Browsing by Author "Giorgi, Salvatore"

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    Smartphone language features may help identify adverse post-traumatic neuropsychiatric sequelae and their trajectories
    (Springer Nature, 2025) Vizer, Lisa; Pierce, Jennifer; Ji, Yinyao; Bucher, Meredith A.; Liu, Mochuan; Ungar, Lyle; Giorgi, Salvatore; Xing, Zhaopeng; House, Stacey L.; Beaudoin, Francesca L.; Stevens, Jennifer S.; Neylan, Thomas C.; Clifford, Gari D.; Jovanovic, Tanja; Linnstaedt, Sarah D.; Zeng, Donglin; Germine, Laura T.; Bollen, Kenneth A.; Rauch, Scott L.; Haran, John P.; Storrow, Alan B.; Lewandowski, Christopher; Musey, Paul I., Jr.; Hendry, Phyllis L.; Sheikh, Sophia; Jones, Christopher W.; Punches, Brittany E.; Hudak, Lauren A.; Pascual, Jose L.; Seamon, Mark J.; Harris, Erica; Pearson, Claire; Peak, David A.; Merchant, Roland C.; Domeier, Robert M.; O'Neil, Brian J.; Sergot, Paulina; Sanchez, Leon D.; Bruce, Steven E.; Harte, Steven E.; Kessler, Ronald C.; Koenen, Karestan C.; McLean, Samuel A.; An, Xinming; Emergency Medicine, School of Medicine
    Language features may reflect underlying cognitive and emotional processes following a traumatic event that portend clinical outcomes. The authors sought to determine whether language features from usual smartphone use were markers associated with concurrent posttraumatic symptoms and worsening or improving posttraumatic symptoms over time following a traumatic exposure. This investigation was a secondary analysis of the Advancing Understanding of RecOvery afteR traumA study, a longitudinal study of traumatic outcomes among survivors recruited from 33 emergency departments across the United States. Adverse posttraumatic sequelae were assessed over the six months following the initial traumatic exposure. Language features were extracted from usual smartphone use in a specialized app. Bivariate linear mixed models were used to identify and validate language features that are markers associated with posttraumatic symptoms. Participants were 1744 trauma survivors, with a mean age of 39 [SD = 13] years old, and 56% were female. Fourteen language features were associated with severity level of posttraumatic symptoms at specific timepoints (cross-sectional markers) and five features were associated with change in severity level of posttraumatic symptoms (longitudinal markers). References to the body and health or illness were predictive of worsening pain, somatic, and thinking/concentration/fatigue symptom severity over time. An increase in references to others was associated with improvement in somatic symptom severity over time and increases in expressions of causation or cognitive processes were associated with improvement in pain symptom severity over time. Language features derived from usual smartphone use can convey important information about health, functioning, and recovery following a traumatic event. Clinicians might utilize such information to determine who may experience a high symptom burden or risk of worsening posttraumatic symptoms.