Estimating the Prevalence of Transparency and Reproducibility-Related Research Practices in Psychology (2014–2017) is a research paper published in Perspectives on Psychological Science (2021). On theSindex it has a DataRank of 0.702. It has been cited 107 times.
Psychologists are navigating an unprecedented period of introspection about the credibility and utility of their discipline. Reform initiatives emphasize the benefits of transparency and reproducibility-related research practices; however, adoption across the psychology literature is unknown. Estimating the prevalence of such practices will help to gauge the collective impact of reform initiatives, track progress over time, and calibrate future efforts. To this end, we manually examined a random sample of 250 psychology articles published between 2014 and 2017. Over half of the articles were publicly available (154/237, 65%, 95% confidence interval [CI] = [59%, 71%]); however, sharing of research materials (26/183; 14%, 95% CI = [10%, 19%]), study protocols (0/188; 0%, 95% CI = [0%, 1%]), raw data (4/188; 2%, 95% CI = [1%, 4%]), and analysis scripts (1/188; 1%, 95% CI = [0%, 1%]) was rare. Preregistration was also uncommon (5/188; 3%, 95% CI = [1%, 5%]). Many articles included a funding disclosure statement (142/228; 62%, 95% CI = [56%, 69%]), but conflict-of-interest statements were less common (88/228; 39%, 95% CI = [32%, 45%]). Replication studies were rare (10/188; 5%, 95% CI = [3%, 8%]), and few studies were included in systematic reviews (21/183; 11%, 95% CI = [8%, 16%]) or meta-analyses (12/183; 7%, 95% CI = [4%, 10%]). Overall, the results suggest that transparency and reproducibility-related research practices were far from routine. These findings establish baseline prevalence estimates against which future progress toward increasing the credibility and utility of psychology research can be compared.
FAIR checklist signals are shown for context only and do not affect DataRank scoring.
Base Score Contribution
0.702
From this paper's citation signal
Citation Network Contribution
0
Citation network not refreshed for this result
This paper's DataRank is currently driven only by its base citation score. Citation network data was not refreshed for this result.
Learn more about DataRank methodology →DataRank blends this paper's own citation count with the influence of the papers that cite it. Here, roughly 100% comes from its base citations and 0% from the citation network.
Citers are pulled from OpenAlex sorted by cited_by_count:descand capped per paper, so when the cap binds we keep the highest-signal references and the score is reproducible across reruns.