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Nicholas C. Jacobson
Pennsylvania State University
21Publications
7H-index
157Citations
Publications 21
Newest
Published on Feb 1, 2019
Nicholas C. Jacobson7
Estimated H-index: 7
(PSU: Pennsylvania State University),
Nicholas C. Jacobson (PSU: Pennsylvania State University)+ 0 AuthorsSabine Wilhelm53
Estimated H-index: 53
(Harvard University)
Current approaches to psychiatric assessment are resource-intensive, requiring time-consuming evaluation by a trained clinician. Development of digital biomarkers holds promise for enabling scalable, time-sensitive, and cost-effective assessment of both psychiatric diagnosis and symptom change. The present study aimed to identify robust digital biomarkers of diagnostic status and changes in symptom severity over ~2 weeks, through re-analysis of public-use actigraphy data collected in patients wi...
Published in Behavior Therapy 3.24
Sabine Wilhelm53
Estimated H-index: 53
(Harvard University),
Hilary Weingarden9
Estimated H-index: 9
(Harvard University)
+ -3 AuthorsNicholas C. Jacobson7
Estimated H-index: 7
(Harvard University)
Abstract Our field has come a long way in establishing cognitive behavioral therapy as the empirically-supported treatment of choice for a wide range of mental and behavioral health problems. Nevertheless, most individuals with mental disorders do not receive any care at all, and those who do often have difficulty accessing care that is consistently high in quality. Addressing these issues is complex and costly and thus progress has been slow. We are entering an exciting stage in which emerging ...
Published on Jul 9, 2019
Sabine Wilhelm53
Estimated H-index: 53
(Harvard University),
Nicholas C. Jacobson7
Estimated H-index: 7
(Harvard University)
Published on Mar 1, 2019in Clinical psychological science
Michelle G. Newman38
Estimated H-index: 38
(PSU: Pennsylvania State University),
Nicholas C. Jacobson7
Estimated H-index: 7
(PSU: Pennsylvania State University)
+ 3 AuthorsMartin J. Sliwinski48
Estimated H-index: 48
(PSU: Pennsylvania State University)
The contrast avoidance model (CAM) suggests that worry increases and sustains negative emotion to prevent a negative emotional contrast (sharp upward shift in negative emotion) and increase the probability of a positive contrast (shift toward positive emotion). In Study 1, we experimentally validated momentary assessment items (N = 25). In Study 2, participants with generalized anxiety disorder (N = 31) and controls (N = 37) were prompted once per hour regarding their worry, thought valence, and...
Published on Apr 1, 2019in Psychological Reports 1.02
Michael J. Roche13
Estimated H-index: 13
(Penn State Altoona),
Nicholas C. Jacobson7
Estimated H-index: 7
(PSU: Pennsylvania State University)
Polling suggested that the 2016 United States presidential election affected citizens' mood and stress levels. Yet, polling often fails to employ repeated measurement designs that can capture pre- and post-levels of change within the same person. In this study, undergraduate students (N = 85) completed a 14-day daily diary where mood, stress, and mental health outcomes were assessed before and after the election. Multilevel modeling revealed an immediate upsurge in anxiety, stress, and poor slee...
Published on Feb 1, 2019in Behavior Research Methods 4.06
Nicholas C. Jacobson7
Estimated H-index: 7
(PSU: Pennsylvania State University),
Sy-Miin Chow15
Estimated H-index: 15
(PSU: Pennsylvania State University),
Michelle G. Newman38
Estimated H-index: 38
(PSU: Pennsylvania State University)
With the recent growth in intensive longitudinal designs and the corresponding demand for methods to analyze such data, there has never been a more pressing need for user-friendly analytic tools that can identify and estimate optimal time lags in intensive longitudinal data. The available standard exploratory methods to identify optimal time lags within univariate and multivariate multiple-subject time series are greatly underpowered at the group (i.e., population) level. We describe a hybrid ex...
Published on Nov 2, 2018in Journal of Personality Assessment 2.83
Michael J. Roche13
Estimated H-index: 13
(Penn State Altoona),
Nicholas C. Jacobson7
Estimated H-index: 7
(PSU: Pennsylvania State University),
Jennifer J. Phillips1
Estimated H-index: 1
(PSU: Pennsylvania State University)
ABSTRACTThe Level of Personality Functioning Scale (LPFS) operationalizes Criterion A of the DSM–5 alternative model for personality disorders. Yet, research on this measure has been slow to accumulate and questions remain regarding its reliability and validity. This study examined the LPFS observer-rated (OR) and self-report (SRA) versions of Criterion A in a sample of 240 students who provided psychological life history data and a variety of self-report measures. The results suggested the LPFS...
Published on Nov 1, 2018in Journal of Psychiatric Research 3.92
Nicholas C. Jacobson7
Estimated H-index: 7
(PSU: Pennsylvania State University),
Michael J. Roche13
Estimated H-index: 13
Abstract Objective Although recent research has begun to examine the impact of elevated anxiety on evolutionary fitness, no prior research has examined anxiety across a continuum. Such research is important as the effect of traits across a continuum on fertility hold important implications for the levels and distribution of the traits in later generations. Method In a three-generational sample ( N = 2657) the linear and quadratic relationship between anxiety and the number of children, grandchil...
Published on Sep 3, 2018in Structural Equation Modeling 4.43
Linying Ji1
Estimated H-index: 1
(PSU: Pennsylvania State University),
Sy-Miin Chow15
Estimated H-index: 15
(PSU: Pennsylvania State University)
+ 2 AuthorsE. Mark Cummings65
Estimated H-index: 65
(ND: University of Notre Dame)
Myriad approaches for handling missing data exist in the literature. However, few studies have investigated the tenability and utility of these approaches when used with intensive longitudinal data. In this study, we compare and illustrate two multiple imputation (MI) approaches for coping with missingness in fitting multivariate time-series models under different missing data mechanisms. They include a full MI approach, in which all dependent variables and covariates are imputed simultaneously,...
Published on Jul 4, 2018in Psychotherapy Research 2.79
Michelle G. Newman38
Estimated H-index: 38
(PSU: Pennsylvania State University),
Lucas S. LaFreniere1
Estimated H-index: 1
(PSU: Pennsylvania State University),
Nicholas C. Jacobson7
Estimated H-index: 7
(PSU: Pennsylvania State University)
AbstractObjective: Evidence is mixed regarding whether relaxation-induced anxiety (RIA) impedes relaxation training (RT) efficacy. Unlike past studies that averaged RIA across sessions, we examined peak RIA, change in RIA level across sessions, and timing of peak RIA with outcome. Method: This was a secondary analysis of Borkovec, Newman, Pincus, and Lytle [2002. A component analysis of cognitive-behavioral therapy for generalized anxiety disorder and the role of interpersonal problems. Journal ...
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