Investigation of factors influencing the implementation of two shared decision-making interventions in contraceptive care: a qualitative interview study among clinical and administrative staff
Bibliographic record
Abstract
BACKGROUND: There is limited evidence on how to implement shared decision-making (SDM) interventions in routine practice. We conducted a qualitative study, embedded within a 2 × 2 factorial cluster randomized controlled trial, to assess the acceptability and feasibility of two interventions for facilitating SDM about contraceptive methods in primary care and family planning clinics. The two SDM interventions comprised a patient-targeted intervention (video and prompt card) and a provider-targeted intervention (encounter decision aids and training). METHODS: Participants were clinical and administrative staff aged 18 years or older who worked in one of the 12 clinics in the intervention arm, had email access, and consented to being audio-recorded. Semi-structured telephone interviews were conducted upon completion of the trial. Audio recordings were transcribed verbatim. Data collection and thematic analysis were informed by the 14 domains of the Theoretical Domains Framework, which are relevant to the successful implementation of provider behaviour change interventions. RESULTS: Interviews (n = 29) indicated that the interventions were not systematically implemented in the majority of clinics. Participants felt the interventions were aligned with their role and they had confidence in their skills to use the decision aids. However, the novelty of the interventions, especially a need to modify workflows and change behavior to use them with patients, were implementation challenges. The interventions were not deeply embedded in clinic routines and their use was threatened by lack of understanding of their purpose and effect, and staff absence or turnover. Participants from clinics that had an enthusiastic study champion or team-based organizational culture found these social supports had a positive role in implementing the interventions. CONCLUSIONS: Variation in capabilities and motivation among clinical and administrative staff, coupled with inconsistent use of the interventions in routine workflow contributed to suboptimal implementation of the interventions. Future trials may benefit by using implementation strategies that embed SDM in the organizational culture of clinical settings.
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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 | 0.045 | 0.073 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.010 | 0.012 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 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".