Cost Utility Analysis of Internet-Based Cognitive Behavioral Therapy for Major Depressive Disorder: Randomized Controlled Trial
Notice bibliographique
Résumé
BACKGROUND: Unguided internet-based cognitive behavioral therapy (ICBT) has been proven effective for major depressive disorder (MDD). However, few studies have examined its cost-effectiveness in low-resource countries and under nonspecialist routine care. OBJECTIVE: This study aimed to evaluate the short- and long-term cost utility of unguided ICBT compared to a waitlist control for persons with MDD from the perspectives of society and the health care system. METHODS: This analysis was implemented alongside an 8-week 2-arm randomized controlled trial with a 12-month follow-up period conducted in Shenzhen, China. Outcomes including cost and health utility were collected at the pretreatment and posttreatment time points and 3, 6, and 12 months after the intervention. Direct medical costs and indirect costs were prospectively collected using the hospital information system and the Sheehan Disability Scale. Health outcomes were measured using the Chinese version of the Short-Form Six-Dimension health index. The primary outcome was incremental cost utility ratio (ICUR) expressed as the difference in costs between 2 therapies by the difference in quality-adjusted life years (QALYs). The seemingly unrelated regression model and the bootstrap method were performed to estimate adjusted ICURs. Cost-effectiveness planes and cost-effectiveness acceptability curves were used to demonstrate uncertainty. A series of scenario analyses were conducted to verify the robustness of base-case results. RESULTS: In total, 244 participants with MDD were randomly allocated to the ICBT (n=122, 50%) or waitlist control (n=122, 50%) groups. At the pretreatment time point, no statistically significant difference was observed in direct medical cost (P=.41), indirect cost (P=.10), or health utility (P=.11) between the 2 groups. In the base-case analysis, the ICBT group reported higher direct medical costs and better quality of life but lower total costs at the posttreatment time point. The adjusted ICURs at the posttreatment time point were CN ¥-194,720.38 (US $-26,551.50; 95% CI CN ¥-198,766.78 to CN ¥-190,673.98 [US $-27,103.20 to US $-25,999.70]) and CN ¥49,700.33 (US $6776.99; 95% CI CN ¥46,626.34-CN ¥52,774.31 [US $6357.83-$7196.15]) per QALY from the societal and health care system perspectives, respectively, with a probability of unguided ICBT being cost-effective of 75.93% and 54.4%, respectively, if the willingness to pay was set at 1 time the per-capita gross domestic product. In the scenario analyses, the probabilities increased to 76.85% and 77.61%, respectively, indicating the potential of ICBT to be cost-effective over the long term. CONCLUSIONS: Unguided ICBT is a cost-effective treatment for MDD. This intervention not only helps patients with MDD improve clinically but also generates societal savings. These findings provide health economic evidence for a potential scalable MDD treatment method in low- and middle-income countries. TRIAL REGISTRATION: Chinese Clinical Trial Registry (ChiCTR) ChiCTR2100046425; https://tinyurl.com/bdcrj4zv.
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 | 0,006 | 0,011 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,005 | 0,006 |
| Bibliométrie | 0,002 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,002 | 0,001 |
| Intégrité de la recherche | 0,002 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,007 | 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 ».