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33,956 result(s) for "RATING-SCALE"
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Test-retest reliability, validity, and minimum detectable change of visual analog, numerical rating, and verbal rating scales for measurement of osteoarthritic knee pain
Several scales are commonly used for assessing pain intensity. Among them, the numerical rating scale (NRS), visual analog scale (VAS), and verbal rating scale (VRS) are often used in clinical practice. However, no study has performed psychometric analyses of their reliability and validity in the measurement of osteoarthritic (OA) pain. Therefore, the present study examined the test-retest reliability, validity, and minimum detectable change (MDC) of the VAS, NRS, and VRS for the measurement of OA knee pain. In addition, the correlations of VAS, NRS, and VRS with demographic variables were evaluated. The study included 121 subjects (65 women, 56 men; aged 40-80 years) with OA of the knee. Test-retest reliability of the VAS, NRS, and VRS was assessed during two consecutive visits in a 24 h interval. The validity was tested using Pearson's correlation coefficients between the baseline scores of VAS, NRS, and VRS and the demographic variables (age, body mass index [BMI], sex, and OA grade). The standard error of measurement (SEM) and the MDC were calculated to assess statistically meaningful changes. The intraclass correlation coefficients of the VAS, NRS, and VRS were 0.97, 0.95, and 0.93, respectively. VAS, NRS, and VRS were significantly related to demographic variables (age, BMI, sex, and OA grade). The SEM of VAS, NRS, and VRS was 0.03, 0.48, and 0.21, respectively. The MDC of VAS, NRS, and VRS was 0.08, 1.33, and 0.58, respectively. All the three scales had excellent test-retest reliability. However, the VAS was the most reliable, with the smallest errors in the measurement of OA knee pain.
Lower synaptic density is associated with depression severity and network alterations
Synaptic loss and deficits in functional connectivity are hypothesized to contribute to symptoms associated with major depressive disorder (MDD) and post-traumatic stress disorder (PTSD). The synaptic vesicle glycoprotein 2A (SV2A) can be used to index the number of nerve terminals, an indirect estimate of synaptic density. Here, we used positron emission tomography (PET) with the SV2A radioligand [ 11 C]UCB-J to examine synaptic density in n  = 26 unmedicated individuals with MDD, PTSD, or comorbid MDD/PTSD. The severity of depressive symptoms was inversely correlated with SV2A density, and individuals with high levels of depression showing lower SV2A density compared to healthy controls ( n  = 21). SV2A density was also associated with aberrant network function, as measured by magnetic resonance imaging (MRI) functional connectivity. This is the first in vivo evidence linking lower synaptic density to network alterations and symptoms of depression. Our findings provide further incentive to evaluate interventions that restore synaptic connections to treat depression. Lowered synaptic density is believed to occur in major depressive disorder and PTSD, possibly as an effect of stress. Here, the authors use positron emission tomography (PET) to measure levels of the synaptic marker SV2A and show that SV2A density is lower in those with more severe symptoms of depression.
The Lille apathy rating scale (LARS), a new instrument for detecting and quantifying apathy: validation in Parkinson’s disease
Background: Apathy is usually defined as reduced interest and participation in various activities. It is a frequent consequence of neurological and psychiatric disorders. Although various scoring methods have been proposed, there is a lack of validated, standardised instruments for detecting apathy and assessing its severity. Objective: To develop an apathy rating scale using a structured standardised interview capable of distinguishing between the condition’s various features. Methods: The Lille Apathy Rating Scale (LARS) is based on a structured interview. It includes 33 items, divided into nine domains. Responses are scored on a dichotomous scale. The participants used to validate the scale consisted of 159 patients with probable Parkinson’s disease and 58 healthy control subjects. The Marin Apathy Scale, the Montgomery and Asberg Depression Rating Scale, and the Mattis Dementia Rating Scale were also administered. Results: Principal component analysis showed that the LARS probed a single construct which forms the root of an oblique factor structure reflecting four dimensions: intellectual curiosity, self awareness, emotion, and action initiation. The main psychometric properties of the LARS (internal consistency, inter-rater and test-retest reliability) were satisfactory. Concurrent validity was evaluated by reference to the Marin scale and to judgements provided by expert clinicians. Conclusions: Standard validity indices showed that the LARS is sensitive and capable of distinguishing between apathy and depression. As a screening tool, the scale is able to support dichotomous judgements accurately and, when greater measurement sensitivity is required, also determine the severity of apathy within a four category classification.
