Dual-Task Assessments for Predicting Future Falls in Neurologic Conditions: A Systematic Review.

ABSTRACT: This review investigated the ability of dual-task tests to predict falls in people with neurological disorders. Databases were searched to identify prospective cohort studies that analyzed dual-task testing and falls in people with neurological disorders. Reviewers screened studies for eligibility and extracted key information like participant characteristics, intervention details, outcome measures, and significant outcomes. Reviewers assessed methodological quality of eligible studies using the Standard Quality Assessment Criteria. Eighteen studies of strong methodological qualified with 1750 participants were included in the review. Dual-task performances were predictive of future falls in people with Huntington's disease, spinal cord injury, and moderate cognitive impairment, although only one independent study was included for each disability type. In people with stroke, 37% of eligible studies showed dual-task assessments to be predictive of future falls. No dual-task tests predicted prospective falling in people with Alzheimer's or Parkinson's disease. Complex dual tasks seemed to be more predictive of fall risk than simpler dual tasks. Results suggest that disability type, severity of disability, and task complexity play a role in the predictive ability of dual-task assessments and future falling in neurological disorders. Future studies may benefit from using this review to guide the design of effective dual-task assessments and fall interventions.

Unreliable Findings Due to Miscalculations and Errors. Comment on Nally et al. The Effectiveness of School-Based Interventions on Obesity-Related Behaviours in Primary School Children: A Systematic Review and Meta-Analysis of Randomised Controlled Trials. Children 2021, 8, 489.

Nally et al. [...].

Improved calibration of area detectors using multiple placements.

Calibration of area detectors from powder diffraction standards is widely used at synchrotron beamlines. From a single diffraction image, it is not possible to determine both the sample-to-detector distance and the wavelength, but, with images taken from multiple positions along the beam direction and where the relative displacement is known, the sample-to-detector distance and wavelength can both be determined with good precision. An example calibration using the GSAS-II software package is presented.