Debates about posttraumatic stress disorder (PTSD) often turn on whether it is a timeless, cross-culturally valid natural phenomenon or a socially constructed idiom of distress. Most clinicians seem to favor the first view, differing only in whether they conceptualize PTSD as a discrete category or the upper end of a dimension of stress responsiveness. Yet both categorical and dimensional construals presuppose that PTSD symptoms are fallible indicators reflective of an underlying, latent variable. This presupposition has governed psychopathology research for decades, but it rests on problematic psychometric premises. In this article, we review an alternative, network perspective for conceptualizing mental disorders as causal systems of interacting symptoms, and we illustrate this perspective via analyses of PTSD symptoms reported by survivors of the Wenchuan earthquake in China. Finally, we foreshadow emerging computational methods that may disclose the causal structure of mental disorders.
IntroductionCurrent evidence has demonstrated the usefulness of mobile technology in supporting smoking cessation. 1 The most recent Cochrane review, based on 20 studies and a total sample size of 9100 smokers, indicated significant benefit of mobile phone-based smoking cessation interventions on long-term outcomes, with a relative risk estimate of 1.71, compared to no intervention or less intensive intervention via mobile.1 These effects were achieved with fully-automated, highly cost-effective programs of unprecedented reach. They were also achieved with a relatively low level of technological sophistication, as up to this point, mobile technology approaches to smoking cessation have largely used text messaging. AbstractIntroduction: Smartphone technology is ideally suited to provide tailored smoking cessation support, yet it is unclear to what extent currently existing smartphone "apps" use tailoring, and if tailoring is related to app popularity and user-rated quality. Methods: We conducted a content analysis of Android smoking cessation apps (n = 225), downloaded between October 1, 2013 to May 31, 2014. We recorded app popularity (>10 000 downloads) and user-rated quality (number of stars) from Google Play, and coded the existence of tailoring features in the apps within the context of using the 5As ("ask, " "advise, " "assess, " "assist, " and "arrange follow-up"), as recommended by national clinical practice guidelines. Results: Apps largely provided simplistic tools (eg, calculators, trackers), and used tailoring sparingly: on average, apps addressed 2.1 ± 0.9 of the 5As and used tailoring for 0.7 ± 0.9 of the 5As. Tailoring was positively related to app popularity and user-rated quality: apps that used two-way interactions (odds ratio ), proactive alerts .38]), responsiveness to quit status ), addressed more of the 5As (OR = 1.53 [1.10-2.14]), used tailoring for more As (OR = 1.67 [1.21-2.30]), and/or used more ways of tailoring 5As content (OR = 1.35 [1.13-1.62]) were more likely to be frequently downloaded. Higher star ratings were associated with a higher number of 5As addressed (b = 0.16 [0.03-0.30]), a higher number of 5As with any level of tailoring (b = 0.14 [0.01-0.27]), and a higher number of ways of tailoring 5As content (b = 0.08 [0.002-0.15]). Conclusions: Publically available smartphone smoking cessation apps are not particularly "smart": they commonly fall short of providing tailored feedback, despite users' preference for these features.
DNA methylation patterns at specific cytosine-phosphate-guanine (CpG) sites predictably change with age and can be used to derive "epigenetic age", an indicator of biological age, as opposed to merely chronological age. A relatively new estimator, called "DNAm GrimAge", is notable for its superior predictive ability in older populations regarding numerous age-related metrics like time-to-death, time-to-coronary heart disease, and time-to-cancer. PTSD is associated with premature mortality and frequently has comorbid physical illnesses suggestive of accelerated biological aging. This is the first study to assess DNAm GrimAge in PTSD patients. We investigated the acceleration of GrimAge relative to chronological age, denoted "AgeAccelGrim" in combat trauma-exposed male veterans with and without PTSD using crosssectional and longitudinal data from two independent well-characterized veteran cohorts. In both cohorts, AgeAccelGrim was significantly higher in the PTSD group compared to the control group (N = 162, 1.26 vs −0.57, p = 0.001 and N = 53, 0.93 vs −1.60 Years, p = 0.008), suggesting accelerated biological aging in both cohorts with PTSD. In 3-year follow-up study of individuals initially diagnosed with PTSD (N = 26), changes in PTSD symptom severity were correlated with AgeAccelGrim changes (r = 0.39, p = 0.049). In addition, the loss of CD28 cell surface markers on CD8 + T cells, an indicator of T-cell senescence/exhaustion that is associated with biological aging, was positively correlated with AgeAccelGrim, suggesting an immunological contribution to the accelerated biological aging. Overall, our findings delineate cellular correlates of biological aging in combat-related PTSD, which may help explain the increased medical morbidity and mortality seen in this disease. Members of the PTSD Systems Biology Consortium are listed in Supplementary information.
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