Piloting CenteringParenting in Two Alberta Public Health Well‐Child Clinics
Bibliographic record
Abstract
OBJECTIVES: To pilot a group health service delivery model, CenteringParenting, for new parents, to assess its feasibility and impact on maternal and infant outcomes. DESIGN AND SAMPLE: Families attended six, 2-hr group sessions in their child's first year of life with three to seven other families. Health assessments, parent-led discussions, and vaccinations occurred within the group. MEASURES: Demographic, breastfeeding, vaccination, maternal psychosocial health, parenting, and satisfaction data were collected and compared to a representative cohort. RESULTS: Four groups ran in two clinics. Four to eight parent/infant dyads participated in each group, 24 total dyads. Most participating parents were mothers. Dyads in the group model received 12 hr of contact with Public Health over the year compared to 3 hr in the typical one-on-one model. Participants were younger, more likely to have lower levels of education, and lower household income than the comparison group. Parents reported improvements in parenting experiences following the program. At 4 months, all CenteringParenting babies were vaccinated compared to 95% of babies in the comparison group. CONCLUSIONS: The pilot was successfully completed. Additional research is required to examine the effectiveness of CenteringParenting. Data collected provide insight into potential primary outcomes of interest and informs larger, rigorously designed longitudinal studies.
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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 | 0.007 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".