Enhancing the Introduction and Scale Up of Self-Administered Injectable Contraception (DMPA-SC) in Health Systems (the EASIER Project): Protocol for Embedded Implementation Research
Bibliographic record
Abstract
BACKGROUND: The introduction of self-administered injectable contraception presents an opportunity to address the unmet need for family planning. As ministries of health scale up self-administered injectable contraception, there is a scarcity of knowledge on the implementation practices and contextual conditions that help and hinder these efforts. The World Health Organization has launched the "enhancing self-administered family planning through embedded research project" (EASIER) to address this challenge. OBJECTIVE: EASIER's objectives are to: (1) assess the coverage of self-injectable contraception, and the readiness of health systems to integrate it into the contraceptive method mix; (2) document strategies used to introduce and scale up self-injectable contraception and understand practices that have led to success and challenges; (3) identify the contextual factors that affect the adoption and implementation of self-injectable contraception throughout health systems; (4) understand whether implementation addresses users' preferences and needs; (5) strengthen collaboration between decision makers, researchers, and implementers; support and build capacity to use evidence. METHODS: EASIER developed a global protocol that implementation research (IR) teams in Burkina Faso, Ghana, and Kenya adapted into country-level embedded IR projects. In all countries (1) at the national level, IR teams evaluate the policy environment for scaling up by conducting a desk review and in-depth interviews; (2) at the local level, IR teams implement quantitative questionnaires on structural and organizational readiness to integrate self-injection into the method mix; (3) in "case study" localities, IR teams conduct in-depth interviews and focus group discussions with implementers, method users, and community members; and (4) IR teams use participatory action research to elicit stakeholder participation and translate findings into programmatic decisions. RESULTS: EASIER has been launched in all 3 countries. Preliminary findings are available from Burkina Faso and Kenya. In Burkina Faso, IR teams identified the need to strengthen health worker training approaches to ensure that family planning providers at primary health care facilities are adequately oriented to depo-medroxyprogesterone acetate subcutaneous (DMPA-SC) and self-injection and capacitated to initiate women to the method. In addition, they report the need for service communication strategies that reach potential users of the method with knowledge about self-injection and how to initiate the practice. In Kenya, the findings illuminate the need for practice guidelines that county health teams can use to coordinate the rollout of self-administered DMPA-SC. In addition, Kenya's findings underscore the importance of addressing logistical bottlenecks to help avoid stock-outs. CONCLUSIONS: EASIER presents a strategy to embed IR in contraceptive method introduction and scale-up, address local knowledge needs, devise ways to maximize the impact of new technologies in health systems, and build capacity for using evidence in programmatic decisions. Adaptation and implementation of country-level IR studies will advance the use of IR to strengthen family planning programs. TRIAL REGISTRATION: Australia New Zealand Clinical Trials Registry ACTRN12622001228774; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=384534&isReview=true. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/44222.
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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 | 0.111 | 0.089 |
| Meta-epidemiology (narrow) | 0.004 | 0.004 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.005 | 0.005 |
| Research integrity | 0.006 | 0.009 |
| Insufficient payload (model declined to judge) | 0.071 | 0.016 |
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".