Posttraumatic stress symptom severity predicts marijuana use coping motives among traumatic event-exposed marijuana users

2007 ◽  
Vol 20 (4) ◽  
pp. 577-586 ◽  
Author(s):  
Marcel O. Bonn-Miller ◽  
Anka A. Vujanovic ◽  
Matthew T. Feldner ◽  
Amit Bernstein ◽  
Michael J. Zvolensky
2012 ◽  
Vol 37 (1) ◽  
pp. 53-59 ◽  
Author(s):  
Sarah J. Bujarski ◽  
Matthew T. Feldner ◽  
Sarah F. Lewis ◽  
Kimberly A. Babson ◽  
Casey D. Trainor ◽  
...  

2011 ◽  
Vol 25 (2) ◽  
pp. 130-141 ◽  
Author(s):  
Anka A. Vujanovic ◽  
Erin C. Marshall-Berenz ◽  
Michael J. Zvolensky

This investigation first examined the incremental validity of distress tolerance in terms of alcohol use coping motives within a trauma-exposed community sample of adults, beyond the variance contributed by posttraumatic stress symptom severity, difficulties in emotion regulation, alcohol consumption, and other (noncriterion) alcohol use motives. Secondly, the potential mediating role of distress tolerance in the association between posttraumatic stress symptom severity and alcohol use coping motives was tested. Participants were 83 community-recruited individuals (63.8% women; Mage = 22.98, SD = 9.24) who endorsed exposure to at least one traumatic life event and past-month alcohol use. Participants were assessed using structured diagnostic interviews and a series of self-report inventories. Results were consistent with hypotheses, because distress tolerance was significantly and incrementally associated with alcohol use coping motives; and distress tolerance at least partially mediated the association between posttraumatic stress and alcohol use coping motives. Theoretical and clinical implications as well as future directions regarding the association between distress tolerance and alcohol use motives among trauma-exposed persons are discussed.


2014 ◽  
Vol 38 (4) ◽  
pp. 449-457 ◽  
Author(s):  
Thomas G. Adams ◽  
Christal L. Badour ◽  
Joshua M. Cisler ◽  
Matthew T. Feldner

2020 ◽  
pp. 088626052097819
Author(s):  
Matthew C. Morris ◽  
Francisco Sanchez-Sáez ◽  
Brooklynn Bailey ◽  
Natalie Hellman ◽  
Amber Williams ◽  
...  

A substantial minority of women who experience interpersonal violence will develop posttraumatic stress disorder (PTSD). One critical challenge for preventing PTSD is predicting whose acute posttraumatic stress symptoms will worsen to a clinically significant degree. This 6-month longitudinal study adopted multilevel modeling and exploratory machine learning (ML) methods to predict PTSD onset in 58 young women, ages 18 to 30, who experienced an incident of physical and/or sexual assault in the three months prior to baseline assessment. Women completed baseline assessments of theory-driven cognitive and neurobiological predictors and interview-based measures of PTSD diagnostic status and symptom severity at 1-, 3-, and 6-month follow-ups. Higher levels of self-blame, generalized anxiety disorder severity, childhood trauma exposure, and impairment across multiple domains were associated with a pattern of high and stable posttraumatic stress symptom severity over time. Predictive performance for PTSD onset was similarly strong for a gradient boosting machine learning model including all predictors and a logistic regression model including only baseline posttraumatic stress symptom severity. The present findings provide directions for future work on PTSD prediction among interpersonal violence survivors that could enhance early risk detection and potentially inform targeted prevention programs.


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