Potential point of care tests (POCTs) for maternal health in Peru, perspectives of pregnant women and their partners
Bibliographic record
Abstract
BACKGROUND: Globally, no qualitative studies have explored the perspectives of women and their partners about the integration of technology - and specifically diagnostic testing technologies - into antenatal care. The study objective was to describe the demand side for pregnancy-related diagnostic tests from the perspective of Peruvian consumers, including female and male community members, by engaging participants about their awareness of and care-seeking for pregnancy-related diagnostic tests and their preferred characteristics and testing conditions for pregnancy-related point-of-care diagnostic tests (POCTs). METHODS: Sixty-seven mothers and fathers of children under one from the peri-urban coast and the peri-urban and rural highlands and jungle of Peru participated in ten focus groups. RESULTS: Participants think that pregnancy-related diagnostic tests are important and they and their fellow community members are committed to ensuring that pregnant women receive the tests they need. Participants expressed clear demands for pregnancy-related POCTs, including important characteristics for the tests themselves (certification, rapid, reliable results) and for test implementation (well-trained, personable good communicators as test administrators at well-equipped, convenient testing sites). Participants emphasized the importance of short waiting times and explained that many people have some ability to pay for POCTs, particularly if they are innovative, rapid or multiplex. CONCLUSIONS: Engaging future POCT users as consumers who are able to make key decisions about the development and implementation of pregnancy-related POCTs is valuable and informative.
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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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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".