Development of a Survey to Assess the Acceptability of an Innovative Contraception Practice among Rural Pharmacists
Bibliographic record
Abstract
Improved access to effective contraceptive methods is needed in Canada, particularly in rural areas, where unintended pregnancy rates are high and specific sexual health services may be further away. A rural pharmacist may be the most accessible health care professional. Pharmacy practice increasingly incorporates cognitive services. In Canada many provinces allow pharmacists to independently prescribe for some indications, but not for hormonal contraception. To assess the acceptability for the implementation of this innovative practice in Canada, we developed and piloted a survey instrument. We chose questions to address the components for adoption and change described in Rogers’ “diffusion of innovations” theory. The proposed instrument was iteratively reviewed by 12 experts, then focus group tested among eight pharmacists or students to improve the instrument for face validity, readability, consistency and relevancy to community pharmacists in the Canadian context. We then pilot tested the survey among urban and rural pharmacies. 4% of urban and 35% of rural pharmacies returned pilot surveys. Internal consistency on repeated re-phrased questions was high (Cronbach’s Alpha = 0.901). We present our process for the development of a survey instrument to assess the acceptability and feasibility among Canadian community pharmacists for the innovative practice of the independent prescribing of hormonal contraception.
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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 | 0.016 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".