Effective Treatment for Mental and Substance Use Disorders in 21 Countries
Notice bibliographique
Résumé
Importance: Accurate baseline information about the proportion of people with mental disorders who receive effective treatment is required to assess the success of treatment quality improvement initiatives. Objective: To examine the proportion of mental and substance use disorders receiving guideline-consistent treatment in multiple countries. Design, Setting, and Participants: In this cross-sectional study, World Mental Health (WMH) surveys were administered to representative adult (aged 18 years and older) household samples in 21 countries. Data were collected between 2001 and 2019 and analyzed between February and July 2024. Twelve-month prevalence and treatment of 9 DSM-IV anxiety, mood, and substance use disorders were assessed with the Composite International Diagnostic Interview. Effective treatment and its components were estimated with cross-tabulations. Multilevel regression models were used to examine predictors. Main Outcomes and Measures: The main outcome was proportion of effective treatment received, defined at the disorder level using information about disorder severity and published treatment guidelines regarding adequate medication type, control, and adherence and adequate psychotherapy frequency. Intermediate outcomes included perceived need for treatment, treatment contact separately in the presence and absence of perceived need, and minimally adequate treatment given contact. Individual-level predictors (multivariable disorder profile, sex, age, education, family income, marital status, employment status, and health insurance) and country-level predictors (treatment resources, health care spending, human development indicators, stigma, and discrimination) were traced through intervening outcomes. Results: Among the 56 927 respondents (69.3% weighted average response rate), 32 829 (57.7%) were female; the median (IQR) age was 43 (31-57) years. The proportion of 12-month person-disorders receiving effective treatment was 6.9% (SE, 0.3). Low perceived need (46.5%; SE, 0.6), low treatment contact given perceived need (34.1%; SE, 1.0), and low effective treatment given minimally adequate treatment (47.0%; SE, 1.7) were the major barriers, but with substantial variation across disorders. Country-level general medical treatment resources were more important than mental health treatment resources. Other than for the multivariable disorder profile, which was associated with all intermediate outcomes, significant predictors were largely mediated by treatment contact. Conclusions and Relevance: In addition to the gaps in treatment quality, these results highlight the importance of increasing perceived need, the largest barrier to effective treatment; the importance of training primary care treatment clinicians in recognition and treatment of mental disorders; the need to improve the continuum of care, especially from minimally adequate to effective treatment; and the importance of bridging the effective treatment gap for men and people with lower education.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 tête enseignante, 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 ».