Evidence map›Paper›PMID 40779743›Full record

Trial reportJournal of medical Internet research2025

Effects of a Theory- and Evidence-Based, Motivational Interviewing-Oriented Artificial Intelligence Digital Assistant on Vaccine Attitudes: A Randomized Controlled Trial.

Yan Li, Mengqi Li, Janelle Yorke, Daniel Bressington, Joyce Chung, Yao-Jie Xie, Lin Yang, Mengting He, Tsz-Ching Sun, Angela Y M Leung

Abstract readRandomized Controlled Trial
In one paragraph

Trial report in Journal of medical Internet research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Trial
  2. Article
  3. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Yan LiSchool of Nursing, The Hong Kong Polytechnic University, 11 Yuk Choi Rd, Hong Kong SAR, 999007, China.ORCID http://orcid.org/0000-0002-5311-9190
Mengqi LiSchool of Nursing, The Hong Kong Polytechnic University, 11 Yuk Choi Rd, Hong Kong SAR, 999007, China.ORCID http://orcid.org/0000-0002-9952-3690
Janelle YorkeSchool of Nursing, The Hong Kong Polytechnic University, 11 Yuk Choi Rd, Hong Kong SAR, 999007, China.ORCID http://orcid.org/0000-0002-1344-5944
Daniel BressingtonFaculty of Nursing, Chiang Mai University, Chiang Mai, Thailand.ORCID http://orcid.org/0000-0003-0951-2208
Joyce ChungSchool of Nursing, The Hong Kong Polytechnic University, 11 Yuk Choi Rd, Hong Kong SAR, 999007, China.ORCID http://orcid.org/0000-0001-5378-8274
Yao-Jie XieSchool of Nursing, The Hong Kong Polytechnic University, 11 Yuk Choi Rd, Hong Kong SAR, 999007, China.ORCID http://orcid.org/0000-0001-9289-4985
Lin YangSchool of Nursing, The Hong Kong Polytechnic University, 11 Yuk Choi Rd, Hong Kong SAR, 999007, China.ORCID http://orcid.org/0000-0002-5964-3233
Mengting HeSchool of Nursing, The Hong Kong Polytechnic University, 11 Yuk Choi Rd, Hong Kong SAR, 999007, China.ORCID http://orcid.org/0009-0007-2987-9070
Tsz-Ching SunSchool of Nursing, The Hong Kong Polytechnic University, 11 Yuk Choi Rd, Hong Kong SAR, 999007, China.ORCID http://orcid.org/0009-0008-6801-0025
Angela Y M LeungSchool of Nursing, The Hong Kong Polytechnic University, 11 Yuk Choi Rd, Hong Kong SAR, 999007, China.ORCID http://orcid.org/0000-0002-9836-1925

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Attitude-targeted interventions are important approaches for promoting vaccination. Educational approaches alone cannot effectively cultivate positive vaccine attitudes. Artificial intelligence (AI)-driven chatbots and motivational interviewing (MI) techniques show high promise in improving vaccine attitudes and facilitating readiness for vaccination. Objective: This study aimed to evaluate the effectiveness of a theory and evidence-based, MI-oriented AI digital assistant in improving COVID-19 vaccine attitudes among adults in Hong Kong. Methods: This 2 parallel-armed randomized controlled trial was conducted from October 2022 to June 2024. Hong Kong adults (N=177) who were vaccine-hesitant were randomly assigned into 2 study groups. The intervention group (n=91) interacted with the AI digital assistant over 5 weeks, including receiving a web-based education program comprising 5 educational modules and communicating with an AI-driven chatbot equipped with MI techniques. The control group (n=86) received WhatsApp (Meta) messages directing them to government websites for COVID-19 vaccine information and knowledge, with the same dosage as the intervention group. Primary outcomes included vaccine hesitancy. Secondary outcomes included vaccine readiness, confidence, trust in government, and health literacy. Outcomes were measured at baseline, postintervention, 3-month, and 6-month follow-up. Focus group interviews were conducted postintervention. Intervention effects were analyzed using the generalized estimating equation model. Interview data were content analyzed. Results: Decreases in vaccine hesitancy were observed while no statistically significant time-by-group interaction effects were found. The intervention showed significant time-by-group interaction effects on vaccine readiness (P=.04), confidence (P=.02), and trust in government (P=.04). Significant between-group differences with medium effect sizes were identified for vaccine readiness (Cohen d=0.52) and trust in government (Cohen d=0.54) postintervention, respectively. Increases in vaccine-related health literacy were observed, and a significant time effect was found (P=.01). In total, three categories were summarized from interview data: (1) improved vaccine literacy, confidence, and trust in government; (2) hesitancy varied while readiness improved; and (3) facilitators, barriers, and recommendations of modifications on the intervention. Conclusions: The intervention indicated promising yet significant effects on vaccine readiness while the effects on vaccine hesitancy require further confirmation. The qualitative findings; however, further consolidate the significant effects on participants' attitudes toward vaccines. The findings provide novel evidence to encourage the adoption and refinement of a MI-oriented AI digital assistant in vaccine promotion.

Indexed as

Artificial IntelligenceCOVID-19COVID-19 VaccinesHealth Knowledge, Attitudes, PracticeMotivational InterviewingVaccinationVaccination HesitancyAdultFemaleHong KongHumansMaleMiddle AgedSARS-CoV-2COVID-19 Vaccinesartificial intelligenceattitudechatbotCOVID-19motivational interviewingvaccine hesitancy

Identifiers

PMID40779743
PMCPMC12334111

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.