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RehabMeasures Instrument

Montreal Cognitive Assessment

Last Updated

Purpose

Rapid screen of cognitive abilities designed to detect mild cognitive dysfunction.

Link to Instrument

instrument details

Acronym MoCA

Area of Assessment

Cognition

Assessment Type

Performance Measure

Administration Mode

Paper & Pencil

Cost

Free

Cost Description

The paper forms are free. The app is 10 USD per month per rater.

CDE Status

Availability
Universities/Foundations/Health Professionals/Hospitals/Clinics/Public Health Institutes:
MoCA may be used, reproduced, and distributed, WITH prior written permission. The test should be made available free of charge.
Commercial Entity/Pharma sponsored research:
MoCA may be used, reproduced, and distributed, WITH prior written permission and Licensing Agreement. The test should be made available free of charge.
For additional information, please visit website: Montreal Cognitive Assessment.
Classification
Supplemental – Highly Recommended: Stroke (based on study type, disease stage and disease type), Epilepsy and Unruptured Cerebral Aneurysms and Subarachnoid Hemorrhage (SAH)
 
Supplemental: Huntington's Disease (HD), Mitochondrial Disease (Mito) and Parkinson's Disease (PD)

Diagnosis/Conditions

  • Cardiac Dysfunction
  • Parkinson's Disease + Neurologic Rehabilitation
  • Stroke Recovery

Key Descriptions

  • 16 items and 11 categories to assess multiple cognitive domains (e.g., visuo-spatial and executive functions, naming, memory, attention, language, abstraction, and orientation).
  • Visuo-spatial / Executive: Alternating trail making, (visuo-constructive skills with cube or other figure, viscuo-constructive skills with clock)
  • Naming: Animals
  • Memory: Introduce word list and delayed recall
  • Attention: Forward digit span, backward digit span, vigilance, serial 7's
  • Language: Sentence repetition and verbal fluency
  • Abstraction: Recognize similarity
  • Orientation: Recall place and date
  • Total possible total score = 30
  • Scoring criteria are provided for each category/item. Three different forms of the test are available to reduce likelihood of practice effects.
  • Test manual (directions, scoring instructions) and score sheets are available at website www.mocatest.org

Number of Items

16

Equipment Required

  • Score Sheet
  • Stop Watch
  • Pencil
  • Paper

Time to Administer

10 minutes

Required Training

Training Course

Required Training Description

As of September 1, 2019 completion of a training and certification program is required.

Age Ranges

Adult

18 - 64

years

Elderly Adult

+

years

Instrument Reviewers

Initially reviewed by Karen McCulloch, PT, PhD, NCS and the TBI Edge task force of the Neurology Section of the APTA in 10/2012; Erin Hussey, DPT, MS, NCS and the PD Edge task force of the Neurology Section of the APTA in 2013.

Brittany Christie, Darshana Patel, Korynna Pepin, and Jessica Walsh Occupational Therapy students at University of Illinois at Chicago in 2020.

Updated by Tri Pham, UNT, 2020.

ICF Domain

Body Structure
Body Function

Measurement Domain

Cognition

Professional Association Recommendation

Recommendations for use of the instrument from the Neurology Section of the American Physical Therapy Association’s Multiple Sclerosis Taskforce (MSEDGE), Parkinson’s Taskforce (PD EDGE), Spinal Cord Injury Taskforce (PD EDGE), Stroke Taskforce (StrokEDGE), Traumatic Brain Injury Taskforce (TBI EDGE), and Vestibular Taskforce (Vestibular EDGE) are listed below. These recommendations were developed by a panel of research and clinical experts using a modified Delphi process.

 

For detailed information about how recommendations were made, please visit:  http://www.neuropt.org/go/healthcare-professionals/neurology-section-outcome-measures-recommendations

 

Abbreviations:

 

HR

Highly Recommend

R

Recommend

LS / UR

Reasonable to use, but limited study in target group  / Unable to Recommend

NR

Not Recommended

 

Recommendations Based on Parkinson Disease Hoehn and Yahr stage: 

 

I

II

III

IV

V

PD EDGE

HR

HR

HR

HR

LS/UR

 

 

Recommendations based on level of care in which the assessment is taken:

 

Acute Care

Inpatient Rehabilitation

Skilled Nursing Facility

Outpatient

Rehabilitation

Home Health

TBI EDGE

NR

LS

NR

LS

NR

 

Recommendations for use based on ambulatory status after brain injury:

 

Completely Independent

Mildly dependant

Moderately Dependant

Severely Dependant

TBI EDGE

N/A

N/A

N/A

N/A

 

Recommendations for entry-level physical therapy education and use in research:

 

Students should learn to administer this tool? (Y/N)

Students should be exposed to tool? (Y/N)

Appropriate for use in intervention research studies? (Y/N)

Is additional research warranted for this tool (Y/N)

PD EDGE

Yes

Yes

Yes

Not reported

TBI EDGE

No

Yes

Yes

Not reported

Considerations

  • Chou et al, 2010 reported task force recommendation (based on review of 353 published articles) was to use MoCA over several other cognitive assessment screens (MMSE, MMP, PANDA, and SCOPA-cog) for detection of MCI in those with PD when cognition is not a primary outcome measure.
  • The MoCA has been extensively used and studied in older adult populations and in PD where cognitive impairment is problematic. 

