Improving the Action Research Arm test: a unidimensional hierarchical scale

The Action Research Arm (ARA) test is a performance test of upper extremity motor function which consists of 19 items divided into four hierarchical subtests. This multidimensionality has not yet been tested empirically. To investigate the dimensionality of the ARA test. Cross-sectional study involving a sample of 63 chronic stroke patients. A Mokken scale analysis was performed. The Mokken scale analysis revealed one strong unidimensional scale containing all 19 items, of which the scalability coefficient H was 0.79, while H per item ranged from 0.69 to 0.86. The reliability coefficient rho equalled 0.98, indicating a very high internal consistency. A subset of 15 out of 19 items showed an invariant hierarchical item-ordering. The ARA test is a unidimensional scale. The use of subtests, as proposed in the original description of the instrument, is not supported by the present findings. The 15-item scale presented here can be used for adaptive testing, i.e. using only a selected subset of items based on prior knowledge about the patient's abilities, thus minimizing testing tim

The 12-item World Health Organization Disability Assessment Schedule II (WHO-DAS II): a nonparametric item response analysis

<p>Abstract</p> <p>Background</p> <p>Previous studies have analyzed the psychometric properties of the World Health Organization Disability Assessment Schedule II (WHO-DAS II) using classical omnibus measures of scale quality. These analyses are sample dependent and do not model item responses as a function of the underlying trait level. The main objective of this study was to examine the effectiveness of the WHO-DAS II items and their options in discriminating between changes in the underlying disability level by means of item response analyses. We also explored differential item functioning (DIF) in men and women.</p> <p>Methods</p> <p>The participants were 3615 adult general practice patients from 17 regions of Spain, with a first diagnosed major depressive episode. The 12-item WHO-DAS II was administered by the general practitioners during the consultation. We used a non-parametric item response method (Kernel-Smoothing) implemented with the TestGraf software to examine the effectiveness of each item (item characteristic curves) and their options (option characteristic curves) in discriminating between changes in the underliying disability level. We examined composite DIF to know whether women had a higher probability than men of endorsing each item.</p> <p>Results</p> <p>Item response analyses indicated that the twelve items forming the WHO-DAS II perform very well. All items were determined to provide good discrimination across varying standardized levels of the trait. The items also had option characteristic curves that showed good discrimination, given that each increasing option became more likely than the previous as a function of increasing trait level. No gender-related DIF was found on any of the items.</p> <p>Conclusions</p> <p>All WHO-DAS II items were very good at assessing overall disability. Our results supported the appropriateness of the weights assigned to response option categories and showed an absence of gender differences in item functioning.</p

Revisiting the dimensional structure of the Edinburgh Postnatal Depression Scale (EPDS): empirical evidence for a general factor

<p>Abstract</p> <p>Background</p> <p>The Edinburgh Postnatal Depression Scale (EPDS) has been proposed as a one-dimensional instrument and used as a single 10-item scale. This might be considered questionable since repeated psychometric studies have shown multi-dimensionality, which would entail using separate component subscales. This study reappraised the dimensional structure of the EPDS, with a focus on the extent of factor correlations and related factor-based discriminant validity as a foundation for deciding how to effectively scale the component items.</p> <p>Methods</p> <p>The sample comprised 811 randomly selected mothers of children up to 5 months attending primary health services of Rio de Janeiro, Brazil. Strict Confirmatory Factor Analysis (CFA) and Exploratory Factor Analysis modeled within a CFA framework (E/CFA) were sequentially used to identify best fitting and parsimonious model(s), including a bifactor analysis to evaluate the existence of a general factor. Properties concerning the related 10-item raw-score scale were also investigated using non-parametric items response theory methods (scalability and monotonicity).</p> <p>Results</p> <p>An initial CFA rejected the one-dimensional structure, while an E/CFA subscribed a three-dimensional solution. Yet, factors were highly correlated (0.66, 0.75 and 0.82). The ensuing CFA showed poor discriminant validity (some square-roots of average variance extracted below the factor correlations). A general bifactor CFA was then fit. Results suggested that, although still weakly encompassing three specific factors, the EPDS might be better described by a model encompassing a general factor (loadings ranging from 0.51 to 0.81). The related 10-item raw score showed adequate scalability (Loevinger's H coefficient = 0.4208), monotonicity e partial double monotonicity (nonintersections of Item Step Response Functions).</p> <p>Conclusion</p> <p>Although the EPDS indicated the presence of specific factors, they do not qualify as independent dimensions if used separately and should therefore not be used empirically as sub-scales (raw scores). An all-encompassing scale seems better suited and continuing its use in clinical practice and applied research should be encouraged.</p

