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The main aim of the present study is to investigate the effects of a Motivational Interviewing-based artificial intelligence chatbot on resting-state brain function in college students with elevated anhedonia and depressive symptoms. The study will use a randomized active-control intervention design with pre- and post-intervention resting-state functional magnetic resonance imaging assessments.
Anhedonia represents a core characteristic of depression and is characterized by reduced experience of pleasure. It is closely related to decreased motivation, altered reward processing, and alterations in intrinsic brain network function. Resting-state fMRI provides a way to examine intrinsic brain activity and functional connectivity without requiring participants to perform a specific task. This is important because changes associated with anhedonia may not only appear during reward-related tasks, but may also be reflected in spontaneous brain network organization.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Motivational Interviewing-based AI chatbot group | Experimental | Motivational Interviewing-based AI chatbot intervention |
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| Active control chatbot group | Active Comparator | Active control nature-story chatbot intervention |
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| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| MI Chatbot Interaction | Behavioral | The experimental chatbot is designed to use principles of Motivational Interviewing to support participants in exploring their personal values, motivation for change, and daily behavioral goals related to pleasure, engagement, and reward-seeking. During the intervention period, participants will interact with the chatbot regularly through brief text-based conversations. The chatbot will provide empathic, non-judgmental responses, encourage reflection on current difficulties, and help participants identify small, feasible actions that may increase daily engagement and positive experiences. It will not provide diagnosis, crisis counseling, or medical treatment. |
| Measure | Description | Time Frame |
|---|---|---|
| Intervention-Related Changes in Resting-State Functional Connectivity After the Intervention | Resting-state fMRI will be used to examine functional connectivity among predefined regions involved in reward, social, and self-referential processing. Connectivity will be estimated from Pearson correlations between regional BOLD time series and then converted using the Fisher z transformation. Changes from baseline to post-intervention will be reported as dimensionless Fisher z values. | Baseline before the first chatbot interaction and Week 1 after completion of the chatbot intervention. |
| Measure | Description | Time Frame |
|---|---|---|
| Intervention-Related Changes in Spontaneous Activity After the Intervention | Indices of spontaneous neural activity in regions involved in motivation, social and self-referential processing, will be extracted from resting-state fMRI scans collected at the two assessment points. These indices will include amplitude of low-frequency fluctuations or fractional amplitude of low-frequency fluctuations, as well as regional homogeneity. Baseline and post-intervention values will then be compared to characterize pre-to-post changes. |
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Inclusion Criteria:
Exclusion Criteria:
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| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Benjamin Becker | Contact | (852) 3917-5097 | bbecker@hku.hk |
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| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| University of Electronic Science and Technology of China | Recruiting | Chengdu | Sichuan | China |
Corresponding individual level data will be made available upon request.
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Between-subject randomized controlled trial comparing a Motivational Interviewing-based AI chatbot intervention with an active control chatbot intervention.
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| Active Control Chatbot Interaction | Behavioral | Participants will interact with a chatbot matched in format and frequency of use. This chatbot will provide neutral nature-related stories or general natural history content. It will be designed to maintain participant engagement while avoiding therapeutic techniques, motivational interviewing strategies, behavioral activation guidance, or personalized mental health advice. This active control condition will help control for nonspecific effects of chatbot interaction, attention, expectancy, and digital engagement. |
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| Baseline before the first chatbot interaction and Week 1 after completion of the chatbot intervention. |