The Relationship Between Open Access Article Publishing and Short-Term Citations in Otolaryngology

OBJECTIVES

The purpose of this study is to compare the number of citations received by open access articles versus subscription access articles in subscription journals in the Otolaryngology literature.

METHODS

Using the Dimensions research database, we examined articles indexed to PubMed with at least 5 citations published in 2018. Articles were included from Otolaryngology-Head and Neck Surgery, The Laryngoscope, JAMA Otolaryngology-Head and Neck Surgery, Annals of Otology, Rhinology, and Laryngology, and American Journal of Otolaryngology. Multivariate Poisson regression modeling was used to adjust for journal, article type, and topic. Practice guidelines, position statements, or retractions were excluded as potential outliers.

RESULTS

137 open access articles and 337 subscription access articles meeting inclusion criteria were identified, with a median citation number of 8 (IQR 6-11). The most common article type was original investigation (82.5%), and the most common study topic was head and neck (28.9%). Open access articles had a higher median number of citations at 9 (IQR 6-13) when compared to subscription access articles at 7 (IQR 6-10) (P = .032). Open access status was significantly associated with a higher number of citations than subscription access articles when adjusting for journal, article type, and topic (β = .272, CI 0.194-0.500, P < .001).

CONCLUSIONS

Although comprising a minority of articles examined in this study of subscription journals, open access articles were associated with a higher number of citations than subscription access articles. Open access publishing may facilitate the spread of novel findings in Otolaryngology.

Evaluating YouTube as a Resource for Trigeminal Neuralgia Patient Education

PURPOSE

The objective of this study was to examine the educational value of YouTube as a source of patient information regarding trigeminal neuralgia and its treatment. We also sought to determine the degree of bias that is present in the top videos regarding this condition.

MATERIALS AND METHODS

We selected 6 search terms related to trigeminal neuralgia to examine on YouTube for quality and bias using the DISCERN criteria. Filtering by relevance and total view count, we determined the top 20 results for each search term and evaluated all videos for overall educational quality and creator bias. We categorized the type of content creator and compared overall DISCERN scores and bias scores between creator type and search term.

RESULTS

There were 80 unique and 40 duplicate videos. There were 10,745,574 total views across all videos, with an average view count of 89,546. The mean DISCERN score for all videos was 1.7, and the mean bias score was 2.2. Based on individual search terms, the highest mean DISCERN score was for trigeminal neuralgia surgery (2.1) and the highest mean bias score was for tic douloureux (2.8). Among creator types, medical professionals had significantly higher overall (2.2) and bias (2.6) scores.

CONCLUSIONS

Overall, YouTube is a relatively poor source of unbiased information about trigeminal neuralgia. Among the existing content, medical professionals provide educational material that is the highest quality and the most unbiased.

Characterising the composition of waste-derived fuels using a novel image analysis tool

An experimental study was completed using a previously developed and innovative image analysis approach, which has been applied here to shredded waste materials representative of waste-derived fuels. Waste components were collected from source-segregated recycling containers and shredded to <150 mm. These materials were then used to produce 3× samples of different composition. The samples were spread to represent materials on a conveyor belt, and multiple images of each sample were captured using 10×10 cm and 20×20 cm quadrats. The images were processed using ERDAS Imagine software to determine the area covered by each waste component. This coverage was converted into a mass using density data determined as part of this study, yielding a determined composition which was then compared with the known composition of the samples. The image analysis results indicated a strong correlation with the actual values (mean r=0.89). The area coverage of the sample (10×10 cm or 20×20 cm) contributes to the accuracy as the dot-grid approach used with the particle size within the samples may result in components not being sufficiently monitored. This manuscript presents initial results of the application of an adapted innovative image-based method, and critically assesses how the technique could be improved and developed in the future.