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