Challenges in institutional ethical review process and approval for international multicenter clinical studies in lower and middle-income countries: the case of PARITY study
Bibliographic record
Abstract
Background: One of the greatest challenges to conducting multicenter research studies in low and middle-income countries (LMICs) is the heterogeneity in regulatory processes across sites. Previous studies have reported variations in requirements with a lack of standardization in the Institutional Review Board (IRB) processes between centers, imposing barriers for approval, participation, and development of multicenter research. Objectives: To describe the regulatory process, variability and challenges faced by pediatric researchers in LMICs during the IRB process of an international multicenter observational point prevalence study (Global PARITY). Design: A 16-question multiple-choice online survey was sent to site principal investigators (PIs) at PARITY study participating centers to explore characteristics of the IRB process, costs, and barriers to research approval. A shorter survey was employed for sites that expressed interest in participating in Global PARITY and started the approval process, but ultimately did not participate in data collection (non-participating sites) to assess IRB characteristics. Results: Of the 91 sites that sought IRB approval, 46 were successful in obtaining approval and finishing the data collection process. The survey was completed by 46 (100%) participating centers and 21 (47%) non-participating centers. There was a significant difference between participating and non-participating sites in IRB approval of a waiver consent and in the requirement for a legal review of the protocol. The greatest challenge to research identified by non-participating sites was a lack of research time and the lack of institutional support. Conclusions: Global collaborative research is crucial to increase our understanding of pediatric critical care conditions in hospitals of all resource-levels and IRBs are required to ensure that this research complies with ethical standards. Critical barriers restrict research activities in some resource limiting countries. Increasing the efficiency and accessibility of local IRB review could greatly impact participation of resource limited sites and enrollment of vulnerable populations.
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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 | 0.728 | 0.673 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.012 | 0.032 |
| Scholarly communication | 0.018 | 0.017 |
| Open science | 0.010 | 0.020 |
| Research integrity | 0.014 | 0.025 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".