An integrative review of Canadian childhood obesity prevention programmes
Bibliographic record
Abstract
To examine successful Canadian nursing and health promotion intervention programmes for childhood obesity prevention during gestation and infancy, an integrative review was performed of the literature from 1980 to September 2005. The following databases were used: PubMed; Cochrane Database of Systematic Reviews; Cochrane Controlled Trials Register; Database of Abstracts of Reviews of Effects; ACP Journal Club; MEDLINE; EMBASE; CINAHL; Web of Science; Scopus; Sociological Abstracts; Sport Discus; PsycInfo; ERIC and HealthStar. MeSH headings included: infancy (0-24 months), gestation, gestational diabetes, nutrition, prenatal care, pregnancy, health education, pregnancy outcome, dietary services with limits of Canadian, term birth. Of 2028 articles found, six Canadian childhood obesity prevention programmes implemented during gestation and/or infancy were found; three addressed gestational diabetes with five targeting low-income Canadian urban and/or Aboriginal populations. No intervention programmes specifically aimed to prevent childhood obesity during gestation or infancy. This paucity suggests that such a programme would be innovative and much needed in an effort to stem the alarming increase in obesity in children and adults. Any attempts either to develop new approaches or to replicate interventions used with obese adults or even older children need careful evaluation and pilot testing prior to sustained use within the perinatal period.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.008 | 0.022 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.021 | 0.036 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 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".