We included manuscripts published in Autism, the Journal of Autism and Developmental Disorders (JADD), and Autism Research. We chose these three journals because they have higher impact factors and more autism-specific published papers than other journals. We also chose to include three journals instead of one so that we could have more complete data surrounding downloads and citations for autism-specific papers.
We included articles published in 2019 to ensure that there was adequate time for work from each month throughout the year to be cited and downloaded. We did not include articles published in 2020, as our findings may have been confounded by the effects of the Covid-19 pandemic on the research publishing process (Harrop et al., 2021). We limited the manuscripts analyzed to original articles, review articles, and short reports. Articles that were excluded from analyses included letters to the editor, commentary, and corrections. In total, there were 729 articles included, with 182 articles from Autism, 401 from JADD, and 146 from Autism Research.
The first author extracted data in June 2021 and entered it into a REDCap database. We obtained the following information from each journal’s website: (1) authorship; (2) initial online publication date; (3) official publication date; (4) open access status; and (5) article type (i.e., short report, original article, review article). The first author also noted each article’s primary methodology based on the abstract (i.e., quantitative, qualitative, mixed method, review paper). We extracted information on the number of public tweets on Twitter, public posts on Facebook, as well as the number of stories from news sources from Altmetric.com. News stories are detected by Altmetric.com if they are posted online and contain a direct link to the article or necessary information for text mining. Autism and JADD websites report the number of downloads per article. As this information is not provided on the Autism Research website, download information was provided by the journal’s editorial team. Citation information for each article was obtained from Google Scholar.
To describe the articles that were most downloaded, cited, and shared on social media, we classified articles into the Interagency Autism Coordinating Committee (IACC)’s Strategic Plan categories of: (1) Diagnosis/Screening, (2) Biology, (3) Risk Factors, (4) Treatments/Interventions, (5) Services, (6) Lifespan Issues, and (7) Surveillance/Infrastructure (IACC, 2018). We also recorded the populations that these articles studied.
We calculated descriptive statistics, including frequencies and percentages, medians, and interquartile ranges. Our dependent variables were: (1) number of downloads; and (2) number of citations. Our primary independent variables were social media and news coverage, quantified by: (1) Twitter shares, (2) Facebook posts, and (3) news stories. We used a generalized linear model with a gamma distribution and log link to quantify the relationship between our dependent and independent variables, in accordance with standards for analyzing continuous, positively-skewed, non-negative data (Ng & Cribbie, 2017). We also classified articles in the 90th percentile for downloads as “highly downloaded” and articles in the 90th percentile for citations as “highly cited.” We used multivariable logistic regression to quantify the relative contributions of each independent variable to the odds being highly downloaded or highly cited. All multivariable analyses controlled for open access status, the number of months since initial online publication (i.e., e-publication ahead of print), and journal of origin. Relationships between the independent and dependent variables were considered statistically significant if the 95% confidence interval for the parameter estimate did not cross 1.0.
Institutional Review Board Approval
This analysis is not based on human subjects research so it was exempt from review from the authors’ institutional review boards.