Population-based validation of a German version of the Brief Resilience Scale
Smith and colleagues developed the Brief Resilience Scale (BRS) to assess the individual ability to recover from stress despite significant adversity. This study aimed to validate the German version of the BRS. We used data from a population-based (sample 1: n = 1.481) and a representative (sample 2: n = 1.128) sample of participants from the German general population (age ≥ 18) to assess reliability and validity. Confirmatory factor analyses (CFA) were conducted to compare one- and two-factorial models from previous studies with a method-factor model which especially accounts for the wording of the items. Reliability was analyzed. Convergent validity was measured by correlating BRS scores with mental health measures, coping, social support, and optimism. Reliability was good (α = .85, ω = .85 for both samples). The method-factor model showed excellent model fit (sample 1: χ2/df = 7.544; RMSEA = .07; CFI = .99; SRMR = .02; sample 2: χ2/df = 1.166; RMSEA = .01; CFI = 1.00; SRMR = .01) which was significantly better than the one-factor model (Δχ2(4) = 172.71, p < .001) or the two-factor model (Δχ2(3) = 31.16, p < .001). The BRS was positively correlated with well-being, social support, optimism, and the coping strategies active coping, positive reframing, acceptance, and humor. It was negatively correlated with somatic symptoms, anxiety and insomnia, social dysfunction, depression, and the coping strategies religion, denial, venting, substance use, and self-blame. To conclude, our results provide evidence for the reliability and validity of the German adaptation of the BRS as well as the unidimensional structure of the scale once method effects are accounted for.
Validity of the SNAP-IV For ADHD Assessment in South African Children With Neurodevelopmental Disorders
This study investigated the psychometric properties of the Swanson, Nolan, and Pelham ADHD Rating Scale (SNAP-IV) in a sample of South African children with neurodevelopmental disorders (n = 201), primarily Autism Spectrum Disorder and Intellectual Disability. We conducted a confirmatory factor analysis to inspect the two-factor structure of the SNAP-IV. We also calculated ordinal coefficient alpha to estimate internal consistency. Fit statistics for the two-factor model approached acceptable levels. The model fit improved slightly after removing an item related to spoken language. The subscales had acceptable internal consistencies. Findings partially support the use of the SNAP-IV in this group of children. However, there are limitations to its performance in this population likely related to the presence of neurodevelopmental disorders.
Efficacy and safety of selegiline for the treatment of Parkinson's disease: A systematic review and meta-analysis
Drug efficacy generally varies with different durations. There is no systematic review analyzing the effect of selegiline for Parkinson's disease (PD) on different treatment duration. This study aims to analyze how the efficacy and safety of selegiline changes for PD over time. PubMed, the Cochrane Library, Embase, China National Knowledge Infrastructure and Wanfang Database were systematically retrieved for randomized controlled trials (RCTs) and observational studies of selegiline for PD. The search period was from inception to January 18th, 2022. The efficacy outcomes were measured by the mean change from baseline in the total and sub Unified Parkinson's Disease Rating Scale (UPDRS), Hamilton Depression Rating Scale (HAMD) and Webster Rating Scale (WRS) scores. The safety outcomes were measured by the proportion of participants having any adverse events overall and that in different system organ classes. Among the 3,786 studies obtained, 27 RCTs and 11 observational studies met the inclusion criteria. Twenty-three studies reported an outcome which was also reported in at least one other study, and were included in meta-analyses. Compared with placebo, selegiline was found with a stronger reduction of total UPDRS score with increasing treatment duration [mean difference and 95% CIs in 1 month: -3.56 (-6.67, -0.45); 3 months: -3.32 (-3.75, -2.89); 6 months: -7.46 (-12.60, -2.32); 12 months: -5.07 (-6.74, -3.41); 48 months: -8.78 (-13.75, -3.80); 60 months: -11.06 (-16.19, -5.94)]. A similar trend was also found from the point estimates in UPDRS I, II, III, HAMD and WRS score. The results of observational studies on efficacy were not entirely consistent. As for safety, compared with placebo, selegiline had higher risk of incurring any adverse events [rate: 54.7% vs. 62.1%; odd ratio and 95% CIs: 1.58 (1.02, 2.44)], with the excess adverse events mainly manifested as neuropsychiatric disorders [26.7% vs. 31.6%; 1.36 (1.06, 1.75)] and no significant change over time. The statistically difference in overall adverse event between selegiline and active controls was not found. Selegiline was effective in improving total UPDRS score with increasing treatment duration, and had a higher risk of incurring adverse events, especially the adverse events in the neuropsychiatric system. https://www.crd.york.ac.uk/prospero/, identifier: PROSPERO CRD42021233145.
