Mental health-related conversations on social media and crisis episodes: a time-series regression analysis

Abstract

We aimed to investigate whether daily fluctuations in mental health-relevant Twitter posts are associated with daily fluctuations in mental health crisis episodes. We conducted a primary and replicated time-series analysis of retrospectively collected data from twitter and two London mental healthcare providers. Daily numbers of 'crisis episodes' were defined as incident inpatient, home treatment team and crisis house referrals between 2010 and 2014. Higher volumes of depression and schizophrenia tweets were associated with higher numbers of same-day crisis episodes for both sites. After adjusting for temporal trends, seven-day lagged analyses showed significant positive associations on day 1, changing to negative associations by day 4 and reverting to positive associations by day 7. There was a 15% increase in crisis episodes on days with above-median schizophrenia-related Twitter posts. A temporal association was thus found between twitter-wide mental health-related social media content and crisis episodes in mental healthcare replicated across two services. Seven-day associations are consistent with both precipitating and longer-term risk associations. Sizes of effects were large enough to have potential local and national relevance and further research is needed to evaluate how services might better anticipate times of higher risk and identify the most vulnerable groups. It has long been recognised that material circulated via news media can have important mental health-relevant outcomes. Research in this area has particularly focused on suicide or non-fatal self-harm carried out by well-known people or fictional portrayals of these issues in widely viewed sources, addressing concerns about imitative behaviour 1. In parallel, there has also been concern around potentially stigmatising material and its longer-term impacts on the wellbeing of people with mental disorders and those who care for them 2. Depictions of mental illness on television and in film 3 and newspaper coverage of high-profile suicides 4 can have profound implications not only for public health and opinion but also directly on those experiencing the mental health issues portrayed 5. The explosion of social media channels and record levels of public use 6 , round-the-clock access to breaking news, stories and discussions as well as the sheer volume of decreasingly controlled information have transformed and amplified exposure to mental health dialogues and representations of mental illness. The use of data-rich, novel sources such as results from internet searches, social media communications and environmental records is becoming a potentially fast and cost-effective way to identify population needs and predict or prevent healthcare emergencies, such as pharmacovigilance 7. More recently, information from Twitter has been utilised for analysing behaviours, attitudes and experiences related to mental health 8 , particularly depression 9,10. In parallel, the expansion of electronic health records (EHRs) has offered extensive, longitudinal clinical

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