Treating Depression in Adolescents and Young Adults Using Remote Intensive Outpatient Programs: Quality Improvement Assessment
Notice bibliographique
Résumé
Background Youth and young adults face barriers to mental health care, including a shortage of programs that accept youth and a lack of developmentally sensitive programming among those that do. This shortage, along with the associated geographically limited options, has contributed to the health disparities experienced by youth in general and by those with higher acuity mental health needs in particular. Although intensive outpatient programs can be an effective option for youth with more complex mental health needs, place-based intensive outpatient programming locations are still limited to clients who have the ability to travel to the clinical setting several days per week. Objective The objective of the analysis reported here was to assess changes in depression between intake and discharge among youth and young adults diagnosed with depression attending remote intensive outpatient programming treatment. Analysis of outcomes and the application of findings to programmatic decisions are regular parts of ongoing quality improvement efforts of the program whose results are reported here. Methods Outcomes data are collected for all clients at intake and discharge. The Patient Health Questionnaire (PHQ) adapted for adolescents is used to measure depression, with changes between intake and discharge regularly assessed for quality improvement purposes using repeated measures t tests. Changes in clinical symptoms are assessed using McNamar chi-square analyses. One-way ANOVA is used to test for differences among age, gender, and sexual orientation groups. For this analysis, 1062 cases were selected using criteria that included a diagnosis of depression and a minimum of 18 hours of treatment over a minimum of 2 weeks of care. Results Clients ranged in age from 11 to 25 years, with an average of 16 years. Almost one-quarter (23%) identified as nongender binary and 60% identified as members of the lesbian, gay, bisexual, transgender, queer (LGBTQ+) community. Significant decreases (mean difference –6.06) were seen in depression between intake and discharge (t967=–24.68; P<.001), with the symptoms of a significant number of clients (P<.001) crossing below the clinical cutoff for major depressive disorder between intake and discharge (388/732, 53%). No significant differences were found across subgroups defined by age (F2,958=0.47; P=.63), gender identity (F7,886=1.20; P=.30), or sexual orientation (F7,872=0.47; P=.86). Conclusions Findings support the use of remote intensive outpatient programming to treat depression among youth and young adults, suggesting that it may be a modality that is an effective alternative to place-based mental health treatment. Additionally, findings suggest that the remote intensive outpatient program model may be an effective treatment approach for youth from marginalized groups defined by gender and sexual orientation. This is important given that youth from these groups tend to have poorer outcomes and greater barriers to treatment compared to cisgender, heterosexual youth.
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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 | 0,008 | 0,009 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,002 |
| 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 ».