Brief Intervention to Prevent Sexually Transmitted Infections and Unintended Pregnancies: Protocol of a Mixed Methods Feasibility Study
Bibliographic record
Abstract
BACKGROUND: Sexual well-being is fundamental to physical and emotional health, and the ability to achieve it depends on access to comprehensive sexuality information and high-quality sexual health care from evidence-informed, nonjudgmental providers. Adequate and timely delivery of these components to individuals who are at high risk for sexually transmitted infections (STIs), including HIV, and unintended pregnancies promotes sexual health and mitigates consequences arising from risky sexual behavior. Brief interventions that allow health care providers to improve the information available to clients and motivate and help them to develop risk-reduction skills are seen as efficient ways to improve knowledge, change client behavior, and reduce provider stigma regarding sexual health. OBJECTIVE: The aim of the study is to evaluate five aspects of feasibility (acceptability, willingness, safety, satisfaction, and process) of a brief sexuality-related communication (BSC) intervention based on motivational interviewing and behavior change techniques in primary health care settings in low- and middle-income countries (LMICs). METHODS: This protocol outlines a multisite, multiphase study of feasibility of a BSC intervention in primary health care settings in LMICs that will be examined across four phases of the study. Phases I through III involve the collection of formative, qualitative data to examine provider and client perceptions of the feasibility of the intervention, adaptation of the intervention guide, and training providers on how to implement the final version of the BSC intervention. During phase IV, the feasibility of the intervention will be tested in a nonrandomized pre-post test trial where providers and clients will be followed for 6 months and participate in multiphase data collection. RESULTS: Phase I is currently underway in Moldova, and phases I and II were completed in Peru in late 2019. Results are expected for the feasibility study in 2021. CONCLUSIONS: This feasibility study will determine whether the implementation of brief intervention programs aimed at improving sexual health outcomes is possible in the constraints of LMIC health systems and will add to our understanding of factors shaping clinical practice among primary care providers. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/15569.
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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 | 0.047 | 0.028 |
| Meta-epidemiology (narrow) | 0.004 | 0.004 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.005 | 0.003 |
| Research integrity | 0.006 | 0.007 |
| Insufficient payload (model declined to judge) | 0.049 | 0.010 |
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".