Tundra Space

Tundra Space

Clinical Research Directory

Browse clinical research sites, groups, and studies.

2 clinical studies listed.

Filters:

Behavior, Addictive

Tundra lists 2 Behavior, Addictive clinical trials. Each listing includes eligibility criteria, study locations, and direct links to research sites in the Tundra directory.

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NOT YET RECRUITING

NCT07819851

A Study of the Correlation Between the Severity of Substance Use Disorder and the Intensity of Dependence on Generative Artificial Intelligence

This bicentric, cross-sectional observational study conducted in France evaluates the relationship between substance use disorder (SUD) severity and generative artificial intelligence dependency among outpatients treated in specialized addiction care centers (CSAPA). While conversational generative artificial intelligence tools have seen rapid widespread adoption, potential problematic usage and cognitive dependency remain poorly documented in clinical addictology. Outpatients followed for substance use disorders present shared cognitive, reward-processing, and behavioral vulnerabilities that may heighten their susceptibility to emerging digital dependencies. Eligible adult patients complete a single 15-minute evaluation comprising the Generative Artificial Intelligence Dependency Scale (GAIDS; 11 items rated on a 5-point Likert scale from 1 to 5, total score range: 11 to 55) and the DSM-5 diagnostic criteria checklist for their primary substance of abuse, alongside sociodemographic characteristics. Clinical data, including documented psychiatric comorbidities, are extracted in parallel from electronic health records. Following questionnaire completion, participants receive a dedicated debriefing and clinical restitution interview with an investigator. The primary objective is to evaluate the linear correlation between SUD severity (number of validated DSM-5 criteria, from 0 to 11) and generative artificial intelligence dependency intensity (total raw GAIDS score). Secondary objectives aim to describe generative artificial intelligence dependency levels across specific primary substance classes (alcohol, tobacco, cannabis, cocaine, opioids, etc.), documented comorbid psychiatric disorders (e.g., mood disorders, ADHD, anxiety, personality disorders), and sociodemographic subgroups (age brackets, sex, education, and occupational status).

Gender: All

Ages: 18 Years - Any

Updated: 2026-09-15

Substance-related Disorders
Behavior, Addictive
Artificial Intelligence (AI)
NOT YET RECRUITING

NCT07574021

The Experience of Short Video Addiction Among College Students

This qualitative study aims to explore the experience of short-video addiction among college students using a directed content analysis approach grounded in the integrated framework of the Stimulus-Organism-Response (S-O-R) theory and the Temporal Self-Regulation Theory (TST).

Gender: All

Ages: 18 Years - 30 Years

Updated: 2026-05-07

1 state

Behavior, Addictive
College Student