“During pregnancy would have been a good time to get that information”: mothers’ concerns and information needs regarding environmental health risks to their children
Bibliographic record
Abstract
Day-to-day exposures to environmental toxicants during the prenatal and early childhood period are risk factors for a range of developmental conditions, yet women often receive little or no information about these risks or protective actions. To inform the development of effective educational strategies, this study examines mothers’ environmental health concerns and protective behaviours, and explores perspectives on environmental health information needs and preferences. Using a qualitative study design, data collection involved semi-structured, face-to-face interviews with mothers of varied ages, incomes, and education levels in Ottawa, Canada. Participants were recruited from among new mothers who took part in a related survey. Interviews were digitally recorded, transcribed verbatim and analysed using thematic analysis. Reported concerns included air pollution, toxic cleaners, pesticides and food preservatives. Most took at least some protective actions but reported barriers to taking others: insufficient or excessive concern, social stigma associated with being over-protective, financial constraints, a lack of safe choices and distrust of information sources. Although mothers most commonly received information from the internet, a preference for information from prenatal care providers was identified. Few reported receiving information from this source. Results further suggest that educational efforts would have the greatest impact during the early stages of pregnancy. This study highlights the need for environmental health education that is appropriately timed, comes from trusted sources and promotes accessible and affordable protective actions. These results are important for the development of educational strategies to reduce early life exposures and improve health over the life-course.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.003 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".