Nurse practitioners on ‘the leading edge’ of medication abortion care: A feminist qualitative approach
Bibliographic record
Abstract
AIMS: To explore nurse practitioners' experiences of medication abortion implementation in Canada and to identify ways to further support the implementation of medication abortion by nurse practitioners in Canada. DESIGN: A qualitative approach informed by feminist theory and integrated knowledge translation. METHODS: Qualitative interviews with stakeholders and nurse practitioners between January 2020 and May 2021. Data were analysed using critical feminist theory. RESULTS: Participants included 20 stakeholders, 16 nurse practitioner abortion providers, and seven nurse practitioners who did not provide abortions. We found that nurse practitioners conduct educational, communication and networking activities in the implementation of medication abortion in their communities. Nurse practitioners navigated resistance to abortion care in the health system from employers, colleagues and funders. Participants valued making abortion care more accessible to their patients and indicated that normalizing medication abortion in primary care was important to them. CONCLUSION: When trained in abortion care and supported by employers, nurse practitioners are leaders of abortion care in their communities and want to provide accessible, inclusive services to their patients. We recommend nursing curricula integrate abortion services in education, and that policymakers and health administrators partner with nurses, physicians, midwives, social workers and pharmacists, for comprehensive provincial/territorial sexual and reproductive health strategies for primary care. IMPACT: The findings from this study may inform future policy, health administration and curriculum decisions related to reproductive health, and raise awareness about the crucial role of nurse practitioners in abortion care and contributions to reproductive health equity. PATIENT OR PUBLIC CONTRIBUTION: This study focused on provider experiences. In-kind support was provided by Action Canada for Sexual Health & Rights, an organization that provides direct support and resources to the public and is committed to advocating on behalf of patients and the public seeking sexual and reproductive health services.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.025 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.015 | 0.016 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 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".