An interventional study of Questionnaire assessment in Substance-related Disorders, Behavior, Addictive and Artificial Intelligence (AI), sponsored by Centre Hospitalier Universitaire de Nice. Not yet recruiting at 1 site in France. Open to participants aged 18 Years and older. Per ClinicalTrials.gov, last updated 2026-09-15.
Sponsored by Centre Hospitalier Universitaire de Nice · Not applicable, Interventional, and Other
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).
2,238 studies on the registry are indexed under Substance-Related Disorders; 409 are open to participants now.
This study's planned enrollment of 100 is close to the median of 108 across 1,840 interventional studies indexed under Substance-Related Disorders.
Browse Substance-Related Disorders studies →Centre Hospitalier Universitaire de Nice is the lead sponsor of 723 studies on the registry; 176 are open to participants now.
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Go through the criteria one by one — yes, no or not sure — and take the list to your doctor or the study team. Kept in this browser only.
Exclusion Criteria:
Underlined terms in the criteria open these too. Explained by clinicaltrials.gg, not part of the registry record. The study team decides who can take part.
The American Psychiatric Association’s manual of mental health diagnoses. DSM-5 (2013, revised as DSM-5-TR in 2022) replaced DSM-IV, and some studies still name the older edition. “Meets DSM criteria for …” means diagnosed by that edition’s diagnostic criteria, usually by a clinician in an interview.
DSM diagnostic criteria
The American Psychiatric Association’s manual of mental health diagnoses. DSM-5 (2013, revised as DSM-5-TR in 2022) replaced DSM-IV, and some studies still name the older edition. “Meets DSM criteria for …” means diagnosed by that edition’s diagnostic criteria, usually by a clinician in an interview.
Explained by clinicaltrials.gg, not part of the registry record. The study team decides who can take part.
Other: Questionnaire assessment
Administration of a single cross-sectional self-questionnaire assessing generative AI dependency (11-item GAIDS scale), DSM-5 substance use disorder criteria (0 to 11 criteria), and sociodemographic data, followed by a personalized debriefing and clinical restitution interview with an investigator (total duration: approximately 15 minutes).
Correlation coefficient between substance use disorder severity and generative AI dependency
Linear correlation coefficient (Pearson or Spearman, depending on distribution normality) between the number of validated DSM-5 criteria for the primary substance (score ranging from 0 to 11, higher scores indicate greater severity) and the total raw score on 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; higher scores suggest greater dependency).
Time frame: Baseline (single cross-sectional assessment, Day 0)
Generative artificial intelligence dependency score broken down by primary substance
Descriptive statistics (mean +/- standard deviation or median) of the total raw score on 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; higher scores suggest greater dependency) broken down by primary substance classes (alcohol, tobacco, cannabis, cocaine hydrochloride, crack cocaine, opioids, benzodiazepines, amphetamines, other substances).
Time frame: Baseline (Day 0)
Generative artificial intelligence dependency score broken down by psychiatric comorbidities
Descriptive statistics (mean +/- standard deviation or median) of the total raw score on 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; higher scores suggest greater dependency) broken down by documented DSM-5 psychiatric comorbidities (unipolar depressive disorders, bipolar disorders, schizophrenia spectrum and other psychotic disorders, ADHD, ASD, anxiety disorders, OCD, PTSD, borderline personality disorder, antisocial personality disorder, eating disorders, other, or absence of disorder).
Time frame: Baseline (Day 0)
Generative artificial intelligence dependency score broken down by sociodemographic characteristics
Descriptive statistics (mean +/- standard deviation or median) of the total raw score on 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; higher scores suggest greater dependency) broken down by sociodemographic characteristics: age brackets (18-24, 25-39, 40-59, 60+), sex, occupational status (employed, student/in training, unemployed), and highest educational level (less than high school, high school diploma, short higher education, long higher education).
Time frame: Baseline (Day 0)
Plan to share: No
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This study is not yet recruiting, as verified in Sep 2026. You cannot join it, but the record below documents what was studied.
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