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NeuroMET Memory Metric: Improving accuracy and comparability with crosswalks
RISE Research Institutes of Sweden, Safety and Transport, Measurement Technology.ORCID iD: 0000-0002-3700-3921
ModusOutcomes, UK.
Universitätsmedizin, Germany.
University Medicine Greifswald, Germany; German Centre for Neurodegenerative Diseases, Germany.
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2023 (English)In: Alzheimer’s & Dementia: Translational Research & Clinical Interventions, E-ISSN 2352-8737, Vol. 19, no S4, article id e063924Article in journal (Refereed) Published
Abstract [en]

Background: The ability to measure, track over time, and compare memory ability for people with neurodegeneration is important. However, currently, full comparability of memory test data is limited by a lack of quality assurance of memory measurements. At AAIC 2021, we presented a preliminary item bank to assess memory, composed by selecting items from legacy tests according to metrological principles through use of the Rasch model and with item equivalence based on entropy. Method: Here, we demonstrate direct comparability of measurements generated from different tests, with the new NeuroMET Memory Metric comprising 87 selected items for task difficulty from: the Corsi Block Test, Digit Span Test, Rey’s Auditory Verbal Learning Test, Word Learning List from the CERAD test battery and the Mini Mental State Examination. Data were collected from the European EMPIR NeuroMET and the SmartAge studies recruited at Charité Hospital (Healthy controls n = 92; Subjective cognitive decline n = 160; Mild Cognitive Impairment n = 50; and Alzheimer’s Disease n = 58; age range 55-87). Results: The Rasch analysis showed well-targeted items for all participants’ abilities; good fit to the measurement model, with 83 items (95%) having fit residuals within the expected range and satisfactory unidimensionality, and item reliability of 0.96. The full item bank comprising 87 short-term memory items gave a person reliability of 0.85. Subsequently, a conversion table was created linking the raw scores from the legacy tests to the common NeuroMET Memory Metric and to individual legacy tests. Conclusion: Legacy memory tests have previously proven useful in clinical practice and research, and will continue to be used, but have to date been metrologically limited. The provided conversion table, linking these legacy memory tests to a metrologically assured scale, viz., the NeuroMET memory metric, remedies this deficiency. The NeuroMET memory metric will be included in the first ever prototype of a metrological validated app used to deliver memory tests. Clinicians and researchers will be able to select sets of items to produce data, via a scoring algorithm for transforming patient responses to measures, in a common frame of reference.

Place, publisher, year, edition, pages
2023. Vol. 19, no S4, article id e063924
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Neurosciences
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URN: urn:nbn:se:ri:diva-66215DOI: 10.1002/alz.063924OAI: oai:DiVA.org:ri-66215DiVA, id: diva2:1795104
Note

This project (EMPIR 18HLT9 NeuroMET2) has received funding from the EMPIR programme co-financed by the Participating States and from the European Union’s Horizon 2020 research and innovation programme

Available from: 2023-09-07 Created: 2023-09-07 Last updated: 2023-09-07Bibliographically approved

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Melin, JeanettePendrill, Leslie

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