Conceptualizing the outcomes of involving people who use mental health services in policy development
Bibliographic record
Abstract
CONTEXT: Inclusion of people who use mental health services in policymaking is a goal of many mental health systems. However, the outcomes of such involvement have not been well articulated or researched. OBJECTIVES: The objectives of this research were to explore how the social and personal outcomes of citizen-user involvement in mental health policymaking were conceptualized by policy actors and to create a conceptual framework to guide the development and evaluation of citizen-user involvement. DESIGN: This qualitative instrumental case study explored the phenomenon of citizen-user involvement using the policy field of mental health and social housing policy in the Province of Manitoba, Canada, as the focal case. PARTICIPANTS: A total of 21 informants from four policy actor groups, citizen-users, representatives of advocacy organizations, government officials and service providers, participated in key informant interviews. Data also included policy documents relevant to the policy field. ANALYSIS: Data collected from interviews and policy documents were analysed using an inductive qualitative paradigm. RESULTS: Participants identified multiple outcomes of citizen-user involvement in policymaking. The resulting conceptual framework illustrated how outcomes in personal, substantive, instrumental and normative dimensions influence micro-, meso- and macrosocial structures. The results also provided a cautionary tale by suggesting how attention needs to be paid to managing the risks as well as optimizing the rewards of involvement. CONCLUSIONS: The framework has application in guiding the development and evaluation of mechanisms that aim to involve citizen-users in policymaking. The framework encourages an approach that takes into account the complexity and multidimensional nature of engaging citizen-users.
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 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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".