Reliability and validity of the Montreal Cognitive Assessment’s auditory items (MoCA-22)

Abstract

Objective: To evaluate the latent structure, internal consistency, convergent and discriminant validity, diagnostic accuracy, and criterion validity of the Montreal Cognitive Assessment’s auditory items (MoCA-22), which has previously been evaluated in small samples if at all. Methods: 11,284 participants completed the MoCA over 1–2 visits to an Alzheimer Disease Research Center (M_age = 69.2, M_education = 15.9, 57.6% women, 92.4% non-Hispanic white). MoCA-22 items were probed with alpha, omega, confirmatory factor analysis, and test-retest correlations. Scores were related to measures of neurocognition, daily functioning, behavioral-psychological symptoms (BPS), and vision performance for convergent-discriminant and criterion validity. Dementia stage was used to calculate area under the receiver operating characteristic (AUC-ROC) curves and cutoffs for mild cognitive impairment (MCI) and dementia. Results: A single-factor had good fit (CFI = .961; TLI = .945; RMSEA = .061; SRMR = .031), with good internal consistency (Omega total = .83) and test-retest consistency (ICC = .92 at 2.7 years). The strongest convergent correlations were with general cognition and executive functioning, while discriminant validity was demonstrated with its weakest and negative correlations being with BPS. There was strong classification accuracy in distinguishing MCI from normal cognition (AUC = .79; optimal cutoff point < 18), and mild-to-moderate dementia from MCI (AUC = .85; optimal cutoff point < 13). Furthermore, the MoCA-22 had negligible-to-small differences among those with and without vision limitations. Conclusions: These findings add to the evidence of the MoCA-22’s utility and it serves as a useful cognitive screening tool with sound reliability and validity.

Keywords:

• Montreal Cognitive Assessment (MoCA)
• Telephone-MoCA (T-MoCA)
• MoCA-Blind
• psychometrics
• reliability
• classification accuracy

Acknowledgements

We would like to thank Atash Sabet for assisting with a preliminary literature review.

Author contributions

A.R.L.—Conceptualization, Validation, Writing—original draft, Writing—review and editing; N.A.—Validation, Writing—original draft, Writing—review and editing; D.A.G—Conceptualization, Project administration, Supervision, Formal analysis, Writing—review and editing.

Disclosure statement

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

Additional information

Funding

The NACC database is funded by NIA/NIH Grant [U24 AG072122]. NACC data are contributed by the NIA-funded ADRCs: P30 AG062429 (PI James Brewer, MD, PhD), P30 AG066468 (PI Oscar Lopez, MD), P30 AG062421 (PI Bradley Hyman, MD, PhD), P30 AG066509 (PI Thomas Grabowski, MD), P30 AG066514 (PI Mary Sano, PhD), P30 AG066530 (PI Helena Chui, MD), P30 AG066507 (PI Marilyn Albert, PhD), P30 AG066444 (PI John Morris, MD), P30 AG066518 (PI Jeffrey Kaye, MD), P30 AG066512 (PI Thomas Wisniewski, MD), P30 AG066462 (PI Scott Small, MD), P30 AG072979 (PI David Wolk, MD), P30 AG072972 (PI Charles DeCarli, MD), P30 AG072976 (PI Andrew Saykin, PsyD), P30 AG072975 (PI David Bennett, MD), P30 AG072978 (PI Neil Kowall, MD), P30 AG072977 (PI Robert Vassar, PhD), P30 AG066519 (PI Frank LaFerla, PhD), P30 AG062677 (PI Ronald Petersen, MD, PhD), P30 AG079280 (PI Eric Reiman, MD), P30 AG062422 (PI Gil Rabinovici, MD), P30 AG066511 (PI Allan Levey, MD, PhD), P30 AG072946 (PI Linda Van Eldik, PhD), P30 AG062715 (PI Sanjay Asthana, MD, FRCP), P30 AG072973 (PI Russell Swerdlow, MD), P30 AG066506 (PI Todd Golde, MD, PhD), P30 AG066508 (PI Stephen Strittmatter, MD, PhD), P30 AG066515 (PI Victor Henderson, MD, MS), P30 AG072947 (PI Suzanne Craft, PhD), P30 AG072931 (PI Henry Paulson, MD, PhD), P30 AG066546 (PI Sudha Seshadri, MD), P20 AG068024 (PI Erik Roberson, MD, PhD), P20 AG068053 (PI Justin Miller, PhD), P20 AG068077 (PI Gary Rosenberg, MD), P20 AG068082 (PI Angela Jefferson, PhD), P30 AG072958 (PI Heather Whitson, MD), P30 AG072959 (PI James Leverenz, MD).