  • This review is not exhaustive, but focused on initial development of the measure and its use with persons with stroke to determine possible appropriateness of the measure for use with TBI. 

  • The MoCA has a greater emphasis on attention and executive function than the MMSE that is commonly used to screen for cognitive impairments. 

  • For those with mild deficits, the MoCA appears to be more sensitive for those with high premorbid IQ, non-AD dementia and early stages of dementia. 

  • There are multiple parallel versions of the MoCA, an advantage when it might be used more than once with a partient. 

Do you see an error or have a suggestion for this instrument summary? Please e-mail us!

Alzheimer's Disease and Progressive Dementia

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Cut-Off Scores

Cut-off Scores

MCI and Dementia (Goldstein et al, 2014; N=81 African Americans; Normal Cognition (NC) n=38, mean age 65.8 (7.7), mean 13.4 (3.1) years of education 13.4; Mild Cognitive Impairment (MCI) n=38, mean age 71.9 (8.9), mean 10.9 (2.4) years of education; Dementia n=27, mean age 70.5 (11.4), mean 11.7 (2.2) years of education)

 

 

≤22

≤23

≤24

≤25

≤26

MCI

 

 

 

 

 

Sensitivity

74

84

95

100

100

Specificity

88

69

63

44

31

AUC

81

77

79

72

66

Dementia

 

 

 

 

 

Sensitivity

96

96

100

100

100

Specificity

88

69

63

44

31

AUC

92

83

81

72

66

 

  • When using the recommended MoCA cutoff score for impairment (26), the MoCA showed excellent sensitivity (100%) for identifying MCI or dementia. The cutoff score had low specificity (31%).
  • The cutoff score of 24 points on the MoCA showed good sensitivity for detecting MCI (95%); specificity improved slightly (63%).
  • A cutoff score of 22 points showed good sensitivity (96%) and specificity (88%).

 

Cut-off Scores:

Alzheimer’s Disease and Mild Cognitive Impairment (Lam et al, 2013; N=107; mean age 72 (10.3); mean 14.5 (3.8) years of education 14.5; Alzheimer’s Disease (AD) n=75; Mild Cognitive Impairment (MCI) n=32; mean MMSE score 24.9 (2.7); mean DRS score 124 (11.2))

  • Based on the results, the recommended Cut-off subscores for the MoCA included:
    • Memory: 7 or 8
    • Visuospatial: 3
    • Language: 4
    • Attention: 3
    • Executive: 4
  •  The memory (0.86, P<0.001), visuospatial ( 0.79, P<0.001), and executive (0.79, P<0.001) MoCA subscores showed good accuracy for identifying impairment. The language (0.70, P=0.001) and attention (0.72, P=0.001) MoCA subscores showed fair accuracy for impairment.

 A cutoff score of 7 for the memory domain shows good specificity (0.93), but lower sensitivity (0.59). A cutoff score of 8 shows lower specificity (0.43), but good sensitivity (0.91). Adjusting the cut-off by just 1 affects the sensitivity and specificity of the measure. The ideal cut-off will depend on the purpose of using the MoCA

Cognitive Impairment

(Nasreddine et al, 2005) 

  • A score of 26 or above is considered normal

  • For individuals with 12 years or fewer of formal education, one point is added to the score as a correction

Sensitivity and Specificity (%) MoCA and MMSE

 

 

 

Cut-off

>26

<26

<26

Group (n)

Normal Controls (90)

Mild Cognitive Impairment (94)

Alzheimer's Disease (93)

MoCA

87

90

100

MMSE

100

18

78

Cognitive Impairment

(Smith et al, 2007; From a population in a memory clinic: 32 subjects diagnosed with dementia; 23 subjects with mild cognitive impairment; 12 comparison subjects; mean age 73.6 (10) years; mean MMSE score at baseline 27.4 (1.6);mean MoCA score 22.3 (3.6)) 

 

Sensitivity (95% CI)

 

Specificity (95% CI)

 

Test

MMSE

MoCA

MMSE

MoCA

MCI

0.17 (0.08-0.34)

0.83 (0.66-0.92)

1.00 (0.82-1.0)

0.50 (0.29-0.72)

dementia

0.25 (0.15-0.39)

0.94 (0.83-0.98)

1.00 (0.82-1.00)

0.50 (0.29-0.72)

  • The MoCA had better sensitivity (100%) identifying subjects with MCI who were diagnosed with dementia at a six month followup, than the MMSE with sensitivity of 25%. 

