Prevalence of Short Peer Reviews in 3 Leading General Medical Journals.

Importance: High-quality peer reviews are often thought to be essential to ensuring the integrity of the scientific publication process, but measuring peer review quality is challenging. Although imperfect, review word count could potentially serve as a simple, objective metric of review quality. Objective: To determine the prevalence of very short peer reviews and how often they inform editorial decisions on research articles in 3 leading general medical journals. Design, Setting, and Participants: This cross-sectional study compiled a data set of peer reviews from published, full-length original research articles from 3 general medical journals (The BMJ, PLOS Medicine, and BMC Medicine) between 2003 and 2022. Eligible articles were those with peer review data; all peer reviews used to make the first editorial decision (ie, accept vs revise and resubmit) were included. Main Outcomes and Measures: Prevalence of very short reviews was the primary outcome, which was defined as a review of fewer than 200 words. In secondary analyses, thresholds of fewer than 100 words and fewer than 300 words were used. Results were disaggregated by journal and year. The proportion of articles for which the first editorial decision was made based on a set of peer reviews in which very short reviews constituted 100%, 50% or more, 33% or more, and 20% or more of the reviews was calculated. Results: In this sample of 11 466 reviews (including 6086 in BMC Medicine, 3816 in The BMJ, and 1564 in PLOS Medicine) corresponding to 4038 published articles, the median (IQR) word count per review was 425 (253-575) words, and the mean (SD) word count was 520.0 (401.0) words. The overall prevalence of very short (<200 words) peer reviews was 1958 of 11 466 reviews (17.1%). Across the 3 journals, 843 of 4038 initial editorial decisions (20.9%) were based on review sets containing 50% or more very short reviews. The prevalence of very short reviews and share of editorial decisions based on review sets containing 50% or more very short reviews was highest for BMC Medicine (693 of 2585 editorial decisions [26.8%]) and lowest for The BMJ (76 of 1040 editorial decisions [7.3%]). Conclusion and Relevance: In this study of 3 leading general medical journals, one-fifth of initial editorial decisions for published articles were likely based at least partially on reviews of such short length that they were unlikely to be of high quality. Future research could determine whether monitoring peer review length improves the quality of peer reviews and which interventions, such as incentives and norm-based interventions, may elicit more detailed reviews.

Data Source Concordance for Infectious Disease Epidemiology.

Background: As highlighted by the COVID-19 pandemic, researchers are eager to make use of a wide variety of data sources, both government-sponsored and alternative, to characterize the epidemiology of infectious diseases. To date, few studies have investigated the strengths and limitations of sources currently being used for such research. These are critical for policy makers to understand when interpreting study findings. Methods: To fill this gap in the literature, we compared infectious disease reporting for three diseases (measles, mumps, and varicella) across four different data sources: Optum (health insurance billing claims data), HealthMap (online news surveillance data), Morbidity and Mortality Weekly Reports (official government reports), and National Notifiable Disease Surveillance System (government case surveillance data). We reported the yearly number of national- and state-level disease-specific case counts and disease clusters according to each of our sources during a five-year study period (2013-2017). Findings: Our study demonstrated drastic differences in reported infectious disease incidence across data sources. When compared against the other three sources of interest, Optum data showed substantially higher, implausible standardized case counts for all three diseases. Although there was some concordance in identified state-level case counts and disease clusters, all four sources identified variations in state-level reporting. Interpretation: Researchers should consider data source limitations when attempting to characterize the epidemiology of infectious diseases. Some data sources, such as billing claims data, may be unsuitable for epidemiological research within the infectious disease context.