Psychometric Performance of the Miller Forensic Assessment of Symptoms Test (M-FAST) in Veteran PTSD Assessment.
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ABSTRACT:
SUBMITTER: Wolf EJ
PROVIDER: S-EPMC7236380 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundDespite extensive research, symptom structure of posttraumatic stress disorder (PTSD) is highly debated. The network approach to psychopathology offers a novel method for understanding and conceptualizing PTSD. However, extant studies have mainly used small samples and self-report measures among sub-clinical populations, while also overlooking co-morbid depressive symptoms.MethodsPTSD symptom network topology was estimated in a sample of 1489 treatment-seeking veteran patients based on a clinician-rated PTSD measure. Next, clinician-rated depressive symptoms were incorporated into the network to assess their influence on PTSD network structure. The PTSD-symptom network was then contrasted with the network of 306 trauma-exposed (TE) treatment-seeking patients not meeting full criteria for PTSD to assess corresponding network differences. Finally, a directed acyclic graph (DAG) was computed to estimate potential directionality among symptoms, including depressive symptoms and daily functioning.ResultsThe PTSD symptom network evidenced robust reliability. Flashbacks and getting emotionally upset by trauma reminders emerged as the most central nodes in the PTSD network, regardless of the inclusion of depressive symptoms. Distinct clustering emerged for PTSD and depressive symptoms within the comorbidity network. DAG analysis suggested a key triggering role for re-experiencing symptoms. Network topology in the PTSD sample was significantly distinct from that of the TE sample.ConclusionsFlashbacks and psychological reactions to trauma reminders, along with their strong connections to other re-experiencing symptoms, have a pivotal role in the clinical presentation of combat-related PTSD among veterans. Depressive and posttraumatic symptoms constitute two separate diagnostic entities, but with meaningful between-disorder connections, suggesting two mutually-influential systems.
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Project description:Warzone deployment increases risk for posttraumatic stress disorder symptoms (PTSS), including among service members who have children. Parental PTSS are associated with child depression, anxiety, hyperactivity, and conduct problems, yet few studies of child behavioral health outcomes in military populations have accounted for PTSS in both warzone veterans and their partners. Fewer still incorporate non-clinically-recruited samples of nationally dispersed warzone veterans and their families. The current research examines whether children whose parent(s) have higher levels of PTSS exhibit more behavioral health symptoms. One hundred and thirty-three Iraq and Afghanistan War veterans and their cohabitating partners completed clinical interviews and self-report questionnaires. Higher intimate partner PTSS, more extensive child exposure to stressful life events, and being an adolescent were significantly associated with child depression after adjusting for warzone veteran PTSS, demographics, and recent warzone veteran absence from the household. Greater child exposure to stressful life events was also associated with child conduct problems. Treatment of PTSD symptoms experienced by warzone veterans' intimate partners, and preventative interventions aimed at helping the children of warzone veterans cope with stress, may ultimately yield positive benefits for the behavioral health of children in military families.
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Project description:Participants with schizophrenia (SCZ) and bipolar disorder (BD) have challenges in self-evaluation of their cognitive and functional abilities, referred to as introspective accuracy (IA). Although psychotic symptoms are commonly found to be uncorrelated with cognitive performance, many models of the development of delusions focus on failures in self-assessment and responses biases during momentary monitoring. We performed a single 4-test cognitive assessment on 240 participants (schizophrenia n = 126; bipolar disorder n = 114) and asked them to make a judgment about their performance immediately after completion of each task. We related performance and these judgments to results of Ecological Momentary Assessments (EMA) of the momentary occurrence of psychotic symptoms (Voices, paranoid ideas, other delusions) collected over up to 90 surveys over a 30 days prior to the single cognitive assessment. We examined test performance and the accuracy of self-assessment at that assessment, looking at diagnostic differences in performance and mis-estimation of performance. Participants with bipolar disorder had better cognitive performance, but there were no differences in mis-estimation. Analyses of the correlation between cognitive performance and self-assessment were all significant and better cognitive performance predicted reduced errors in self-assessment. Examination of the 30-day course of psychotic symptoms and IA could only be performed in participants with schizophrenia, revealing correlations between more common occurrences of all three psychotic symptoms and increased absolute values for IA errors. These data are consistent with theories of cognitive response biases and the formation of delusions.
