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Expecting the unexpected: Predicting panic attacks from mood and Twitter

E. W. McGinnis, S. Lunna, I. Berman, S. Bagdon, G. Lewis, M. V. Arnold, C. M. Danforth, P. S. Dodds, M. Price, W. E. Copeland, R. S. McGinnis

Times cited: 0

Abstract:

\textbf{Background:} Panic attacks are an impairing mental health problem that affects about one in 10 US adults every year. Current DSM criteria describe panic attacks as unexpected, occurring without warning or triggering events. The unexpected nature of panic attacks not only leads to increased anxiety for the individual but has also made panic attacks particularly challenging to study. However, recent evidence suggests that individuals who experience such attacks could identify attack triggers.\newline\newline
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BibTeX:

@Misc{mcginnis2023a,
  author = 	 {E. W. McGinnis, S. Lunna, I. Berman, S. Bagdon, G. Lewis, M. V. Arnold, C. M. Danforth, P. S. Dodds, M. Price, W. E. Copeland, R. S. McGinnis},
  title = 	 {Expecting the unexpected: {P}redicting panic attacks from mood and {T}witter},
  year = 	 {2023},
  key = 	 {health,people,prediction,social media},
  note = 	 {Availabe online at \href{https://www.medrxiv.org/content/10.1101/2023.01.26.23285057v1}{https://www.medrxiv.org/content/10.1101/2023.01.26.23285057v1}},
}
 
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