Trial reportJournal of medical Internet research2022
The Effects of Health Care Chatbot Personas With Different Social Roles on the Client-Chatbot Bond and Usage Intentions: Development of a Design Codebook and Web-Based Study.
Trial report in Journal of medical Internet research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 1 of them a synthesis that pooled 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.
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.
Who cites it
20 citing papers in PubMed, 1 synthesis or guideline pooled it, 67 citations in OpenAlex.
- Attrition in Conversational Agent-Delivered Mental Health Interventions: Systematic Review and Meta-Analysis.Journal of medical Internet research · 2024Pooled it
- Mental Health Chatbot for Young Adults With Depressive Symptoms During the COVID-19 Pandemic: Single-Blind, Three-Arm Randomized Controlled Trial.Journal of medical Internet research · 2022Trial
- Does AI communication strategy matter for health persuasion? Comparing three archetypes in visual health education.Frontiers in psychology · 2026Article
- Leveraging Influencers to Reach and Engage Vulnerable Individuals With a Digital Health Intervention: Quasi-Experimental Field Study.Journal of medical Internet research · 2025Article
- Exploring the Acceptance and Opportunities of Using a Specific Generative AI Chatbot to Assist Parents in Managing Pediatric Rheumatological Chronic Health Conditions: Mixed Methods Study.JMIR pediatrics and parenting · 2025Article
- Designing Chatbots to Treat Depression in Youth: Qualitative Study.JMIR human factors · 2025Article
- Multimodal machine learning enables AI chatbot to diagnose ophthalmic diseases and provide high-quality medical responses.NPJ digital medicine · 2025Article
- Determinants of Dropout From a Virtual Agent-Based App for Insomnia Management in a Self-Selected Sample of Users With Insomnia Symptoms: Longitudinal Study.JMIR mental health · 2025Article
- Article
- Ethical Considerations in Human-Centered AI: Advancing Oncology Chatbots Through Large Language Models.JMIR bioinformatics and biotechnology · 2024Article
- Roles, Users, Benefits, and Limitations of Chatbots in Health Care: Rapid Review.Journal of medical Internet research · 2024Review
- The Role of Humanization and Robustness of Large Language Models in Conversational Artificial Intelligence for Individuals With Depression: A Critical Analysis.JMIR mental health · 2024Article
- Artificial intelligence vs. human coaches: examining the development of working alliance in a single session.Frontiers in psychology · 2024Article
- Democratizing the Development of Chatbots to Improve Public Health: Feasibility Study of COVID-19 Misinformation.JMIR human factors · 2023Article
- Exploring the potential of mobile health interventions to address behavioural risk factors for the prevention of non-communicable diseases in Asian populations: a qualitative study.BMC public health · 2023Article
- Evaluating Conversational Agents for Mental Health: Scoping Review of Outcomes and Outcome Measurement Instruments.Journal of medical Internet research · 2023Article
- Development of "LvL UP 1.0": a smartphone-based, conversational agent-delivered holistic lifestyle intervention for the prevention of non-communicable diseases and common mental disorders.Frontiers in digital health · 2023Article
- Waiting for a digital therapist: three challenges on the path to psychotherapy delivered by artificial intelligence.Frontiers in psychiatry · 2023Article
- Does realizing strengths, insight, and behavioral practice through a psychological intervention promote personality change? An intensive longitudinal study.European journal of personalityArticle
- Public opinion on types of voice systems for older adults.Journal of rehabilitation and assistive technologies engineeringArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe working alliance refers to an important relationship quality between health professionals and clients that robustly links to treatment success. Recent research shows that clients can develop an affective bond with chatbots. However, few research studies have investigated whether this perceived relationship is affected by the social roles of differing closeness a chatbot can impersonate and by allowing users to choose the social role of a chatbot.
objectiveThis study aimed at understanding how the social role of a chatbot can be expressed using a set of interpersonal closeness cues and examining how these social roles affect clients' experiences and the development of an affective bond with the chatbot, depending on clients' characteristics (ie, age and gender) and whether they can freely choose a chatbot's social role.
methodsInformed by the social role theory and the social response theory, we developed a design codebook for chatbots with different social roles along an interpersonal closeness continuum. Based on this codebook, we manipulated a fictitious health care chatbot to impersonate one of four distinct social roles common in health care settings-institution, expert, peer, and dialogical self-and examined effects on perceived affective bond and usage intentions in a web-based lab study. The study included a total of 251 participants, whose mean age was 41.15 (SD 13.87) years; 57.0% (143/251) of the participants were female. Participants were either randomly assigned to one of the chatbot conditions (no choice: n=202, 80.5%) or could freely choose to interact with one of these chatbot personas (free choice: n=49, 19.5%). Separate multivariate analyses of variance were performed to analyze differences (1) between the chatbot personas within the no-choice group and (2) between the no-choice and the free-choice groups.
resultsWhile the main effect of the chatbot persona on affective bond and usage intentions was insignificant (P=.87), we found differences based on participants' demographic profiles: main effects for gender (P=.04, η
conclusionsManipulating a chatbot's social role is a possible avenue for health care chatbot designers to tailor clients' chatbot experiences using user-specific demographic factors and to improve clients' perceptions and behavioral intentions toward the chatbot. Our results also emphasize the benefits of letting clients freely choose between chatbots.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.