“Meeting Patients Where They're at”: Clinician Perspectives on Integration of Family Planning Services into Office-Based Addiction Treatment
Bibliographic record
Abstract
OBJECTIVES: To study clinician perspectives on the feasibility of incorporating family planning services within office-based addiction treatment (OBAT) clinics. We sought to understand the unique facilitators of and barriers to the integration of contraceptive services within the OBAT model with a goal to support the design and implementation of a program tailored to meet the reproductive health needs of patients with substance use disorder. METHODS: After obtaining institutional review board approval, we conducted qualitative semistructured interviews with OBAT clinicians (registered nurses, advanced practice registered nurses, and physicians) at a tertiary-care safety-net hospital. Interview transcripts were analyzed using deductive codes utilizing key components of the Promoting Action on Research Implementation in Health Services and Ottawa Decision Support Frameworks. RESULTS: We analyzed 20 interviews. Our data noted 3 major themes: (1) evidence to support integration of family planning and OBAT, (2) inherent strengths and facilitative factors of the OBAT model, and (3) barriers and challenges of the OBAT model influencing successful integration. Strengths included the destigmatizing and trust-building OBAT approach to care, common use of patient-centered counseling, and providers' nuanced understanding of substance use disorder-specific impacts on reproductive health. Barriers included time constraints, balancing urgent patient recovery needs, the desire for additional contraception provision training, and concern for potential contraceptive coercion. CONCLUSIONS: Office-based addiction treatment clinics have inherent strengths that may make it a beneficial location for integrated family planning services. Future research should elicit patient perspectives to ensure the implementation of a family planning program in OBAT that supports patients' reproductive goals while avoiding stigma or reproductive coercion.
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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 | 0.017 | 0.033 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.014 | 0.007 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.004 | 0.007 |
| 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".