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Using scite to find active research topics

Mon Jan 16 2023

One of my favorite pastimes is using scite to find active areas of research - topics that invite lively discussion, or hypotheses that are highly contested. This can be accomplished by searching for a topic and filtering the results to only show articles that have a relatively high number of both supporting and contrasting citations.

One contentious finding is the relationship between the COVID-19 pandemic and mental health. It’s not surprising that there has been a large number of papers published on this topic (over 60,000!), but exactly how the pandemic has impacted mental health is still a largely open question.

Take, for example, Xiong et al. (2020). In this meta analysis (a systematic review of previously-published studies), the authors identify a number of risk factors associated with poorer mental health. One such finding is that women were at greater risk of poorer mental health over the course of the pandemic.

However, subsequent studies have shown otherwise. Limiting the report page to contrasting citations, we can see that many papers have failed to show any sex difference in various indicators of mental health over the course of the pandemic.

Other citing papers failed to find a robust decline in mental health over the course of the pandemic. For example, Zhao et al. (2022) found no decrease in depression or anxiety.

Still, there were plenty of supporting works citing Xiong et al. Using the filtering feature on the report page, we see that a number of mental health indicators - depression, stress, and anxiety, for example - were found to be elevated during the pandemic, and especially during lockdown periods.

In short, the mental health impact of the COVID-19 pandemic is a lively area of research, as indicated by the relatively high number of both supporting and contrasting citations to a key paper.

Let’s try the same trick with a search for papers about social media. This brings us to Correra and colleagues (2010), who identify a number of personality characteristics associated with higher levels of social media use. Specifically, they (not surprisingly) find that social media use is positively correlated with extraversion, but Acar (2020) failed to find the same relationship. Similarly, Andreassen et al. (2014) failed to find relationships between other personality variables - such as agreeableness and creativity - and social media use.

Once again, however, there is no shortage of papers that replicate many of Correra et al.’s findings. For example, Mancinelli et al (2019) found similar correlations between extraversion and social media use, and Bai et al. (2012) found similar results for openness to experience (another widely-studied personality trait).

These are just two small examples, but they show how scite.ai can be used to find areas where healthy scientific debate is alive and well.