New Research from Clinical Psychological Science

Posttraumatic Stress Disorder Near and Far: Symptom Networks From 2 to 12 Months After the Virginia Tech Campus Shootings
Anthony D. Mancini, Heather L. Littleton, Amie E. Grills, and Payton J. Jones
Open Materials badge
To understand how posttraumatic stress disorder (PTSD) develops, Mancini and colleagues assessed the symptoms of female students exposed to the 2008 Virginia Tech campus shootings 2 and 12 months after the shootings. They surveyed participants regarding their PTSD symptoms, such as reexperiencing, avoidance/numbing, and arousal. Mancini and colleagues computed the networks of symptoms (i.e., networks representing what symptoms occurred, how intense/central they were, and how connected they were) and their changes from 2 to 12 months after the shootings. Results indicated that PTSD networks got stronger (symptoms became more associated with each other) and their structures changed from 2 to 12 months. Psychological reactivity at reminders of the shooting was the most central symptom at 2 months after the shooting but among the least central at 12 months. Reliving and flashbacks of the shooting, anhedonia, and physiological reactivity to reminders of the shooting became more central at 12 months than they were at 2 months. These findings suggest that PTSD development is affected by memory and fear conditioning, given that symptoms automatically cued by situations—such as reliving, thought avoidance, and physiological reactions—become more central to the network over time. Given these results, Mancini et al. propose that exposure-based approaches are counterindicated as a blanket intervention for PTSD and that early interventions might be more effective if they use cognitive techniques that seek to modify the interpretation of the traumatic event and initial PTSD symptoms.

Critical Fluctuations as an Early-Warning Signal for Sudden Gains and Losses in Patients Receiving Psychotherapy for Mood Disorders
Merlijn Olthof, Fred Hasselman, Guido Strunk, Marieke van Rooij, Benjamin Aas, Marieke A. Helmich, Günter Schiepek, and Anna Lichtwarck-Aschoff

Olthof and colleagues examined whether certain early-warning signals (EWSs) in patients receiving psychotherapy for mood disorders can predict future sudden gains or losses (i.e., abrupt changes toward lower or higher symptom severity, respectively). They collected data from patients who had a diagnosis of bipolar disorder, major depressive disorder, or persistent mood disorder and who were receiving intensive psychotherapy. For at least 30 days, patients completed a daily questionnaire assessing therapy progress, relationship quality and trust in therapists, relationships with fellow patients, and problem intensity. Problem intensity self-ratings were used to calculate sudden gains and losses. The other scales were used to identify critical fluctuations in the patients’ daily self-ratings of the psychotherapeutic process that might be classified as EWSs. Results indicated that the presence of these critical fluctuations predicted an increased probability for sudden gains or losses within the next 4 days of treatment. These findings support the idea that gains and losses in psychotherapy are preceded by EWSs in patients’ self-ratings. Olthof and colleagues suggest that small interventions targeted in these sensitive periods when EWSs are detected may have disproportionately large effects compared with their effects during more stable periods of the psychotherapeutic process.


APS regularly opens certain online articles for discussion on our website. Effective February 2021, you must be a logged-in APS member to post comments. By posting a comment, you agree to our Community Guidelines and the display of your profile information, including your name and affiliation. Any opinions, findings, conclusions, or recommendations present in article comments are those of the writers and do not necessarily reflect the views of APS or the article’s author. For more information, please see our Community Guidelines.

Please login with your APS account to comment.