Psychological science has thrived thanks to new methods and innovative practices. Journals, including Behavior Research Methods (BRM), continue to support the dissemination and evaluation of research assets including data, software/hardware, statistical code, and databases of stimuli. However, such research assets rarely allow for computational reproducibility, meaning they are difficult to reuse. Therefore, in this preregistered report, we explore how BRM's authors and BRM structures shape the landscape of functional research assets. Our broad research questions concern: (1) How quickly methods and analytical techniques reported in BRM can be used and developed further by other scientists; (2) Whether functionality has improved following changes to BRM journal policy in support of computational reproducibility; (3) Whether we can disentangle such policy changes from changes in reproducibility over time. We randomly sampled equal numbers of papers (N = 204) published in BRM before and after the implementation of policy changes. Pairs of researchers recorded how long it took to ensure assets (data, software/hardware, statistical code, and materials) were fully operational. They also coded the completeness and reusability of the assets. While improvements were observed in all measures, only changes to completeness were altered significantly following the policy changes (d = .37). The effects varied between different types of research assets, with data sets from surveys/experiments showing the largest improvements in completeness and reusability. Perhaps more importantly, changes to policy do appear to have improved the life span of research products by reducing natural decline. We conclude with a discussion of how, in the future, research and policy might better support computational reproducibility within and beyond psychological science.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11525395 | PMC |
http://dx.doi.org/10.3758/s13428-024-02501-5 | DOI Listing |
Skelet Muscle
December 2024
Rehabilitation Sciences Institute, University of Toronto, Toronto, ON, Canada.
Background: INTER- and INTRAmuscular fat (IMF) is elevated in high metabolic states and can promote inflammation. While magnetic resonance imaging (MRI) excels in depicting IMF, the lack of reproducible tools prevents the ability to measure change and track intervention success.
Methods: We detail an open-source fully-automated iterative threshold-seeking algorithm (ITSA) for segmenting IMF from T1-weighted MRI of the calf and thigh within three cohorts (CaMos Hamilton (N = 54), AMBERS (N = 280), OAI (N = 105)) selecting adults 45-85 years of age.
BMC Med Inform Decis Mak
December 2024
School of Mathematics, Statistics & Computer Science, University of KwaZulu Natal, Durban, South Africa.
Background: In causal analyses, some third factor may distort the relationship between the exposure and the outcome variables under study, which gives spurious results. In this case, treatment groups and control groups that receive and do not receive the exposure are different from one another in some other essential variables, called confounders.
Method: Place of birth was used as exposure variable and age-specific childhood vaccination status was used as outcome variables.
Ann Surg Oncol
December 2024
Department of Colon and Rectal Surgery, The University of Texas MD Anderson Cancer Center, Houston, USA.
Background: The Peritoneal Cancer Index (PCI), calculated intraoperatively, has previously yielded mixed results when correlated with computed tomography. This study aimed to quantify variation in this scoring method comparing radiologists' and surgeons' radiologic PCI (rPCI) assessment.
Methods: The rPCI of 104 patients treated at a single institution for peritoneal carcinomatosis was calculated by an abdominal radiologist and a surgeon.
Sci Rep
December 2024
Department of Electronics and Telecommunications, Politecnico di Torino, 10123, Torino, Italy.
Chronic wounds are a syndrome that affects around 4% of the world population due to several pathologies. The COV-19 pandemic has enforced the need of developing new techniques and technologies that can help clinicians to monitor the affected patients easily and reliably. In this prospective observational study a new device, the Wound Viewer, that works through a memristor-based Discrete-Time Cellular Neural Network (DT-CNN) has been developed and tested through a clinical trial of 150 patients.
View Article and Find Full Text PDFTomography
December 2024
Department of Nuclear Medicine and Molecular Imaging, Ajou University School of Medicine, Suwon 16499, Republic of Korea.
Background/objectives: Calculating the radiation dose from CT in F-PET/CT examinations poses a significant challenge. The objective of this study is to develop a deep learning-based automated program that standardizes the measurement of radiation doses.
Methods: The torso CT was segmented into six distinct regions using TotalSegmentator.
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