Contraceptive decision-making and priorities: What happens before patients see a healthcare provider
Bibliographic record
Abstract
Extensive research has been conducted on the contraceptive decision-making that patients engage in during their appointment with healthcare providers and the approaches used by providers during this process, but less information is available on what happens prior to the appointment that may contribute to patients’ decisions. Here, we use data from semi-structured interviews with 17 patients at a sexual health clinic about their experience obtaining contraception to explore the process of choosing a method. Participants were recruited through posters in the clinic waiting room and via information posted on the clinic’s social media feeds. Interviews were thematically analyzed, and two main themes identified. The first theme was the importance of seeking out information online and from social networks prior to seeing a provider, to the extent that most participants had settled on a method prior to their discussion with a physician. The second theme was the priorities identified by participants in their decision-making, primarily side effects. The findings suggest that key moments of decision-making may not take place during a contraceptive counselling appointment, but rather beforehand through independent research, discussions with others, and previous experiences with contraception. The experiences of participants in this study indicate that contraceptive counselling should include discussion of the information patients have gleaned from other sources and acknowledge the importance of experiential information as well as factual.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.000 | 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".