Perceptions, Preparedness, and Challenges of Artificial Intelligence Integration in Government Healthcare Institutions in Al Buraimi Governorate, Oman: A Cross‑Sectional Study

  1. Ali Saif Sulieman Al-Bahri
  2. Badryia Saif Sulireman Al-Bahri
  3. Yasmine Mahmoud Ali Al-Kalbaniyah

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Abstract

Background: Artificial Intelligence (AI) is increasingly positioned as a catalyst for improving clinical decision‑making, operational efficiency, and service quality in healthcare. In Oman, however, government institutions remain in the early stages of digital transformation, and evidence on frontline readiness is limited.Objective: To assess healthcare professionals’ perceptions of AI, their preparedness and training, and the perceived barriers and recommendations for AI integration within government healthcare institutions in Al Buraimi Governorate, Oman.Methods: We conducted a quantitative, cross‑sectional survey of 300 healthcare professionals and administrative staff recruited via stratified random sampling. Data were collected using a structured, closed‑ended questionnaire and analyzed using descriptive statistics, reliability analysis, Pearson correlation, chi‑square tests, and multiple linear regression.Results: indicate strong positive perceptions of AI’s benefits (M=3.95, SD=0.89), particularly in improving patient care (86% high) and reducing errors (81.7% high), though skepticism persists regarding personalized treatment (58% high). Preparedness is notably low (M=2.94, SD=1.01), with 77.3% reporting inadequate training and 75.7% noting limited institutional training opportunities. Key barriers include infrastructure limitations (86% high), high costs (84.7% high), and data privacy concerns (77.7% high), alongside staff resistance (66.7% high). Recommendations emphasize scalable digital infrastructure, role-specific training, and stakeholder collaboration (93.7% high) Conclusions: Adoption is challenged by insufficient infrastructure, cost, and limited training/awareness among healthcare professionals. Targeted training, governance, and infrastructure are necessary to convert favorable attitudes into safe, sustainable adoption.

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  1. PREreview

    This Zenodo record is a permanently preserved version of a Structured PREreview. You can view the complete PREreview at https://prereview.org/reviews/17930232.

    Does the introduction explain the objective of the research presented in the preprint? Yes The study addressed the objectives by examining the perceived benefits of AI in clinical decision-making and service delivery, the preparedness and training, the perceived barriers and made recommendations for effective integration in government healthcare institutions.
    Are the methods well-suited for this research? Highly appropriate The study design was appropriate and well linked to the theoretical model used in the study.
    Are the conclusions supported by the data? Highly supported 1. The conclusion aligned with the results and it integrated the findings with the existing literatures referenced in the study. 2. The challenges identified from the data collected were also given realistic recommendations.
    Are the data presentations, including visualizations, well-suited to represent the data? Highly appropriate and clear They were clear and easy to comprehend.
    How clearly do the authors discuss, explain, and interpret their findings and potential next steps for the research? Very clearly 1. The study highlighted clear and practical opportunities for improvement. 2. It identified challenges, offered solutions to them and also recommended the planned integration of artificial intelligence (AI) into the government healthcare system.
    Is the preprint likely to advance academic knowledge? Highly likely The study confirmed that skepticism which was a major challenge for the participants could be transformed into acceptability through awareness-building via education, targeted training that improved professional confidence, alignment of AI with institutional goals, and investment in organizational infrastructure. The findings also suggested that the healthcare sector could strategically employ AI as one of the most impactful and transformative tools to improve service delivery and enhance efficiency.
    Would it benefit from language editing? No The study was well explained and structured for clarity.
    Would you recommend this preprint to others? Yes, it's of high quality It is timely, realistic, feasible and relatable.
    Is it ready for attention from an editor, publisher or broader audience? Yes, as it is It is well structured and ready for attention and publishing.

    Competing interests

    The authors declare that they have no competing interests.

    Use of Artificial Intelligence (AI)

    The authors declare that they did not use generative AI to come up with new ideas for their review.

  2. PREreview

    This Zenodo record is a permanently preserved version of a Structured PREreview. You can view the complete PREreview at https://prereview.org/reviews/17270095.

    Does the introduction explain the objective of the research presented in the preprint? Partly The introduction explains the objective clearly, but only after a very long literature review. For clarity, I would suggest to start clarifying the objective early in the introduction, and later provide the context, so that the aim of the study is clear from the beginning. Also, while most of the citations are very recent and updated, the frequent use of in-text citation takes away from the fluidity of the paper. I would suggest to reduce the number of in-text citations and prefer parenthetical citation.
    Are the methods well-suited for this research? Highly appropriate The survey is an adequate tool for this type of research. The respondents are correctly classified in different cathegories and statistical analysis is well explained. Many data are provided in the research to support the analysis.
    Are the conclusions supported by the data? Highly supported Tables and data are provided and clearly illustrate the results
    Are the data presentations, including visualizations, well-suited to represent the data? Highly appropriate and clear
    How clearly do the authors discuss, explain, and interpret their findings and potential next steps for the research? Somewhat clearly Discussion of the results does not include a short paragraph stating the limitations of the study analysis, which should be included to complete the paper
    Is the preprint likely to advance academic knowledge? Somewhat likely The preprint provides interesting insights and can be of useful when conducting research on integrating AI in different healthcare contexts or for local analysis
    Would it benefit from language editing? No It is overall clear, even if there are some language issues that need editing. For example, the sentences "Within these obscure confines near recent, regulation emphasizes that AI should be both actionable and reliable. These cannot, Olawade et al (2023), and later clear 'go public leading public health strategy', strong said in 'coarse of systems include, through shaped purposes and public good, alignment', of superbly thoughtful and consolidated interdisciplinary framing." in the introduction should be rephrased, as some words are probably missing.
    Would you recommend this preprint to others? Yes, but it needs to be improved Yes, after these minor adjustments
    Is it ready for attention from an editor, publisher or broader audience? Yes, after minor changes

    Competing interests

    The author declares that they have no competing interests.

    Use of Artificial Intelligence (AI)

    The author declares that they did not use generative AI to come up with new ideas for their review.

  3. PREreview

    This Zenodo record is a permanently preserved version of a Structured PREreview. You can view the complete PREreview at https://prereview.org/reviews/17233146.

    Does the introduction explain the objective of the research presented in the preprint? Yes
    Are the methods well-suited for this research? Somewhat appropriate Instrument appears adapted but the paper doesn't document content/construct validation beyond Cronbach's alpha (e.g., expert review, pilot testing, factor analysis); sampling uses stratified random selection and email recruitment but lacks detail on response rate/non-response bias; cross-sectional design limits causal inference; use of Google Forms is fine but data-quality controls aren't described (e.g., attention checks).
    Are the conclusions supported by the data? Somewhat supported
    Are the data presentations, including visualizations, well-suited to represent the data? Neither appropriate and clear nor inappropriate and unclear
    How clearly do the authors discuss, explain, and interpret their findings and potential next steps for the research? Somewhat clearly
    Is the preprint likely to advance academic knowledge? Moderately likely
    Would it benefit from language editing? Yes
    Would you recommend this preprint to others? Yes, but it needs to be improved
    Is it ready for attention from an editor, publisher or broader audience? Yes, after minor changes

    Competing interests

    The author declares that they have no competing interests.

    Use of Artificial Intelligence (AI)

    The author declares that they did not use generative AI to come up with new ideas for their review.

  4. Version published to 10.20944/preprints202509.0934.v2
  5. Version published to 10.20944/preprints202509.0934.v1