Clinical and Psychosocial Outcomes Associated With a Tele-behavioral Health Platform for Families: Retrospective Study
Notice bibliographique
Résumé
BACKGROUND: The burden of pediatric mental illness in the United States has steadily worsened over the past decade. A recent increase in employer-sponsored behavioral health programs has focused on the needs of the general population. However, these programs do not provide the specialty mental health care required for children, adolescents, and their families. OBJECTIVE: This study aimed to evaluate the effects of a technology-enabled pediatric and family behavioral health service on clinical outcomes among children and caregiver strain. The service is available to commercially insured populations and provides educational content; tele-behavioral health care, including coaching, therapy, and psychiatry; and care escalation and coordination. METHODS: A retrospective cohort analysis of members using the service between February and September 2022 was conducted. Clinical outcomes for children and their caregivers were collected using the Pediatric Symptom Checklist-17 (PSC-17), Generalized Anxiety Disorder 7-item (GAD-7), Patient Health Questionnaire 8-item (PHQ-8), and Caregiver Strain Questionnaire-Short Form 7 (CGSQ-SF7). Rates of reliable improvement were determined by calculating the reliable change index for each outcome. Paired, 2-tailed t tests were used to evaluate significant changes in assessment scores at follow-up compared to baseline. RESULTS: Of the 4139 participants who enrolled with the service, 48 (1.2%) were referred out for more intensive care, 2393 (57.8%) were referred to coaching, and 1698 (41%) were referred to therapy and psychiatry. Among the 703 members who completed the intervention and provided pre- and postintervention outcomes data, 386 (54.9%) used psychoeducational content, 345 (49.1%) received coaching, and 358 (50.9%) received therapy and psychiatry. In coaching, 75% (183/244) of participants showed reliable improvement on the PSC-17 total score, 72.5% (177/244) on the PSC-17 internalizing score, and 31.5% (105/333) on the CGSQ-SF7 total score (average improvement: PSC-17 total score, 3.37 points; P<.001; PSC-17 internalizing score, 1.58 points; P<.001; and CGSQ-SF7 total score, 1.02 points; P<.001). In therapy and psychiatry, 68.8% (232/337) of participants showed reliable improvement on the PSC-17 total score, 70.6% (238/337) on the PSC-17 internalizing score, 65.2% (219/336) on the CGSQ-SF7 total score, 70.7% (82/116) on the GAD-7 score, and 67.5% (77/114) on the PHQ-8 score (average improvement: PSC-17 total score, 3.16 points; P<.001; PSC-17 internalizing score, 1.66 points; P<.001; CGSQ-SF7 total score, 1.06 points; P<.001; GAD-7 score, 3.00 points; P<.001; and PHQ-8 score, 2.91 points; P<.001). CONCLUSIONS: Tele-behavioral health offerings can be effective in improving caregiver strain and psychosocial functioning and depression and anxiety symptoms in a pediatric population. Moreover, these digital mental health offerings may provide a scalable solution to children and their families who lack access to essential pediatric mental health services.
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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 | 0,004 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| 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 ».