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Objective: To evaluate open science policies of imaging journals, and compliance to these policies in published articles. Methods: From imaging journals listed we extracted open science policy details: protocol registration, reporting guidelines, funding, ethics and conflicts of interest (COI), data sharing, and open access publishing. The 10 most recently published studies from each journal were assessed to determine adherence to these policies. We calculated the proportion of open science policies into an Open Science Score (OSS) for all journals and articles. We evaluated relationships between OSS and journal/article level variables. Results: 82 journals/820 articles were included. The OSS of journals and articles was 58.3% and 31.8%, respectively. Of the journals, 65.9% had registration and 78.1% had reporting guideline policies. 79.3% of journals were members of COPE, 81.7% had plagiarism policies, 100% required disclosure of funding, and 97.6% required disclosure of COI and ethics approval. 81.7% had data sharing policies and 15.9% were fully open access. 7.8% of articles had a registered protocol, 8.4% followed a reporting guideline, 77.4% disclosed funding, 88.7% disclosed COI, and 85.6% reported ethics approval. 12.3% of articles shared their data. 51% of articles were available through open access or as a preprint. OSS was higher for journal with DOAJ membership (80% vs 54.2%; P <.0001). Impact factor was not correlated with journal OSS. Knowledge synthesis articles has a higher OSS scores (44.5%) than prospective/retrospective studies (32.6%, 30.0%, P <.0001). Conclusion: Imaging journals endorsed just over half of open science practices considered; however, the application of these practices at the article level was lower. [ABSTRACT FROM AUTHOR]

Background: P-hacking, the tendency to run selective analyses until they become significant, is prevalent in many scientific disciplines. Purpose: This study aims to assess if p-hacking exists in imaging research. Methods: Protocol, data, and code available here https://osf.io/xz9ku/?view%5fonly=a9f7c2d841684cb7a3616f567db273fa. We searched imaging journals Ovid MEDLINE from 1972 to 2021. Text mining using Python script was used to collect metadata: journal, publication year, title, abstract, and P -values from abstracts. One P -value was randomly sampled per abstract. We assessed for evidence of p-hacking using a p-curve, by evaluating for a concentration of P -values just below.05. We conducted a one-tailed binomial test (α =.05 level of significance) to assess whether there were more P -values falling in the upper range (e.g.,.045 < P <.05) than in the lower range (e.g.,.04 < P <.045). To assess variation in results introduced by our random sampling of a single P -value per abstract, we repeated the random sampling process 1000 times and pooled results across the samples. Analysis was done (divided into 10-year periods) to determine if p-hacking practices evolved over time. Results: Our search of 136 journals identified 967,981 abstracts. Text mining identified 293,687 P -values, and a total of 4105 randomly sampled P -values were included in the p-hacking analysis. The number of journals and abstracts that were included in the analysis as a fraction and percentage of the total number was, respectively, 108/136 (80%) and 4105/967,981 (.4%). P-values did not concentrate just under.05; in fact, there were more P -values falling in the lower range (e.g.,.04 < P <.045) than falling just below.05 (e.g.,.045 < P <.05), indicating lack of evidence for p-hacking. Time trend analysis did not identify p-hacking in any of the five 10-year periods. Conclusion: We did not identify evidence of p-hacking in abstracts published in over 100 imaging journals since 1972. These analyses cannot detect all forms of p-hacking, and other forms of bias may exist in imaging research such as publication bias and selective outcome reporting. [ABSTRACT FROM AUTHOR]