Reliability and validity of a novel mobile-based automatic battery of cognitive tests in healthy young Chinese adults

Abstract

Purpose

To evaluate the reliability and validity of a newly developed computerized Automated Battery of Cognitive Tests in healthy individuals without cognitive impairments or psychiatric disorders.

Methods

From April 20 to July 1, 2023, 142 healthy individuals in Beijing and Tangshan, China were assessed using the Automated Battery of Cognitive Tests. After a 3-week interval, 36 participants were randomly selected for retesting. The assessment also included administration of the Repeatable Battery for the Assessment of Neuropsychological Status and the Automated Battery of Cognitive Tests to 59 participants.

Results

The Automated Battery of Cognitive Tests consists of 16 subtests. Internal consistency reliability was 0.75. The test-retest reliability for each factor ranged from 0.337 to 0.850 (p < 0.05). The criterion-related validity, as measured by correlation with the total Repeatable Battery for the Assessment of Neuropsychological Status score, was 0.748 (p < 0.001). The cumulative variance contribution rate is 70.109%. The results of the confirmatory factor analysis indicated a good model fit.

Conclusions

The computerized Automated Battery of Cognitive Tests is a cognitive self-assessment tool with good reliability and validity. It can evaluate multiple aspects of cognitive performance in healthy individuals and is suitable for self-administration through remote access via Internet.

Keywords:

• Cognition
• factor analysis
• neurocognitive assessment
• validity

Acknowledgments

The authors thank the developers who have been involved in the technical design, development, and optimization of the ABCT. This study would also not have been possible without the partnership with Jinghan Wang and Xinrui Wang, who provided instruction on the assessment of RBANS. We would like to thank Editage (www.editage.cn) for English language editing.

Author contributions

Jiajia Li: methodology, formal analysis, writing-original draft, validation, investigation, visualization, review, editing. Shuping Tan: review, editing, writing, funding acquisition, supervision. Hongzhen Fan: software, visualization, review, data curation, methodology, supervision. Wei Qu: software, resources. Ronghuan Jiang: review, editing.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work was funded by the Beijing Municipal Health Commission [grant number 2022-1 G-2132].