Assessment of the psychosocial predictors of health-related quality of life in a PTSD clinical sample

Although a wide array of the scientific literature explores the links between posttraumatic stress disorder (PTSD) symptoms, coping strategies, and social support and health-related quality of life (HRQoL) as an outcome variable, their connections remain unclear. It is unknown whether PTSD symptom severity, coping strategies, and social support explain each a unique portion of variance of HRQoL of individuals with PTSD. In the current study, based on pretreatment results of a broader study assessing a specific intervention for PTSD, 94 individuals with PTSD were screened for psychiatric disorders and completed several questionnaires concerning social support, coping strategies, PTSD symptoms, and HRQoL. Coping strategies, social support, and PTSD all appeared to be predictors of HRQoL; however, PTSD seemed to constitute the major predictor among these variables. Indeed, coping strategies and social support did not explain a unique share of variability of HRQoL beyond that of PTSD symptomatology. A causal pathway integrating these variables should be tested in future studies

Coupling multi-fidelity kriging and model-order reduction for the construction of virtual charts

International audienceThis article presents the coupling between multi-fidelity kriging and a database generated on-the-fly by model reduction to accelerate the generation of a surrogate model. The two-level multi-fidelity kriging method Evofusion is used for data fusion. The remarkable point is the generation of low-fidelity and high-fidelity observations from the same solver using the Proper Generalized Decomposition, a model-order reduction method. A 17× speedup is obtained here on an elasto-viscoplastic test case

Overt social support behaviors : Associations with PTSD, concurrent depressive symptoms and gender

Women are twice as likely as men to develop a posttraumatic stress disorder (PTSD). Gender differences in social support after a traumatic event might partially explain this disparity. However, the portrait of the links among PTSD, depression, social support, and gender is still unclear. This study examined behaviors of individuals with PTSD and their significant other in relation to PTSD and concurrent depressive symptoms, and tested gender as a moderator of these associations. Observed overt supportive and countersupportive behaviors of 68 dyads composed of an individual with PTSD and a significant other in a trauma-oriented discussion were coded with a support coding system and analyzed according to gender. Gender was revealed to act as a moderator of the links between interactional behaviors of individuals with PTSD and their concurrent depressive symptoms. More specifically, women were less implicated and less likely to propose positive solutions compared with men. On the other hand, men were more implicated and less likely to criticize their significant other than were women. PTSD and concurrent depressive symptoms were related to poorer interpersonal communication in women. Hence, women and men with PTSD and concurrent depressive symptoms might benefit from gender-tailored interventions targeting symptoms and dyadic behaviors

The effect of talking about psychological trauma with a significant other on heart rate reactivity in individuals with posttraumatic stress disorder

Individuals with posttraumatic stress disorder (PTSD) commonly make efforts to avoid trauma-oriented conversations with their significant others, which may interfere with the natural recovery process. Trauma-oriented conversations can be experienced as physiologically arousing, depending on the intensity of PTSD symptoms and perceptions of social support. In the current investigation, changes in heart rate responses to a trauma-oriented social interaction with a significant other were assessed. Perceived supportive and unsupportive or negative social interactions were examined as moderators of the association between heart rate changes to this context and intensity of PTSD symptoms. A total of 46 individuals with PTSD completed diagnostic interviews and self-report measures of symptoms and perceived supportive and negative social interactions during a trauma-oriented social interaction with a significant other. Heart rate was continuously measured during this interaction. Results showed that engagement in a trauma-oriented social interaction was predictive of elevations in heart rate that positively correlated with intensity of PTSD symptoms. The moderation hypothesis was partially supported. In addition, perceived negative social interactions positively correlated with elevations in heart rate. These findings can inform social intervention efforts for individuals with PTSD

The buffering power of overt socially supportive and unsupportive behaviors from the significant other on posttraumatic stress disorder individuals’ emotional state

Social support is one of the three strongest predictors of posttraumatic stress disorder (PTSD). In the present study, we aimed to assess the buffering power of overt socially supportive and unsupportive behaviors from the significant other, in a group with PTSD and a comparison group. Design and methods: A total of 46 individuals with PTSD and 42 individuals with obsessive-compulsive disorder (OCD) or panic disorder (PD) completed diagnostic interviews and an anxiety-oriented social interaction with a significant other. Heart rate of participants was continuously measured during this interaction and overt social behaviors from the significant other were recorded on videotape and coded using a validated system. Results: Changes in heart rate in PTSD participants correlated negatively with changes in overt socially supportive behaviors from their significant other (r from −.36 to −.50, p  .05). No such statistically significant association emerged in the group with OCD or PD (r from .01 to −.27, p > .05). Conclusions: This study sustain the buffering power of overt supportive behaviors from the significant other on heart rate changes in PTSD

How do social interactions with a significant other affect PTSD symptoms? An empirical investigation with a clinical sample

Social support and coping are both related to posttraumatic stress disorder (PTSD) symptoms, but the mechanisms underlying their relationships remain unclear. This study explores these relationships by examining the perceived frequency of supportive and countersupportive interactions with a significant other in PTSD patients. Ninety-six participants with PTSD were recruited and completed questionnaires assessing social interactions, ways of coping, and PTSD symptoms. Associations of social interactions (r2 = 4.1%–7.9%, p < .05) and coping (r2 = 15.9%– 16.5%, p < .001) with symptoms were independent, and suggested a direct association between social interactions and PTSD. Countersupportive interactions were more associated to symptoms than supportive interactions. Our findings suggest the development of psychotherapies that integrate social support interventions

Aircraft Numerical "Twin": A Time Series Regression Competition

International audienceThis paper presents the design and analysis of a data science competition on a problem of time series regression from aeronautics data. For the purpose of performing predictive maintenance, aviation companies seek to create aircraft "numerical twins", which are programs capable of accurately predicting strains at strategic positions in various body parts of the aircraft. Given a number of input parameters (sensor data) recorded in sequence during the flight, the competition participants had to predict output values (gauges), also recorded sequentially during test flights, but not recorded during regular flights. The competition data included hundreds of complete flights. It was a code submission competition with complete blind testing of algorithms. The results indicate that such a problem can be effectively solved with gradient boosted trees, after preprocessing and feature engineering. Deep learning methods did not prove as efficient

Optimisation de structures viscoplastiques par couplage entre métamodèle multi-fidélité et modèles réduits

International audienceLes travaux présentés portent sur deux types de problèmes : la génération rapide d'un abaque virtuel d'une quantité d'intérêt d'une part, et l'optimisation d'un critère d'autre part. Ces deux problèmes utilisent des métamodèles qui exploitent des données multi-fidélités associées à la génération à la volée d'une base réduite des champs mécaniques. Le point clé est la génération d'observations basse et haute fidélité à partir du même solveur non linéaire exploitant un modèle réduit PGD. Cette méthode permet une accélération des calculs pouvant aller jusqu'à un facteur 55 sur le cas-test proposé

An overview of aircraft vibration environment prediction using machine learning

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