JMIR Publications

ABSTRACT

Background:

人工智能（AI）在医疗保健领域越来越突出。接受是人工智能广泛实施不可或缺的先决条件。

Objective:

The aim of this systematic review is to explore barriers and facilitators influencing patients’ acceptance of AI.

Methods:

A systematic literature review was conducted following the PRISMA guidelines, searching PubMed, Embase, CINAHL, Web of Science, Cochrane Library, CNKI, VIP, Wanfang, and CBM databases up to October 2024. Studies were included if they examined patient attitudes and perceptions of medical AI using qualitative, quantitative, or mixed methods. Two researchers independently performed literature selection, data extraction, and quality assessment using the Mixed Methods Appraisal Tool (MMAT). Conceptual framework analysis was based on the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) and the Theoretical Domains Framework (TDF), with intervention strategies mapped using the Behavior Change Techniques Taxonomy (BCTs).

Results:

52 studies met the inclusion criteria out of a total of 6023 search results. The main facilitating factors included the interpretability of AI decisions, improved doctor-patient communication, and transparent design. Major barriers comprised perceived technical uncertainty, lack of trust in algorithms, reduced interpersonal interaction, patient privacy protection, and ethical concerns. After mapping the TDF to Behavior Change Techniques (BCT), 32 intervention strategies across 10 domains were derived.

Conclusions:

To conclude, in order to facilitate acceptance of AI among patient it is advisable to integrate end-users in the early stages of AI development as well as to offer needs-adjusted training for the use of AI in healthcare and providing adequate infrastructure. Therefore, future research should focus on enhancing device and data security, balancing performance improvements with humanistic care, and validating the effectiveness of these strategies to address cognitive changes arising from technological advancements. Clinical Trial: The protocol was registered with the PROSPERO in October 2024 (registration number: CRD42024598884)