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Impact of podcasting on novel and conventional measures of academic impact

Abstract

Objective Altmetric Attention Score (AAS) is an alternative metric for estimating the impact of academic publications. We studied the association of using podcasting to highlight publications about gynecological cancer with AAS and citation scores.

Methods Articles that were featured in the International Journal of Gynecological Cancer (IJGC) podcast series January 2019 to September 2022 were matched 1:1 to control articles by the journal in which the article was published, study topic and design, single/multicenter data, and year of publication. Podcast articles were compared with matched-controls by citation metrics and altmetric scores.

Results A total of 99 podcasted articles published in 16 journals were matched. Median AAS was significantly higher in the podcast group than the matched-control group (22 (14–42) vs 5 (1–17), p<0.001). In a multivariable regression analysis, podcasting was the only factor associated with a high AAS (adjusted odds ratio (aOR) 8.6, 95% CI 3.8 to 19.7). In the podcast group, the median number of citations per year was higher than matched-control studies (5.5 (3.0–12.7) vs 4.5 (2.0–9.5), p=0.047). The only article characteristics that were independently associated with ≥12 citations per year were if the publication described a randomized controlled trial (aOR 4.7, 95% CI 1.6 to 13.6) or featured cervical carcinoma as the subject focus (aOR 2.9, 95% CI 1.3 to 6.5). Compared with all articles published in IJGC during the study period, articles that were featured in a podcast had higher median citations per year (5 (2–10) vs 1 (0–2.5), p<0.001).

Conclusion When compared with matched-controls, podcasting an article is associated with a higher AAS but is not associated with generating a high (≥12) number of citations per year. When compared with all articles published in the same journal during the same study period, articles that were featured in a podcast had higher median citations per year.

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Data availability statement

Data are available upon reasonable request. Database was generated from publicly available resources.

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