Utilization of the DSM-5 Self-Rated Level 1 Cross-Cutting Symptom Measure-Adult to Screen Healthy Volunteers for Research Studies.
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ABSTRACT:
SUBMITTER: Mahoney MR
PROVIDER: S-EPMC7382979 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:The DSM-5 Self-Rated Level 1 Cross-Cutting Symptom Measure was developed to aid in clinical decision-making for clients seeking psychiatric services and to facilitate empirical investigation of the dimensional nature of mental health issues. Preliminary evidence supports its utility with clinical samples. However, the brief, yet comprehensive structure of the DSM-5 Level 1 measure may benefit a high-risk population that is less likely to seek treatment. College students have high rates of hazardous substance use and co-occurring mental health symptoms, yet rarely seek treatment. Therefore, the current study evaluated the psychometric properties (i.e., construct and criterion-related validity) of the DSM-5 Level 1 measure with a large, diverse sample of non-treatment-seeking college/university students. Data from 7,217 college students recruited from 10 universities in 10 different states across the United States evidenced psychometric validation of the DSM-5 Level 1 measure. Specifically, we found acceptable internal consistency across multi-item DSM-5 domains and moderate to strong correlations among domains (internal validity). Further, several DSM-5 domains were positively associated with longer, validated measures of the same mental health construct and had similar strengths of associations with substance use outcomes compared to longer measures of the same construct (convergent validity). Finally, all DSM-5 domains were negatively associated with self-esteem and positively associated with other theoretically relevant constructs, such as posttraumatic stress (criterion-related validity). Taken together, the DSM-5 Level 1 measure appears to be a viable tool for evaluating psychopathology in college students. Several opportunities for clinical application and empirical investigation of the DSM-5 Level 1 measure are discussed. (PsycINFO Database Record (c) 2018 APA, all rights reserved).
| S-EPMC6172148 | biostudies-literature
Project description:ObjectivesThe DSM-5 Level 1 Cross-Cutting Symptom Measure (DSM-XC) is a transdiagnostic mental health symptom measure that has shown promise in informing clinical diagnostic evaluations and as a screening tool for research. However, few studies have assessed the latent dimensionality of the DSM-XC. We examined the factor structure of the DSM-XC in a large convenience sample of participants with varying degrees of psychological health.MethodsParticipants (n=3533) enrolled in a protocol conducted at the National Institute of Mental Health ( NCT04339790 ). We used a factor analytic framework to evaluate an existing two-factor solution (Lace & Merz, 2020) and two additional candidate solutions.ResultsThe Lace and Merz solution had acceptable fit. Exploratory factor analysis yielded two candidate solutions: a six-factor (characterized as mood, worry, activation, somatic, thoughts, and substance use) and a bifactor (general factor of non-specific psychopathology, residual factors characterized as internalizing and thought disorder), which both had good fit and full measurement invariance across age, sex, and enrollment date.ConclusionsOur findings confirm that the DSM-XC may be conceptualized as a multidimensional instrument and provide a scoring solution for researchers who wish to measure distinct constructs. Future research on the psychometric profile of the DSM-XC is needed, focused on the validity of these candidate solutions and their performance across research populations and settings.
| S-EPMC8095225 | biostudies-literature
Project description:AimsPreclinical results suggest therapeutic potential of mild hyperbilirubinemia in T2DM and cardiovascular disease. Translational data are limited, because an appropriate bilirubin formulation for parenteral human use is lacking. Considering its use in both clinical practice and medical research in the past, we explored the feasibility to reintroduce parenteral bilirubin for translational experiments.MethodsWe developed a preparation method in accordance with good manufacturing practice and evaluated the parenteral applicability in healthy volunteers (n = 8). Explorative pharmacokinetic and safety data were compared to the results from a literature study on the former parenteral use of bilirubin. Bilirubin was administered intra-arterially to raise the local plasma concentration in the forearm vascular bed (n = 4) and intravenously to raise the systemic plasma concentration (n = 4). Finally, pharmacokinetic characteristics were studied following a single bolus infusion (n = 3).ResultsDuring parenteral application, no side effects occurred. Adverse events mentioned during the two-week observation period were in general mild and self-limiting. Three more significant adverse events (appendicitis, asymptomatic cardiac arrhythmia and atopic eczema) were judged unrelated by independent physicians. A dose-concentration relationship appeared sufficiently predictable for both intra-arterial and intravenous administration. In line with existing knowledge, bilirubin pharmacokinetics could be described best according to a two-compartment model with a volume of distribution of 9.9 (±2.0) l and a total plasma clearance of 36 (±16) ml per minute.ConclusionsSupported by previous reports, our data suggest that it is both feasible and safe to perform translational experiments with parenteral albumin bound bilirubin.
