Predicting self-injurious thoughts in daily life using ambulatory assessment of state cognition
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https://hdl.handle.net/10037/24454Date
2021-04-12Type
Journal articleTidsskriftartikkel
Peer reviewed
Author
Le, Thanh P.; Moscardini, Emma; Cowan, Tovah; Elvevåg, Brita; Holmlund, Terje Bektesevic; Foltz, Peter W.; Tucker, Raymond P.; Schwartz, Elana K.; Cohen, Alex S.Abstract
Self-injurious thoughts (SITs) fluctuate considerably from moment to moment. As such, “static” and temporally stable predictors (e.g., demographic variables, prior history) are suboptimal in predicting imminent SITs. This concern is particularly true for “online” cognitive abilities, which are important for understanding SITs, but are typically measured using tests selected for temporal stability. Advances in ambulatory assessments (i.e., real-time assessment in a naturalistic environment) allow for measuring cognition with improved temporal resolution. The present study measured relationships between “state” cognitive performance, measured using an ambulatory-based Trail Making Test, and SITs. Self-reported state hope and social connectedness was also measured. Data were collected using a specially designed mobile application (administered 4x/week up to 28 days) in substance use inpatients (N = 99). Consistent with prior literature, state hope and social connectedness was significantly associated with state SITs. Importantly, poorer state cognitive performance also significantly predicted state SITs, independent of hallmark static and state self-report risk variables. These findings highlight the potential importance of “online” cognition to predict SITs. Ambulatory recording reflects an efficient, sensitive, and ecological valid methodology for evaluating subjective and objectives predictors of imminent SITs.
Publisher
ElsevierCitation
Le, Moscardini, Cowan, Elvevåg, Holmlund, Foltz, Tucker, Schwartz, Cohen. Predicting self-injurious thoughts in daily life using ambulatory assessment of state cognition. Journal of Psychiatric Research. 2021;138:335-341Metadata
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