Association of illness perceptions and exclusive breastfeeding intentions among pregnant women with chronic conditions: A community-based pregnancy cohort study
Bibliographic record
Abstract
OBJECTIVE: We examined whether changes in illness perceptions from preconception to pregnancy were associated with intentions to exclusively breastfeed to 6 months postpartum among women with chronic physical health conditions. METHODS: We analyzed self-reported cross-sectional questionnaire data collected in the third trimester from 361 women with chronic conditions enrolled in a community-based cohort study (Alberta, Canada). For individual and total illness perceptions, measured with the Brief Illness Perception Questionnaire, women were classified using change scores (preconception minus pregnancy) into one of the following groups: "worsening," "improving," or "stable" in pregnancy. Intention to exclusively breastfeed was defined as plans to provide only breast milk for the recommended first 6 months after birth. We calculated odds ratios (ORs) and 95% confidence intervals (CIs) using multivariable logistic regression modelling, with the "stable" group as the reference and controlling for demographic factors, chronic condition duration and medication, prenatal class attendance, and social support. RESULTS: Overall, 61.8% of women planned to exclusively breastfeed to 6 months. Worsened total illness perceptions (adjusted OR 0.50, 95% CI 0.30-0.82) as well as perceptions of worsened identity (i.e., degree of symptoms; adjusted OR 0.49, 95% CI 0.28-0.85) or consequences (i.e., impact on functioning; adjusted OR 0.60, 95% CI 0.34-1.06) were associated with lower odds of intending to exclusively breastfeed to 6 months. CONCLUSIONS: Women who perceive their illness experience to worsen during pregnancy are less likely to plan to exclusively breastfeed to 6 months in accordance with public health recommendations.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".