Views of pregnant women and clinicians regarding discussion of exposure to phthalate plasticizers
Bibliographic record
Abstract
OBJECTIVE: This study explores the views of pregnant women and clinicians regarding discussion of exposure to phthalate plasticizers during pregnancy, subsequent to the 2011 Health Canada ban of certain phthalates at a concentration greater than 1000 mg/kg in baby toys. This occurred with no regulation of products to which pregnant women are exposed, such as food packaging and cosmetics. METHODS: Pregnant women, physicians and midwives were recruited through posters and pamphlets in prenatal clinics in Southwestern Ontario for a semi-structured interview. All interviews were audiotaped, transcribed, and subjected to rigorous qualitative analysis through a grounded theory approach, supported by NVIVO™ software. Themes emerged from line by line, open, and axial coding in an iterative manner. RESULTS: Theoretical sufficiency was reached after 23 pregnant women and 11 clinicians had been interviewed. The themes (and subthemes from which they arose) were: Theme I-Information Provision (IA-Sources of Information, IB-Standardization, IC-Constraints, ID-Role of Government); Theme II-Risk (IIA-Significant Risk, IIB-Perceived Relevance, IIC-Reconciliation); and Theme III- Factors Influencing Level of Concern (IIIA-Current Knowledge, IIIB-Demographic Factors). CONCLUSION: To respond to the increasing media and research attention regarding risk of phthalates to women, and pregnant women in particular, national professional organizations should provide patient information. This could include pamphlets on what a pregnant woman should know about phthalates and how they can be avoided, as well as information to clinicians to facilitate this discussion.
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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 | 0.019 | 0.055 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.007 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".