 

Normative Data

Cognitive Impairment

(Nasreddine et al, 2005 and mocatest.org website)

MoCA Items Average Scores

 

 

 

 

NC

MCI

AD

Trails

0.87 (0.34)

0.56 (0.50)

0.27 (0.45)

Cube

0.71 (0.46)

0.46 (0.50)

0.25 (0.43)

Clock

2.65 (0.65)

2.16 (0.82)

1.56 (0.98)

Naming

2.88 (0.36)

2.64 (0.58)

2.19 (0.82)

Memory

3.73 (1.27)

1.17 (1.47)

0.52 (1.03)

Digit Span

1.82 (0.44)

1.83 (0.43)

1.49 (0.62)

Letter A

0.97 (0.18)

0.93 (0.26)

0.67 (0.47)

Serial 7

2.89 (0.41)

2.65 (0.65)

1.82 (1.12)

Sentence Rep

1.83 (0.37)

1.49 (0.71)

1.37 (0.80)

Fluency F

0.87 (0.34)

0.71 (0.45)

0.32 (0.47)

Abstraction

1.83 (0.43)

1.43 (0.68)

0.99 (0.80)

Orientation

5.99 (0.11)

5.52 (0.84)

3.92 (1.73)

Total*

27.37 (2.20)

22.12 (3.11)

16.16 (4.81)

*Total is adjusted for education

 

 

 

Test/Retest Reliability

Older adults with MCI and AD:

(Nasreddine et al, 2005; = 94 with MCI, mean age 75.2 (6.3) years; mean 12.28 (4.3) years of education; = 93 patients with AD, mean age = 76.7 (8.8) years; mean 10.03 (3.8) years of education; = 90 healthy controls; mean age 72.8 (7.0) years; mean 13.3 (3.4) years of education)

  • Excellent test retest reliability (= 0.92) with subgroup of 26 patients with cognitive impairment tested on average 35.0 (17.6) days apart

  • Mean change in scores =  0.9 + 2.5 points

Internal Consistency

Older adults with MCI and AD:

(Nasreddine et al, 2005)

  •  Excellent internal consistency (a = 0.83)

Criterion Validity (Predictive/Concurrent)

 

Concurrent Validity:

Alzheimer’s Disease and Mild Cognitive Impairment (Raolf et al, 2013)

  • Cut-off scores on the MMSE can be reliably compared with scores on the MoCA.
  • Researchers used equipercentile equating to find comparable scores between the MoCA and the MMSE, resulting in conversion scores.
  • Lower MoCA scores were associated with higher MMSE scores. For example, 20-21 on the MoCA is equivalent to 26 on the MMSE.

 

Concurrent Validity:

Alzheimer’s Disease and Mild Cognitive Impairment (Lam et al, 2013)

  • Excellent correlations between the MoCA total scores and the Dementia Rating Scale (correlation coefficient (r)=0.77, P<0.001).
  • Excellent correlations between the MoCA and the memory criterion measures (r=0.66, P<0.001).
  • There was a stronger association between the Dementia Rating Scale and the MoCA in comparison to the association between the Dementia Rating Scale and the Mini-Mental State Examination, which showed adequate correlations (r=0.57, P<0.001).
  • Results showed a moderate to strong correlations between the MoCA subscores and analogous domain-specific criterion measures:
    • Excellent correlations with the memory domain ( r=0.73 , P <.001).
    • Adequate correlations with the visuospatial domain (r=0.56, P<.001).
    • Adequate correlations with the language domain (r=0.46, P<.001).
    • Adequate correlations with the attention domain (r=0.51, P<.001).
    • Excellent correlations with the executive domain (r=0.60, P<.001).

Construct Validity

Convergent Validity:

Alzheimer’s Disease and Mild Cognitive Impairment (Lam et al, 2013)

  • Excellent convergent validity between the English MoCA and MMSE (r=0.66, P<0.001)

Older adults with MCI and AD:

(Nasreddine et al, 2005) 

  • Total scores and majority of items differentiated between known groups of healthy controls, individuals with MCI and AD 
  • All items differentiated between at least two of the groups

Face Validity

  • Was developed based on clinical intuition of first author and clinical testing over a five year period prior to validation study in 2005 (Nasreddine et al, 2005)

Parkinson's Disease

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Cut-Off Scores

Parkinson's Disease:

(Dalyrimple-Alford et al, 2010; = 114 PD and 47 controls; median duration PD motor symptoms 12.5, (1-30) years. 3 groups identified as PD-N (normal cognition, = 72, disease duration 4.6 (3.9), HY stage 1.9 (0.9)], PD-MCI (mild cognitive impairment, = 21, disease duration 7.3 (5.2), Mean HY 2.6 (0.9)]and PD-D [dementia, = 21, disease duration 12.6 (8.1); H&Y stage mean = 3.4 (0.8)]. 

  • MoCA screening cutoff for PD-MCI < 26/30 (SN 90%, SP 75%; AUC 90%; 95% CI 82-95%, NPV = 92%) 
  • MoCA best at differentiating PD-MCI
    • MoCA vs SCOPA-Cog (AUC difference of 12%, p < 0.05) 
    • MoCA vs MMSE-sevens (AUC difference 12%; p < 0.05) 
  • MoCA screening cutoff for PD-D = 21/30 (SN 81%, SP 95%, AUC 97%; 95% CI 92-99%, NPV = 95%) 
    • MoCA vs MMSE-world (AUC difference 10%, p < 0.05) 
    • MoCA, MMSE, and SCOPA-COG, All 3 accurately discriminated for PD-D without statistical distinction on ROC values between measures

(Hoops et al, 2009; = 132 with idiopathic PD; 75.8% male; 94.7% white; mean age 65.1 (9.7); PD duration 6.5 (5.3); Education level = 16.4 (3.1) years. 30% determined to have cognitive disorder using Dementia criteria: > 1.5 SD below normative mean in at least 2 of 4 cognitive domains, self-report of cognitive dysfunction, and cognition interfering with IADL. PD-Norm (= 92): H&Y stage 1: 50%, 2: 41.3% 3: 7.6% 4: 1.1%; GDS-15 3.0 (3.4), (= 40) PD-MCI and PD-D (= 40): H&Y stage 1 = 17.5%, 2 = 62.5%, 3 = 15.0%, 4 = 2.5%, 5 = 2.5%; GDS-15 score 4.3 (4.0). 

