Substance-related DisordersADDICT-IANCT07819851
A Study of the Correlation Between the Severity of Substance Use Disorder and the Intensity of Dependence on Generative Artificial Intelligence
A study testing Questionnaire assessment in people with Substance-related Disorders and Behavior, Addictive, run by Centre Hospitalier Universitaire de Nice at 1 site in France.
Trial summary
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). Read more about this study
- Who is it for?
- Ages 18 years and older
- Conditions the study is for
- Substance-related Disorders, Behavior, Addictive, Artificial Intelligence (AI)
- What is being tested?
- Questionnaire assessment
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 100 participants
- Where
- 1 siteFrance
- Study dates
- 5 Oct 2026to 5 Jun 2027
- Phase
- Interventional
- Are there results?
- Not yet: the study is under way
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 years and older
- All sexes
- No healthy volunteers
- Adult, Older adult
Who may be able to join
- Adult patient (aged 18 years or older), with or without legal protection measures
- Actively followed for a substance use disorder (SUD) characterized according to DSM-5 criteria at a participating specialized addiction care center (Nice University Hospital or Sainte-Marie Hospital in Nice, France).
- Self-reported use of a conversational generative artificial intelligence tool at least once in the past 12 months.
- Ability to understand, read, and complete a self-administered questionnaire in French.
- Oral non-opposition obtained from the patient (and from their legal representative if applicable).
- Affiliated with or beneficiary of a French social security healthcare system.
Who cannot join
- Minor patient (< 18 years old).
- Major neurocognitive disorders, intellectual disability, or acute psychiatric decompensation precluding comprehension or questionnaire completion.
- Explicit opposition to participate expressed by the patient or their legal representative.
- Withdrawal of non-opposition during the study.
- Incomplete questionnaire or clinical record preventing computation of primary scores.
Trial locations and contacts
1 site in 1 country. Contact the study team or a site near you to ask about taking part.
France1 site
CHU de Nice
Nice
Bruno GIORDANA, Dr, 4 92 03 87 75 ext. +33, giordana.b@chu-nice.fr
About this study
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.
Read more
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).
- Being tested
- Questionnaire assessment
- Keywords
- Artificial Intelligence, Addictive behavior, Substance-related disorders
- Medical subject headings
- Substance-Related Disorders, Behavior, Addictive
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Questionnaire assessmentOther
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).
| Study group | Role | What they receive |
|---|---|---|
| CSAPA outpatients using generative AI | Experimental | Not described Receives: Other: Questionnaire assessment |
What is being measured
The primary outcome is the main question the study is designed to answer.
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).
Measured: Baseline (single cross-sectional assessment, Day 0)
Secondary outcomes (3)
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).
Measured: 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).
Measured: 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).
Measured: Baseline (Day 0)
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted15 Sep 2026
- Study start5 Oct 2026 (estimated)
- Primary completion5 Jun 2027 (estimated)
- Study completion5 Jun 2027 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Substance-related DisordersStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Other
- Allocation
- Not applicable
- Intervention model
- Single group
- Masking
- None (open label)
- Enrolment
- 100 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Centre Hospitalier Universitaire de Nice
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07819851
- Sponsor's protocol ID
- 26-PP-15
- Acronym
- ADDICT-IA
- Status last verified
- Sep 2026
- First submitted
- 9 Sep 2026
- Last updated
- 15 Sep 2026
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Study at a glance
From the registry record, last updated by the sponsor on 15 Sep 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- A Study of the Correlation Between the Severity of Substance Use Disorder and the Intensity of Dependence on Generative Artificial Intelligence
- ClinicalTrials.gov ID
- NCT07819851
- Acronym / sponsor ID
- ADDICT-IA / 26-PP-15
- Keywords
- Artificial Intelligence, Addictive behavior, Substance-related disorders
- Study type
- Interventional
- Recruitment status
- Not yet recruiting
- Enrolment
- 100 participants (estimated)
- Lead sponsor
- Centre Hospitalier Universitaire de NiceUniversity, hospital or other
- Study start
- 5 Oct 2026 (estimated)
- Primary completion
- 5 Jun 2027 (estimated)
- Study completion
- 5 Jun 2027 (estimated)
- First posted
- 15 Sep 2026 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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).
Study design
- Primary purpose
- Other
- Allocation
- Not applicable
- Intervention model
- Single group
- Masking
- None (open label)
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| CSAPA outpatients using generative AI | Experimental | Other: Questionnaire assessment |
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
Key inclusion criteria (6 listed)
- Adult patient (aged 18 years or older), with or without legal protection measures
- Actively followed for a substance use disorder (SUD) characterized according to DSM-5 criteria at a participating specialized addiction care center (Nice University Hospital or Sainte-Marie Hospital in Nice, France).
- Self-reported use of a conversational generative artificial intelligence tool at least once in the past 12 months.
- Ability to understand, read, and complete a self-administered questionnaire in French.
- Oral non-opposition obtained from the patient (and from their legal representative if applicable).
Key exclusion criteria (5 listed)
- Minor patient (< 18 years old).
- Major neurocognitive disorders, intellectual disability, or acute psychiatric decompensation precluding comprehension or questionnaire completion.
- Explicit opposition to participate expressed by the patient or their legal representative.
- Withdrawal of non-opposition during the study.
- Incomplete questionnaire or clinical record preventing computation of primary scores.
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Questionnaire assessmentAdministration 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). | Other | CSAPA outpatients using generative AI |
Primary outcome
Correlation coefficient between substance use disorder severity and generative AI dependency
Time frame: Baseline (single cross-sectional assessment, Day 0)
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).
3 secondary outcomes
Generative artificial intelligence dependency score broken down by primary substance
Time frame: Baseline (Day 0)
Generative artificial intelligence dependency score broken down by psychiatric comorbidities
Time frame: Baseline (Day 0)
Generative artificial intelligence dependency score broken down by sociodemographic characteristics
Time frame: Baseline (Day 0)
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 15 Sep 2026.
- Individual participant dataSharing planned: No
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part.
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing Questionnaire assessment in people with Substance-related Disorders and Behavior, Addictive, run by Centre Hospitalier Universitaire de Nice at 1 site in France.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 6 inclusion and 5 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: opening soon, as of the sponsor's last update on 15 Sep 2026. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in France. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
Contact Bruno GIORDANA, Dr (4 92 03 87 75 ext. +33, giordana.b@chu-nice.fr), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Correlation coefficient between substance use disorder severity and generative AI dependency (time frame: Baseline (single cross-sectional assessment, Day 0)). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 15 Sep 2026.