Currently submitted to: Online Journal of Public Health Informatics
Date Submitted: Jun 12, 2026
Open Peer Review Period: Jun 19, 2026 - Aug 14, 2026
(closed for review but you can still tweet)
NOTE: This is an unreviewed Preprint
Warning: This is a unreviewed preprint (What is a preprint?). Readers are warned that the document has not been peer-reviewed by expert/patient reviewers or an academic editor, may contain misleading claims, and is likely to undergo changes before final publication, if accepted, or may have been rejected/withdrawn (a note "no longer under consideration" will appear above).
Peer review me: Readers with interest and expertise are encouraged to sign up as peer-reviewer, if the paper is within an open peer-review period (in this case, a "Peer Review Me" button to sign up as reviewer is displayed above). All preprints currently open for review are listed here. Outside of the formal open peer-review period we encourage you to tweet about the preprint.
Citation: Please cite this preprint only for review purposes or for grant applications and CVs (if you are the author).
Final version: If our system detects a final peer-reviewed "version of record" (VoR) published in any journal, a link to that VoR will appear below. Readers are then encourage to cite the VoR instead of this preprint.
Settings: If you are the author, you can login and change the preprint display settings, but the preprint URL/DOI is supposed to be stable and citable, so it should not be removed once posted.
Submit: To post your own preprint, simply submit to any JMIR journal, and choose the appropriate settings to expose your submitted version as preprint.
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
Faculty Beliefs, Perceptions, and Characteristics Underpinning the Institutional Implementation of AI in Public Health Education: A Comparative Analysis
ABSTRACT
Background:
Despite the consensus that faculty, artificial intelligence (AI), and education are interconnected, discipline-specific literature is limited.
Objective:
This study expands current understanding by assessing perceptions and beliefs about AI in higher education among public health faculty in the United States.
Methods:
A Qualtrics survey was developed and sent to 7,969 faculty of public health schools and programs accredited by the Council on Education for Public Health (CEPH). Frequency statistics, Chi-squared, and Fisher’s Exact tests were conducted to examine dominant AI beliefs about and perceptions, as well as differences by faculty rank, gender, and effort allocation.
Results:
The resulting sample (n = 411) consisted primarily of non-Hispanic white, research-oriented faculty aged 35 to 64. Faculty appeared receptive to AI but agreed that much progress in AI development and institutional training is needed for successful implementation. Furthermore, there was little consensus on what constituted appropriate student use of AI. Two main faculty features, effort and academic rank, significantly shaped faculty perceptions and beliefs concerning AI. Additionally, faculty identified impaired critical thinking and problem-solving, as well as limited skills and knowledge of AI, as primary concerns and barriers influencing implementation in academia.
Conclusions:
These results highlight the importance of faculty's professional experience and focus, as well as prevalent negative perceptions about AI, when implementing academic AI initiatives and developing training programs. By targeting varying dispositions towards AI, areas of effort, and duration in academia, we can hope to increase faculty’s receptiveness to AI implementation, increasing the likelihood of successful AI adoption in public health higher education.
Citation
Request queued. Please wait while the file is being generated. It may take some time.
Copyright
© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.