Implementation in mental health systems
Bibliographic record
Abstract
Effectively addressing mental health and substance use problems are important challenges faced globally. People experiencing such problems encounter many societal barriers that can affect their ability to participate as full members of society and have life expectancies much shorter than the general population. Policies to address mental health and substance use problems require the mobilization of multiple sectors, such as health, education, and justice. While there is strong evidence for programs and services that work, and there are policy directions aimed at achieving better service experiences and improved health and social outcomes, there is a lack of knowledge about how to get these policies and programs embedded effectively into daily practice – a process called implementation. The objective of this dissertation is to advance the understanding of implementation strategies for addressing such complex challenges through five original scientific contributions. The first is a critical interpretive synthesis of existing literature to generate a theoretical framework of the implementation process from the perspective of a policy goal by integrating findings from the public policy, implementation science and knowledge translation fields. Next is a two-part comparative case study exploring how policy implementation was structured and the strategies used in large, well-developed mental health systems. Last is a two-part in-depth examination of mental health policy implementation efforts in Ontario, Canada, beginning with an analysis of the development and implementation of the province’s mental health strategy, followed by an examination of the role that citizens and other stakeholder groups played in its implementation. Together these studies contribute theoretical, substantive and methodological insights toward understanding the effective implementation of policy directions for complex social challenges. Better implementation means more citizens can benefit from effective policies and programs that are needed across populations.
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 | 0.031 | 0.059 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.010 | 0.010 |
| Scholarly communication | 0.016 | 0.009 |
| Open science | 0.004 | 0.019 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.031 | 0.002 |
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".