Evidence mapPaperPMID 41550736Full record

ArticleiScience2026

Exploring the impact of AI technostress on physicians' job insecurity and performance from an empirical multi-hospital study.

Chung-Feng Liu, Tzu-Chi Lin, Yen-Ling Ko

Abstract read
In one paragraph

Article in iScience, 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

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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.

Chung-Feng LiuDepartment of Medical Research, Chi Mei Medical Center, Tainan 710402, Taiwan.
Tzu-Chi LinDepartment of Nursing, Chi Mei Medical Center, Liouying, Tainan 73657, Taiwan.
Yen-Ling KoDepartment of Internal Medicine, Chi Mei Medical Center, Tainan 710402, Taiwan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study expands Califf's technostress model, which explores the psychological stress caused by technology, by integrating "perceived self-esteem threat" as a key stressor driven by the growing influence of medical artificial intelligence (AI), examining its impact on physicians' job insecurity and performance. A survey of 400 physicians from three Taiwanese hospitals (92.4% response rate) revealed the nuanced effects of AI-related technostress. Structural equation modeling (SEM), a statistical method used to test relationships between variables, showed that complexity and technology overload significantly increase job insecurity, while AI reliability, unexpectedly, also heightens it. AI self-esteem threat emerged as the most influential source of technostress. Job insecurity negatively affects job satisfaction but unexpectedly boosts job performance, suggesting a motivational response to perceived threats. The expanded model explains 44.6% of the variance in psychological reactions to AI, underscoring the critical role of self-esteem threat in shaping physicians' well-being and performance.

Indexed as

Health sciencesSocial sciences

Identifiers

PMID41550736
PMCPMC12811485

What Socratic holds

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Registered trials

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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 Socratic graph.