From Planning to Implementation of the YouthCan IMPACT Project: a Formative Evaluation
Bibliographic record
Abstract
In order to improve the youth mental health system, there is an international movement toward developing community-based service hubs that provide integrated, collaborative care to youth. However, the implementation of multisystem collaboration is complex and can be hampered by barriers. This paper presents a formative evaluation of the YouthCan IMPACT integrated youth services project based on the Consolidated Framework for Implementation Research (CFIR), to identify facilitators and barriers to successful implementation. Results highlight that previous positive working relationships along with collaborative investment of resources from partnering organizations are essential to implement an integrated youth service model. In addition, it is important that representative members of all key stakeholder groups, including staff, youth, and caregivers, be involved in the development and execution of the project to ensure effective implementation. Attention to the facilitators and barriers to implementation may help teams seeking to implement highly collaborative, integrated models of service delivery for youth in the community.
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 | 0.264 | 0.280 |
| Meta-epidemiology (narrow) | 0.004 | 0.003 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.006 | 0.013 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".