Chatbot Intervention Effects on Belief Updating in Anhedonia

ConditionHealthy

Trial statusRecruiting

Trial phaseNot applicable

Trial typeInterventional

Biological sexAll

Age18-40

SponsorUniversity of Electronic Science and Technology of China

About this trial

The main aim of the present study is to investigate the effects of a Motivational Interviewing-based artificial intelligence chatbot on belief updating in college students with elevated levels of depression and anhedonia by combining a randomized active-control intervention design with pre- and post-intervention behavioral belief updating task assessments.

Eligibility criteria

This trial accepts healthy volunteers

Qualifiers

18-40 years

Right-handed

Normal or corrected normal visual acuity

Participants must show elevated anhedonia and depressive symptoms at screening, defined as a total score of 22 or higher on the Snaith-Hamilton Pleasure Scale and a score of 14 or higher on the Beck Depression Inventory

Disqualifiers

History of major central nervous system disorders, such as epilepsy, traumatic brain injury, stroke, or brain tumors.

History of severe mental illness, including schizophrenia spectrum disorders, bipolar disorder, or other psychotic disorders.

History of substance or alcohol use disorder or substance or alcohol misuse within the past 12 months that may affect study participation or outcome assessment.

Individuals currently at high risk of suicide, severe self-harm, or experiencing an acute psychiatric crisis.

Trial design

Design model

Parallel

Treatments tested in this trial

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.
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.

Treatment groups

80 Participants

are divided into 2 treatment groups

Group A: Motivational Interviewing-based AI chatbot groupExperimental treatment 1 intervention

Group B: Active control chatbot groupActive comparator 1 intervention

Trial outcomes

Primary outcomes

Valence-dependent belief updating bias

Belief updating magnitude will be calculated separately for positive and negative information conditions in the belief updating task before and after the intervention. Updating magnitude will be quantified based on changes in probability estimates before and after the presentation of new information. The difference in updating magnitude between positive and negative information conditions will be calculated and compared from baseline to post-intervention.

Time frame

Baseline before the first chatbot interaction and Week 1 after completion of the chatbot intervention.

Secondary outcomes

Expectancy bias for life events

Before receiving base-rate information or new information, participants will provide initial probability estimates for positive and negative life events at baseline and post-intervention. Mean initial estimates will be calculated separately for the two event types, and pre-to-post changes in the difference between positive and negative event estimates will be compared.

Time frame

Baseline before the first chatbot interaction and Week 1 after completion of the chatbot intervention

Sponsors and contacts

Click on the lead sponsor to view all of their trials.

University of Electronic Science and Technology of China

Lead sponsor

Source ClinicalTrials.gov

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