Family Planning in the Sierra Leone Ebola Outbreak: Women's Proximal and Distal Reasoning
Bibliographic record
Abstract
Sierra Leone was highly impacted by the 2014-2016 West Africa Ebola outbreak, with 3,955 recorded deaths. Already stressed maternal health services were deeply affected by the outbreak due to fears of viral transmission, reallocation of maternity staff, and broader policies to stop transmission including travel restrictions. This research sought to explore women's perspectives on delaying pregnancy during the Ebola outbreak using family planning methods. Qualitative data collection took place in Kambia District in 2018 and included 35 women participants, with women who were either family planning users or nonusers at the time of the outbreak. Women reported a variety of reasons for choosing to take or not to take family planning during the outbreak, which we categorized as proximal (directly related to the outbreak) or distal (not directly outbreak related). Proximal reasons to take family planning included to avoid interacting with health care spaces where Ebola could be transmitted, to avoid the economic burden of additional children in a time when economic activities were curtailed and to return to school when education resumed postoutbreak. Distal reasoning included gender roles affecting women's decision making to seek family planning, concerns related to the physiological side effects of family planning, and the economic burden of paying for family planning. Women's perspectives for choosing to take or not take family planning during the Sierra Leone Ebola crisis had not been explored prior to this paper. Using the lens of family planning to consider how women choose to access health care in an outbreak gives us a unique perspective into how all health care interactions are impacted by a generalized outbreak of Ebola, and how outbreak responses struggle to ensure such services remain a priority.
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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 | 0.007 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.010 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".