1,254 research outputs found
Publishing a Research Article in a Major Radiology Journal:Time Investment From Conception to Proofreading After Acceptance
The peer review process:A survey among scientists in radiology
Purpose: To map the experience and view of scientists in radiology on the peer review process.Method: A survey with 12 closed-ended questions and 5 conditional sub-questions was conducted among corresponding authors who published in general radiology journals.Results: 244 corresponding authors participated. In considering a peer review invitation, most respondents found the topic and the availability of time very important (62.1% [144/132] and 57.8% [134/232], respectively), the quality of the abstract, the prestige/impact factor of the journal, and the sense of professional duty important (43.7% [101/231], 42.2% [98/232], and 53.9% [125/232], respectively), and were indifferent about a reward (35.3% [82/232]). However, 61.1% (143/234) believed that a reviewer should be rewarded. Direct financial compensation (27.6% [42/152]), discounted fees for society memberships, conventions, and/or journal subscriptions (24.3% [37/152]), and Continuing Medical Education credits (23.0% [35/152]) were the most frequently desired rewards. 73.4% (179/244) of respondents never received formal peer review training, of whom 31.2% (54/173) would like to, particularly less experienced researchers (Chi-Square P = 0.001). The median reported review time per article was 2.5 h. 75.2% (176/234) of respondents found it acceptable that a manuscript is rejected by an editor without formal peer review. The double-blinded peer review model was preferred by most respondents (42.3% [99/234]). A median of 6 weeks was considered the maximum acceptable time from manuscript submission to initial decision by a journal.Conclusion: Publishers and journal editors may use the experiences and views of authors that were provided in this survey to shape the peer review process.</p
Diagnostic radiology and its future:what do clinicians need and think?
Objective: To investigate the view of clinicians on diagnostic radiology and its future. Methods: Corresponding authors who published in the New England Journal of Medicine and the Lancet between 2010 and 2022 were asked to participate in a survey about diagnostic radiology and its future. Results: The 331 participating clinicians gave a median score of 9 on a 0–10 point scale to the value of medical imaging in improving patient-relevant outcomes. 40.6%, 15.1%, 18.9%, and 9.5% of clinicians indicated to interpret more than half of radiography, ultrasonography, CT, and MRI examinations completely by themselves, without consulting a radiologist or reading the radiology report. Two hundred eighty-nine clinicians (87.3%) expected an increase in medical imaging utilization in the coming 10 years, whereas 9 clinicians (2.7%) expected a decrease. The need for diagnostic radiologists in the coming 10 years was expected to increase by 162 clinicians (48.9%), to remain stable by 85 clinicians (25.7%), and to decrease by 47 clinicians (14.2%). Two hundred clinicians (60.4%) expected that artificial intelligence (AI) will not make diagnostic radiologists redundant in the coming 10 years, whereas 54 clinicians (16.3%) thought the opposite. Conclusion: Clinicians who published in the New England Journal of Medicine or the Lancet attribute high value to medical imaging. They generally need radiologists for cross-sectional imaging interpretation, but for a considerable proportion of radiographs, their service is not required. Most expect medical imaging utilization and the need for diagnostic radiologists to increase in the foreseeable future, and do not expect AI to make radiologists redundant. Clinical relevance statement: The views of clinicians on radiology and its future may be used to determine how radiology should be practiced and be further developed. Key Points: • Clinicians generally regard medical imaging as high-value care and expect to use more medical imaging in the future. • Clinicians mainly need radiologists for cross-sectional imaging interpretation while they interpret a substantial proportion of radiographs completely by themselves. • The majority of clinicians expects that the need for diagnostic radiologists will not decrease (half of them even expect that we need more) and does not believe that AI will replace radiologists.</p
Which factors are associated with fraud in medical imaging research?
