Impact of AI-Assisted Diagnosis on American Patients’ Trust in and Intention to Seek Help From Health Care Professionals: Randomized, Web-Based Survey Experiment
Abstract BackgroundArtificial intelligence (AI) technologies are increasingly integrated into medical practice, with AI-assisted diagnosis showing promise. However, patient acceptance of AI-assisted diagnosis, compared with human-only procedures, remains understudied, especial...
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JMIR Publications
2025-06-01
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| Series: | Journal of Medical Internet Research |
| Online Access: | https://www.jmir.org/2025/1/e66083 |
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| author | Catherine Chen Zhihan Cui |
| author_facet | Catherine Chen Zhihan Cui |
| author_sort | Catherine Chen |
| collection | DOAJ |
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Abstract
BackgroundArtificial intelligence (AI) technologies are increasingly integrated into medical practice, with AI-assisted diagnosis showing promise. However, patient acceptance of AI-assisted diagnosis, compared with human-only procedures, remains understudied, especially in the wake of generative AI advancements such as ChatGPT.
ObjectiveThis research examines patient preferences for doctors using AI assistance versus those relying solely on human expertise. It also studies demographic, social, and experiential factors influencing these preferences.
MethodsWe conducted a preregistered 4-group randomized survey experiment among a national sample representative of the US population on several demographic benchmarks (n=1762). Participants viewed identical doctor profiles, with varying AI usage descriptions: no AI mention (control, n=421), explicit nonuse (No AI, n=435), moderate use (Moderate AI, n=481), and extensive use (Extensive AI, n=425). Respondents reported their tendency to seek help, trust in the doctor as a person and a professional, knowledge of AI, frequency of using AI in their daily lives, demographics, and partisan identification. We analyzed the results with ordinary least squares regression (controlling for sociodemographic factors), mediation analysis, and moderation analysis. We also explored the moderating effect of past AI experiences on the tendency to seek help and trust in the doctor.
ResultsMentioning that the doctor uses AI to assist in diagnosis consistently decreased trust and intention to seek help. Trust and intention to seek help (measured with a 5-point Likert scale and coded as 0‐1 with equal intervals in between) were highest when AI was explicitly absent (control group: mean 0.50; No AI group: mean 0.63) and lowest when AI was extensively used (Extensive AI group: mean 0.30; Moderate AI group: mean 0.34). A linear regression controlling for demographics suggested that the negative effect of AI assistance was significant with a large effect size (β=−.45, 95% CI −0.49 to −0.40, t1740Pt1733Pt1735Pt1735Pt1736P
ConclusionsDespite AI’s growing role in medicine, patients still prefer human-only expertise, regardless of partisanship and demographics, underscoring the need for strategies to build trust in AI technologies in health care. |
| format | Article |
| id | doaj-art-d4b4eeea885b4d6eb735228a6febaf20 |
| institution | Kabale University |
| issn | 1438-8871 |
| language | English |
| publishDate | 2025-06-01 |
| publisher | JMIR Publications |
| record_format | Article |
| series | Journal of Medical Internet Research |
| spelling | doaj-art-d4b4eeea885b4d6eb735228a6febaf202025-08-20T03:29:38ZengJMIR PublicationsJournal of Medical Internet Research1438-88712025-06-0127e66083e6608310.2196/66083Impact of AI-Assisted Diagnosis on American Patients’ Trust in and Intention to Seek Help From Health Care Professionals: Randomized, Web-Based Survey ExperimentCatherine Chenhttp://orcid.org/0000-0002-3367-0655Zhihan Cuihttp://orcid.org/0000-0003-0883-2322 Abstract BackgroundArtificial intelligence (AI) technologies are increasingly integrated into medical practice, with AI-assisted diagnosis showing promise. However, patient acceptance of AI-assisted diagnosis, compared with human-only procedures, remains understudied, especially in the wake of generative AI advancements such as ChatGPT. ObjectiveThis research examines patient preferences for doctors using AI assistance versus those relying solely on human expertise. It also studies demographic, social, and experiential factors influencing these preferences. MethodsWe conducted a preregistered 4-group randomized survey experiment among a national sample representative of the US population on several demographic benchmarks (n=1762). Participants viewed identical doctor profiles, with varying AI usage descriptions: no AI mention (control, n=421), explicit nonuse (No AI, n=435), moderate use (Moderate AI, n=481), and extensive use (Extensive AI, n=425). Respondents reported their tendency to seek help, trust in the doctor as a person and a professional, knowledge of AI, frequency of using AI in their daily lives, demographics, and partisan identification. We analyzed the results with ordinary least squares regression (controlling for sociodemographic factors), mediation analysis, and moderation analysis. We also explored the moderating effect of past AI experiences on the tendency to seek help and trust in the doctor. ResultsMentioning that the doctor uses AI to assist in diagnosis consistently decreased trust and intention to seek help. Trust and intention to seek help (measured with a 5-point Likert scale and coded as 0‐1 with equal intervals in between) were highest when AI was explicitly absent (control group: mean 0.50; No AI group: mean 0.63) and lowest when AI was extensively used (Extensive AI group: mean 0.30; Moderate AI group: mean 0.34). A linear regression controlling for demographics suggested that the negative effect of AI assistance was significant with a large effect size (β=−.45, 95% CI −0.49 to −0.40, t1740Pt1733Pt1735Pt1735Pt1736P ConclusionsDespite AI’s growing role in medicine, patients still prefer human-only expertise, regardless of partisanship and demographics, underscoring the need for strategies to build trust in AI technologies in health care.https://www.jmir.org/2025/1/e66083 |
| spellingShingle | Catherine Chen Zhihan Cui Impact of AI-Assisted Diagnosis on American Patients’ Trust in and Intention to Seek Help From Health Care Professionals: Randomized, Web-Based Survey Experiment Journal of Medical Internet Research |
| title | Impact of AI-Assisted Diagnosis on American Patients’ Trust in and Intention to Seek Help From Health Care Professionals: Randomized, Web-Based Survey Experiment |
| title_full | Impact of AI-Assisted Diagnosis on American Patients’ Trust in and Intention to Seek Help From Health Care Professionals: Randomized, Web-Based Survey Experiment |
| title_fullStr | Impact of AI-Assisted Diagnosis on American Patients’ Trust in and Intention to Seek Help From Health Care Professionals: Randomized, Web-Based Survey Experiment |
| title_full_unstemmed | Impact of AI-Assisted Diagnosis on American Patients’ Trust in and Intention to Seek Help From Health Care Professionals: Randomized, Web-Based Survey Experiment |
| title_short | Impact of AI-Assisted Diagnosis on American Patients’ Trust in and Intention to Seek Help From Health Care Professionals: Randomized, Web-Based Survey Experiment |
| title_sort | impact of ai assisted diagnosis on american patients trust in and intention to seek help from health care professionals randomized web based survey experiment |
| url | https://www.jmir.org/2025/1/e66083 |
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