| S-EPMC5777445 | biostudies-literature
Project description:Healthy volunteers are crucial for biomedical research. Inadvertent inclusion of subjects with nonalcoholic fatty liver disease (NAFLD) as controls can compromise study validity and subject safety. Given the rising prevalence of NAFLD in the general population, we sought to identify its prevalence and potential impact in volunteers for clinical trials. We conducted a cross-sectional study of subjects who were classified as healthy volunteers between 2011 and 2015 and had no known liver disease. Subjects were classified as presumed NAFLD (pNF; alanine aminotransferase [ALT] level???20 for women or???31 for men and body mass index [BMI]?>?25?kg/m2 ), healthy non-NAFLD controls (normal ALT and BMI), or indeterminate. A total of 3160 subjects participated as healthy volunteers in 149 clinical trials (1-29 trials per subject); 1732 of these subjects (55%) had a BMI?>?25?kg/m2 and 1382 (44%) had abnormal ALT. pNF was present in 881 subjects (27.9%), and these subjects were older than healthy control subjects and had higher triglycerides, low-density lipoprotein cholesterol, and HbA1c and lower high-density lipoprotein cholesterol (P?<?0.001 for all). The 149 trials included 101 non-interventional, 33 interventional, and 15 vaccine trials. The impact on study validity of recruiting NAFLD subjects as controls was estimated as likely, probable, and unlikely in 10, 41, and 98 trials, respectively. The proportion of pNF subjects (28%-29%) did not differ by impact. Only 14% of trials used both BMI and ALT for screening. ALT cutoffs for screening were based on local reference values. Grade 3-4 ALT elevations during the study period were rare but more common in pNF subjects than in healthy control subjects (4 versus 1). CONCLUSION:NAFLD is common and often overlooked in volunteers for clinical trials, despite its potential impact on subject safety and validity of study findings. Increased awareness of NAFLD prevalence and stricter ALT cutoffs may ameliorate this problem. (Hepatology 2017;66:825-833).
| S-EPMC5570632 | biostudies-literature
Project description:Network theory, which conceptualizes psychiatric disorders as networks of interacting symptoms, may provide a useful framework for understanding psychopathology. However, questions have arisen regarding the stability and generalizability of network analytic methods, with some researchers arguing that symptom networks have limited replicability. The aim of this study was to evaluate assessment modality as one possible source of instability in the estimation of posttraumatic stress disorder (PTSD) symptom networks. We estimated two cross-sectional DSM-5 PTSD symptom networks in 378 U.S. veterans: one using data from a clinician-rated assessment instrument (Clinician-Administered PTSD Scale for DSM-5; CAPS-5) and one using data from a self-rated questionnaire (the PTSD Checklist for DSM-5; PCL-5). We calculated centrality indices, conducted community structure analyses, and compared the strength and structure of the networks. The CAPS-5 and PCL-5 symptom networks were highly similar, challenging the notion that network methods produce unreliable results due to estimations consisting primarily of measurement error. Furthermore, each network contained distinct symptom communities that only partially overlapped with the DSM-5 PTSD symptom clusters. These findings may provide guidance for future revisions of the DSM, suggest hypotheses about how PTSD symptoms interact, and inform recent debate about replicability of psychopathology symptom networks. (PsycINFO Database Record
| S-EPMC7059999 | biostudies-literature
Project description:BackgroundThe ability to assess the hemostatic effect of the direct oral anticoagulant (DOACs) may be valuable in clinical situations such as bleeding or thrombosis, before urgent surgery, or reversal of anticoagulation. We sought to assess the anticoagulant effect of DOACs with the new-generation fully automated thrombelastograph TEG 6s using resonance-frequency viscoelasticity measurements and disposable multichannel microfluidic cartridges.MethodsA single dose of oral dabigatran 150 mg, rivaroxaban 20 mg, or apixaban 5 mg was given to 9 healthy males. Phlebotomy was performed at 0, 1, and 3 hours after administration of DOAC. TEG parameters were measured using TEG _6s. Concentrations of DOACs were measured using chromogenic assays. The TEG parameters were correlated to the DOAC concentrations.ResultsThe reaction time (R) demonstrated the strongest response to DOAC intake. There were no correlations between other TEG parameters and DOAC concentrations. Using the direct thrombin inhibitor (DTI) channel, R was significantly correlated with dabigatran levels (r = 0.94, P < 0.0001). Using the anti-factor Xa (AFXa) channel, R was significantly correlated with rivaroxaban and apixaban levels (r = 0.93 and r = 0.83, respectively; P < 0.0001 for both). R >2.5 minutes for dabigatran (DTI channel), >2.5 minutes for apixaban, and >1.8 minutes for rivaroxaban (AFXa channel) were associated with 100% sensitivity and ? 90% specificity to detect DOAC levels of ? 50 ng/mL.ConclusionWe have demonstrated that TEG _6s R has significant correlation with DOAC blood concentrations and has potential for monitoring the DOAC's effect on hemostasis with reasonable sensitivity in the small sample analyzed. This novel technology is easy to use on a small volume of whole blood without requiring a specialized laboratory. Further study is warranted to correlate R with clinical outcomes.
