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Full-Text Articles in Psychiatry and Psychology
Measuring Novel Antecedents Of Mental Illness: The Questionnaire Of Unpredictability In Childhood, Laura M. Glynn, Hal S. Stern, Mariann A. Howland, Victoria B. Risbrough, Dewleen G. Baker, Caroline M. Nievergelt, Tallie Z. Baram, Elysia P. Davis
Measuring Novel Antecedents Of Mental Illness: The Questionnaire Of Unpredictability In Childhood, Laura M. Glynn, Hal S. Stern, Mariann A. Howland, Victoria B. Risbrough, Dewleen G. Baker, Caroline M. Nievergelt, Tallie Z. Baram, Elysia P. Davis
Psychology Faculty Articles and Research
Increasing evidence indicates that, in addition to poverty, maternal depression, and other well-established factors, unpredictability of maternal and environmental signals early in life influences trajectories of brain development, determining risk for subsequent mental illness. However, whereas most risk factors for later vulnerability to mental illness are readily measured using existing, clinically available tools, there are no similar measures for assessing early-life unpredictability. Here we validate the Questionnaire of Unpredictability in Childhood (QUIC) and examine its associations with mental health in the context of other indicators of childhood adversity (e.g., traumatic life events, socioeconomic status, and parenting quality). The QUIC was …
A Markov Approach For Increasing Precision In The Assessment Of Data-Intensive Behavioral Interventions, Vincent Berardi, Ricardo Carretero-González, John Belletierre, Marc A. Adams, Suzanne C. Hughes, Melbourne Hovell
A Markov Approach For Increasing Precision In The Assessment Of Data-Intensive Behavioral Interventions, Vincent Berardi, Ricardo Carretero-González, John Belletierre, Marc A. Adams, Suzanne C. Hughes, Melbourne Hovell
Psychology Faculty Articles and Research
Health interventions using real-time sensing technology are characterized by intensive longitudinal data, which has the potential to enable nuanced evaluations of individuals’ responses to treatment. Existing analytic tools were not developed to capitalize on this opportunity as they typically focus on first-order findings such as changes in the level and/or slope of outcome variables over different intervention phases. This paper introduces an exploratory, Markov-based empirical transition method that offers a more comprehensive assessment of behavioral responses when intensive longitudinal data are available. The procedure projects a univariate time-series into discrete states and empirically determines the probability of transitioning from one …