NeuralCipher Research overview
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ObjectiveTo systematically review the literature of existing evidence on the measurement properties of the Quality of Life in Neurological Disorders (Neuro-QoL) measurement system among neurorehabilitation populations.Data sourcesThe Consensus-based Standards for the selection of health Measurement Instruments (COSMIN) guided this systematic review in which we searched nine electronic databases and registries, and hand-searched reference lists of included articles.Study selectionTwo independent reviewers screened selected articles and extracted data from 28 included studies.Data extractionCOSMIN's approach guided extraction and synthesizing measurement properties evidence (insufficient, sufficient), and the modified GRADE approach guided synthesizing evidence quality (very-low, low, moderate, high) by diagnosis.Data synthesisNeuro-QoL has sufficient measurement properties when used by individuals with Huntington's disease, Multiple Sclerosis, Parkinson's disease, stroke, lupus, cognitive decline, and amyotrophic lateral sclerosis. The strongest evidence is for the first four conditions, where test-retest reliability, construct validity, and responsiveness are nearly always sufficient (GRADE: moderate-high). Structural validity is assessed only in multiple sclerosis and stroke but is often insufficient (GRADE: moderate-high). Criterion validity is sufficient in some stroke and Huntington's disease domains (GRADE: high). Item response theory analyses were reported for some stroke domains only. There is limited, mixed evidence for responsiveness and measurement error (GRADE: moderate-high), and no cross-cultural validity evidence CONCLUSIONS: Neuro-QoL domains can describe and evaluate patients with Huntington's disease, multiple sclerosis, Parkinson's disease, and stroke, but predictive validity evidence would be beneficial. In the other conditions captured in this review, a limited number of Neuro-QoL domains have evidence for descriptive use only. For these conditions, further evidence of structural validity, measurement error, cross-cultural validity and predictive validity would enhance the use and interpretation of Neuro-QoL.
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