The COVID-19 pandemic, like many of the disease outbreaks that have preceded it, is likely to have a profound effect on mental health. Understanding its impact can inform strategies for mitigating negative consequences. In this work, we seek to better understand the effects of COVID-19 on mental health by examining discussions within mental health support communities on Reddit. First, we quantify the rate at which COVID-19 is discussed in each community, or subreddit, in order to understand levels of pandemic-related discussion. Next, we examine the volume of activity in order to determine whether the number of people discussing mental health has risen. Finally, we analyze how COVID-19 has influenced language use and topics of discussion within each subreddit.

Bipolar Disorder, a mood disorder with recurrent mania and depression, requires ongoing monitoring and specialty management. Current monitoring strategies are clinically-based, engaging highly specialized medical professionals who are becoming increasingly scarce. Automatic speech-based monitoring via smartphones has the potential to augment clinical monitoring by providing inexpensive and unobtrusive measurements of a patient's daily life. The success of such an approach is contingent on the ability to successfully utilize "in-the-wild" data. However, most existing work on automatic mood detection uses datasets collected in clinical or laboratory settings. This study presents experiments in automatically detecting depression severity in individuals with Bipolar Disorder using data derived from clinical interviews and from personal conversations. We find that mood assessment is more accurate using data collected from clinical interactions, in part because of their highly structured nature. We demonstrate that although the features that are most effective in clinical interactions do not extend well to personal conversational data, we can identify alternative features relevant in personal conversational speech to detect mood symptom severity. Our results highlight the challenges unique to working with "in-the-wild" data, providing insight into the degree to which the predictive ability of speech features is preserved outside of a clinical interview.

Like many of the disasters that have preceded it, the COVID-19 pandemic is likely to have a profound impact on people’s mental health. Understanding its impact can inform strategies for mitigating negative consequences. This work seeks to better understand the impacts of COVID-19 on mental health by examining how discussions on mental health subreddits have changed in the three months following the WHO’s declaration of a global pandemic. First, the rate at which the pandemic is discussed in each community is quantified. Then, volume of activity is measured to determine whether the number of people with mental health concerns has risen, and user interactions are analyzed to determine how they have changed during the pandemic. Finally, the content of the discussions is analyzed. Each of these metrics is considered with respect to a set of control subreddits to better understand if the changes present are specific to mental health subreddits or are representative of Reddit as a whole. There are numerous changes in the three mental health subreddits that we consider, r/Anxiety, r/depression, r/SuicideWatch; there is reduced posting activity in most cases, and there are significant changes in discussion of some topics such as work and anxiety. The results suggest that there is not an overwhelming increase in online mental health support-seeking on Reddit during the pandemic, but that discussion content related to mental health has changed.

The COVID-19 pandemic, like many of the disease outbreaks that have preceded it, is likely to have a profound effect on mental health. Understanding its impact can inform strategies for mitigating negative consequences. In this work, we seek to better understand the effects of COVID-19 on mental health by examining discussions within mental health support communities on Reddit. First, we quantify the rate at which COVID-19 is discussed in each community, or subreddit, in order to understand levels of preoccupation with the pandemic. Next, we examine the volume of activity in order to determine whether the quantity of people seeking online mental health support has risen. Finally, we analyze how COVID-19 has influenced language use and topics of discussion within each subreddit.

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