| S-EPMC6611480 | biostudies-literature
Project description:BackgroundDiesel engine exhaust causes adverse health effects. Meanwhile, the impact of renewable diesel exhaust, such as hydrotreated vegetable oil (HVO), on human health is less known. Nineteen healthy volunteers were exposed to HVO exhaust for 3 h in a chamber with a double-blind, randomized setup. Exposure scenarios comprised of HVO exhaust from two modern non-road vehicles with 1) no aftertreatment system ('HVOPM+NOx' PM1: 93 µg m-3, EC: 54 µg m-3, NO: 3.4 ppm, NO2: 0.6 ppm), 2) an aftertreatment system containing a diesel oxidation catalyst and a diesel particulate filter ('HVONOx' PM1: ~ 1 µg m-3, NO: 2.0 ppm, NO2: 0.7 ppm) and 3) filtered air (FA) as control. The exposure concentrations were in line with current EU occupational exposure limits (OELs) of NO, NO2, formaldehyde, polycyclic aromatic hydrocarbons (PAHs), and the future OEL (2023) of elemental carbon (EC). The effect on nasal patency, pulmonary function, and self-rated symptoms were assessed. Calculated predicted lung deposition of HVO exhaust particles was compared to data from an earlier diesel exhaust study.ResultsThe average total respiratory tract deposition of PM1 during HVOPM+NOx was 27 µg h-1. The estimated deposition fraction of HVO PM1 was 40-50% higher compared to diesel exhaust PM1 from an older vehicle (earlier study), due to smaller particle sizes of the HVOPM+NOx exhaust. Compared to FA, exposure to HVOPM+NOx and HVONOx caused higher incidence of self-reported symptoms (78%, 63%, respectively, vs. 28% for FA, p < 0.03). Especially, exposure to HVOPM+NOx showed 40-50% higher eye and throat irritation symptoms. Compared to FA, a decrement in nasal patency was found for the HVONOx exposures (- 18.1, 95% CI: - 27.3 to - 8.8 L min-1, p < 0.001), and for the HVOPM+NOx (- 7.4 (- 15.6 to 0.8) L min-1, p = 0.08). Overall, no clinically significant change was indicated in the pulmonary function tests (spirometry, peak expiratory flow, forced oscillation technique).ConclusionShort-term exposure to HVO exhaust concentrations corresponding to EU OELs for one workday did not cause adverse pulmonary function changes in healthy subjects. However, an increase in self-rated mild irritation symptoms, and mild decrease in nasal patency after both HVO exposures, may indicate irritative effects from exposure to HVO exhaust from modern non-road vehicles, with and without aftertreatment systems.
