Pharmacists’ Insights on Offering Contraceptive Implant Services
Bibliographic record
Abstract
Context Contraceptive implant use in North America remains low (<5%). This may be due to limited clinician training and restricted access to qualified providers. Expanding pharmacists’ scope of practice to include implant insertion could improve accessibility to this essential reproductive health service. Objective To assess pharmacists’ insights on the feasibility of expanding their scope of practice to include contraceptive implant insertion, identifying required training, resources, barriers, and readiness for implementation. Study Design & Analysis We conducted qualitative interviews using a semi-structured interview guide via Zoom. Thematic qualitative analysis was employed to explore pharmacists’ perspectives on offering implant services. Data were inductively analyzed, and findings were categorized into themes. Setting This study was conducted in British Columbia, Canada Population We included twelve community pharmacists in active clinical practice who provide direct patient care from both urban and rural communities in the study. Instrument A semi-structured interview guide was used to facilitate discussions with participating pharmacists Outcomes pharmacists’ perspectives on the feasibility of providing contraceptive implant services, including their willingness to offer such services, perceived training and resource needs, anticipated challenges, and potential facilitators. Key focus areas include pharmacists’ views on required competencies, logistical and regulatory considerations, and factors that could support successful implementation. Results Pharmacists expressed strong interest in offering implant insertion. Facilitators included access to proper training, adequate staffing, private consultation spaces, financial compensation, and public awareness. Challenges involved space constraints, added workload, liability concerns, physician resistance, and uncertainty about implant removals. Pharmacists emphasized the need for affordable, accredited in-person certification training with recertification options integrated into pharmacy education. Conclusions As trusted medication experts, pharmacists have the potential to expand access to long-acting reversible contraception by providing contraceptive implant insertion services. This could help reduce wait times, enhance patient convenience, and improve overall access to reproductive healthcare. Addressing training, regulatory, and logistical factors is essential for successful integration
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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 | 0.006 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".