Rationale and Design of the Diet, CKD, and Apolipoprotein L1 Study in Low-Income and Middle-Income Countries
Bibliographic record
Abstract
Introduction: nephropathy. We describe enrollment and retention efforts and highlight facilitators and barriers to enrollment and operational challenges, as well as accommodations made in the study protocol. Methods: The DCA study is enrolling participants in 7 centers in West Africa. Participants who consented were invited to complete dietary recalls and 24-hour urine collections in year 1. We conducted focus groups and semistructured interviews among study personnel to identify facilitators and barriers to enrollment as well as retention and operational challenges in the execution of the study protocol. We analyzed emerging themes using content analyses. Results: A total of 712 participants were enrolled in 18 months with 1256 24-hour urine and 1260 dietary recalls. Barriers to enrollment were the following: (i) a lack of understanding of research, (ii) the burden of research visits, and (iii) incorporating cultural and traditional nuances when designing research protocols. Factors facilitating enrollment were the following: (i) designing convenient research visits, (ii) building rapport and increased communication between the research team and participants, and (iii) cultural sensitivity - adapting research protocols for the populations involved. Offering home visits, providing free dietary counseling, reducing the volume of study blood collection, and reducing the frequency of visits were some changes made in the study protocol that increased participant satisfaction. Conclusion: Adopting a participant-centered approach with accommodations in the protocol for cultural adaptability and incorporating participant feedback is vital for carrying out research in low-income and middle-income regions.
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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 | 0.110 | 0.043 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.019 | 0.006 |
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".