Evidence map›Paper›PMID 41737181›Full record

ArticlePakistan journal of medical sciences2026

Artificial Intelligence perception and its influence on the Psychological Distress of Healthcare Professional.

Badr Alnasser, Rakesh Kumar

Abstract read
In one paragraph

Article in Pakistan journal of medical sciences, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Article
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

2 authors.

Badr AlnasserBadr Alnasser, Ph.D., Department of Health Management, College of Public Health and Health Informatics, University of Ha'il, Ha'il, Saudi Arabia.
Rakesh KumarRakesh Kumar, Ph.D., Department of Health Management, College of Public Health and Health Informatics, University of Ha'il, Ha'il, Saudi Arabia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objectives: Th research examines how AI perception (AIP) affect psychological distress of healthcare professional in Kingdom of Saudi Arabia (KSA). The study also investigates the moderating role of technology readiness (TRD). Methodology: This research adopts cross-sectional design. A self-administrative, close ended, survey was used to collect primary data. Total 411 healthcare professionals voluntarily participated from public hospitals of the Hail Health Cluster, in KSA. The survey was carried out through convenience sampling method. Data was processed through SPSS 27 version. Analysis consisted of demographic summary, descriptive analysis and regression analysis through Hayes process. Results: A total of 411 healthcare professionals participated, with the majority being male (60.8%) and aged 36-45 (41.4%). Additionally, the descriptive statistics revealed adequate reliability for all variables including AIP, DASS-21 and TRD. Moreover, the regression analysis showed that AIP significantly influenced DASS-21 ( Conclusion: The study highlights that AI perception significantly impacts psychological distress, particularly Depression and Anxiety, among healthcare professionals. While technology readiness significantly strengthens this relationship. Future research should explore other potential moderating factors, such as organizational support, to further understand the impact of AI perception in healthcare settings.

Indexed as

AI perceptionHealthcare professionalPsychological DistressSaudi ArabiaTechnology Readiness

Identifiers

PMID41737181
PMCPMC12927172

What Socratic 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 Socratic graph.