Mental health-related conversations on social media and crisis episodes: a time-series regression analysis
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Mental health-related conversations on social media and crisis episodes: a time-series regression analysis. / Kolliakou, Anna; Bakolis, Ioannis; Chandran, David; Derczynski, Leon; Werbeloff, Nomi; Osborn, David PJ; Bontcheva, Kalina; Rob, Stewart.
In: Scientific Reports, Vol. 10, 1342, 02.2020.Research output: Journal Article or Conference Article in Journal › Journal article › Research › peer-review
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TY - JOUR
T1 - Mental health-related conversations on social media and crisis episodes: a time-series regression analysis
AU - Kolliakou, Anna
AU - Bakolis, Ioannis
AU - Chandran, David
AU - Derczynski, Leon
AU - Werbeloff, Nomi
AU - Osborn, David PJ
AU - Bontcheva, Kalina
AU - Rob, Stewart
PY - 2020/2
Y1 - 2020/2
N2 - 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.
AB - 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.
U2 - 10.1038/s41598-020-57835-9
DO - 10.1038/s41598-020-57835-9
M3 - Journal article
VL - 10
JO - Scientific Reports
JF - Scientific Reports
SN - 2045-2322
M1 - 1342
ER -
ID: 84743770