MEASURING USER ATTITUDES AND PREFERENCES TOWARDS THE USE OF AI-ENABLED HEALTH TECHNOLOGIES: A SCOPING REVIEW PROTOCOL

Author(s)

Nikolett Jónás, MsC1, László Gulácsi, MD, PhD2, László Berek, PhD3, Marta Pentek, MD, PhD2, Áron Hölgyesi, PharmD, PhD1.
1Innovation Management Doctoral School, Obuda University, Budapest, Hungary, 2Health Economics Research Center, University Research and Innovation Center, Obuda University, Budapest, Hungary, 3Obuda University, Budapest, Hungary.
OBJECTIVES: The successful implementation of AI-enabled health technologies (AIHT) depends on the attitudes and preferences of end users, including patients and healthcare professionals. However, validated instruments available for their measurement are fragmented across the literature, and no comprehensive overview or guidance is currently available on their use in practice. This review aims to identify and analyse available studies to provide a structured evidence base for researchers and decision-makers and support the selection of appropriate instruments for assessing user attitudes and preferences.
METHODS: The review has been designed in accordance with the PRISMA guideline. The research question and search queries were formulated according to the PICOTS framework, focusing on healthcare users of AIHT (Population), validated questionnaires assessing user attitudes and preferences towards them (Intervention), any alternative measurement method (Comparator), and the acceptance of AIHT (Outcome). No time restrictions were applied, and only English-language studies conducted in healthcare settings were included. The literature search was conducted in four databases. As no validated search string was available in this context, relevant keywords related to the concepts defined by the PICOTS were used.
RESULTS: The preliminary search conducted in May 2026 identified N=245 articles in Embase, N=383 in PubMed, N=307 in Scopus, and N=973 in Web of Science. Removal of duplicates (N=792) and non-English articles (N=8) left N=1,108 publications for the ongoing screening by title and abstract and subsequent full-text review. Eligible studies will be systematically evaluated and data on the number of items, dimensions measured, and psychometric properties of the identified instruments will be extracted to support evidence synthesis.
CONCLUSIONS: The review will provide a structured overview of existing instruments and help identify gaps in the literature on AIHT acceptance. The findings may support the selection of appropriate measurement tools, improve methodological consistency across studies, and contribute to the evidence-based implementation of AIHT in healthcare systems.

Conference/Value in Health Info

2026-11, ISPOR Europe 2026, Vienna, Austria

Value in Health, Volume 29, Issue 12S

Code

MT28

Topic

Medical Technologies, Patient-Centered Research

Topic Subcategory

Digital Health

Disease

No Additional Disease & Conditions/Specialized Treatment Areas

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