Barriers and Facilitators for Referrals of Primary Care Patients to Blended Internet-Based Psychotherapy for Depression: Mixed Methods Study of General Practitioners’ Views
Notice bibliographique
Résumé
BACKGROUND: Major depressive disorder (MDD) is highly prevalent and often managed by general practitioners (GPs). GPs mostly prescribe medication and show low referral rates to psychotherapy. Many patients remain untreated. Blended psychotherapy (bPT) combines internet-based interventions with face-to-face psychotherapy and could increase treatment access and availability. Effectively implementing bPT in routine care requires an understanding of professional users' perspectives and behavior. OBJECTIVE: This study aims to identify barriers and facilitators perceived by GPs in referring patients to bPT. Explanations for variations in referral rates were examined. METHODS: Semistructured interviews were conducted with 12 of 110 GPs participating in a German randomized controlled trial (RCT) to investigate barriers to and facilitators for referrals to bPT for MDD (10 web-based modules, app-based assessments, and 6 face-to-face sessions). The interview guide was based on the theoretical domains framework. The interviews were audio recorded and transcribed verbatim, and the qualitative content was analyzed by 2 independent coders (intercoder agreement, k=0.71). A follow-up survey with 12 interviewed GPs enabled the validation of emergent themes. The differences in the barriers and facilitators identified between groups with different characteristics (eg, GPs with high or low referral rates) were described. Correlations between referrals and characteristics, self-rated competences, and experiences managing depression of the RCT-GPs (n=76) were conducted. RESULTS: GPs referred few patients to bPT, although varied in their referral rates, and interviewees referred more than twice as many patients as RCT-GPs (interview-GPs: mean 6.34, SD 9.42; RCT-GPs: mean 2.65, SD 3.92). A negative correlation was found between GPs' referrals and their self-rated pharmacotherapeutic competence, r(73)=-0.31, P<.001. The qualitative findings revealed a total of 19 barriers (B) and 29 facilitators (F), at the levels of GP (B=4 and F=11), patient (B=11 and F=9), GP practice (B=1 and F=3), and sociopolitical circumstances (B=3 and F=6). Key barriers stated by all interviewed GPs included "little knowledge about internet-based interventions" and "patients' lack of familiarity with technology/internet/media" (number of statements, each k=22). Key facilitators were "perceived patient suitability, e.g. well-educated, young" (k=22) and "no conflict with GP's role" (k=16). The follow-up survey showed a very high agreement rate of at least 75% for 71% (34/48) of the identified themes. Descriptive findings indicated differences between GPs with low and high referral rates in terms of which and how many barriers (low: mean 9.75, SD 1.83; high: mean 10.50, SD 2.38) and facilitators (low: mean 18.25, SD 4.13; high: mean 21.00; SD 3.92) they mentioned. CONCLUSIONS: This study provides insights into factors influencing GPs' referrals to bPT as gatekeepers to depression care. Barriers and facilitators should be considered when designing implementation strategies to enhance referral rates. The findings should be interpreted with care because of the small and self-selected sample and low response rates.
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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 | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| 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
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