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Project description:Eighty Gram-negative bacilli (54 Enterobacteriaceae and 26 nonfermenting Gram-negative bacilli) obtained from multiple institutions in the United States were distributed in a blinded manner to seven testing laboratories to compare their performance of a test for detection of carbapenemase production, the Carba NP test. The Carba NP test was performed by all laboratories, following the Clinical and Laboratory Standards Institute (CLSI) procedure. Site-versus-site comparisons demonstrated a high level of consistency for the Carba NP assay, with just 3/21 site comparisons yielding a difference in sensitivity (P < 0.05). Previously described limitations with blaOXA-48-like carbapenemases and blaOXA carbapenemases associated with Acinetobacter baumannii were noted. Based on these data, we demonstrate that the Carba NP test, when implemented with the standardized CLSI methodology, provides reproducible results across multiple sites for detection of carbapenemases.
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Project description:BackgroundNo short patient-reported outcome (PRO) instruments assess overall health status across different obstructive lung diseases. Thus, the wording of the introduction to the Chronic Obstructive Pulmonary Disease (COPD) Assessment Test (CAT) was modified to permit use in asthma and/or COPD. This tool is called the Chronic Airways Assessment Test (CAAT).MethodsThe psychometric properties of the CAAT were evaluated using baseline data from the NOVELTY study (NCT02760329) in patients with physician-assigned asthma, asthma + COPD or COPD. Analyses included exploratory/confirmatory factor analyses, differential item functioning and analysis of construct validity. Responses to the CAAT and CAT were compared in patients with asthma + COPD and those with COPD.ResultsCAAT items were internally consistent (Cronbach's alpha: > 0.7) within each diagnostic group (n = 510). Models for structural and measurement invariance were strong. Tests of differential item functioning showed small differences between asthma and COPD in individual items, but these were not consistent in direction and had minimal overall impact on the total score. The CAAT and CAT were highly consistent when assessed in all NOVELTY patients who completed both (N = 277, Pearson's correlation coefficient: 0.90). Like the CAT itself, CAAT scores correlated moderately (0.4-0.7) to strongly (> 0.7) with other PRO measures and weakly (< 0.4) with spirometry measures.ConclusionsCAAT scores appear to reflect the same health impairment across asthma and COPD, making the CAAT an appropriate PRO instrument for patients with asthma and/or COPD. Its brevity makes it suitable for use in clinical studies and routine clinical practice.Trial registrationNCT02760329.
| S-EPMC10082977 | biostudies-literature
Project description:BackgroundPosttraumatic stress disorder (PTSD) among US military veterans can adversely impact their concerned significant others (CSOs; eg, family members and romantic partners). Mobile apps can be tailored to support CSO mental health through psychoeducation, coping skills, and stress monitoring.ObjectiveThis study assessed the feasibility, acceptability, and potential efficacy of PTSD Family Coach 1.0, a free, publicly available app that includes psychoeducation, stress management tools, self-assessments, and features for connecting to alternative supports, compared with a psychoeducation-only version of the app for cohabitating CSOs of veterans with PTSD.MethodsA total of 200 participants with an average age of 39 (SD 8.44) years, primarily female (193/200, 97%), and White (160/200, 80%) were randomized to self-guided use of either PTSD Family Coach 1.0 (n=104) or a psychoeducation-only app (n=96) for 4 weeks. Caregiver burden, stress, depression, anxiety, beliefs about treatment, CSO self-efficacy, and relationship functioning assessed using measures of dyadic adjustment, social constraints, and communication danger signs were administered via a web survey at baseline and after treatment. User satisfaction and app helpfulness were assessed after treatment. Data were analyzed using linear mixed methods.ResultsOverall, 50.5% (101/200) of randomized participants used their allocated app. Participants found PTSD Family Coach 1.0 somewhat satisfying (mean 4.88, SD 1.11) and moderately helpful (mean 2.99, SD 0.97) to use. Linear mixed effects models revealed no significant differences in outcomes by condition for caregiver burden (P=.45; Cohen d=0.1, 95% CI -0.2 to 0.4), stress (P=.64; Cohen d=0.1, 95% CI -0.4 to 0.6), depression (P=.93; Cohen d= 0.0, 95% CI -0.3 to 0.3), anxiety (P=.55; Cohen d=-0.1, 95% CI -0.4 to 0.2), beliefs about treatment (P=.71; Cohen d=0.1, 95% CI -0.2 to 0.3), partner self-efficacy (P=.59; Cohen d=-0.1, 95% CI -0.4 to 0.2), dyadic adjustment (P=.08; Cohen d=-0.2, 95% CI -0.5 to 0.0), social constraints (P=.05; Cohen d=0.3, 95% CI 0.0-0.6), or communication danger signs (P=.90; Cohen d=-0.0, 95% CI -0.3 to 0.3). Post hoc analyses collapsing across conditions revealed a significant between-group effect on stress for app users versus nonusers (β=-3.62; t281=-2.27; P=.02).ConclusionsApproximately half of the randomized participants never used their allocated app, and participants in the PTSD Family Coach 1.0 condition only opened the app approximately 4 times over 4 weeks, suggesting limitations to this app version's feasibility. PTSD Family Coach 1.0 users reported moderately favorable impressions of the app, suggesting preliminary acceptability. Regarding efficacy, no significant difference was found between PTSD Family Coach 1.0 users and psychoeducation app users across any outcome of interest. Post hoc analyses suggested that app use regardless of treatment condition was associated with reduced stress. Further research that improves app feasibility and establishes efficacy in targeting the domains most relevant to CSOs is warranted.Trial registrationClinicalTrials.gov NCT02486705; https://clinicaltrials.gov/ct2/show/NCT02486705.