An initial application of computerized adaptive testing (CAT) for measuring disability in patients with low back pain

<p>Abstract</p> <p>Background</p> <p>Recent approaches to outcome measurement involving Computerized Adaptive Testing (CAT) offer an approach for measuring disability in low back pain (LBP) in a way that can reduce the burden upon patient and professional. The aim of this study was to explore the potential of CAT in LBP for measuring disability as defined in the International Classification of Functioning, Disability and Health (ICF) which includes impairments, activity limitation, and participation restriction.</p> <p>Methods</p> <p>266 patients with low back pain answered questions from a range of widely used questionnaires. An exploratory factor analysis (EFA) was used to identify disability dimensions which were then subjected to Rasch analysis. Reliability was tested by internal consistency and person separation index (PSI). Discriminant validity of disability levels were evaluated by Spearman correlation coefficient (r), intraclass correlation coefficient [ICC(2,1)] and the Bland-Altman approach. A CAT was developed for each dimension, and the results checked against simulated and real applications from a further 133 patients.</p> <p>Results</p> <p>Factor analytic techniques identified two dimensions named "body functions" and "activity-participation". After deletion of some items for failure to fit the Rasch model, the remaining items were mostly free of Differential Item Functioning (DIF) for age and gender. Reliability exceeded 0.90 for both dimensions. The disability levels generated using all items and those obtained from the real CAT application were highly correlated (i.e. > 0.97 for both dimensions). On average, 19 and 14 items were needed to estimate the precise disability levels using the initial CAT for the first and second dimension. However, a marginal increase in the standard error of the estimate across successive iterations substantially reduced the number of items required to make an estimate.</p> <p>Conclusion</p> <p>Using a combination approach of EFA and Rasch analysis this study has shown that it is possible to calibrate items onto a single metric in a way that can be used to provide the basis of a CAT application. Thus there is an opportunity to obtain a wide variety of information to evaluate the biopsychosocial model in its more complex forms, without necessarily increasing the burden of information collection for patients.</p

To be objective in Experimental Phenomenology: a Psychophysics application

Background Several scientific psychologists consider the approach for the study of perceptive problems of the Experimental Phenomenology is problematic, namely that the phenomenological demonstrations are subjectively based and they do not produce quantifiable results. Aim The aim of this study is to show that Experimental Phenomenology can lead to conclusions objective and quantifiable and propose a procedure allowing to obtain objective measuring using the Rasch mathematical model able to describe the experimental data gathered in Experimental Phenomenology procedures. Method In order to demonstrate this, a Psychophysics simulated study is proposed. Results/conclusions It is possible to carry out a fundamental measurement starting from Experimental Phenomenology by way of the Theory of Conjoint Measurement

Discovery of enzymes for toluene synthesis from anoxic microbial communities

Microbial toluene biosynthesis was reported in anoxic lake sediments more than three decades ago, but the enzyme catalyzing this biochemically challenging reaction has never been identified. Here we report the toluene-producing enzyme PhdB, a glycyl radical enzyme of bacterial origin that catalyzes phenylacetate decarboxylation, and its cognate activating enzyme PhdA, a radical S-adenosylmethionine enzyme, discovered in two distinct anoxic microbial communities that produce toluene. The unconventional process of enzyme discovery from a complex microbial community (&gt;300,000 genes), rather than from a microbial isolate, involved metagenomics- and metaproteomics-enabled biochemistry, as well as in vitro confirmation of activity with recombinant enzymes. This work expands the known catalytic range of glycyl radical enzymes (only seven reaction types had been characterized previously) and aromatic-hydrocarbon-producing enzymes, and will enable first-time biochemical synthesis of an aromatic fuel hydrocarbon from renewable resources, such as lignocellulosic biomass, rather than from&nbsp;petroleum