Purpose: To investigate the determinants of fraud in medical imaging research. Method: This study analyzed aggregated survey data on scientific integrity completed by 877 corresponding authors who published in imaging journals in 2021. Multivariate regression analyses were performed to determine the association of scientific fraud with the following variables: survey participants’ age (<18, 18–24, 25–34, 35–44, 45–54, 55–64, or > 65 years), gender (male, female, or other), Corruption Perceptions Index (CPI) of their country of work (linear 0–100 scale), academic degree (medical doctor or other), academic position (none, fellow/resident, instructor/ lecturer, assistant professor, associate professor, full professor, or other), and years of research experience (<5, 5–10, or > 10 years). Results: Thirty-seven survey participants (4.2%) indicated they had committed scientific fraud in the past 5 years, and 223 (25.4%) indicated they had witnessed or suspected scientific fraud by departmental colleagues in the past 5 years. Instructors/lecturers were significantly more likely (P = 0.029) and fellows/residents were nearly significantly more likely (P = 0.050) to have committed scientific fraud, with odds ratios (ORs) of 4.954 and 5.156, respectively (Nagelkerke R2 of 0.114). Survey participants > 65 years of age and survey participants working in less corrupt countries were significantly less likely (P = 0.022 and P = 0.044, respectively) to have witnessed or suspected scientific fraud committed by their departmental colleagues, with ORs of 0.412 and 0.988 (per unit increase in CPI), respectively (Nagelkerke R2 of 0.064). Conclusions: Fraud in medical imaging research appears to be more common among junior faculty and in more corrupt countries.</p
Scientific Fraud, Publication Bias, and Honorary Authorship in Nuclear Medicine
Our objective was to investigate nuclear medicine scientists’ experience with scientific fraud, publication bias, and honorary authorship. Methods: Corresponding authors who published an article in one of the 15 general nuclear medicine journals (according to Journal Citation Reports) in 2021 received an invitation to participate in a survey on scientific integrity. Results: In total, 254 (12.4%) of 1,897 corresponding authors completed the survey, of whom 11 (4.3%) admitted to having committed scientific fraud and 54 (21.3%) reported having witnessed or suspected scientific fraud by someone in their department in the past 5 y. Publication bias was considered present by 222 (87.4%) respondents, and honorary authorship practices were experienced by 100 (39.4%) respondents. Respondents assigned a median score of 8 (range, 2–10) on a 1- to 10-point scale for their overall confidence in the integrity of published work. On multivariate analysis, researchers in Asia had significantly more confidence in the integrity of published work, with a b-coefficient of 0.983 (95% CI, 0.512–1.454; P < 0.001). A subset of 22 respondents raised additional concerns, mainly about authorship criteria and assignments, the generally poor quality of published studies, and perverse incentives of journals and publishers. Conclusion: Scientific fraud, publication bias, and honorary authorship appear to be nonnegligible practices in nuclear medicine. Overall confidence in the integrity of published work is high, particularly among researchers in Asia.</p
Diagnostic radiology and its future:what do clinicians need and think?
Objective: To investigate the view of clinicians on diagnostic radiology and its future. Methods: Corresponding authors who published in the New England Journal of Medicine and the Lancet between 2010 and 2022 were asked to participate in a survey about diagnostic radiology and its future. Results: The 331 participating clinicians gave a median score of 9 on a 0–10 point scale to the value of medical imaging in improving patient-relevant outcomes. 40.6%, 15.1%, 18.9%, and 9.5% of clinicians indicated to interpret more than half of radiography, ultrasonography, CT, and MRI examinations completely by themselves, without consulting a radiologist or reading the radiology report. Two hundred eighty-nine clinicians (87.3%) expected an increase in medical imaging utilization in the coming 10 years, whereas 9 clinicians (2.7%) expected a decrease. The need for diagnostic radiologists in the coming 10 years was expected to increase by 162 clinicians (48.9%), to remain stable by 85 clinicians (25.7%), and to decrease by 47 clinicians (14.2%). Two hundred clinicians (60.4%) expected that artificial intelligence (AI) will not make diagnostic radiologists redundant in the coming 10 years, whereas 54 clinicians (16.3%) thought the opposite. Conclusion: Clinicians who published in the New England Journal of Medicine or the Lancet attribute high value to medical imaging. They generally need radiologists for cross-sectional imaging interpretation, but for a considerable proportion of radiographs, their service is not required. Most expect medical imaging utilization and the need for diagnostic radiologists to increase in the foreseeable future, and do not expect AI to make radiologists redundant. Clinical relevance statement: The views of clinicians on radiology and its future may be used to determine how radiology should be practiced and be further developed. Key Points: • Clinicians generally regard medical imaging as high-value care and expect to use more medical imaging in the future. • Clinicians mainly need radiologists for cross-sectional imaging interpretation while they interpret a substantial proportion of radiographs completely by themselves. • The majority of clinicians expects that the need for diagnostic radiologists will not decrease (half of them even expect that we need more) and does not believe that AI will replace radiologists.</p
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