Evidence map›Paper›PMID 40103878›Full record

ArticlePakistan journal of medical sciences2025

Unlocking the Power of AI: Healthcare Workforce Perception and Its Impact on their Work Performance in Saudi Arabia.

Rakesh Kumar, Ajay Singh, Ahmed Subahi Ahmed Kassar, Mohammed Ismail Humaida, Sudhanshu Joshi, Manu Sharma

Abstract read
In one paragraph

Article in Pakistan journal of medical sciences, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

6 authors.

Rakesh KumarRakesh Kumar, PhD Department of Health Management, College of Public Health and Health Informatics, University of Hail, Saudi Arabia.
Ajay SinghAjay Singh, PhD Department of Management & Information Systems, College of Business Administration, University of Hail, Saudi Arabia.
Ahmed Subahi Ahmed KassarAhmed Subahi Ahmed Kassar, PhD Department of Public Health, College of Public Health and Health Informatics, University of Hail, Saudi Arabia.
Mohammed Ismail HumaidaMohammed Ismail Humaida, PhD Department of Public Health, College of Public Health and Health Informatics, University of Hail, Saudi Arabia.
Sudhanshu JoshiSudhanshu Joshi, PhD School of Management, Doon University, Dehradun, Uttarakhand, India.
Manu SharmaManu Sharma, PhD Department of Management Studies, Graphic Era University, Dehradun, Uttarakhand, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: To investigate the perception of AI among the healthcare workforce and its impact on their performance, with technology readiness acting as a moderating factor. Methods: In this cross-sectional study, a close-ended, self-administered survey questionnaire was used between 02 June to 04 August, 2024 to collect responses from 434 participants working in the public hospitals in Hail health cluster in Saudi Arabia. The study employed demographic summaries, descriptive statistics, regression analysis using Hayes' Process, and regression diagnostics for data analysis. The data were analyzed using SPSS version 27. Results: The participant demographics indicated a majority of male respondents from the medical field, primarily aged between 36-45 years. Most participants had 9-10 or more years of experience in their current position and held graduate degrees in the healthcare sector of Saudi Arabia. Regression analysis using Hayes' Process showed an insignificant negative impact of AI perception on workforce performance (β_1 = -0.0062, p = .315). However, technology readiness significantly moderated this effect, turning it into a positive and significant impact (β_3 = 0.2512, p = .0209). Conclusion: The study demonstrates that while AI perception alone has a negligible effect on workforce performance, its influence becomes significant when moderated by higher levels of technology readiness. Future research should examine how factors such as organizational culture and resource availability influence AI perceptions in healthcare.

Indexed as

Artificial IntelligenceHealthcareSaudi ArabiaTechnology ReadinessWorkforce Performance

Identifiers

PMID40103878
PMCPMC11911756

What OpenQuestion 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 OpenQuestion graph.