Reconsidering the associations between self-reported alcohol use disorder and mental health problems in the light of co-occurring addictions in young Swiss men
Notice bibliographique
Résumé
BACKGROUND: Alcohol use disorder (AUD) is known to co-occur with other addictions, as well as with mental health problems. However, the effects of other addictions co-occurring with AUD on mental health problems were rarely studied and not considering them may bias estimates of the association between AUD and mental health problems. This study investigated which role co-occurring addictions play for the cross-sectional associations between self-reported AUD and mental health problems. METHOD: Participants were 5516 young Swiss men (73.0% of those that gave written informed consent) who completed a self-report questionnaire. Using short screening questionnaires, we assessed three substance use disorders (alcohol, cannabis and tobacco), seven behavioural addictions (internet, gaming, smartphone, internet sex, gambling, work, exercise) and four mental health problems (major depression, bipolar disorder, attention deficit hyperactivity disorder (ADHD) and social anxiety disorder). Differences in the proportions of mental health problems were tested using logistic regressions between (1) participants with no AUD and AUD, (2) participants with no AUD and AUD alone and (3) participants with no AUD and AUD plus at least one co-occurring addiction. RESULTS: Overall, (1) participants with AUD had higher proportions of major depression (Odds ratio (OR [95% confidence interval]) = 3.51 [2.73, 4.52]; ADHD (OR = 3.12 [2.41, 4.03]); bipolar disorder (OR = 4.94 [3.38, 7.21]) and social anxiety (OR = 2.21 [1.79, 2.73])) compared to participants with no AUD. Considering only participants with AUD alone compared to participants with no AUD (2), differences in proportions were no longer significant for major depression (OR = 0.83 [0.42, 1.64]), bipolar disorder (OR = 1.69 [0.67, 4.22]), social anxiety (OR = 1.15 [0.77, 1.73]) and ADHD (OR = 1.65 [1.00, 2.72]) compared to participants with no AUD. In contrast, (3) proportions of mental health problems were considerably higher for participants with AUD plus at least one other addiction when compared to participants with no AUD, with OR's ranging from 2.90 [2.27, 3.70] for social anxiety, 4.03 [3.02, 5.38] for ADHD, 5.29 [4.02, 6.97] for major depression to 6.64 [4.44, 9.94] for bipolar disorder. CONCLUSIONS: AUD was associated with all four measured mental health problems. However, these associations were mainly due to the high proportions of these mental health problems in participants with AUD plus at least one co-occurring addiction and only to a lesser degree due to participants with AUD alone (i.e. without any other co-occurring addictions). Hence, estimates of the association between AUD and mental health problems that do not consider other addictions may be biased (i.e. overestimated). These findings imply that considering addictions co-occurring with AUD, including behavioural addictions, is important when investigating associations between AUD and mental health problems, and for the treatment of AUD and co-morbid disorders.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».