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Moving intra-individual variability (IIV) towards clinical utility: IIV measured using a commercial testing platform.
Journal of the Neurological Sciences 2023 Februrary 13
OBJECTIVES: Intra-individual variability (IIV), measured across repeated response times (RT) during continuous psychomotor tasks, is an early marker of cognitive change in the context of neurodegeneration. To advance IIV towards broader application in clinical research, we evaluated IIV from a commercial cognitive testing platform and compared it to the calculation approaches used in experimental cognitive studies.
METHODS: Cognitive assessment was administered in participants with multiple sclerosis (MS) during the baseline of an unrelated study. Cogstate was used for computer-based measures providing three timed-trial tasks measuring simple (Detection; DET) and choice (Identification; IDN) RT and working memory (One-Back; ONB). IIV for each task was automatically output by the program (calculated as a log10 -transformed standard deviation or "LSD"). We calculated IIV from the raw RTs using coefficient of variation (CoV), regression-based, and ex-Gaussian methods. The IIV from each calculation was then compared by rank across participants.
RESULTS: A total of n = 120 participants with MS aged 20-72 (Mean ± SD, 48.99 ± 12.09) completed the baseline cognitive measures. For each task, the interclass correlation coefficient was generated. Each ICC showed that LSD, CoV, ex-Gaussian, and regression methods clustered strongly (Average ICC for DET: 0.95 with 95% CI [0.93, 0.96]; Average ICC for IDN: 0.92 with 95% CI [0.88 to 0.93]; Average ICC for ONB: 0.93 with 95% CI [0.90 to 0.94]). Correlational analyses indicated the strongest correlation between LSD and CoV for all tasks (rs ≥ 0.94).
CONCLUSION: The LSD was consistent with research-based methods for IIV calculations. These findings support the use of LSD for the future measurement of IIV for clinical studies.
METHODS: Cognitive assessment was administered in participants with multiple sclerosis (MS) during the baseline of an unrelated study. Cogstate was used for computer-based measures providing three timed-trial tasks measuring simple (Detection; DET) and choice (Identification; IDN) RT and working memory (One-Back; ONB). IIV for each task was automatically output by the program (calculated as a log10 -transformed standard deviation or "LSD"). We calculated IIV from the raw RTs using coefficient of variation (CoV), regression-based, and ex-Gaussian methods. The IIV from each calculation was then compared by rank across participants.
RESULTS: A total of n = 120 participants with MS aged 20-72 (Mean ± SD, 48.99 ± 12.09) completed the baseline cognitive measures. For each task, the interclass correlation coefficient was generated. Each ICC showed that LSD, CoV, ex-Gaussian, and regression methods clustered strongly (Average ICC for DET: 0.95 with 95% CI [0.93, 0.96]; Average ICC for IDN: 0.92 with 95% CI [0.88 to 0.93]; Average ICC for ONB: 0.93 with 95% CI [0.90 to 0.94]). Correlational analyses indicated the strongest correlation between LSD and CoV for all tasks (rs ≥ 0.94).
CONCLUSION: The LSD was consistent with research-based methods for IIV calculations. These findings support the use of LSD for the future measurement of IIV for clinical studies.
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