-enabled instructor care and physical fitness performance in police cadets: the mediating roles of emotions, engagement, and recovery.

Zeyu Zhang, Mahpiret Kanji, Xiaomei Lu

Abstract read
In one paragraph

Article in Frontiers in psychology, 2026. 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

3 authors.

Zeyu ZhangJudicial Police College, Xinjiang University of Political Science and Law, Urumqi, China.
Mahpiret KanjiXinjiang Key Laboratory of Mental Development and Learning Science, Xinjiang Normal University, Urumqi, China.
Xiaomei LuHospital of Sihong, Suqian, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Police training is physically demanding and psychologically stressful, which may undermine training adaptation and physical performance. Artificial intelligence (AI)-supported learning analytics systems have been proposed as scalable tools to support training management, yet empirical evidence remains limited regarding how such systems may operate when embedded in human instructor care practices. Methods: We conducted a quasi-experimental pre-post study among police cadets ( Results: DID estimates indicated a significant net improvement in physical fitness performance in the AI-enabled instructor care condition ( Conclusion: AI-supported instructor care may represent a low-risk and scalable approach to supporting physical training performance in high-stress educational settings. The findings provide quasi-experimental evidence consistent with an intervention effect, while the mediation results should be interpreted as exploratory evidence of associated psychological and recovery-related pathways.

Indexed as

affective processesAI-supported careburnoutphysical fitness performancepolice trainingsleep qualitytraining engagement

Identifiers

PMID42495218
PMCPMC13391276

What OpenQuestion holds

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LicenceCC BY
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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.