  • MoCA cutoff for any cognitive disorder (MCI or D) = 26/30 (sensitivity = 0.90, specificity = 0.53). PPV = 46; NPV = 92, and 64% accuracy. 
  • In comparison, cutoff for MMSE = 29/30 (SN 0.9, SP 0.38), PPV = 0.39 and 54% accuracy 

(Robben et al, 2010; = 41; Young group (< 66, = 22. PDD, = 5, HY stages [%]: 1 = 7, 2 = 12, 3 = 3) Older group (> 65, = 19, PDD = 10; HY stages [%]: 2 = 6, 3 = 6, 4 = 6, 5 = 1). Prospective study; Blinded examiner. Questionnaire, MoCA, FAB, ACE-R) 

  • MoCA cutoff for PD-Dementia = 22/30 for the older group. (SN 100%, SP 100%, AUC (95% CI) = 1.0 (1.0-1.0) and 23/30 for PDD young group (SN 80%, SP 88.2%, AUC (95% CI) = 0.81 (0.58-1.0). Scores on MoCA, FAB, and ACE-R significantly lower in PDD young group (MW U: p < 0.05) Scores on MoCA, FAB, and ACE-R significantly lower in PDD older group (MW-U: p < 0.01) 
  • MoCA did not show a false negative result but did take longer to administer (~16 min) than FAB and ACE-R. 
  • Recommended sequence: 1) questionnaire, if positive, follow-up with 2) Screening with MoCA or other screening measure, if positive, followup with 3) full Neuropsychologic Exam assessment battery

Normative Data

Parkinson Disease:

(Hoops et al, 2009)

  • PD norm = MoCA score 26.2 (2.9); MMSE score 28.7 (1.5), 
  • PD-MCI and PD-D = MoCA score 22.2 (4.1); MMSE score 26.8 (2.3)

(Gill et al, 2008; = 38 (17.5% female); mean age = 71.3 (10.5) yrs, Education 14.8 (3.1) yrs, , H&Y stage 2.9 (0.94), Schwab and England 79% (12), Symptom duration 6.6 (5.4) yrs, Geriatric Depression Scale 1.9 (1.3)) 

  • MoCA displays lower scores across progressive disease stages and wider range of scores than MMSE. Range of scores: 6-28 for MoCA, while MMSE range was 16-30
  • Mean MoCA score of 23.3 (2.1) was significantly lower than mean MMSE score of 27.4 (1.9) for this group (p < 0.01) 
    • HY Stages 1-2: Mean MoCA = 23.3 (4.1); MMSE = 27.6 (2.5) 
    • HY stage 3: mean MOCA = 21.2 (4.8) ; MMSE = 26.9 (3.5) 
    • HY stages 4-5: Mean MoCA = 19.9 (4.3); MMSE = 25.4 (3.0)

Test/Retest Reliability

Parkinson's Disease:

(Gill et al, 2008) 

  • Excellent test-retest reliability (= 8): ICC = 0.79 (95% CI: 0.36–1.2); Tested on average 133 days apart

Interrater/Intrarater Reliability

Parkinson's Disease: 

(Gill et al, 2008) 

  • Excellent interrater reliability (= 11): ICC = 0.81 (95%, CI: 0.41–1.2); tested on average 129 days apart

Criterion Validity (Predictive/Concurrent)

Parkinson's Disease: 

(Gill et al, 2008) 

  • Excellent correlation with neuropsychologic battery ICC = 0.72 (< 0.0001). Neuropsychology Battery included Hopkins Verbal Learning Test-Revised, the Letter Number Sequencing subtest of the Wechsler Adult Intelligence Scale, the Comalli–Kaplan adaptation of the Stroop, and the Phonemic and Category Verbal Fluency tests 
  • Excellent correlation between MMSE and MoCA ICC = 0.66 (< 0.0001)

Construct Validity

Parkinson's Disease: 

(Dalyrimple et al, 2010) 

  • Poor correlation with premorbid IQ (= 0.19; < 0.05) 

(Nazem et al, 2009): N = 100 with idiopathic PD (70% male, 96% white); Age 65.3 (11.5); Education level 15.7 (3.6) years; disease duration 7.7 (6.4) years; median Hoehn & Yahr stage = 2; mean GDS-15 score 3.4 (3.8) (26% showing clinically sig depression); evaluated “on” medication state; 19% with DBS; intact global cognition (MMSE > 25; in top 75th percentile when adjusted for age & education)

  • Despite normal MMSE scores (> 25), 52% scored positive for cognitive impairment on MoCA (< 26) indicating greater potential sensitivity of MoCA. 
  • Association between MoCA and UPDRS (Odds Ratio 1.07 (95% CI = 1.02–1.11) p = 0.006 was determined to be due to the motor items of the MoCA. 
  • Regression analysis demonstrated: Poor correlation MoCA (visuospatial and executive subscores) and UPDRS motor score (r = -0.14, p = 0.17)

Floor/Ceiling Effects

Ceiling Effects:

Parkinson’s Disease (Kletzel et al, 2017)

  • Poor: 37% of participants performed all items correctly indicating a large ceiling effect.