| S-EPMC8785558 | biostudies-literature
Project description:The Earable device is a behind-the-ear wearable originally developed to measure cognitive function. Since Earable measures electroencephalography (EEG), electromyography (EMG), and electrooculography (EOG), it may also have the potential to objectively quantify facial muscle and eye movement activities relevant in the assessment of neuromuscular disorders. As an initial step to developing a digital assessment in neuromuscular disorders, a pilot study was conducted to determine whether the Earable device could be utilized to objectively measure facial muscle and eye movements intended to be representative of Performance Outcome Assessments, (PerfOs) with tasks designed to model clinical PerfOs, referred to as mock-PerfO activities. The specific aims of this study were: To determine whether the Earable raw EMG, EOG, and EEG signals could be processed to extract features describing these waveforms; To determine Earable feature data quality, test re-test reliability, and statistical properties; To determine whether features derived from Earable could be used to determine the difference between various facial muscle and eye movement activities; and, To determine what features and feature types are important for mock-PerfO activity level classification. A total of N = 10 healthy volunteers participated in the study. Each study participant performed 16 mock-PerfOs activities, including talking, chewing, swallowing, eye closure, gazing in different directions, puffing cheeks, chewing an apple, and making various facial expressions. Each activity was repeated four times in the morning and four times at night. A total of 161 summary features were extracted from the EEG, EMG, and EOG bio-sensor data. Feature vectors were used as input to machine learning models to classify the mock-PerfO activities, and model performance was evaluated on a held-out test set. Additionally, a convolutional neural network (CNN) was used to classify low-level representations of the raw bio-sensor data for each task, and model performance was correspondingly evaluated and compared directly to feature classification performance. The model's prediction accuracy on the Earable device's classification ability was quantitatively assessed. Study results indicate that Earable can potentially quantify different aspects of facial and eye movements and may be used to differentiate mock-PerfO activities. Specially, Earable was found to differentiate talking, chewing, and swallowing tasks from other tasks with observed F1 scores >0.9. While EMG features contribute to classification accuracy for all tasks, EOG features are important for classifying gaze tasks. Finally, we found that analysis with summary features outperformed a CNN for activity classification. We believe Earable may be used to measure cranial muscle activity relevant for neuromuscular disorder assessment. Classification performance of mock-PerfO activities with summary features enables a strategy for detecting disease-specific signals relative to controls, as well as the monitoring of intra-subject treatment responses. Further testing is needed to evaluate the Earable device in clinical populations and clinical development settings.
| S-EPMC9931353 | biostudies-literature
Project description:Diffusion tensor imaging (DTI) studies have provided evidence of widespread white matter (WM) abnormalities in schizophrenia. Although these abnormalities appear clinically significant, the relationship to specific clinical symptoms is limited and heterogeneous. This study examined the association between WM microstructure and the severity of the five main DSM-5 schizophrenia symptom dimensions. DTI was measured in forty patients with schizophrenia spectrum disorders. Using Tract-Based Spatial Statistics controlling for age, gender and antipsychotic dosage, our analyses revealed significant negative relationships between WM microstructure and two DSM-5 symptom dimensions: Whereas abnormal psychomotor behavior was particularly related to WM of motor tracts, negative symptoms were associated with WM microstructure of the prefrontal and right temporal lobes. However, we found no associations between WM microstructure and delusions, hallucinations or disorganized speech. These data highlight the relevance of characteristic WM disconnectivity patterns as markers for negative symptoms and abnormal psychomotor behavior in schizophrenia and provide evidence for relevant associations between brain structure and aberrant behavior.
| S-EPMC4925890 | biostudies-other
Project description:Assessment of mental illness typically relies on a disorder classification system that is considered to be at odds with the vast disorder comorbidity and symptom heterogeneity that exists within and across patients. Patients with the same disorder diagnosis exhibit diverse symptom profiles and comorbidities creating numerous clinical and research challenges. Here we provide a quantitative analysis of the symptom heterogeneity and disorder comorbidity across a sample of 107,349 adult individuals (aged 18-85 years) from 8 English-speaking countries. Data were acquired using the Mental Health Quotient, an anonymous, online, self-report tool that comprehensively evaluates symptom profiles across 10 common mental health disorders. Dissimilarity of symptom profiles within and between disorders was then computed. We found a continuum of symptom prevalence rather than a clear separation of normal and disordered. While 58.7% of those with 5 or more clinically significant symptoms did not map to the diagnostic criteria of any of the 10 DSM-5 disorders studied, those with symptom profiles that mapped to at least one disorder had, on average, 20 clinically significant symptoms. Within this group, the heterogeneity of symptom profiles was almost as high within a disorder label as between 2 disorder labels and not separable from randomly selected groups of individuals with at least one of any of the 10 disorders. Overall, these results quantify the scale of misalignment between clinical symptom profiles and DSM-5 disorder labels and demonstrate that DSM-5 disorder criteria do not separate individuals from random when the complete mental health symptom profile of an individual is considered. Greater emphasis on empirical, disorder agnostic approaches to symptom profiling would help overcome existing challenges with heterogeneity and comorbidity, aiding clinical and research outcomes.
| S-EPMC8669440 | biostudies-literature