Assessing Health Equity in Partnership with Children’s Mental Health Organizations: Considerations Before the Implementation of Parenting Programs
Why this work is in the frame
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Bibliographic record
Abstract
Objectives: Understanding and addressing how an individual's social, political, economic, and cultural context affects their ability to achieve optimal health is essential to designing and implementing interventions. Before evaluating two parenting programs, in partnership with four children's mental health organizations, we used the Health Equity Impact Assessment tool (HEIA) to identify groups that may experience unintended health impacts, as well as generated mitigation strategies to address these impacts. Methods: = 7), and a geographic information systems analysis. All sources of evidence were considered and analyzed using reflective thematic analysis. Summary reports were shared with all partners. Results: A range of groups were identified as at risk of experiencing unintended health impacts, including caregivers who are racialized, immigrants, Indigenous, living with mental health issues or addictions, dealing with intellectual challenges and/or low literacy levels, survivors of childhood trauma, single parent families, or families experiencing financial difficulties. Unintended health impacts were sorted into 6 main themes which fell under the overarching themes of accessibility of the programs and cultural appropriateness. Mitigation strategies as well as innovative strategies already being applied by participating organizations are discussed. Conclusion: Although this HEIA focused on parenting programs, the findings address equity issues applicable to the provision of a wide spectrum of children's mental health services.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 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 it