Impact of the Jamaican birth cohort study on maternal, child and adolescent health policy and practice
Bibliographic record
Abstract
The Jamaica Perinatal Morbidity and Mortality Survey (JPMMS) was a national study designed to identify modifiable risk factors associated with poor maternal and perinatal outcome. Needing to better understand factors that promote or retard child development, behaviour and academic achievement, we conducted follow-up studies of the birth cohort. The paper describes the policy developments from the JPMMS and two follow-up rounds. The initial study (1986-87) documented 94% of all births and their outcomes on the island over 2 months (n = 10 508), and perinatal (n = 2175) and maternal deaths (n = 62) for a further 10 months. A subset of the birth cohort, identified by their date of birth through school records, was seen at ages 11-12 (n = 1715) and 15-16 years (n = 1563). Findings from the initial survey led to, inter alia, clinic-based screening for syphilis, referral high-risk clinics run by visiting obstetricians, and the redesign and construction of new labour wards at referral hospitals. The follow-up studies documented inadequate academic achievement among boys and children attending public schools, and associations between under- and over-nutrition, excessive television viewing (>20 h/week), inadequate parental supervision and behavioural problems. These contributed to the development of a television programming code for children, a National Parenting Policy, policies aimed at improving inter-sectoral services to children from birth to 5 years (Early Childhood Commission) and behavioural interventions of the Violence Prevention Alliance (an inter-sectoral NGO) and the Healthy Lifestyles project (Ministry of Health). Indigenous maternal and child health research provided a local evidence base that informed public policy. Collaboration, good communication, being vigilant to opportunities to influence policy, and patience has contributed to our success.
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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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".