The main aim of the present study is to investigate the effects of a Motivational Interviewing-based artificial intelligence chatbot on social incentive processing in college students with elevated levels of depression and anhedonia by combining a randomized active-control intervention design with pre- and post-intervention Social Incentive Delay Task assessments during fMRI.
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
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.
Parallel
MI Chatbot Interaction
BehavioralThe 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
BehavioralParticipants 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.
Neural Activity During Social Incentive Anticipation
Participants will undergo task-based BOLD fMRI while completing the Social Incentive Delay Task. Neural responses during the anticipation of social incentive cues will be compared with responses to neutral cues using a general linear model. Pre-to-post intervention changes will be evaluated from the resulting beta contrast estimates.
Neural Activity During Monetary Incentive Anticipation
Task-based BOLD fMRI data will be acquired while participants perform the Monetary Incentive Delay Task. Neural responses associated with the anticipation of monetary reward and punishment will be estimated using a general linear model. Beta contrast estimates will be calculated for monetary reward versus neutral and monetary punishment versus neutral conditions. These estimates will be used to assess changes between baseline and post-intervention.
Behavioral Responsiveness to Social Incentive Cues
Reaction time, accuracy, and hit rate will be calculated separately for social incentive cue conditions and neutral cue conditions in the Social Incentive Delay Task before and after the intervention. Behavioral differences between social incentive and neutral cue conditions will also be derived and compared from baseline to post-intervention.
Behavioral responsiveness to monetary incentives
The Monetary Incentive Delay Task will be administered before and after the intervention. Reaction time, accuracy, and hit rate will be extracted separately for monetary incentive cue conditions and neutral cue conditions, and changes in behavioral differences between monetary incentive and neutral cue conditions will be calculated.
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