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Background: Myotonic dystrophy type 1 (DM1) is a rare multisystemic genetic disorder with motor hallmarks of myotonia, muscle weakness and wasting. DM1 patients have an increased risk of falling of multifactorial origin, and proprioceptive and vestibular deficits can contribute to this risk. Abnormalities of muscle spindles in DM1 have been known for years. This observational cross-sectional study was based on the hypothesis of impaired cervical proprioception caused by alterations in the neck spindles. Methods: Head position sense was measured in 16 DM1 patients and 16 age- and gender-matched controls. A head-to-target repositioning test was requested from blindfolded participants. Their head was passively rotated approximately 30° leftward or rightward and flexed or extended approximately 25°. Participants had to replicate the imposed positions. An optoelectronic system was adopted to measure the angular differences between the reproduced and the imposed positions (joint position error, JPE, °) concerning the intended (sagittal, horizontal) and unintended (including the frontal) planar projections. In DM1 patients, JPEs were correlated with clinical and balance measures. Static balance in DM1 patients was assessed through dynamic posturography. Results: The accuracy and precision of head repositioning in the intended sagittal and horizontal error components did not differ between DM1 and controls. On the contrary, DM1 patients showed unintended side-bending to the left and the right: the mean [95%CI] of frontal JPE was −1.29° [−1.99°, −0.60°] for left rotation and 0.98° [0.28°, 1.67°] for right rotation. The frontal JPE of controls did not differ significantly from 0° (left rotation: 0.17° [−0.53°, 0.87°]; right rotation: −0.22° [−0.91°, 0.48°]). Frontal JPE differed between left and right rotation trials (p < 0.001) only in DM1 patients. No correlation was found between JPEs and measures from dynamic posturography and clinical scales. Conclusions: Lateral head bending associated with head rotation may reflect a latent impairment of neck proprioception in DM1 patients. [ABSTRACT FROM AUTHOR]

Purpose: The present paper presents developments and advanced practical applications of Rasch's theory and statistical analysis to construct questionnaires for measuring a person's traits. The flaws of questionnaires providing raw scores are well known. Scores only approximate objective, linear measures. The Rasch Analysis allows you to turn raw scores into measures with an error estimate, satisfying fundamental measurement axioms (e.g., unidimensionality, linearity, generalizability). A previous companion article illustrated the most frequent graphic and numeric representations of results obtained through Rasch Analysis. A more advanced description of the method is presented here. Conclusions: Measures obtained through Rasch Analysis may foster the advancement of the scientific assessment of behaviours, perceptions, skills, attitudes, and knowledge so frequently faced in Physical and Rehabilitation Medicine, not less than in social and educational sciences. Furthermore, suggestions are given on interpreting and managing the inevitable discrepancies between observed scores and ideal measures (data-model "misfit"). Finally, twelve practical take-home messages for appraising published results are provided. The current work is the second of two papers addressed to rehabilitation clinicians looking for an in-depth introduction to the Rasch analysis. The first paper illustrates the most common results reported in published papers presenting the Rasch analysis of questionnaires. The present article illustrates more advanced applications of the Rasch analysis, also frequently found in publications. Twelve take-home messages are given for a critical appraisal of the results. [ABSTRACT FROM AUTHOR]

Purpose: The present article summarises the characteristics of Rasch's theory, providing an original metrological model for persons' measurements. Properties describing the person "as a whole" are key outcome variables in Medicine. This is particularly true in Physical and Rehabilitation Medicine, targeting the person's interaction with the outer world. Such variables include independence, pain, fatigue, balance, and the like. These variables can only be observed through behaviours of various complexity, deemed representative of a given "latent" person's property. So how to infer its "quantity"? Usually, behaviours (items) are scored ordinally, and their "raw" scores are summed across item lists (questionnaires). The limits and flaws of scores (i.e., multidimensionality, non-linearity) are well known, yet they still dominate the measurement in Medicine. Conclusions: Through Rasch's theory and statistical analysis, scores are transformed and tested for their capacity to respect fundamental measurement axioms. Rasch analysis returns the linear measure of the person's property ("ability") and the item's calibrations ("difficulty"), concealed by the raw scores. The difference between a person's ability and item difficulty determines the probability that a "pass" response is observed. The discrepancy between observed scores and the ideal measures (i.e., the residual) invites diagnostic reasoning. In a companion article, advanced applications of Rasch modelling are illustrated. Questionnaires' ordinal scores are poor approximations of measures. The Rasch analysis turns questionnaires' scores into interval measures, provided that its assumptions are respected. Thanks to the Rasch analysis, accurate measures of independence, pain, fatigue, cognitive capacities and other whole person's variables of paramount importance in rehabilitation are available. The current work is addressed to rehabilitation professionals looking for an introduction to interpreting published results based on Rasch analysis. The first of a series of two, the present article illustrates the most common graphic and numeric outputs found in published papers presenting the Rasch analysis of questionnaires. [ABSTRACT FROM AUTHOR]