A Study of the Correlation Between the Severity of Substance Use Disorder and the Intensity of Dependence on Generative Artificial Intelligence (ADDICT-IA)
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).
Visão geral do estudo
Status
Condições
Intervenção / Tratamento
Tipo de estudo
Inscrição (Estimado)
Estágio
- Não aplicável
Contactos e Locais
Contato de estudo
- Nome: Bruno GIORDANA, Dr
- Número de telefone: +33 4 92 03 87 75
- E-mail: giordana.b@chu-nice.fr
Locais de estudo
-
-
-
Nice, França
- Chu De Nice
-
Contato:
- Bruno GIORDANA, Dr
- Número de telefone: +33 4 92 03 87 75
- E-mail: giordana.b@chu-nice.fr
-
-
Critérios de participação
Critérios de elegibilidade
Idades elegíveis para estudo
- Adulto
- Adulto mais velho
Aceita Voluntários Saudáveis
Descrição
Inclusion Criteria:
- 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.
Exclusion Criteria:
- 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.
Plano de estudo
Como o estudo é projetado?
Detalhes do projeto
- Finalidade Principal: Outro
- Alocação: N / D
- Modelo Intervencional: Atribuição de grupo único
- Mascaramento: Nenhum (rótulo aberto)
Armas e Intervenções
Grupo de Participantes / Braço |
Intervenção / Tratamento |
|---|---|
|
Experimental: CSAPA outpatients using generative AI
|
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).
|
O que o estudo está medindo?
Medidas de resultados primários
Medida de resultado |
Descrição da medida |
Prazo |
|---|---|---|
|
Correlation coefficient between substance use disorder severity and generative AI dependency
Prazo: 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).
|
Baseline (single cross-sectional assessment, Day 0)
|
Medidas de resultados secundários
Medida de resultado |
Descrição da medida |
Prazo |
|---|---|---|
|
Generative artificial intelligence dependency score broken down by primary substance
Prazo: Baseline (Day 0)
|
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).
|
Baseline (Day 0)
|
|
Generative artificial intelligence dependency score broken down by psychiatric comorbidities
Prazo: Baseline (Day 0)
|
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).
|
Baseline (Day 0)
|
|
Generative artificial intelligence dependency score broken down by sociodemographic characteristics
Prazo: Baseline (Day 0)
|
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).
|
Baseline (Day 0)
|
Colaboradores e Investigadores
Patrocinador
Datas de registro do estudo
Datas Principais do Estudo
Início do estudo (Estimado)
Conclusão Primária (Estimado)
Conclusão do estudo (Estimado)
Datas de inscrição no estudo
Enviado pela primeira vez
Enviado pela primeira vez que atendeu aos critérios de CQ
Primeira postagem (Real)
Atualizações de registro de estudo
Última Atualização Postada (Real)
Última atualização enviada que atendeu aos critérios de controle de qualidade
Última verificação
Mais Informações
Termos relacionados a este estudo
Termos MeSH relevantes adicionais
Outros números de identificação do estudo
- 26-PP-15
Plano para dados de participantes individuais (IPD)
Planeja compartilhar dados de participantes individuais (IPD)?
Informações sobre medicamentos e dispositivos, documentos de estudo
Estuda um medicamento regulamentado pela FDA dos EUA
Estuda um produto de dispositivo regulamentado pela FDA dos EUA
Essas informações foram obtidas diretamente do site clinicaltrials.gov sem nenhuma alteração. Se você tiver alguma solicitação para alterar, remover ou atualizar os detalhes do seu estudo, entre em contato com register@clinicaltrials.gov. Assim que uma alteração for implementada em clinicaltrials.gov, ela também será atualizada automaticamente em nosso site .