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. 2022 Nov 8:4:933265.
doi: 10.3389/fdgth.2022.933265. eCollection 2022.

Unsupervised mobile app-based cognitive testing in a population-based study of older adults born 1944

Affiliations

Unsupervised mobile app-based cognitive testing in a population-based study of older adults born 1944

Fredrik Öhman et al. Front Digit Health. .

Abstract

Background: Mobile app-based tools have the potential to yield rapid, cost-effective, and sensitive measures for detecting dementia-related cognitive impairment in clinical and research settings. At the same time, there is a substantial need to validate these tools in real-life settings. The primary aim of this study was thus to evaluate the feasibility, validity, and reliability of mobile app-based tasks for assessing cognitive function in a population-based sample of older adults.

Method: A total of 172 non-demented (Clinical Dementia Rating 0 and 0.5) older participants (aged 76-77) completed two mobile app-based memory tasks-the Mnemonic Discrimination Task for Objects and Scenes (MDT-OS) and the long-term (24 h) delayed Object-In-Room Recall Task (ORR-LDR). To determine the validity of the tasks for measuring relevant cognitive functions in this population, we assessed relationships with conventional cognitive tests. In addition, psychometric properties, including test-retest reliability, and the participants' self-rated experience with mobile app-based cognitive tasks were assessed.

Result: MDT-OS and ORR-LDR were weakly-to-moderately correlated with the Preclinical Alzheimer's Cognitive Composite (PACC5) (r = 0.3-0.44, p < .001) and with several other measures of episodic memory, processing speed, and executive function. Test-retest reliability was poor-to-moderate for one single session but improved to moderate-to-good when using the average of two sessions. We observed no significant floor or ceiling effects nor effects of education or gender on task performance. Contextual factors such as distractions and screen size did not significantly affect task performance. Most participants deemed the tasks interesting, but many rated them as highly challenging. While several participants reported distractions during tasks, most could concentrate well. However, there were difficulties in completing delayed recall tasks on time in this unsupervised and remote setting.

Conclusion: Our study proves the feasibility of mobile app-based cognitive assessments in a community sample of older adults, demonstrating its validity in relation to conventional cognitive measures and its reliability for repeated measurements over time. To further strengthen study adherence, future studies should implement additional measures to improve task completion on time.

Keywords: Alzheimers disease (AD); digital cognitive assessment; episodic memory; remote and unsupervised assessment; smartphone-based cognitive assessments.

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Conflict of interest statement

DB has co-founded neotiv GmbH and owns shares. KVP has served as a paid consultant for Biogen Idec, Digital Cognition Technologies, Cogstate and Prothena, outside the scope of this work. MS has served on a scientific advisory board for Servier and received speaker honoraria by Genentech, outside the scope of this work. SK has served at scientific advisory boards and/or as consultant for Geras Solutions and Biogen, outside the scope of this work. The remaining authors declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
Flowchart of baseline and follow-up examinations. ORR-LDR, Object-in-Room Recall Task; MDT-OS, Mnemonic Discrimination Task for Objects and Scenes. *Please note, these numbers represent participants that correctly completed all phases after initial filtering (see section 3.1).
Figure 2
Figure 2
(A) ORR-LDR and (B) MDT-OS. ORR-LDR, Object-in-Room Recall Task; MDT-OS, Mnemonic Discrimination Task for Objects and Scenes. Used with permission from neotiv GmbH.
Figure 3
Figure 3
Distribution of test scores across (A) ORR-LDR and (B) MDT-OS. ORR-LDR, Object-in-Room Recall Task; MDT-OS, Mnemonic Discrimination Task for Objects and Scenes.
Figure 4
Figure 4
ORR-LDR, MDT-OS and correlation with PACC5. (A) ORR-LDR and (B) MDT-OS were weakly to moderately correlated with PACC5 (r = 0.44, p < .001, and r = 0.32, p < .001). The correlation values represent Spearman's Rho. Colored dots represent Clinical Dementia Rating (CDR) 0 (black) and CDR 0.5 (orange). ORR-LDR, Object-in-Room Recall Task; MDT-OS, Mnemonic Discrimination Task for Objects and Scenes; PACC5, Preclinical Alzheimer's Cognitive Composite.
Figure 5
Figure 5
ORR-LDR and correlation with PACC5 subtests. ORR-LDR were weakly to moderately correlated with PACC5 subtests (A) RAVLT delayed recall (r = 0.40, p < .001) and (B) Digit-Symbol-Coding (r = 0.28, p = 0.008). ORR-LDR was not significantly correlated with the PACC5 subtests (C) Word fluency animals and (D) MMSE. The correlation values represent Spearman's Rho. Coloured dots represent Clinical Dementia Rating (CDR) 0 (black) and CDR 0.5 (orange). ORR-LDR, Object-in-Room Recall Task; RAVLT, Rey Auditory Verbal Learning Test; MMSE, Mini-Mental State Examination; PACC5, Preclinical Alzheimer's Cognitive Composite.
Figure 6
Figure 6
MDT-OS and correlation with PACC5 subtests. (A) MDT-OS was weakly correlated with the PACC5 subtest RAVLT Recall (r = 0.32, p < .001). MDT-OS was not significantly correlated with the PACC5 subtests (B) Digit-Symbol-Coding, (C) Word fluency animals, and (D) MMSE. The correlation values represent Spearman's Rho. Colored dots represent Clinical Dementia Rating (CDR) 0 (black) and CDR 0.5 (orange). MDT-OS, Mnemonic Discrimination Task for Objects and Scenes; RAVLT, Rey Auditory Verbal Learning Test; MMSE, Mini-Mental State Examination; PACC5, Preclinical Alzheimer's Cognitive Composite.

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