The Repetitive Behavior Scale-Revised: Independent Validation in Individuals with Autism Spectrum Disorders
A key feature of autism is restricted repetitive behavior (RRB). Despite the significance of RRBs, little is known about their phenomenology, assessment, and treatment. The Repetitive Behavior Scale-Revised (RBS-R) is a recently-developed questionnaire that captures the breadth of RRB in autism. To validate the RBS-R in an independent sample, we conducted a survey within the South Carolina Autism Society. A total of 320 caregivers (32%) responded. Factor analysis produced a five-factor solution that was clinically meaningful and statistically sound. The factors were labeled \"Ritualistic/Sameness Behavior,\" \"Stereotypic Behavior,\" \"Self-injurious Behavior,\" \"Compulsive Behavior,\" and \"Restricted Interests.\" Measures of internal consistency were high for this solution, and interrater reliability data suggested that the RBS-R performs well in outpatient settings.
The Negative Symptom Inventory-Psychosis Risk (NSI-PR): Psychometric Validation of the Final 11-Item Version
Abstract Background and Hypotheses The lack of psychometrically validated assessment tools designed specifically to assess negative symptoms in individuals at clinical high risk (CHR) for psychosis represents a significant barrier to the early identification and prevention of psychosis. To address this need, the Negative Symptom Inventory-Psychosis Risk (NSI-PR) was developed based on the iterative, data-driven approach recommended by the National Institute of Mental Health consensus conference on negative symptoms. Study Design This manuscript reports the results of the second study phase that psychometrically validates the final 11-item version of the scale in data collected across 3 sites. A total of 222 participants (144 CHR and 78 clinical help-seeking controls) completed the NSI-PR, 1 week of ecological momentary assessment (EMA), and additional convergent and discriminant validity measures. Study Results Structural analyses replicated the previously reported strong fit for the 5-factor (anhedonia, avolition, asociality, alogia, and blunted affect) and hierarchical structures (2 super-ordinate dimensions and 5 lower-level domains). The 5 domains and 2 dimensions generally demonstrated good internal consistency, temporal stability, and interrater reliability. Convergent validity was demonstrated in relation to the 16-item beta version of the NSI-PR, Structured Interview for Psychosis-risk Syndromes negative subscale, Global Functioning Scale social and role, and EMA measures. Discriminant validity was supported by low correlations with positive, disorganized, and general psychiatric symptoms. Conclusions Findings indicate the final 11-item version of the NSI-PR has sound psychometric properties. The scale, which is designed specifically for CHR individuals, is brief and appropriate for use in research and clinical contexts. Accompanying training materials have been developed to support its use in multisite trials.
Deep learning-based behavioral analysis reaches human accuracy and is capable of outperforming commercial solutions
To study brain function, preclinical research heavily relies on animal monitoring and the subsequent analyses of behavior. Commercial platforms have enabled semi high-throughput behavioral analyses by automating animal tracking, yet they poorly recognize ethologically relevant behaviors and lack the flexibility to be employed in variable testing environments. Critical advances based on deep-learning and machine vision over the last couple of years now enable markerless tracking of individual body parts of freely moving rodents with high precision. Here, we compare the performance of commercially available platforms (EthoVision XT14, Noldus; TSE Multi-Conditioning System, TSE Systems) to cross-verified human annotation. We provide a set of videos—carefully annotated by several human raters—of three widely used behavioral tests (open field test, elevated plus maze, forced swim test). Using these data, we then deployed the pose estimation software DeepLabCut to extract skeletal mouse representations. Using simple post-analyses, we were able to track animals based on their skeletal representation in a range of classic behavioral tests at similar or greater accuracy than commercial behavioral tracking systems. We then developed supervised machine learning classifiers that integrate the skeletal representation with the manual annotations. This new combined approach allows us to score ethologically relevant behaviors with similar accuracy to humans, the current gold standard, while outperforming commercial solutions. Finally, we show that the resulting machine learning approach eliminates variation both within and between human annotators. In summary, our approach helps to improve the quality and accuracy of behavioral data, while outperforming commercial systems at a fraction of the cost.