Parkinson's Disease: 

(Hoops et al, 2009) 

  • There was no ceiling effect for MoCA but there was ceiling effect for MMSE. MoCA results involved larger range of scores with 19-point spread (12-30) while the MMSE range was narrower at 9-point spread (22-30) 

(Zadikoff et al, 2008; = 88 (M: 62, F: 26); mean age = 65 +/-10 yrs; mean disease duration 9.5 (5) years; mean UPDRS III 20.7 (11.6); Education level identified for adjustment; Tested “on” med status; Tested using combined version of MoCA and MMSE using cutoff of 26 for each measure) 

  • MoCA demonstrated less of a ceiling effect when compared to the MMSE (when controlled for educational level). 
  • More subjects scored < 26 on MoCA than on MMSE (x= 22.5, < 000002) 
  • If subject scored > 25 on MoCA, they did not score < 26 on the MMSE. 
  • In contrast, 36% of those who scored >25 on MMSE had score of <26 on MoCA (< 0.0001)

Non-Specific Patient Population

back to Populations

Cut-Off Scores

Vascular cognitive impairment: (Koski, 2013)  

  • When using the originally published cut-off scores, the prevalence of cognitive impairment among individuals with cerebrovascular disease is greater when using the MoCA than the MMSE
  • For any impairment versus no impairment, the optimal cut-off score for the MoCA yielded a sensitivity of 0.72 and a specificity of 0.67
    • When discriminating between the MCI (CDR 0.5) and no impairment (CDR 0), sensitivity declined to 0.63, while specificity stayed at 0.67
  • In a total of 90 patients with mild-to-moderate stroke severity, a cut-off score of <24 was determined on the MoCA, resulting in a sensitivity of 0.88 and a specificity of 0.71 for detecting cognitive impairment (including dementia)
    • Lowering the cut-off score to <23 caused a specificity of 0.77 and lowered the sensitivity to 0.78
    • MMSE cut-off scores obtained comparable sensitivities and specificities to the MoCA
  • In 91 non-demented stroke or TIA patients, a cut-off score of <26 resulted in a sensitivity of 0.87 and a specificity of 0.63, while decreasing the cut-off score to <25 increased the specificity to 0.82 and reduced sensitivity to 0.77
    • With a cut-off score of <29 for the MMSE, the sensitivity was 0.77 and the specificity was 0.81
  • Optimal cut-off scores for detecting cognitive impairments tends to be lower when the MoCA is utilized in populations that include individuals with higher cognitive impairment

Chronic kidney disease: (Tiffin-Richards et al., 2014; chronic kidney disease patients undergoing hemodialysis (HD); n = 43; age = 58.3 years (patients) and 57.9 years (control); gender = 52.1% male (patients) and 47.6% male (control); education = 12.0 years (patients) and 13.0 years (control); time on dialysis = 4.0 hours)

  • An optimal cut-off score of ≤24 was identified for the MoCA, with a sensitivity of 76.7%, specificity of 78.6%, and AUC of 0.755 (95% CI, 0.602 – 0.872)
    • The optimal cut-off score of ≤24 points is lower than the cut-off score of ≤26 determined in populations of patients with Alzheimer’s disease and mild cognitive impairment (MCI).

Heart Disease

(Rossetti et al, 2011; n = 2653; mean age 50.03, range 18-85; sample from Dallas Heart Study incorporating multiple ethnicities: 25% Caucasian, 52% African-American, 11% Hispanic)

  • Suggests the cut-off score recommended by developers may be too low, since 62% of the sample would be classified with cognitive impairment even with points added based on years of education.

  • Normative values provided in study may be a better guide for performance especially for different ethnic backgrounds.

Normative Data

Normative sample:

(Rossetti et al, 2011) 

MoCA Score by Age and Education Level

 

 

 

 

 

 

 

 

 

Years of Education

 

 

 

 

 

 

 

 

<12

 

12

 

 

 

>12

 

 

 

Total by age

 

Age group, y

No.

