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TRUVACE RECORD VERSION
record: TRV-2026-2641
version: 1
kind: certified
reason: Certified into the record
timestamp: 2026-11-12T16:55:36.014384Z
status: published
lens: trace
sector: health
headline: Encouraging disclosure: the role of personalization in pre-consultation chatbots
dek: Purpose This study aims to explore how personalized services provided by pre-consultation chatbots influence patients' intentions to self-disclose and the boundary conditions of this effect. Drawing on the Communication Privacy Management Theory, it identifies AI interactive trust as a mediator and examines how disease sensitivity moderates this mechanism. Design/methodology/approach Three scenario experiments and a field survey were conducted to test hypotheses. Experiments 1 and 2 were between-subjects experim…
gain_title: In three scenario experiments and a field survey, researchers found that a more personalized pre-consultation chatbot increased patients' willingness to self-disclose by building trust in the AI, for low-sensitivity diseases.
problem_title: In three scenario experiments and a field survey on pre-consultation chatbots, the trust-driven boost in patients' willingness to self-disclose weakened or disappeared for high-sensitivity diseases.
trace_subject: Personalization in pre-consultation chatbots and patient self-disclosure
gain_reading: In three scenario experiments and a field survey, researchers found that a more personalized pre-consultation chatbot increased patients' willingness to self-disclose by building trust in the AI, for low-sensitivity diseases.
gain_evidence: Service personalization increased patients' willingness to self-disclose by enhancing AI interactive trust, but only for low-sensitivity diseases.
problem_reading: In three scenario experiments and a field survey on pre-consultation chatbots, the trust-driven boost in patients' willingness to self-disclose weakened or disappeared for high-sensitivity diseases.
problem_evidence: For high-sensitivity conditions, this trust-based effect weakens or even disappears.
quick_read: A peer-reviewed study in the Asia Pacific Journal of Marketing and Logistics tested whether personalized service from pre-consultation chatbots makes patients more willing to share information. Three scenario experiments and a field survey found that higher personalization increased willingness to self-disclose, and that the effect ran through greater trust in the AI.

The effect depended on the condition. It held for low-sensitivity diseases, but for high-sensitivity conditions the trust-based effect weakened or disappeared. Where patients most need to share delicate details, personalization alone did not reliably encourage disclosure.

The work draws on Communication Privacy Management Theory and treats AI interactive trust as the mediating mechanism, with disease sensitivity as the boundary condition. The fourth study, a survey, reconfirmed all the hypotheses.
limitation: The main experiments used scenario designs, and the trust-based effect weakened or disappeared for high-sensitivity conditions, so findings do not show that personalization encourages disclosure across all diseases.
tag: Dual reading
key_points: The research combined three between-subjects scenario experiments with one field survey. | Experiments 1 and 2 manipulated chatbot service personalization (low vs. high) in different disease contexts. | Experiment 3 used a 2 (personalization: low vs. high) × 2 (disease type: low vs. high sensitivity) design. | Personalization raised willingness to self-disclose by increasing AI interactive trust. | The effect appeared only for low-sensitivity diseases; for high-sensitivity conditions it weakened or vanished. | Survey 4 reconfirmed all of the study's hypotheses.
rundown: The study examined pre-consultation chatbots, which collect information from patients before they see a clinician. It asked whether personalized service changes patients' intention to disclose personal information, and under what conditions.

Experiments 1 and 2 varied personalization between low and high in different disease contexts. Experiment 3 crossed personalization with disease sensitivity, allowing the researchers to test whether the type of illness changes the effect.

Results pointed to AI interactive trust as the mechanism: personalization built trust, and trust raised willingness to disclose. That chain held for low-sensitivity diseases but weakened or disappeared for high-sensitivity ones, and a field survey reconfirmed the pattern.
sources:
- peer_reviewed | Asia Pacific Journal of Marketing and Logistics | https://doi.org/10.1108/apjml-01-2026-0238 | 2026-10-22
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