Rhesus D factor (RhD) negative women’s experiences with pregnancy: An interpretive description
Bibliographic record
Abstract
BACKGROUND: The development of rh immune globulin (RhIG) for the prevention of Rhesus D (RhD) alloimmunization has significantly decreased the incidence of RhD alloimmunization. Despite long-standing prevention, the experiences of RhD negative women with pregnancy is absent in the literature. AIM: The purpose of this study was to explore the experiences of RhD negative women with pregnancy. METHODS: Utilizing an Interpretive Description approach, semi-structured interviews were conducted with RhD negative women about their pregnancies. This study took place within the geographic context of northern British Columbia (BC). The analysis involved a two-cycle approach to identify themes within the data. FINDINGS: Sixteen RhD negative women that live in northern BC participated in this study. The analysis identified that RhD negative women are uninformed and want to be involved in the decision-making process regarding the prevention of RhD alloimmunization. The themes that emerged from the interview data were communication, information-seeking behaviour, out of sight out of mind, choice and trust, and patient advocacy. DISCUSSION: The participants in this study described lacking information regarding the prevention of RhD alloimmunization. They sought information to overcome the gaps in knowledge and a desire to be involved in the decision-making process. CONCLUSION: RhD negative women want information and to be involved in the decision-making process in the prevention of RhD alloimmunization. Working with RhD negative women to develop decision-aids and/or other educational tools to aid in the decision-making process are warranted.
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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 | 0.009 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.010 | 0.014 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.002 | 0.004 |
| 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".