Mean(SD)Median

No

Mean(SD)Median

No

Mean(SD)Median

No

 

Mean(SD)

<35

20

22.8(3.38)23

65

24.46(3.49)25

122

25.93(2.48)26

207

25.16(3.08)

30-40

37

22.84(3.18)23

106

23.99(2.93)24

264

25.81(2.64)26

408

25.07(2.95)

35-45

55

22.11(3.33)23

177

23.02(3.67)24

355

25.38(3.05)26

588

24.37(3.51)

40-50

77

21.36(3.73)22

227

22.26(3.94)23

418

25.09(3.16)26

723

23.80(3.80)

45-55

77

20.75(3.80)21

216

21.87(3.95)22

461

24.70(3.24)25

755

23.48(3.84)

50-60

62

19.94(4.34)20

172

22.25(3.46)22

424

24.34(3.38)25

659

23.37(3.78)

55-65

60

19.60(4.14)20

143

21.58(3.93)22

369

24.43(3.31)25

573

23.20(3.96)

60-70

57

19.30(3.79)19

113

20.89(4.50)21

246

24.32(3.04)25

418

22.69(4.12)

65-75

38

18.37(3.87)19

67

20.57(4.79)21

122

24.00(3.35)24

228

22.05(4.48)

70-80

14

16.07(3.17)17

23

20.35(4.91)20

42

23.60(3.47)24

79

21.32(4.78)

Total by education

230

20.55(4.04)21

608

22.34(3.97)23

1306

24.81(3.20)25

2148

23.65(3.84)

 

Test/Retest Reliability

Vascular cognitive impairment: (Koski, 2013)  

  • Excellent correlation between ischemic stroke patients with small vessel disease and controls tested two weeks apart (r=0.96)
  • Poor correlation in older persons from community or memory clinic-based populations due to longer test-retest intervals of 4-8 weeks (r=0.75-0.92)

Internal Consistency

Vascular cognitive impairment: (Koski, 2013)  

  • Moderate-to-high internal consistency 
    • Adequate internal consistency for small vessel disease (Cronbach’s alpha = 0.72)
    • Adequate internal consistency for mild subacute stroke patients undergoing rehab (Cronbach’s alpha = 0.78)
    • Excellent internal consistency for patients studied 3 months after a stroke (Cronbach’s alpha = 0.86)
    • Excellent internal consistency for patients with vascular dementia (Cronbach’s alpha = 0.83)
  • Positive correlation between individual MoCA subtests scores and the total MoCA score in individuals with vascular dementia
  • Coefficients ranged from poor 0.49 (memory) to excellent 0.78 (attention, concentration, and working memory)

Criterion Validity (Predictive/Concurrent)

Concurrent validity:

Chronic kidney disease

(Tiffin-Richards et al., 2014)

  • Adequate to excellent Correlation between the composite scores of the MoCA and the test battery in the memory (rs = .53, p<.001) and executive function (rs = .60, p<.001) domains.
  • Adequate positive correlation between the MoCA and MMSE total scores (rs = .54, p<.001).
  • No significant association between the attention, language, and visuospatial composites were exhibited.

Construct Validity

Discriminant validity:

Chronic kidney disease

(Tiffin-Richards et al., 2014)

  • Adequate association in the patient group between MoCA total score and age of HD patients (rs = -.38, p<.05).
  • Poor association between MoCA and education (rs = .28, p<.01).
  • Adequate correlation between the CCI score for HD patients and MoCA total scores (rs = -.53, p<.001).

Stroke

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Interrater/Intrarater Reliability

Interrater Reliability:

Stroke (Cumming et al, 2018)

  • Interrater reliability between original and blind scoring for the visuospatial/executive MoCA items was the following:
    • Almost Perfect for trail-making ( Kappa=0.94, 95% confidence interval [CI] 0.92-0.96)
    • Substantial for cube copy (Kappa=0.80, 95% CI 0.76-0.83)
    • Substantial for clock numbers (Kappa=0.67, 95% CI 0.62-0.73)
    • Moderate for clock hands (Kappa=0.46, 95% CI 0.42-0.51)
    • Moderate for clock contour (Kappa=0.49, 95% CI 0.40-0.58)

Internal Consistency

Subacute mild stroke

(Toglia et al, 2011; = 72; mean age 70 (17) years; 8.5 days post-stroke with mild neurological (NIHSS 4) and cognitive (MMSE median 25) deficits)

  • Excellent internal consistency (Chronbach’s alpha = 0.78)

  • Higher internal consistency than MMSE (a = 0.60)

Criterion Validity (Predictive/Concurrent)

Subacute mild stroke:

(Toglia et al, 2011)

  • Excellent correlation of MoCA with MMSE (= 0.79) and Cognitive FIM scores (= 0.67)

  • Adequate correlation with discharge status (= 0.40), which is higher than MMSE (r = 0.30)

  • Stronger relationship of MoCA scores to rate of functional improvement (formula using admission and discharge FIM scores, LOS) than the MMSE

  • MoCA visuoexecutive subscore was strongest predictor of functional status and improvement in FIM scores

Floor/Ceiling Effects

Subacute mild stroke:

(Toglia et al, 2011)

  • Identified more patients as having cognitive impairment than usual cutoff points for MMSE (89% vs. 63%)

  • Attributed to greater ceiling effects with MMSE

  • Mean scores for delayed recall, visuoexecutive and verbal fluency were all < 50% of maximum score

Older Adults and Geriatric Care

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Standard Error of Measurement (SEM)

Older Adults (Feeney, et al., 2016; n=130; participants aged 55 or older)

  • SEM of the MoCA was 1.5

Minimal Detectable Change (MDC)

Older Adults (Feeney, et al., 2016; n=130; participants aged 55 or older)

  • An individual score would have to change by greater than or equal to 4 points on the MoCA for the rater to be confident that the change was not due to measurement error.
  • 3.54 and 4.21 at the 90% and 95% level

