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.
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.
1 April 2014 in Research in Developmental Disabilities
Little is known about anticipatory postural adjustments (APAs) developing when body segments of tiny mass are moved. Thus, APAs in the human upper-limb were investigated during a gentle and small index finger tap (35 mm stroke in 50 ms). This task was fulfilled by ten subjects either with prone or supine hand. EMG was recorded from Flexor Digitorum Superficialis (FDS), the prime mover, and from several upper-limb muscles under slight tonic contraction. Regardless of hand posture, EMG was inhibited in Flexor Carpi Radialis and facilitated in Extensor Carpi Radialis well before the FDS burst. With the prone hand, the prime mover activity was preceded by Biceps inhibition and Triceps facilitation; this effect reverted in sign with the supine hand. A postural reversal was also observed in Anterior Deltoid and Trapezius which were both inhibited with the prone hand. The effect in Trapezius was present only with the unsupported forearm. It is thus demonstrated that a gentle small finger tap produces well-defined anticipatory natural synergies behaving as the most “classical” APAs: (1) they are distributed to several upper-limb muscles creating a postural chain aiming to prevent the effects of the interaction torques generated by the voluntary movement; (2) they change in amplitude according to the level of postural stability and (3) they revert in sign when movement direction is reverted. These results are also corroborated by data obtained from a simple mechanical model simulating finger tapping in a fictive upper-limb. A possible role of APAs in controlling movements’ accuracy is also discussed.