Stakeholder perspectives on implementation of internet-delivered cognitive behaviour therapy in physical medicine rehabilitation setting using the Consolidated Framework for Implementation Research
Bibliographic record
Abstract
INTRODUCTION: Despite the growing evidence for the effects of tailored internet-delivered cognitive behaviour therapy (ICBT) programmes for those receiving physical rehabilitation, there is a lack of implementation of these programmes in a clinical or community setting. The aim of the current study was to evaluate barriers and facilitators of implementing an ICBT programme into a physical medicine rehabilitation setting. METHODS: Stakeholders with expertise in physical medicine rehabilitation were recruited (n = 25) including: 16 clinicians, 4 administrators, 3 persons with lived experience, and 2 care partners. Individual semi-structured interviews were conducted based on the domains of the Consolidated Framework for Implementation Research (CFIR). Transcripts were analysed using a positivist approach, using deductive thematic content analysis. Themes were coded based on the domains of CFIR. RESULTS: Facilitators for implementation primarily fell under intervention characteristics including relative advantage, strong evidence and quality, and design quality. Perceived barriers for implementation were identified in the inner setting including leadership engagement, culture, and available resources. CONCLUSIONS: The results from the current study provide insight on the factors that may contribute towards successful implementation of an ICBT programme in a physical medicine setting.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.183 | 0.116 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.007 | 0.010 |
| Scholarly communication | 0.010 | 0.007 |
| Open science | 0.003 | 0.009 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".