Bibliographic record
Abstract
AIM: To report an analysis of the concept of risk perception in pregnancy. BACKGROUND: Pregnant women are increasingly exposed to the view that pregnancy and childbirth are intrinsically dangerous, requiring medical monitoring and management. Societal pressures are applied to women that dictate appropriate behaviours during pregnancy. These changes have resulted in increased perception of risk for pregnant women. DESIGN: Walker and Avant's method was selected to guide this analysis. DATA SOURCES: Peer-reviewed articles published in English from CINAHL, Scopus, PubMed and Psychinfo. No date limits were applied. METHODS: Thematic analysis was conducted on 79 articles. Attributes, antecedents and consequences of the concept were identified. RESULTS: The attributes of the concept are the possibility of harm to mother or infant and beliefs about the severity of the risk state. The physical condition of pregnancy combined with the cognitive ability to perceive a personal risk state is antecedents. Risk perception in pregnancy influences women's affective state and has an impact on decision-making about pregnancy and childbirth. There are limited empirical referents with which to measure the concept. CONCLUSION: Women today know more about their developing infant than at any other time in history; however, this has not led to a sense of reassurance. Nurses and midwives have a critical role in assisting pregnant women, and their families make sense of the information they are exposed to. An understanding of the complexities of the concept of risk perception in pregnancy may assist in enabling nurses and midwives to reaffirm the normalcy of pregnancy.
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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 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.003 | 0.006 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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".