Estimate of halo ellipticity as a function of radius with flexions

The cold dark matter theory predicts triaxial dark matter haloes. The radial distribution of halo ellipticity depends on baryonic processes and the nature of dark matter particles (collisionless or collisional). Here we show that we can use lensing flexion ratios to measure the halo ellipticity as a function of radius. We introduce a weight function and study the relationship between the first and second order statistics of flexion ratios, both of which can be used to reduce the bias in the estimate of ellipticity. we perform numerical tests for our method, and demonstrate that it can reduce the bias and determine the halo ellipticity as a function of radius. We also point out that the minimum mean flexion ratio can be used to trace the centres of galaxy clusters.Comment: 9 pages,9 figures, MNRAS accepte

Physical trauma patients with symptoms of an acute and posttraumatic stress disorder:Protocol for an observational prospective cohort study

Background: Injury, medical treatment, and rehabilitation can have major impacts on patients’ wellbeing. About 25-33% of the patients experience an acute stress disorder (ASD) or a posttraumatic stress disorder (PTSD) after injury. ASD is a relatively new diagnosis. Therefore, knowledge about patients’ experiences, the course of ASD and PTSD, and who is at risk for developing ASD or PTSD is lacking. Objective: The aims of this multi-method study are to explore patients’ experiences with injury (and their care) using a focus group study. Then, in the observational study, different courses of ASD, PTSD, and quality of life will be examined. In addition, this study will examine if these courses could be characterized by socio-demographic, clinical, and psychological variables. Consequently, a risk profile will be developed to determine which patients are at risk for developing ASD or PTSD during the 12 months after injury. Methods: Trauma patients treated in the shock room (in 2015) of the Elisabeth-TweeSteden Hospital will share their experiences with injury in the focus group study. Open, axial, and selective coding will be used to analyze the data. Concerning the observational study, patients treated in the shock room (during 2016 and 2017, Elisabeth-TweeSteden Hospital and Erasmus Medical Centre) will be asked to participate. The inclusion period is 12 months. Participants will complete the Impact of Event Scale-Revised, MINI-plus, the Hospital Anxiety and Depression Scale, and the World Health Organization Quality of Life-BREF after inclusion and at 3, 6, 9, and 12 months after injury. The NEO-Five Factor Inventory and the State-Trait Anxiety Inventory-Trait are completed after inclusion only. Repeated measures of latent class analysis and linear mixed models will be used to examine the research aims. Results: This project was funded in August 2015 by ZonMw. The results of the focus group study are expected in the first trimester of 2018. With regard to the observational study, recruitment is currently underway. Data collection will be completed in November 2018. The first results will be expected in the first trimester of 2019. Conclusions: This is the first multi-method study in trauma patients that examines patients’ experiences (qualitative design) as well as psychological disorders (observational prospective). This study will contribute to necessary information on psychological consequences after injury. Moreover, it provides knowledge about which patients to include in future psychological intervention research. Finally, awareness in clinicians about the psychological consequences can be created, so they are able to act more effectively to provide patient-oriented care

Psychological risk factors that characterize the trajectories of quality of life after a physical trauma:A longitudinal study using latent class analysis

Background The course and corresponding characteristics of quality of life (QOL) domains in trauma population are unclear. Our aim was to identify longitudinal QOL trajectories and determine and predict the sociodemographic, clinical, and psychological characteristics of trajectory membership in physical trauma patients using a biopsychosocial approach. Methods Patients completed a questionnaire set after inclusion, and at 3, 6, 9, and 12 months follow-up. Trajectories were identified using repeated-measures latent class analysis. The trajectory characteristics were ranked using Cohen’s d effect size or phi coefficient. Results Altogether, 267 patients were included. The mean age was 54.1 (SD = 16.1), 62% were male, and the median injury severity score was 5.0 [2.0—9.0]. Four latent trajectories were found for psychological health and environment, five for physical health and social relationships, and seven trajectories were found for overall QOL and general health. The trajectories seemed to remain stable over time. For each QOL domain, the identified trajectories differed significantly in terms of anxiety, depressive symptoms, acute stress disorder, post-traumatic stress disorder, Neuroticism, trait anxiety, Extraversion, and Conscientiousness. Discussion Psychological factors characterized the trajectories during 12 months after trauma. Health care providers can use these findings to identify patients at risk for impaired QOL and offer patient-centered care to improve QOL