Cut-Off Scores

Cut-Off Scores:

Older Adults (Carson, Leach, & Murphy, 2017; N= 304 articles; Mean age 75)

  • The cutoff of 23 optimally balanced sensitivity and specificity and provided the highest classification accuracy
    • overall sensitivity of .83 and specificity of .88
  • A MoCA cutoff score of 23, rather than the initially recommended score of 26, lowers the false positive rate and shows overall better diagnostic accuracy

Normative Data

Normative Data:

Older Adults (Malek-Ahmadi et al, 2015)

 

Normative Data based on age and education

 

 

 

Years of Education

 

 

≤12 Years

13-15 Years

≥16 Years

Age Range

 

 

 

70-79

25.25 (4.11)

n=4

27.78 (2.24)

n=27

27.59 (2.04)

n=22

80-89

23.47 (2.97)

n=15

25.08 (3.13)

n=40

25.82 (2.75)

n=34

90-99

23.00 (2.63)

n=14

23.35 (3.43)

n=26

24.61 (2.59)

n=23

Interrater/Intrarater Reliability

Older Adults (Feeney, et al., 2016; n=130; participants aged 55 or older)

  • Excellent reliability of 0.81

Mixed Populations

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Cut-Off Scores

Cardiovascular sample: (McLennan et al., 2011; n = 110; mean age = 67.9 (11.7) years; gender = 40% (44) male; education = 10.5 (3.2) years)

  • The recommended cut-off score was <26.

 

Amnestic MCI

Multiple-Domain MCI

MoCA Cut-Off Score

Sensitivity

Specificity

Sensitivity

Specificity

<22

66.7%

70.8%

75.0%

75.3%

<23

66.7%

62.3%

75.0%

66.3%

<24

100.0%

50.0%

83.3%

52.0%

<25

100.0%

39.6%

83.3%

40.8%

<26

100.0%

29.2%

83.3%

29.6%

<27

100.0%

18.9%

91.7%

19.4%

<28

100.0%

8.5%

91.7%

8.2%

 

HIV: (Fazeli et al, 2017; n = 100; mean age = 58.2(6.5) years; sex = 88% male; education = 14.3 (2.6) years; race = 82% white)

  • The receiver operating characteristic (ROC) analysis for the MoCA determined the cut-off score of ≤26. This is the most optimal balance of sensitivity (84.21%) and specificity (55.81%) (AUC = 70.42 (95% CI = -0.49 to -0.14, p<.01)).
  • The ROC yielded the same cut-off score of ≤26 in a sample 84 participants without severe contributing neuromedical comorbidities, determining a sensitivity of 86.36% and specificity of 57.50% (AUC = 71.19 (95% CI = -0.52 to -0.14, p<.01)).

Internal Consistency

Cardiovascular sample: (McLennan et al., 2011; n = 110)

  • Poor Cronbach’s alpha was 0.55

Criterion Validity (Predictive/Concurrent)

Predictive Validity

HIV: (Fazeli et al, 2017)

  • Poor correlation with IADL declines (r = -0.29), Karnofsky score (r = 0.28), and reported cognitive symptoms (r = 0.28).
  • Poor correlation with current depressive symptoms (r = -0.04, p = .72)

Construct Validity

Convergent Validity

Cardiovascular sample  (McLennan et al., 2011)

  • Moderate positive correlation between the MoCA and the Neuropsychological Assessment Battery Screening Module (NAB-SM) global score (p=0.49, P<0.001)
  • Moderate positive correlation between the MoCA and each of the Neuropsychological Assessment Battery Screening Module (NAB-SM) domain scores: attention (rs = .34, P < .001); memory (rs .25, P=.007); spatial (rs = .48, P < .001); and executive (rs = .41, P < .001)

HIV: (Fazeli et al, 2017)

  • Adequate correlations with the following domains of neurocognitive performances: verbal (r = -0.34), working memory (r = -0.38), executive functions (r = -0.49), learning (r = -0.39), speed of information processing (r = -0.31), and global (r = -0.44).
  • Poor correlation with the domain of neurocognitive performance: motor (r = -0.11)
  • Adequate correlation with education levels (r = 0.35)

Neuromuscular Conditions

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Cut-Off Scores

Huntington’s disease (Bezdicek et al., 2013; n = 20 (HD) and 23 (normal control (NC)); gender = 12 males, 8 females (HD) and 12 males, 11 females (NC))

  • The optimal cut-off score was 25/26, with a sensitivity of 0.94 and a specificity of 0.84 (PPV = 0.81, NPV – 0.95) for 3 measures: optimal diagnostic cut-off, optimal screening cut-off, and point of maximal combined sensitivity and specificity

Internal Consistency

Huntington’s disease: (Bezdicek et al., 2013; n = 20 (HD) and 23 (normal control (NC)); gender = 12 males, 8 females (HD) and 12 males, 11 females (NC))

  • Adequate internal consistency for seven subtests of MoCA for 20 HD patients (Cronbach’s alpha = .82) and 23 controls (Cronbach’s alpha = .56)

Criterion Validity (Predictive/Concurrent)

Concurrent validity:

