Improving experience of medical abortion at home in a changing therapeutic, technological and regulatory landscape: a realist review
Bibliographic record
Abstract
Abstract Objectives To synthesise evidence on user experience of medical abortion at home To develop a realist programme theory to explain what interventions improve user experience for whom and in what context. To use this programme theory to develop recommendations for service providers and those having medical abortions at home Background Changes in the therapeutic, technological and regulatory landscape are increasing access to medical abortion at home. This intervention is safe, effective and acceptable to most. Clinical pathways and user experience are nevertheless variable and a minority would not choose this method again. We synthesised evidence to inform service development and responsiveness for different people and contexts. Methods We used a realist approach to literature review that starts from an initial programme theory and generates causal explanations in the form of context-mechanism-outcome configurations to test and develop that theory. We searched the literature 01/01/2000 - 09/12/2022 using broad search terms and then selected papers for their relevance to theory development in contexts relevant to service development in the UJ. Data were analysed using a realist approach to analysis to develop causal explanations. Results Our searches identified 12,517 potentially relevant abstracts with 835 selected for the full text assessment and 49 papers included in the final review. Our synthesis suggests that having a choice of abortion location remains essential as some people are unable to have a medical abortion at home. Choice of place of abortion (home or clinical setting) was influenced by service factors (number, timing and wait for appointments), personal responsibilities (caring/work commitments), geography (travel time/distance), relationships (need for secrecy) and wish to be aware of/involved in the process. We found that the option for self-referral through a telemedicine consultation, realistic information on range of experiences, opportunities to personalise the process, improved pain relief and choice of when and how to discuss contraception could improve experience. Discussion Acknowledging the work done by patients when moving an intervention from clinic to home is important. This includes preparing a space, managing privacy, managing work/caring obligations, deciding when/how to take medications, understanding what is normal, assessing experience and deciding when and how to ask for help. Strategies that reduce surprise or anxiety and enable preparation and a sense of control support the transition of this complex intervention outside healthcare environments. Strenghts and limitations – Strengths: systematic and transparent approach to the realist review, which was conducted in accordance with the RAMSES standards (27); Authorship team represents a variety of clinical and academic backgrounds – Limitations: analysis on publicly accessible literature, located through recognised research databases and Google; there were gaps in the evidence that we found and we have highlighted these in our conclusions.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".