Mixed-method evaluation of a community-based postpartum support program: a study protocol
Bibliographic record
Abstract
INTRODUCTION: Becoming a parent is one of the most significant events an individual will experience in their lifetime. The postpartum period can be a difficult time, especially for mothers, who may require extra support during this challenging time. The proposed study seeks to understand the issue of postpartum support for mothers and their families. It will address this aim by using the Mothercraft Ottawa Postpartum Support Drop-in Program as real-life illustration of a community-based service organisation delivering these services. METHODS AND ANALYSIS: A three-phased mixed-method programme evaluation guided by the Reach, Effectiveness, Adoption, Implementation, and Maintenance (RE-AIM) evaluation framework and the tenets of community-based participatory research. Instrumental case study methodology will be employed to gain an in-depth understanding of what impact(s) the programme is having on mothers, their partners and their families (phase I-qualitative). A questionnaire, regression modelling, and geospatial analysis will be conducted to gain a deeper understanding of specific programme outputs and to generate information that will help inform programme reach (phase II-quantitative). Study phase III will focus on knowledge translation activities to stakeholders and the broader academic community. ETHICS AND DISSEMINATION: Ethics approval was granted by the University of Ottawa Research Ethics Board (H-12-18-1492). The results of this study will be disseminated at a community workshop, in an academic thesis, at academic conferences and in peer-reviewed publications.
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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 | 0.164 | 0.085 |
| Meta-epidemiology (narrow) | 0.004 | 0.003 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.006 | 0.005 |
| Research integrity | 0.007 | 0.006 |
| Insufficient payload (model declined to judge) | 0.037 | 0.008 |
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".