An Internet-Delivered Cognitive Behavioral Therapy for Depression and Anxiety Among Clients Referred and Funded by Insurance Companies Compared With Those Who Are Publicly Funded: Longitudinal Observational Study
Notice bibliographique
Résumé
BACKGROUND: Anxiety and depression are leading causes of disability but are often undertreated. Internet-delivered cognitive behavioral therapy (ICBT) improves access to treatment by overcoming barriers to obtaining care. ICBT has been found to be efficacious in research trials and routine care, but there is limited research of ICBT when it is recommended and funded by insurance companies for clients on or recently in receipt of disability benefits or accommodations. OBJECTIVE: The aim of this study was to examine ICBT engagement, treatment satisfaction, and effectiveness among individuals involved with 2 insurance companies. The 2 samples were benchmarked against published outcomes from a publicly funded (PF) ICBT clinic. METHODS: Individuals who were on or recently in receipt of disability benefits and were either insurance company (IC) employees (n=21) or IC plan members (n=19) were referred to ICBT funded by the respective insurance companies. Outcomes were benchmarked against outcomes of ICBT obtained in a PF ICBT clinic, with clients in the clinic divided into those who reported no involvement with insurance companies (n=414) and those who were on short-term disability (n=44). All clients received the same 8-week, therapist-assisted, transdiagnostic ICBT course targeting anxiety and depression. Engagement was assessed using completion rates, log-ins, and emails exchanged. Treatment satisfaction was assessed posttreatment. Depression, anxiety, and disability measures were administered pretreatment, posttreatment, and at 3 months. RESULTS: All samples showed high levels of ICBT engagement and treatment satisfaction. IC employees experienced significant improvement at posttreatment (depression d=0.77; anxiety d=1.13; and disability d=0.91) with outcomes maintained at 3 months. IC plan members, who notably had greater pretreatment disability than the other samples, experienced significant moderate effects at posttreatment (depression d=0.58; anxiety d=0.54; and disability d=0.60), but gains were not maintained at 3 months. Effect sizes at posttreatment in both IC samples were significantly smaller than in the PF sample who reported no insurance benefits (depression d=1.14 and anxiety d=1.30) and the PF sample who reported having short-term disability benefits (depression d=0.95 and anxiety d=1.07). No difference was seen in effect sizes among IC employees and the PF samples on disability. However, IC plan members experienced significantly smaller effects on disability d=0.60) compared with the PF sample with no disability benefits d=0.90) and those on short-term disability benefits d=0.94). CONCLUSIONS: Many clients referred and funded by insurance companies were engaged with ICBT and found it acceptable and effective. Results, however, were not maintained among those with very high levels of pretreatment disability. Small sample sizes in the IC groups are a limitation. Directions for research related to ICBT funded by insurance companies have been described.
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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 | 0,002 | 0,005 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,002 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,001 |
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 ».