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

Anna Kolliakou, Ioannis Bakolis, David Chandran, Leon Derczynski, Nomi Werbeloff, David P.J. Osborn, Kalina Bontcheva, Robert Stewart

Research output: Contribution to journalArticlepeer-review

13 Scopus citations


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.

Original languageEnglish
Article number1342
JournalScientific Reports
Issue number1
StatePublished - 1 Dec 2020
Externally publishedYes

Bibliographical note

Funding Information:
This research was partially funded by the European Union/EU under the Information and Communication Technologies (ICT) theme of the 7th Framework Programme for R&D (FP7) grant PHEME (611233). The NIHR Biomedical Research Centre at the South London and Maudsley NHS Foundation Trust and King’s College London provided core support in the development and delivery of the study. Research by IB is supported by the National Institute for Health Research (NIHR) Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and by the National Institute for Health Research (NIHR) Collaboration for Leadership in Applied Health Research and Care South London at King’s College Hospital NHS Foundation Trust, King’s College London. Research by NW is supported by the UCLH NIHR Biomedical Research Centre.

Publisher Copyright:
© 2020, The Author(s).


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