Organizational Readiness for Implementing an Internet-Based Cognitive Behavioral Therapy Intervention for Depression Across Community Mental Health Services in Albania and Kosovo: Directed Qualitative Content Analysis
Notice bibliographique
Résumé
BACKGROUND: The use of digital mental health programs such as internet-based cognitive behavioral therapy (iCBT) holds promise in increasing the quality and access of mental health services. However very little research has been conducted in understanding the feasibility of implementing iCBT in Eastern Europe. OBJECTIVE: The aim of this study was to qualitatively assess organizational readiness for implementing iCBT for depression within community mental health centers (CMHCs) across Albania and Kosovo. METHODS: We used qualitative semistructured focus group discussions that were guided by Bryan Weiner's model of organizational readiness for implementing change. The questions broadly explored shared determination to implement change (change commitment) and shared belief in their collective capability to do so (change efficacy). Data were collected between November and December 2017. A range of health care professionals working in and in association with CMHCs were recruited from 3 CMHCs in Albania and 4 CMHCs in Kosovo, which were participating in a large multinational trial on the implementation of iCBT across 9 countries (Horizon 2020 ImpleMentAll project). Data were analyzed using a directed approach to qualitative content analysis, which used a combination of both inductive and deductive approaches. RESULTS: Six focus group discussions involving 69 mental health care professionals were conducted. Participants from Kosovo (36/69, 52%) and Albania (33/69, 48%) were mostly females (48/69, 70%) and nurses (26/69, 38%), with an average age of 41.3 years. A directed qualitative content analysis revealed several barriers and facilitators potentially affecting the implementation of digital CBT interventions for depression in community mental health settings. While commitment for change was high, change efficacy was limited owing to a range of situational factors. Barriers impacting "change efficacy" included lack of clinical fit for iCBT, high stigma affecting help-seeking behaviors, lack of human resources, poor technological infrastructure, and high caseload. Facilitators included having a high interest and capability in receiving training for iCBT. For "change commitment," participants largely expressed welcoming innovation and that iCBT could increase access to treatments for geographically isolated people and reduce the stigma associated with mental health care. CONCLUSIONS: In summary, participants perceived iCBT positively in relation to promoting innovation in mental health care, increasing access to services, and reducing stigma. However, a range of barriers was also highlighted in relation to accessing the target treatment population, a culture of mental health stigma, underdeveloped information and communications technology infrastructure, and limited appropriately trained health care workforce, which reduce organizational readiness for implementing iCBT for depression. Such barriers may be addressed through (1) a public-facing campaign that addresses mental health stigma, (2) service-level adjustments that permit staff with the time, resources, and clinical supervision to deliver iCBT, and (3) establishment of a suitable clinical training curriculum for health care professionals. TRIAL REGISTRATION: ClinicalTrials.gov NCT03652883; https://clinicaltrials.gov/ct2/show/NCT03652883.
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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 | 0,009 | 0,011 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,002 | 0,002 |
| Études des sciences et des technologies | 0,004 | 0,003 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,001 | 0,003 |
| 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 ».