Huntington’s disease

  • Modest-to-strong correlations between the MoCA and other measures of cognitive functioning (Bezdicek et al., 2013)
    • Excellent correlation between visuospatial/executive and Rey Complex Figure Test (RCFT) Immediate Recall (r=.64)
    • Poor correlation between naming and Rey Complex Figure Test (RCFT) Immediate Recall (r=.30)
    • Excellent correlation between attention and free recall from Free and Cued Selective Reminding Test (FCSRT) (r=.63)
    • Excellent correlation between language and Controlled Oral Word Association Test (COWAT) (r=.81)
    • Excellent correlation between abstraction and Controlled Oral Word Association Test (COWAT) (r=.62)
    • Excellent correlation between delayed recall and Symbol-Digit Modalities Test (SDMT) (r=.72)
    • Adequate correlation between orientation and Symbol-Digit Modalities Test (SDMT) (r=.47)

Construct Validity

Discriminant Validity:

Huntington’s Disease

  • Excellent AUC (95%) was 0.90 (0.809-0.997), p<.001 for the MoCA in comparison with the brief cognitive battery(Bezdicek et al., 2013)

Mental Health

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Cut-Off Scores

Cutoff Scores:

Schizophrenia (Yang et al, 2018; N=64 with schizophrenia; Aged 16-65; Mean 13.58 (2.72) years of education; Mean 9.10 (7.29) duration of iIlness; Mean 12.86 (6.85) duration of psychiatric treatment)

  • For severe cognitive impairments, the optimal MoCA cut-off score was <23. AUC for the MoCA was 0.814 (95% CI=0.710-0.918, p<0.001)
  • For mild cognitive impairments, the optimal MoCA cut-off score was <25. AUC for the MoCA was 0.816 (95% CI=0.698-0.934, p<0.001).

 

Substance Use Disorder (Bruijnen et al., 2018; n = 82; mean age = 44.1; gender = 68.3% male; primary substance abuse problem = alcohol (70.7%); 54.9% had neurocognitive disorder)

  • AUC value of .676 was found and an optimal cut-off score of 24 resulted in a sensitivity of .56 and a specificity of .62 (PPV = 64.1% and NPV = 53.5%)
    • 39 out of 82 patients were classified as having a NCD when using this cut-off score
  • AUC value of .745 was found and an optimal cut-off score of 25 resulted in a sensitivity of .67 and a specificity of .73 (PPV = 75.0% and NPV = 64.3%)
    • 40 out of 82 patients were classified as having NCD when using this cut-off score

 

Substance Use Disorder (Ewert et al., 2017; n=56; 31 with cognitive impairment and 25 without; mean age= 49.5; gender= 40 men, 16 women)

Using the 1‐point correction for education level increases the cutoff score by 1 point, it is suggested that the uncorrected score be used with the usual cutoff, that is, 26

Criterion Validity (Predictive/Concurrent)

Concurrent Validity:

Schizophrenia (Yang et al, 2018)

  • Excellent correlations between the MoCA adjusted total score and the Brief Assessment of Cognition in Schizophrenia composite Z-score (r=0.61, p<0.001).
  • Adequate correlations between the MoCA and the Z-scores of five Brief Assessment of Cognition in Schizophrenia subscales:
    • Adequate correlations with the Verbal Memory subscale (r=.44, p<0.001).
    • Adequate correlations with the Digit Sequencing subscale (r = .57, p < .001).
    • Adequate correlations with the  Semantic Fluency subscale (r = .47, p < .001).
    • Adequate correlations with the  Symbol Coding subscale (r = .35, p = .004).
    • Adequate correlations with the Tower of London subscale (r = .45, p < .001).
  • Adequate correlations between the adjusted MoCA total score and the Brief UCSD Performance-based Skills Assessment (r(60)=0.51, p<0.001).

Concurrent validity:

Substance Use Disorder (Bruijnen et al., 2018)

  • Significant correlations between performance on the MoCA and NPA at baseline
    • Poor correlation for executive functioning (r=.238, p=.032)
    • Poor correlation for abstract reasoning (r=.300, p=.006),
    • Adequate correlation for memory (r=.423, p<.001)
  • Near perfect correlation between performance on the MoCA and NPA at follow-up
    • Significant correlation between all MoCA domain and corresponding NPA domains
      • Adequate correlation for executive functioning: r=.328, p=.003
      • Poor correlation for visuospatial abilities: r=.241, p=.029
      • Adequate correlation for attention: r=.396, p<.001
      • Adequate correlation for abstract reasoning: r=.542, p<.001
      • Adequate correlation for memory: r=.455, p<.001
      • Poor correlation for orientation: r=.229, p=.043

Predictive validity:

Substance Use Disorder (Bruijnen et al., 2018)

  • During baseline and follow-up, patients with a NCD performed significantly worse on the MoCA than patients without a NCD
    • Similar results were found for the executive functioning domain on the MoCA (p=.003; p=.009)
    • Performance on the memory domain on the MoCA was significant at baseline between both groups (p=.014; p=.073)
    • Performance on the language and abstract reasoning domains on the MoCA were significantly different between both groups at follow-up (p=.984; p=.043 & p=.423; p=.010)
  • Performances on other domains on the MoCA did not differ significantly between both patient groups

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