What question did this study set out to answer?

This study aims to assess patient attitudes towards AI in healthcare and identify correlates affecting acceptance.

July 11, 2026Open Access

Patient attitudes toward artificial intelligence in Jordanian Healthcare: A cross-sectional survey study

ZAZeena Al-DabbasAl-Balqa Applied University LKLaith KhandakjiAl-Balqa Applied University NANour Al-ShataratAl-Balqa Applied University

Key Points

This study aims to assess patient attitudes towards AI in healthcare and identify correlates affecting acceptance.
Cross-sectional survey conducted with 500 participants in three Jordanian governorates (Amman, Balqa, Irbid).
Participants rated AI healthcare exposure using a 25-item questionnaire on a 5-point Likert scale.
Multivariable regression analysis was performed to explore associations with demographic and digital literacy factors.
Patients showed high empathy and human interaction acceptance (M = 4.33), indicating they prefer AI to assist rather than replace physicians (M = 4.47).
Strong positive correlations were found between trust, perceived usefulness, and readiness (r = 0.48, r = 0.44; p < .001).
Lower educational attainment and self-rated digital skill negatively affected readiness (R 2 = 0.101).

Abstract

Artificial intelligence (AI) is increasingly integrated into healthcare delivery, yet patient acceptance in resource constrained settings remains incompletely characterized. This study assessed attitudes toward AI supported care among patients attending hospitals in three Jordanian governorates (Amman, Balqa, Irbid) and examined demographic and digital literacy correlates of acceptance. In a cross sectional survey (n = 500 complete questionnaires), participants rated exposure to AI in healthcare and five attitudinal domains, namely perceived usefulness or performance expectancy, trust and transparency, privacy and perceived risks, empathy and human interaction, and readiness or behavioral intention, using 25 items on 5 point Likert scales. Patients expressed conditional optimism: empathy and human interaction was most strongly endorsed (M = 4.33, SD = 0.58), alongside relatively high perceived usefulness (M = 3.97, SD = 0.68), while trust and transparency (M = 3.57, SD = 0.74) and readiness (M = 3.66, SD = 0.90) were moderate to high; privacy and risk concerns were moderate (M = 3.51, SD = 0.77) and self reported exposure was lowest (M = 2.57, SD = 1.07). The highest agreement item indicated preference for AI to work alongside physicians rather than be relied on alone (M = 4.47, SD = 0.81). Trust and transparency and perceived usefulness were positively associated with readiness (r = 0.48 and r = 0.44, respectively; p < .001), while privacy and perceived risks were negatively correlated with trust and usefulness. In multivariable regression adjusting for gender, age group, education, prior AI health app or device use, and self rated digital skill, lower educational attainment and self-rated digital skill were associated with readiness (R 2 = 0.101). These findings suggest that implementation strategies in Jordan should emphasize human involvement alongside AI, transparent communication and governance, and attention to education- and digital-confidence-related differences in readiness.

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