Improving access to quality contraceptive counselling in community pharmacy: examining the knowledge, attitudes and practices of community pharmacists in Australia
Bibliographic record
Abstract
BACKGROUND: Across most of Australia, the role of community pharmacists in contraceptive care has been unchanged since 2004. To understand their current scope of practice and potential for practice advancements, we examined community pharmacists' contraceptive knowledge and their attitudes, practices and perceived barriers to and benefits of contraceptive counselling provision. METHODS: , linear regression) and non-parametric (Mann-Whitney, logistic regression) tests were computed for the outcomes: practices, knowledge (reported and tested), confidence, attitudes, barriers and benefits. RESULTS: Eligible responses were received from 366 pharmacies (19%). Pharmacists' median age was 34. Most (85% of) pharmacists agreed that contraceptive counselling fits within their current professional activities and emphasised benefits to their patients, including improved access to contraceptive decision support (80%), as being key motivators of counselling. A lack of payment mechanisms (66%), training opportunities (55%) and technical assistance tools (54%) were the most important barriers. Self-rated knowledge and confidence were highest for combined oral contraceptive pills and lowest for the copper intrauterine device (IUD). When tested, pharmacists were very knowledgeable about method, dosage, frequencies and costs, and relatively less knowledgeable about side-effects and IUD suitability for adolescents. CONCLUSIONS: Community pharmacists provide contraceptive information and counselling but lack the necessary resources and support to be able to consistently provide quality, person-centred care. Remuneration mechanisms, training opportunities and pharmacy-specific professional resources need to be explored.
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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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 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".