Virtual training and coaching of health behavior: Example from mindfulness meditation training
Open accessAbstract
Objective Computer-based virtual coaches are increasingly being explored for patient education, counseling, and health behavior training and coaching. The objective of this research was to develop and evaluate a Virtual Mindfulness Coach for training and coaching in mindfulness meditation.Methods The coach was implemented as an embodied conversational character, providing mindfulness training and coaching via mixed initiative, text-based, natural language dialog with the student, and emphasizing affect-adaptive interaction. (The term 'mixed initiative dialog' refers to a human-machine dialog where either can initiate a conversation or a change in the conversation topic.)Results Findings from a pilot evaluation study indicate that the coach-based training is more effective in helping students establish a regular practice than self-administered training using written and audio materials. The coached group also appeared to be in more advanced stages of change in terms of the transtheoretical model, and have a higher sense of self-efficacy regarding establishment of a regular mindfulness practice.Conclusion These results suggest that virtual coach-based training of mindfulness is both feasible, and potentially more effective, than a self-administered program. Of particular interest is the identification of the specific coach features that contribute to its effectiveness.Practice implications Virtual coaches could provide easily accessible and cost-effective customized training for a range of health behaviors. The affect-adaptive aspect of these coaches is particularly relevant for helping patients establish long-term behavior changes.
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ECA interventions have been found to be easier to use and used more frequently than interventions without an ECA.
“Results are promising, as ECA interventions have been found to be easier to use [5] and used more frequently [5,11-13] than interventions without an ECA.”
From Use and Effect of Embodied Conversational Agents for Improving Eating Behavior and Decreasing Loneliness Among Community-Dwelling Older Adults: Randomized Controlled Trial (2022) · cites this paper as [13]
The Introduction (§1.2; page unavailable) says ECAs require minimal or no training, but does not compare their ease of use with interventions without an ECA. The Results (§3; page unavailable) report more frequent meditation and greater engagement in the coached group, not more frequent use of the intervention itself. (LLM, conf=0.84)
Experimental — accuracy not yet measuredSome potentially relevant conversational agents developed for the treatment of mental health problems were excluded from this review because of not reporting a mental health outcome measure.
“Furthermore, some potentially relevant conversational agents developed for the treatment of mental health problems were excluded from this review because of not reporting a mental health outcome measure (eg, ELIZA [2,42-44]).”
From Conversational agents in the treatment of mental health problems: mixed-method systematic review (2019) · cites this paper as [43]
Other studies have yielded positive outcomes for ECAs to deliver health education on topics such as exercise, eating fruits and vegetables, and preconception care.
“Other studies have also yielded positive outcomes for ECAs to deliver health education on topics such as: exercise, eating fruits and vegetables, and preconception care [12, 16, 21–24].”
From Engaging women with an embodied conversational agent to deliver mindfulness and lifestyle recommendations: A feasibility randomized control trial (2017) · cites this paper as [22]
In a pilot study of a virtual coach delivering mindfulness training, participants with coach-based training performed the techniques more effectively and regularly than those who taught themselves using paper and audio materials.
“Similarly, one pilot study implemented a virtual coach to provide mindfulness training, and found that participants who had coach-based training performed the techniques more effectively and regularly than participants who had to teach themselves the same techniques using paper and audio materials [22].”
From Engaging women with an embodied conversational agent to deliver mindfulness and lifestyle recommendations: A feasibility randomized control trial (2017) · cites this paper as [22]
Most previous chatbot research relied on either finite-state or frame-based systems.
“Most previous chatbot research relied on either finite-state (ie, dialog consisting of a sequence of predetermined steps or states) or frame-based systems (ie, dialog is not predetermined but dependent on the content of the user’s input and the information that the system has to elicit) [34-36].”
The largest proportion of included conversational agents (12/31, 39%) addressed mental health issues.
“The largest proportion of them (12/31, 39%) addressed mental health issues [13,32-42]”
From The Effectiveness of Artificial Intelligence Conversational Agents in Health Care: Systematic Review (2020) · cites this paper as [35]
The most frequently raised issue with conversational agents (9 studies) was poor understanding because of limited vocabulary, voice recognition accuracy, or error management of word inputs.
“The most frequently raised issue with conversational agents (9 studies) was poor understanding because of limited vocabulary, voice recognition accuracy, or error management of word inputs [13,32-37,41,52].”
From The Effectiveness of Artificial Intelligence Conversational Agents in Health Care: Systematic Review (2020) · cites this paper as [35]
Feedback from users in 5 studies expressed a preference for interactivity; users in 1 study liked the interactivity of the chatbot, and users in 4 studies desired greater interactivity or relational skills.
“Feedback from users in 5 studies expressed a preference for interactivity, with users in 1 study noting that they liked the interactivity of the chatbot [35,37], and users in the other 4 studies expressed a desire for greater interactivity or relational skills in the conversational agent [14,32,34,53].”
From The Effectiveness of Artificial Intelligence Conversational Agents in Health Care: Systematic Review (2020) · cites this paper as [35]
Users in 4 studies reported liking that the agent had a personality and/or showed empathy, whereas users in other studies reported disliking the lack of personal connection or had difficulty empathizing with the agent or reported disliking its limited conversation and responses.
“Similarly, users in 4 studies reported liking that the agent had a personality and/or showed empathy [13,32,34,42], whereas users in other studies reported disliking the lack of personal connection or had difficulty in empathizing with the agent [35,37,50] or reported disliking its limited conversation and responses [35,56].”
From The Effectiveness of Artificial Intelligence Conversational Agents in Health Care: Systematic Review (2020) · cites this paper as [35]
Several studies reported feedback concerned with customization or availability of feature options: 2 studies commented positively, and 3 studies desired more features and more control.
“However, several studies reported feedback concerned with customization or availability of feature options, with 2 studies commenting on it positively (eg, having both voice and touch modes to allow hands-free work and rapid data input on a triage system for nurses) [8,35], and 3 studies desiring more features and more control [33,37,48].”
From The Effectiveness of Artificial Intelligence Conversational Agents in Health Care: Systematic Review (2020) · cites this paper as [35]
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- Authors
- Hudlicka, E.
- Venue
- Patient Education and Counseling
- Publisher
- Elsevier BV
- Published
- 2013-08
- Volume
- 92
- Issue
- 2
- Pages
- 160-166
- ISSN
- 0738-3991 (ISSN-L)
- PMC
- PMC3970714
- OpenAlex
- W2022401732
- Cited by
- 104
- References
- 29
- Citations by year
- 2026: 2 · 2025: 11 · 2024: 5 · 2023: 11 · 2022: 13 · 2021: 13 · 2020: 13 · 2019: 13 · 2018: 6 · 2017: 9 · 2016: 4 · 2015: 2 · 2014: 1 · 2013: 1
- FWCI
- 4.11
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Patient Education and Counseling (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- NIH SBIR (1R43 AT005397-01)
- Topics
- Social Sciences › Psychology › Applied Psychology › Digital Mental Health Interventions
- Social Sciences › Psychology › Clinical Psychology › Mindfulness and Compassion Interventions
- Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
- Keywords
- virtual coach, mindfulness meditation, embodied conversational agents, mixed-initiative dialogue, natural language dialogue, self-efficacy, stages of change, transtheoretical model, health behavior change, patient education
- MeSH terms
- Adult, Communication, Counseling, Female, Humans, Male, Patient Education as Topic, Self Care, Teaching, Program Evaluation, Health Behavior, Program Development, Treatment Outcome, Meditation, Mind-Body Therapies, Mindfulness
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