28
Views
0
CrossRef citations to date
0
Altmetric
Research Article

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

, , , &

References

  • Bentler, P. M., & Bonett, D. G. (1980). Significance tests and goodness of fit in the analysis of covariance structures. Psychological Bulletin, 88(3), 588–606. https://doi.org/10.1037/0033-2909.88.3.588
  • Benuzzi, F., Ballotta, D., Casadio, C., Zanelli, V., Porro, C. A., Nichelli, P. F., & Lui, F. (2023). “When you’re smiling”: How posed facial expressions affect visual recognition of emotions. Brain Sciences, 13(4), 668. https://doi.org/10.3390/brainsci13040668
  • Bombassaro, T., Carrilho, C. G., Peixoto, C., Alves, G. S., Kahn, J. P., Nardi, A. E., & Veras, A. B. (2023). Cognition in schizophrenia: A systematic review of Wechsler Adult Intelligence Scale studies. The Primary Care Companion for CNS Disorders, 25(5), 22r03456. https://doi.org/10.4088/PCC.22r03456
  • Browne, M. W., & Cudeck, R. (1992). Alternative ways of assessing model fit. Sociological Methods & Research, 21(2), 230–258. https://doi.org/10.1177/0049124192021002005
  • Fried, R., DiSalvo, M., Kelberman, C., & Biederman, J. (2021). Can the CANTAB identify adults with attention-deficit/hyperactivity disorder? A controlled study. Applied Neuropsychology. Adult, 28(3), 318–327. https://doi.org/10.1080/23279095.2019.1633328
  • Gallegos, M., Morgan, M. L., Cervigni, M., Martino, P., Murray, J., Calandra, M., Razumovskiy, A., Caycho-Rodríguez, T., & Gallegos, W. L. A. (2022). 45 Years of the mini-mental state examination (MMSE): A perspective from Ibero-America. Dementia & Neuropsychologia, 16(4), 384–387. https://doi.org/10.1590/1980-5764-DN-2021-0097
  • Gao, Y., Xiao, Y., Miao, R., Zhao, J., Cui, M., Huang, G., & Fei, M. (2016). The prevalence of mild cognitive impairment with type 2 diabetes mellitus among elderly people in China: A cross-sectional study. Archives of Gerontology and Geriatrics, 62, 138–142. https://doi.org/10.1016/j.archger.2015.09.003
  • Greenfield, D. N., Cazala, F., Carre, J., Mitchell-Somoza, A., Decety, J., Thornton, D., Kiehl, K. A., & Harenski, C. L. (2023). Emotional intelligence in incarcerated sexual offenders with sexual sadism. The Journal of Sexual Aggression, 29(1), 68–85. https://doi.org/10.1080/13552600.2021.2015469
  • Gur, R. C., Richard, J., Hughett, P., Calkins, M. E., Macy, L., Bilker, W. B., Brensinger, C., & Gur, R. E. (2010). A cognitive neuroscience-based computerized battery for efficient measurement of individual differences: Standardization and initial construct validation. Journal of Neuroscience Methods, 187(2), 254–262. https://doi.org/10.1016/j.jneumeth.2009.11.017
  • Hicks, R. G. (1970). Experimenter effects on the physiological experiment. Psychophysiology, 7(1), 10–17. https://doi.org/10.1111/j.1469-8986.1970.tb02272.x
  • Hong, J., Su, Y., Wang, J., Xu, X., Qu, W., Fan, H., Tan, Y., Wang, Z., Zhao, Y., & Tan, S. (2023). Association between video gaming time and cognitive functions: A cross-sectional study of Chinese children and adolescents. Asian Journal of Psychiatry, 84, 103584. https://doi.org/10.1016/j.ajp.2023.103584
  • Huang, X., Zhao, X., Li, B., Cai, Y., Zhang, S., Wan, Q., & Yu, F. (2022). Comparative efficacy of various exercise interventions on cognitive function in patients with mild cognitive impairment or dementia: A systematic review and network meta-analysis. Journal of Sport and Health Science, 11(2), 212–223. https://doi.org/10.1016/j.jshs.2021.05.003
  • Huepe, D., Roca, M., Salas, N., Canales-Johnson, A., Rivera-Rei, Á. A., Zamorano, L., Concepción, A., Manes, F., & Ibañez, A. (2011). Fluid intelligence and psychosocial outcome: From logical problem solving to social adaptation. PLOS One, 6(9), e24858. https://doi.org/10.1371/journal.pone.0024858
  • Kelley, T. L. (1939). The selection of upper and lower groups for the validation of test items. Journal of Educational Psychology, 30(1), 17–24. https://doi.org/10.1037/h0057123
  • Langa, K. M., & Levine, D. A. (2014). The diagnosis and management of mild cognitive impairment: A clinical review. JAMA, 312(23), 2551–2561. https://doi.org/10.1001/jama.2014.13806
  • Lin, C., Gou, M., Pan, S., Tong, J., Zhou, Y., Xie, T., Yu, T., Feng, W., Li, Y., Chen, S., Tian, B., Tan, S., Wang, Z., Luo, X., Li, C.-S R., Zhang, P., Huang, J., Elliot Hong, L., & Tan, Y. (2022). Serum hyperhomocysteine and cognitive impairment in first-episode patients with schizophrenia: Moderated by brain cortical thickness. Neuroscience Letters, 788, 136826. https://doi.org/10.1016/j.neulet.2022.136826
