Challenges of adopting the role of care manager when implementing the collaborative care model for people with common mental illnesses: A scoping review
Bibliographic record
Abstract
This review aimed to identify the main factors influencing the adoption of the role of care manager (CM) by nurses when implementing the collaborative care model (CCM) for common mental illnesses in primary care settings. A total of 19 studies met the inclusion criteria, reporting on 14 distinct interventions implemented between 2000 and 2017 in five countries. Two categories of factors were identified and described as follows: (i) strategies for the CCM implementation (e.g. initial care management training and supervision by a mental health specialist) and (ii) context-specific factors (e.g. organizational factors, collaboration with team members, nurses' care management competency). Identified implementation strategies were mainly aimed towards improving the nurse's care management competency, but their efficacy in developing the set of competencies needed to fulfil a CM role was not well demonstrated. There is a need to better understand the relationship between the nurses' competencies, the care management activities, the strategies used to implement the CCM and the context-specific factors. Strategies to optimize the adoption of the CM role should not be solely oriented towards the individual's competency in care management, but also consider other context-specific factors. The CM also needs a favourable context in order to perform his or her activities with competency.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".