An integrative review of how providers can use tools or strategies to support shared decision-making for contraceptive counselling in primary care
Bibliographic record
Abstract
Shared decision-making (SDM) is central component of patient-centered care and is of particular interest in contraceptive counselling, where a range of potentially suitable options are available, and personal preferences and values must guide clinical decisions. A systematic search was conducted in MEDLINE (via Ovid) and CINAHL to identify qualitative, quantitative, and mixed-methods studies published between 2019 and 2024. Inclusion criteria focused on studies evaluating SDM tools or strategies in clinic-based settings with women of reproductive age. Among the seven articles included in this review, a variety of SDM tools and strategies were used: decision aids, interview guides, provider prompts, and physical models. Key outcomes included improved patient satisfaction, decisional certainty, interpersonal quality of contraceptive counselling, perceived self-efficacy in decision-making and increased contraceptive knowledge. However, there was variability in how SDM was measured and whether outcomes were explicitly linked to SDM processes. Findings suggest that effective implementation of SDM tools or strategies in primary care practice may require a multifaceted approach involving both pre-visit patient tools and provider and patient supports during contraceptive counselling. Future research should seek to more clearly establish causal links between SDM strategies and outcomes, and to evaluate SDM tools or strategies in the Canadian context.,
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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 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.011 | 0.013 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".