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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 P J; Bontcheva, Kalina; Stewart, Robert.
Afiliação
  • Kolliakou A; Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom. anna.kolliakou@kcl.ac.uk.
  • Bakolis I; Department of Biostatistics and Health Informatics, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom.
  • Chandran D; Centre for Implementation Science, Health Services and Population Research Department, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom.
  • Derczynski L; Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom.
  • Werbeloff N; Department of Computer Science, IT University of Copenhagen, Copenhagen, Denmark.
  • Osborn DPJ; Division of Psychiatry, University College London, London, United Kingdom.
  • Bontcheva K; Camden and Islington NHS Foundation Trust, London, United Kingdom.
  • Stewart R; Division of Psychiatry, University College London, London, United Kingdom.
Sci Rep ; 10(1): 1342, 2020 02 06.
Article em En | MEDLINE | ID: mdl-32029754
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.
Assuntos

Texto completo: 1 Bases de dados: MEDLINE Assunto principal: Saúde Mental / Mídias Sociais / Transtornos Mentais Tipo de estudo: Diagnostic_studies / Etiology_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Limite: Humans País/Região como assunto: Europa Idioma: En Revista: Sci Rep Ano de publicação: 2020 Tipo de documento: Article País de afiliação: Reino Unido

Texto completo: 1 Bases de dados: MEDLINE Assunto principal: Saúde Mental / Mídias Sociais / Transtornos Mentais Tipo de estudo: Diagnostic_studies / Etiology_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Limite: Humans País/Região como assunto: Europa Idioma: En Revista: Sci Rep Ano de publicação: 2020 Tipo de documento: Article País de afiliação: Reino Unido