Background And Objective: Neurosurgical research is a rapidly evolving field, with numerous studies continuously published. As the body of research grows, upholding high-quality standards becomes increasingly essential. Open science practices offer tools to ensure quality and transparency. However, the prevalence of these practices remains unclear. This study investigated the extent to which neurosurgical publications have implemented open science practices.
Methods: Five open science practices (preprint, equator guidelines, published peer review comments, preregistration, and open accessibility to data and methods) were measured from five top-ranked neurosurgical journals (Neurosurgery, Journal of Neurosurgery, World Neurosurgery, Neurosurgical Review, and Acta Neurochirurgica), according to Google Scholar. One hundred fifty articles were randomly sampled from January 1, 2022, to December 31, 2023. Two reviewers analyzed these articles for their utilization of open science practices. A third reviewer settled disagreements.
Results: One journal required (20%) and three journals (60%) recommended utilizing EQUATOR guidelines. Three journals (60%) allowed preprints, and all five journals (100%) recommended or required preregistration of clinical trials, but only two (40%) recommended preregistration for systematic reviews (Fig. 1). All five journals (100%) recommended or required methods to be publicly available, but none (0%) published peer-review comments. Neurosurgical Review utilized the most open science practices, with a mean utilization of 1.4 open science practices per publication versus 0.9 across the other four journals (p < 0.001). Moreover, Neurosurgical Review significantly utilized more open science practices versus Journal of Neurosurgery (p < 0.05) and World Neurosurgery (p < 0.05). Both randomized controlled trials (p < 0.001) and systematic reviews (p < 0.001) significantly utilized more open science practices compared to observational studies.
Conclusions: Despite advocacy from neurosurgical journals, the adoption of open science practices still needs improvement. Implementing incentives and clearer requirements may prove beneficial. Promoting these practices is crucial to enhancing research quality in neurosurgery.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1007/s10143-024-03008-5 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Good Practices for Health Technology Assessment Guideline Development: A Report of the Health Technology Assessment International, HTAsiaLink, and ISPOR Special Task Force.
Value Health
October 2024
Health Intervention and Technology Assessment Program (HITAP), Ministry of Public Health, Nonthaburi, Thailand; Saw Swee Hock School of Public Health, National University of Singapore, Singapore.
Objectives: Health technology assessment (HTA) guidelines are intended to support successful implementation of HTA by enhancing consistency and transparency in concepts, methods, process, and use, thereby enhancing the legitimacy of the decision-making process. This report lays out good practices and practical recommendations for developing or updating HTA guidelines to ensure successful implementation.
Methods: The task force was established in 2022 and comprised experts and academics from various geographical regions, each with substantial experience in developing HTA guidelines for national health policymaking.
Development of a Multiplex RT-PCR Detection for Six Viruses Infecting Strawberry.
Viruses
November 2024
Institute of Industrial Crops, Hubei Academy of Agricultural Sciences, Wuhan 430064, China.
Strawberry viruses are significant pathogenic agents in strawberry. The development and application of efficient virus detection technology can effectively reduce the economic losses incurred by virus diseases for strawberry cultivators. In order to rapidly identify strawberry virus species and prevent the spread of virus disease, a multiplex reverse transcription polymerase chain reaction system was established for the simultaneous detection and identification of strawberry mild yellow edge virus (SMYEV), strawberry vein banding virus (SVBV), strawberry mottle virus (SMoV), strawberry polerovirus 1 (SPV-1), strawberry pallidosis-associated virus (SPaV), and strawberry crinivirus 4 (SCrV-4).
View Article and Find Full Text PDFFusion of Visible and Infrared Aerial Images from Uncalibrated Sensors Using Wavelet Decomposition and Deep Learning.
Sensors (Basel)
December 2024
Department of Electrical and Computer Engineering, University of Missouri, Columbia, MO 65211, USA.
Multi-modal systems extract information about the environment using specialized sensors that are optimized based on the wavelength of the phenomenology and material interactions. To maximize the entropy, complementary systems operating in regions of non-overlapping wavelengths are optimal. VIS-IR (Visible-Infrared) systems have been at the forefront of multi-modal fusion research and are used extensively to represent information in all-day all-weather applications.
View Article and Find Full Text PDFOn Security Performance of SWIPT Multi-User Jamming Based on Mixed RF/FSO Systems with Untrusted Relay.
Sensors (Basel)
December 2024
Key Laboratory of Electromagnetic Wave Information Technology and Metrology of Zhejiang Province, College of Information Engineering, China Jiliang University, Hangzhou 310018, China.
This paper presents research on the security performance of a multi-user interference-based mixed RF/FSO system based on SWIPT untrusted relay. In this work, the RF and FSO channels experience Nakagami-m fading distribution and Málaga (M) turbulence, respectively. Multiple users transmit messages to the destination with the help of multiple cooperating relays, one of which may become an untrusted relay as an insider attacker.
View Article and Find Full Text PDFBinary Transformer Based on the Alignment and Correction of Distribution.
Sensors (Basel)
December 2024
Faculty of Information Engineering and Automation, Kunming University of Science and Technology, Kunming 650500, China.
Transformer is a powerful model widely used in artificial intelligence applications. It contains complex structures and has extremely high computational requirements that are not suitable for embedded intelligent sensors with limited computational resources. The binary quantization technology takes up less memory space and has a faster calculation speed; however, it is seldom studied for the lightweight transformer.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!