Barriers and Facilitators to the Implementation of an Integrated Youth Services Network in Ontario
Bibliographic record
Abstract
Introduction: In response to the challenges of the traditional mental health system for youth both in Canada and abroad, models of integrated youth services (IYS) that span the integration of mental health, health, substance use, eucation, employment, peer support, and navigation into 'one-stop shops' are being established nationally and internationally. IYS models, however, need to be better described and evaluated to inform the replicability of this approach in other jurisdictions. Description: This paper describes the implementation of an IYS in a small urban city and rural county in Ontario, Canada, including insights from key informants into barriers, facilitators, and lessons learned. Discussion: This evaluation identified a number of barriers and facilitators to the implementation of the IYS model in this specific context. Implementation facilitators included youth and family engagement, network partner collaboration, leadership, governance structure, community enthusiasm and support, and collaborative funding models. Barriers to implementation included the COVID-19 pandemic and related public health restrictions, the diverse needs of youth, change management, sustainable funding, and transportation. Lessons learned: By establishing a shared vision of delivering youth services across the integrated network, and engaging youth early in the process of model development, IYS have the potential to transform the service system for youth and their families. Meeting the diverse needs and challenges of youth who live in rural or small urban communities will enhance service delivery and experience for young people.
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 | 0.007 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".