The development of a national nutrition and mental health research agenda with comparison of priorities among diverse stakeholders
Bibliographic record
Abstract
OBJECTIVE: To develop a national nutrition and mental health research agenda based on the engagement of diverse stakeholders and to assess research priorities by stakeholder groups. DESIGN: A staged, integrated and participatory initiative was implemented to structure a national nutrition and mental health research agenda that included: (i) national stakeholder consultations to prioritize research questions; (ii) a workshop involving national representatives from research, policy and practice to further define priorities; (iii) triangulation of data to formulate the agenda; and (iv) test hypotheses about stakeholder influences on decision making. SETTING: Canada. SUBJECTS: Diverse stakeholders including researchers, academics, administrators, service providers, policy makers, practitioners, non-profit, industry and funding agency representatives, front-line workers, individuals with lived experience of a mental health condition and those who provide care for them. RESULTS: This first-of-its-kind research priority-setting initiative showed points of agreement among diverse stakeholders (n 899) on research priorities aimed at service provision; however, respondents with lived experience of a mental health condition (themselves or a family member) placed emphasis on prevention and mental health promotion-based research. The final integrated agenda identified four research priorities, including programmes and services, service provider roles, the determinants of health and knowledge translation and exchange. These research priorities aim to identify effective models of care, enhance collaboration, inform policy makers and foster knowledge dissemination. CONCLUSIONS: Since a predictor of research uptake is the involvement of relevant stakeholders, a sustained and deliberate effort must continue to engage collaboration that will lead to the optimization of nutrition and mental health-related outcomes.
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 | 0.017 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.011 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".