Who is in Your Waiting Room? Social Determinants of Health and Adverse Childhood Experiences in Pediatric Surgery Clinics
Bibliographic record
Abstract
BACKGROUND: Social determinants of health (SDoH) influence overall health, although little is known about the SDoH for pediatric patients requiring surgical services. This study aims to describe SDoH for pediatric surgical patients attending out-patient, community, and outreach clinics, as well as demonstrate the feasibility of identifying and addressing SDoH and Adverse Childhood Experiences (ACEs) when appropriate. METHODS: A cross-sectional study using surveys evaluating SDoH that were distributed to families attending pediatric surgical clinics over a two-year period. The pilot survey used validated questions and was later refined to a shorter version with questions on: Barriers to care, Economic factors, Adversity, Resiliency and Social capital (BEARS). Data was analyzed with descriptive and inferential statistics. RESULTS: 851 families across 13 clinics participated. One third of families reported not having a primary health care provider or being unable to turn to them for additional support. One in four families were found to have a household income less than the Canadian after-tax low-income threshold (<$40,000 CAD). Two-thirds of families answered questions about ACEs, and those with more ACEs were more likely to report a low income. Forty percent of families rarely or only sometimes had adequate social support. CONCLUSION: This survey tool enabled discussions between families and care providers, which allowed clinicians to appropriately follow-up with families and refer them to social work for further support when indicated. Addressing concerns around SDoH within a busy surgical clinical is feasible and may positively affect long-term health outcomes and equitable resource allocation. LEVEL OF EVIDENCE: IV.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".