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Project description:Face recognition is a valuable forensic tool for criminal investigators since it certainly helps in identifying individuals in scenarios of criminal activity like fugitives or child sexual abuse. It is, however, a very challenging task as it must be able to handle low-quality images of real world settings and fulfill real time requirements. Deep learning approaches for face detection have proven to be very successful but they require large computation power and processing time. In this work, we evaluate the speed-accuracy tradeoff of three popular deep-learning-based face detectors on the WIDER Face and UFDD data sets in several CPUs and GPUs. We also develop a regression model capable to estimate the performance, both in terms of processing time and accuracy. We expect this to become a very useful tool for the end user in forensic laboratories in order to estimate the performance for different face detection options. Experimental results showed that the best speed-accuracy tradeoff is achieved with images resized to 50% of the original size in GPUs and images resized to 25% of the original size in CPUs. Moreover, performance can be estimated using multiple linear regression models with a Mean Absolute Error (MAE) of 0.113, which is very promising for the forensic field.
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Project description:Progress in the development of new pharmacological and psychosocial treatments for the negative symptoms of schizophrenia is impeded by limitations of available assessment instruments. The multi-site Collaboration to Advance Negative Symptom Assessment in Schizophrenia (CANSAS) was established to develop and validate a new clinical rating scale using a transparent, iterative, and data-driven process. The Clinical Assessment Interview for Negative Symptoms (CAINS) was designed to address limitations of existing measures and assess consensus-based sub-domains, including asociality, avolition, anhedonia, affective blunting, and alogia. The structure and psychometric properties of the CAINS were evaluated in a sample of 281 schizophrenia and schizoaffective outpatients at four sites. Converging structural analyses indicated that the scale was comprised of two moderately correlated factors - one reflecting experiential impairments (diminished motivation and enjoyment of social, vocational, and recreational activities) and one reflecting expressive impairments (diminished non-verbal and verbal communication). Item-level analyses revealed generally good distributional properties, inter-rater agreement, discriminating anchor points, and preliminary convergent and discriminant validity. Results indicate that the CAINS is a promising new measure for quantifying negative symptoms in clinical neuroscience and treatment studies. Results guided item modification or deletion, and the reliability and validity of the revised, shorter version of the CAINS is in the final phase of development within the CANSAS project.
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Project description:Interpreting the performance of deep learning models beyond test set accuracy is challenging. Characteristics of individual data points are often not considered during evaluation, and each data point is treated equally. We examine the impact of a test set question's difficulty to determine if there is a relationship between difficulty and performance. We model difficulty using well-studied psychometric methods on human response patterns. Experiments on Natural Language Inference (NLI) and Sentiment Analysis (SA) show that the likelihood of answering a question correctly is impacted by the question's difficulty. As DNNs are trained with more data, easy examples are learned more quickly than hard examples.
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Project description:As of yet, no collective agreement has been reached regarding the precise factor structure of posttraumatic stress disorder (PTSD). Several alternative factor-models have been proposed in the last decades.The current study examined the fit of a hierarchical adaptation of the Simms et al. (2002) dysphoria model and compared it to the fit of the PTSD model as depicted in the Diagnostic and Statistical Manual for Mental Disorders, Fourth Edition (DSM-IV), a correlated four-factor emotional numbing, and a correlated four-factor dysphoria model.Data were collected using the Clinician-Administered PTSD Scale in a mixed-trauma sample of treatment-seeking PTSD patients (N=276).All examined models provided superior fit to the three-factor model of DSM-IV. The hierarchical four-factor solution provided a better fit than competing models.The present study provides empirical support for a conceptualization of PTSD that includes a higher-order PTSD factor that encompasses re-experiencing, arousal, and effortful avoidance sub-factors and a dysphoria factor.
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