The social paediatrics initiative: a RICHER model of primary health care for at risk children and their families
Bibliographic record
Abstract
BACKGROUND: The Responsive Interdisciplinary Child-Community Health Education and Research (RICHER) initiative is an intersectoral and interdisciplinary community outreach primary health care (PHC) model. It is being undertaken in partnership with community based organizations in order to address identified gaps in the continuum of health services delivery for 'at risk' children and their families. As part of a larger study, this paper reports on whether the RICHER initiative is associated with increased: 1) access to health care for children and families with multiple forms of disadvantage and 2) patient-reported empowerment. This study provides the first examination of a model of delivering PHC, using a Social Paediatrics approach. METHODS: This was a mixed-methods study, using quantitative and qualitative approaches; it was undertaken in partnership with the community, both organizations and individual providers. Descriptive statistics, including logistic regression of patient survey data (n=86) and thematic analyses of patient interview data (n=7) were analyzed to examine the association between patient experiences with the RICHER initiative and parent-reported empowerment. RESULTS: Respondents found communication with the provider clear, that the provider explained any test results in a way they could understand, and that the provider was compassionate and respectful. Analysis of the survey and in-depth interview data provide evidence that interpersonal communication, particularly the provider's interpersonal style (e.g., being treated as an equal), was very important. Even after controlling for parents' education and ethnicity, the provider's interpersonal style remained positively associated with parent-reported empowerment (p<0.01). CONCLUSIONS: This model of PHC delivery is unique in its purposeful and required partnerships between health care providers and community members. This study provides beginning evidence that RICHER can better meet the health and health care needs of people, especially those who are vulnerable due to multiple intersecting social determinants of health. Positive interpersonal communication from providers can play a key role in facilitating situations where individuals have an opportunity to experience success in managing their and their family's health.
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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 | 0.010 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.006 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".