Evidence map›Paper›PMID 42386811›Full record

ArticleScientific reports2026

Work autonomy mediates associations between medical AI readiness and well being in a three wave nurse study.

Mei Xie, Junming Xu, Yuexiang Liu, Huimin Su, Quanyi Long, Yuanyuan Zou

Abstract read
In one paragraph

Article in Scientific reports, 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

6 authors.

Mei Xie *Department of Psychology of Developmental and Socialization Processes, Sapienza University of Rome, Rome, Italy.
Junming Xu *Department of Psychosomatic Medicine, Langzhong People's Hospital, Nanchong, China.
Yuexiang LiuDepartment of Addiction Medicine, Shandong Daizhuang Hospital, Jining, China.
Huimin SuDepartment of Internal Medicine II, The Third Affiliated Hospital of Kunming Medical University, Kunming, China.
Quanyi LongSchool of Nursing, Kunming Medical University, Kunming, China.
Yuanyuan ZouDepartment of Neurosciences, Mental Health and Sensory Organs - NESMOS, Sapienza University of Rome, Rome, Italy. yuanyuan.zou@uniroma1.it.

Funding

China Scholarship Council 202207000022China Scholarship Council 202208530084
6 · The paper itself

Abstract

This three-wave longitudinal study aimed to examine how medical artificial intelligence (AI) readiness impacts general well-being among nurses, focusing on the mediating role of work autonomy. The study further investigated potential reciprocal relationships among psychological readiness, motivational control, and well-being over time. A three-wave panel survey was administered at one-month intervals using validated instruments to measure medical AI readiness, perceived work autonomy, and general well-being. Data were collected from both clinical and educational departments of a major teaching hospital affiliated with a medical university in southwestern China, where smart healthcare systems and AI-powered technologies have been widely adopted. The final sample comprised 230 full-time registered nurses, each with at least one year of clinical experience and full participation across all three time points. Structural equation modeling (SEM) was conducted using AMOS 24.0 to test a full longitudinal mediation model. Measurement invariance and cross-lagged panel modeling were applied to assess autoregressive and reciprocal pathways. Indirect effects were examined via bootstrapping with 5,000 resamples and bias-corrected confidence intervals. Medical AI readiness significantly predicted general well-being both directly and indirectly through work autonomy, supporting a partial longitudinal mediation model. Specifically, higher readiness was associated with higher perceived autonomy over time, which in turn predicted higher well-being. Reciprocal pathways also emerged: general well-being predicted subsequent autonomy, and autonomy predicted later changes in AI readiness, indicating a dynamic feedback loop. All model fit indices met accepted thresholds, supporting the proposed structure. This study offers novel longitudinal evidence of a sequential and bidirectional mechanism linking technological readiness, workplace control, and well-being among nurses. Efforts to enhance nurses' readiness for AI integration should consider how perceptions of autonomy affect well-being outcomes and, conversely, how psychological well-being feeds back into motivational orientations and adaptation to innovation. Supportive leadership, inclusive technology design, and autonomy-enhancing strategies may interrupt maladaptive cycles and improve the human experience of digital transformation in healthcare.

Indexed as

Artificial IntelligenceNursesProfessional AutonomyAdultChinaFemaleHumansLongitudinal StudiesMaleMotivationPsychological Well-BeingSurveys and Questionnairesbidirectional effectscross-lagged panel modelgeneral well-beinglongitudinal mediationmedical AI readinessnurseswork autonomy

Identifiers

PMID42386811
PMCPMC13416128

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.