Predictors and barriers to minimally adequate treatment among treated individuals with mental disorders: results from the World Mental Health Surveys
Notice bibliographique
Résumé
BACKGROUND: Treatments for mental disorders vary widely in type and quality, with many patients failing to receive treatments that meet even minimally adequate standards. We use data from the World Mental Health (WMH) surveys to investigate this variation by examining the prevalence and correlates of minimally adequate treatment (MAT) among patients receiving treatment for common mental disorders. METHODS: Data comes from 25 WMH cross-sectional surveys implemented in 21 countries (n = 1,838 respondents with n = 3,538 12-month treated disorders). MAT was defined according to widely used criteria: pharmacotherapy (≥ 1 month of medication with ≥ four visits to a healthcare provider) or counseling (≥ eight sessions with any provider). Multivariable regression analyses were used to examine associations of socio-demographic, disorder-related, and treatment-related factors with MAT. RESULTS: Approximately two-thirds (66.2%) of treated cases met MAT criteria. There was limited variation in MAT prevalence across disorder types, number of disorders, or years since disorder onset, but MAT prevalence was positively associated with increased disorder severity. Socio-demographic differences were nonsignificant. Relatively substantial differences in MAT prevalence were found by treatment sector (highest MAT prevalence among patients treated by mental health specialists and those treated by multiple provider types). Further analysis showed that these associations were explained by differences in premature discontinuation, completion of a full course of treatment that did not qualify as MAT, and still being in treatment at the time of interview that did not yet qualify as MAT. Low perceived disorder severity unrelated to more objective measures of severity was a central factor in accounting for premature discontinuation. CONCLUSIONS: While approximately two-thirds of treated cases meet MAT criteria, significant gaps remain involving both premature discontinuation and cases where respondents reported completing a 'full recommended course of treatment' that did not involve enough visits or medication duration to meet the MAT standards. Expanding access to mental health specialty providers and increasing patient education about disorder severity would be useful in increasing the proportion of treated cases that receive MAT. Future research should focus on validating MAT definitions against clinical outcomes, standardizing assessment frameworks, and exploring provider- and system-level determinants of treatment adequacy.
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 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 | 0,003 | 0,011 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 ».