Patients' experiences and wellbeing after injury:A focus group study

Background Injury can have physical, psychological and social consequences. It is unclear which factors have an impact on patients’ wellbeing after injury. This study aimed to explore, using focus groups, patients’ experiences and wellbeing after injury and which factors, impede or facilitate patients’ wellbeing. Methods Trauma patients, treated in the shock room of the Elisabeth-TweeSteden Hospital, the Netherlands, participated in focus groups. Purposive sampling was used. Exclusion criteria were younger than 18 years old, severe traumatic brain injury, dementia, and insufficient knowledge of the Dutch language. The interviews were recorded, transcribed verbatim, and analyzed using coding technique open, axial, and selective coding, based on phenomenological approach. Results Six focus groups (3 to 7 participants) were held before data saturation was reached. In total, 134 patients were invited, 28 (21%) agreed to participate (Median age: 59.5; min. 18 –max. 84). Main reasons to decline were fear that the discussion would be too confronting or patients experienced no problems regarding the trauma or treatment. Participants experienced difficulties on physical (no recovery to pre-trauma level), psychological (fear of dying or for permanent limitations, symptoms of posttraumatic stress disorder, cognitive dysfunction), social (impact on relatives and social support) wellbeing. These are impeding factors for recovery. However, good communication, especially clarity about the injury and expectations concerning recovery and future perspectives could help patients in surrendering to care. Patients felt less helpless when they knew what to expect. Conclusions This is the first study that explored patients’ experiences and wellbeing after injury. Patients reported that their injury had an impact on their physical, psychological, and social wellbeing up to 12 months after injury. Professionals with the knowledge of consequences after injury could improve their anticipation on patients’ need

Psychological risk factors that characterize acute stress disorder and trajectories of posttraumatic stress disorder after injury:A study using latent class analysis

BACKGROUND: The course and different characteristics of acute and posttraumatic stress disorder (ASD, PTSD) in trauma populations are unclear. OBJECTIVE: The aims were to identify longitudinal trajectories of PTSD, to establish a risk profile for ASD and PTSD based on patients’ sociodemographic, clinical, and psychological characteristics, and to study the effect of ASD and dissociation on PTSD during 12 months after trauma. METHOD: Patients completed questionnaires after inclusion and at 3, 6, 9, and 12 months afterwards. Trajectories were identified using repeated measures latent class analysis (RMLCA). The risk profile was based on a ranking of importance of each characteristic using Cohen’s d effect sizes and odds ratios. The impact of ASD and dissociation on PTSD was examined using logistic regression analyses. RESULTS: Altogether, 267 patients were included. The mean age was 54.0 (SD = 16.1) and 62% were men. The prevalence rate of ASD was approximately 21.7% at baseline, and 36.1% of trauma patients exhibited PTSD at 12 months after injury. Five trajectories were identified: (1) no PTSD symptoms, (2) mild, (3) moderate, (4) subclinical, and (5) severe PTSD symptoms. These trajectories seemed to remain stable over time. Compared with patients in other trajectories, patients with ASD and (subclinical) PTSD were younger and scored higher on anxiety, depressive symptoms, neuroticism, and trait anxiety. Regarding dissociation symptoms, inability to recall memories about the event was significantly more present than an altered sense of reality, (105 (40.7%) versus 56 (21.7%), p = .031), although that symptom had the strongest likelihood for PTSD. Patients with dissociation were significantly at risk for PTSD than patients without dissociation (OR = 4.82; 95%CI: 1.91–12.25). CONCLUSIONS: Psychological factors characterized ASD and trajectories of PTSD during 12 months post-trauma. Healthcare providers who are aware of these findings could early identify patients at risk for ASD and PTSD and refer them for patient-centred interventions