  • Memória, C. M., Yassuda, M. S., Nakano, E. Y., & Forlenza, O. V. (2014). Contributions of the computer-administered neuropsychological screen for mild cognitive impairment (CANS-MCI) for the diagnosis of MCI in Brazil. International Psychogeriatrics, 26(9), 1483–1491.https://doi.org/10.1017/S1041610214000726
  • Meng, F., & Xuan, B. (2023). Reliability and validity of the Chinese version of the Comprehensive Autistic Trait Inventory-Short Form (CATI-SF-C) in the general population. Asian Journal of Psychiatry, 84, 103580. https://doi.org/10.1016/j.ajp.2023.103580
  • Plichta, P., Tyburski, E., Bielecki, M., Mak, M., Kucharska-Mazur, J., Podwalski, P., Rek-Owodziń, K., Waszczuk, K., Sagan, L., Michalczyk, A., Misiak, B., & Samochowiec, J. (2023). Cognitive dysfunctions measured with the MCCB in deficit and non-deficit schizophrenia. Journal of Clinical Medicine, 12(6), 2257. https://doi.org/10.3390/jcm12062257
  • Rajji, T. K., Voineskos, A. N., Butters, M. A., Miranda, D., Arenovich, T., Menon, M., Ismail, Z., Kern, R. S., & Mulsant, B. H. (2013). Cognitive performance of individuals with schizophrenia across seven decades: A study using the MATRICS consensus cognitive battery. The American Journal of Geriatric Psychiatry, 21(2), 108–118. https://doi.org/10.1016/j.jagp.2012.10.011
  • Randolph, C., Tierney, M. C., Mohr, E., & Chase, T. N. (1998). The repeatable battery for the assessment of neuropsychological status (RBANS): Preliminary clinical validity. Journal of Clinical and Experimental Neuropsychology, 20(3), 310–319. https://doi.org/10.1076/jcen.20.3.310.823
  • Rizzolatti, G., & Craighero, L. (2004). The mirror-neuron system. Annual Review of Neuroscience, 36, 489–517. https://doi.org/10.1146/annurev.neuro.27.070203.144230
  • Shi, J., He, G., & Liu, X. (2018). Anomaly detection for key performance indicators through machine learning. 2018 International Conference on Network Infrastructure and Digital Content (IC-NIDC) (pp. 1–5). https://doi.org/10.1109/ICNIDC.2018.8525714
  • Shura, R. D., Brearly, T. W., Rowland, J. A., Martindale, S. L., Miskey, H. M., & Duff, K. (2018). RBANS validity indices: A systematic review and meta-analysis. Neuropsychology Review, 28(3), 269–284. https://doi.org/10.1007/s11065-018-9377-5
  • Silverberg, N. D., Wertheimer, J. C., & Fichtenberg, N. L. (2007). An effort index for the repeatable battery for the assessment of neuropsychological status (RBANS). The Clinical Neuropsychologist, 21(5), 841–854. https://doi.org/10.1080/13854040600850958
  • Sinclair, L. I., Ball, H. A., & Bolea-Alamanac, B. M. (2023). Does depression in mid-life predispose to greater cognitive decline in later life in the Whitehall II cohort? Journal of Affective Disorders, 351, 994–119. https://doi.org/10.1016/j.jad.2023.05.014
  • Sun, R., Ge, B., Wu, S., Li, H., & Lin, L. (2023). Optimal cut-off MoCA score for screening for mild cognitive impairment in elderly individuals in China: A systematic review and meta-analysis. Asian Journal of Psychiatry, 87, 103691. https://doi.org/10.1016/j.ajp.2023.103691
  • Tabachnick, B. G., & Fidell, L. S. (2007). Using multivariate statistics (5th ed., pp. xxvii–xx980). Allyn & Bacon/Pearson Education.
  • Terwee, C. B., Bot, S. D. M., de Boer, M. R., van der Windt, D. A. W. M., Knol, D. L., Dekker, J., Bouter, L. M., & de Vet, H. C. W. (2007). Quality criteria were proposed for measurement properties of health status questionnaires. Journal of Clinical Epidemiology, 60(1), 34–42. https://doi.org/10.1016/j.jclinepi.2006.03.012
  • Transcript of the Press Conference of the National Health Commission on August 25, 2022 (n.d.). Retrieved November 3, 2023, from http://www.nhc.gov.cn/xcs/s3574/202208/7a207303d09b4112836c27623f62c988.shtml
  • Ursenbach, J., O'Connell, M. E., Neiser, J., Tierney, M. C., Morgan, D., Kosteniuk, J., & Spiteri, R. J. (2019). Scoring algorithms for a computer-based cognitive screening tool: An illustrative example of overfitting machine learning approaches and the impact on estimates of classification accuracy. Psychological Assessment, 31(11), 1377–1382. https://doi.org/10.1037/pas0000764
  • Wu, Y., Zhang, Y., Yuan, X., Guo, J., & Gao, X. (2023). Influence of education level on MMSE and MoCA scores of elderly inpatients. Applied Neuropsychology. Adult, 30(4), 414–418. https://doi.org/10.1080/23279095.2021.1952588
  • Zhang, B. H., Tan, Y. L., Zhang, W. F., & Zhou, D. F. (2008). Reliability and validity of the repeatable battery for the assessment of neuropsychological status. The Chinese Journal of Mental Health, 22(12), 865–869.

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.