Institutional Review Boards and Multisite Studies in Health Services Research: Is There a Better Way?
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVE: The following paper examines the issue of whether the current system for ethics review of multisite health services research protocols is adequate, or whether there exist alternative methods that should be considered. PRINCIPAL FINDINGS: (1) Investigators at different sites in a multisite project often have very different experiences with respect to the requirements and requests of the review board. Other problems include the waste of time and resources spent on document preparation for review boards, and delays in the commencement of research activities. (2) There are several possible reasons why there is variability in ethics review. These include the absence of standardized forms, differences in the background and experiences of board members, the influence of institutional or professional culture, and regional thinking. (3) Given the limited benefits derived from the variability in recommendations of multiple boards and the numerous problems encountered in seeking ethics approval from multiple boards suggest that some sort of reform is in order. CONCLUSIONS: The increasing number of multisite, health services research studies calls for a centralized system of ethics review. The local review model is simply not conducive to multisite studies, and jeopardizes the integrity of the research process. Centralized multisite review boards, together with standardized documents and procedure, electronic access to documentation, and training for board members are all possible solutions. Changes to the current system are necessary not only to facilitate the conduct of multisite research, but also to preserve the integrity of the ethics approval process in general.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.097 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.022 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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 it