ArticleBMC medical ethics2015
Latent variable modeling and its implications for institutional review board review: variables that delay the reviewing process.
Article in BMC medical ethics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
3 citing papers in PubMed.
- The IRB structure and medical research reform.Clinical and translational medicine · 2018Article
- Effects of Regulatory Support Services on Institutional Review Board Turnaround Times.Journal of empirical research on human research ethics : JERHRE · 2017Article
- A personalized Institutional Review Board Liaison Service: Evaluation over its initial 30 months.International journal of academic medicineArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundTo investigate the factors related to approval after review by an Institutional Review Board (IRB), the structure equation model was used to analyze the latent variables 'investigators', 'vulnerability' and 'review process' for 221 proposals submitted to our IRB.
methodsThe vulnerability factor included vulnerable cases, and studies that involved drug tests and genetic analyses. The principal investigator (PI) factor included the license level of the PI and whether they belonged to our institution. The review factor included administration time, total review time, and revision frequency. The revision frequency and total review time influenced the efficiency of review.
resultsThe latent variable of reviewing was the most important factor mediating the PIs and vulnerability to IRB review approval. The local PIs moderated with genetic study and revision frequency had an impact on the review process and mediated non-approval.
conclusionsBetter guidance of the investigators and reviewers might improve the efficiency with which IRBs function.
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Registered trials
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