Implementing a Canadian Shared-Care ADHD Program in Beijing: Barriers and Facilitators To Consider Prior To Start-Up.
Bibliographic record
Abstract
Abstract Background The ADHD Shared Care Pathways is a program that has been developed in Canada with two main strategies: (a) to implement shared care between general practitioners (GPs) and specialists, and (b) to implement stepped care in which the patient is treated at the most appropriate level of care, depending on complexity or outcome of their illness. The current study aims to identify challenges and facilitators in implementing this program in a Chinese context. Methods Two focus groups were conducted using semi-structured interviews with a total of 7 healthcare providers in Beijing. A grounded theory approach using open, axial and selective coding provided three main themes pertaining to the barriers and facilitators faced at: (1) a Social-level from of the perspectives of patients and healthcare providers; (2) at a structural-level related to both internal and external organizational environments; (3) and at the intervention-level. Results Results reveal multilayered challenges in implementing an ADHD Shared Care Pathways program for children in China. Conclusion Our study highlights the importance of consultation in a new implementation context in order to get a “lay of the land”. By extension, our results demonstrate areas for service development and further research.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.009 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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".