TY - JOUR
T1 - The trajectories of online mental health information seeking
T2 - Modeling search behavior before and after completion of self-report screens
AU - Lekkas, Damien
AU - Yom-Tov, Elad
AU - Heinz, Michael V.
AU - Gyorda, Joseph A.
AU - Nguyen, Theresa
AU - Barr, Paul J.
AU - Jacobson, Nicholas C.
N1 - Publisher Copyright:
© 2024 Elsevier Ltd
PY - 2024/8
Y1 - 2024/8
N2 - There is an appreciable mental health treatment gap in the United States. Efforts to bridge this gap and improve resource accessibility have led to the provision of online, clinically-validated tools for mental health self-assessment. In theory, these screens serve as an invaluable component of information-seeking, representing the preparative and action-oriented stages of this process while altering or reinforcing the search content and language of individuals as they engage with information online. Accordingly, this work investigated the association of screen completion with mental health-related search behaviors. Three-year internet search histories from N = 7572 Microsoft Bing users were paired with their respective depression, anxiety, bipolar disorder, or psychosis online screen completion and sociodemographic data available through Mental Health America. Data was transformed into network representations to model queries as discrete steps with probabilities and times-to-transition from one search type to another. Search data subsequent to screen completion was also modeled using Markov chains to simulate likelihood trajectories of different search types through time. Differences in querying dynamics relative to screen completion were observed, with searches involving treatment, diagnosis, suicidal ideation, and suicidal intent commonly emerging as the highest probability behavioral information seeking endpoints. Moreover, results pointed to the association of low risk states of psychopathology with transitions to extreme clinical outcomes (i.e., active suicidal intent). Future research is required to draw definitive conclusions regarding causal relationships between screens and search behavior.
AB - There is an appreciable mental health treatment gap in the United States. Efforts to bridge this gap and improve resource accessibility have led to the provision of online, clinically-validated tools for mental health self-assessment. In theory, these screens serve as an invaluable component of information-seeking, representing the preparative and action-oriented stages of this process while altering or reinforcing the search content and language of individuals as they engage with information online. Accordingly, this work investigated the association of screen completion with mental health-related search behaviors. Three-year internet search histories from N = 7572 Microsoft Bing users were paired with their respective depression, anxiety, bipolar disorder, or psychosis online screen completion and sociodemographic data available through Mental Health America. Data was transformed into network representations to model queries as discrete steps with probabilities and times-to-transition from one search type to another. Search data subsequent to screen completion was also modeled using Markov chains to simulate likelihood trajectories of different search types through time. Differences in querying dynamics relative to screen completion were observed, with searches involving treatment, diagnosis, suicidal ideation, and suicidal intent commonly emerging as the highest probability behavioral information seeking endpoints. Moreover, results pointed to the association of low risk states of psychopathology with transitions to extreme clinical outcomes (i.e., active suicidal intent). Future research is required to draw definitive conclusions regarding causal relationships between screens and search behavior.
KW - Markov chain
KW - Mental health
KW - Network model
KW - Online search behavior
KW - Screen
KW - Simulation
UR - http://www.scopus.com/inward/record.url?scp=85190750072&partnerID=8YFLogxK
U2 - 10.1016/j.chb.2024.108267
DO - 10.1016/j.chb.2024.108267
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C2 - 38774307
AN - SCOPUS:85190750072
SN - 0747-5632
VL - 157
JO - Computers in Human Behavior
JF - Computers in Human Behavior
M1 - 108267
ER -