Safety, Quality, and Acceptability of Contraceptive Subdermal Implant Provision by Community Health Extension Workers Versus Nurses and Midwives in Nigeria: Protocol for a Quasi-Experimental, Noninferiority Study
Bibliographic record
Abstract
BACKGROUND: As part of its Family Planning 2020 commitment, the Nigerian government is aiming for a contraceptive prevalence rate of 36% by 2018, and in 2014, approved a policy to allow community health extension workers (CHEWs), in addition to doctors, nurses, and midwives, to provide contraceptive subdermal implants. There is a lack of rigorous evidence on the safety of long-acting reversible contraceptive provision, such as implants, among lower cadres of health providers. OBJECTIVE: This study aimed to compare implant provision by CHEWs versus nurses and midwives up to 14 days post insertion. METHODS: The quasi-experimental, noninferiority study will take place in public sector facilities in Kaduna and Ondo States. In each state, we will select 60 facilities, and from these, we will select a total of 30 nurses and midwives and 30 CHEWs to participate. Selected providers will be trained to provide implant services. Once trained, providers will recruit a minimum of 8125 women aged between 18 and 49 years who request and are eligible for an implant, following comprehensive family planning counseling. During implant insertion, providers will record data about the process and any adverse events, and 14 days post insertion, providers will ask 4410 clients about adverse events arising from the implant. Supervisors will observe 792 implant insertions to assess service provision quality and ask clients about their satisfaction with the procedure. We will conclude noninferiority if the CI for the difference in the proportion of adverse events between CHEWs and nurses and midwives on the day of insertion or 14 days post insertion lies to the right of -2%. RESULTS: In September and October 2015, we trained 60 CHEWs and a total of 60 nurses and midwives from 12 local government areas (LGAs) in Kaduna and 23 LGAs in Ondo. Recruitment took place between November 2015 and December 2016. Data analysis is being finalized, and results are expected in March 2018. CONCLUSIONS: The strength of this study is having a standard care (nurse and midwife provision) group with which CHEW provision can be compared. The intervention builds on existing training and supervision procedures, which increases the sustainability and scalability of CHEW implant provision. Important limitations include the lack of randomization due to nurses and midwives in Nigeria working in separate types of health care facilities compared with CHEWs, and that providers self-assess their own practices. It is unfeasible to observe all procedures independently, and observation may change practice. Although providers will be trained to conduct implant removals, the study time will be too short to reach the sample size required to make noninferiority comparisons for removals. TRIAL REGISTRATION: ClinicalTrials.gov NCT03088722; https://clinicaltrials.gov/ct2/show/NCT03088722 (Archived by WebCite at http://www.webcitation.org/6xIHImWvu).
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".