ArticleAddiction biology2025
How Transparent and Reproducible Are Studies That Use Animal Models of Opioid Addiction?
Article in Addiction biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
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
The reproducibility crisis in psychology has caused various fields to consider the reliability of their own findings. Many of the unfortunate aspects of research design that undermine reproducibility also threaten translation potential. In preclinical addiction research, the rates of translation have been disappointing. We tallied indices of transparency and accurate and thorough reporting in animal models of opioid addiction from 2019 to 2023. By examining the prevalence of these practices, we aimed to understand whether efforts to improve reproducibility are relevant to this field. For 255 articles, we report the prevalence of transparency measures such as preregistration, registered reports, open data and open code, as well as compliance to the Animal Research: Reporting of In Vivo Experiments (ARRIVE) guidelines. We also report rates of bias minimization practices (randomization, masking and data exclusion), sample size calculations and multiple corrections adjustments. Lastly, we estimated the accuracy of test statistic reporting using a version of StatCheck. All the transparency measures and the ARRIVE guideline items had low prevalence, including no cases of study preregistration and no cases where authors shared their analysis code. Similarly, the levels of bias minimization practices and sample size calculations were unsatisfactory. In contrast, adjustments for multiple comparisons were implemented in most articles (76.5%). Lastly, p-value inconsistencies with test statistics were detected in about half of papers, and 11% contained statistical significance errors. We recommend that researchers, journal editors and others take steps to improve study reporting and to facilitate both replication and translation.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.