Qualitative Study Exploring Implementation of Digital CBT for Substance Use Disorders in Ontario, Canada: Delivery of “Breaking Free” at Hôtel-Dieu Grace Healthcare in Windsor-Essex
Bibliographic record
Abstract
ABSTRACT Objectives: In December 2020, Hôtel-Dieu Grace Healthcare (HDGH) adopted a digital cognitive behavioral therapy program, “Breaking Free,” to help support people in Windsor-Essex (Ontario, Canada) with substance use disorders. This study used an implementation science framework to conceptualize findings from qualitative interviews conducted with HDGH staff to learn about the barriers and facilitators of the implementation of Breaking Free within HDGH. Methods: Initial interviews with HDGH staff were conducted from May to June 2021; the same staff participated in follow-up interviews conducted from November to December 2021. Results: Initial interviews revealed that staff and clients were receptive to Breaking Free, but that early stages of implementation were challenged by lack of access to technology (Wi-Fi, hardware) and client digital literacy. Staff also suggested that other competing priorities for their time affected their ability to integrate Breaking Free into existing HDGH programs. Facilitators to client engagement with the program included staff providing consistent messaging on the benefits of Breaking Free, acquiring hardware to deliver the program on (tablets, computers, color printers), and having strong relationships across HDGH programs to support continued delivery. Conclusions: This study has demonstrated that although the initial implementation of new digital health technologies within health care systems can be challenging, with the appropriate resources in place and support for staff and clients, implementation and engagement can be achieved, though this process may take some time. Objectifs: En décembre 2020, Hôtel-Dieu Grace Healthcare (HDGH) a adopté un programme numérique de thérapie cognitivo-comportementale, « Breaking Free », pour offrir du support aux personnes de Windsor-Essex (Ontario, Canada) souffrant de troubles liés à la consommation de substances. Cette étude a utilisé comme cadre de travail la science de la mise en œuvre pour conceptualiser les résultats des entretiens qualitatifs menés avec le personnel de l’HDGH, afin de comprendre les obstacles et les facteurs favorisant la mise en œuvre de Breaking Free au sein de de l’HDGH. Méthodes: Les entretiens initiaux avec le personnel de l’HDGH ont eu lieu de mai à juin 2021, puis le même personnel a participé à des entretiens de suivi menés de novembre à décembre 2021. Résultats: Les entretiens initiaux ont révélé que le personnel et les clients étaient réceptifs à Breaking Free, mais que les premières étapes de la mise en œuvre ont été entravées par le manque d’accès à la technologie (Wi-Fi, matériel informatique) et par la culture numérique des clients. Le personnel a également suggéré que d’autres priorités en concurrence pour leur temps ont affecté leur capacité à intégrer Breaking Free dans les programmes existants de l’HDGH. Les facilitateurs de l’engagement des clients dans le programme étaient le personnel fournissant des messages cohérents sur les avantages de Breaking Free, l’acquisition de matériel pour offrir le programme (tablettes, ordinateurs, imprimantes couleur), ainsi que l’existence de relations solides entre les programmes de l’HDGH pour soutenir la poursuite de l’exécution. Conclusions: Cette étude a démontré que, bien que la mise en œuvre initiale de nouvelles technologies numériques de santé puisse être difficile dans les systèmes de soins de santé, avec les ressources appropriées en place et le soutien du personnel et des clients, la mise en œuvre et l’engagement peuvent être réalisés, même si ce processus peut prendre un certain temps.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".