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Mini-Mental State Examination

Mini-Mental State Examination

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Purpose

The MMSE is a brief screening tool that provides a quantitative assessment of cognitive impairment and to record cognitive changes over time.

Acronym MMSE

Area of Assessment

Activities of Daily Living
Cognition

Assessment Type

Observer

Administration Mode

Paper & Pencil

Cost

Not Free

Cost Description

The MMSE-1 is freely available on the Internet. The current version of the MMSE (MMSE-2) is owned by Psychological Assessment Resources (PAR)

Diagnosis/Conditions

  • Brain Injury Recovery
  • Cardiac Dysfunction
  • Parkinson's Disease & Movement Disorders
  • Stroke Recovery

Key Descriptions

  • The MMSE consists of 11 simple questions or tasks grouped into 7 cognitive domains:
    1) Orientation to time
    2) Orientation to place
    3) Registration of three words
    4) Attention and calculation
    5) Recall of three words
    6) Language
    7) Visual construction
  • A possible score of 30 is used to provide a picture of an individual's present cognitive performance based on direct observation of completion of test items/tasks.
  • A score of < 24 is the generally an accepted cutoff indicating the presence of cognitive impairment (Dick et al., 1984).
  • Levels of impairment have been classified as (Tombaugh & McIntyre, 1992):
    None: score = 24-30
    Mild: score = 18-24
    Severe: score = 0-17

Number of Items

11

Equipment Required

  • Score sheet that demonstrates figure to copy
  • Writing instrument

Time to Administer

Less than 10 minutes

Required Training

No Training

Age Ranges

Adult

18 - 64

years

Elderly Adult

65 +

years

Instrument Reviewers

Initially reviewed by Jason Raad, MS and the Rehabilitation Measures Team in 2010; Updated with references for the PD population by Lily Dawson, SPT and Erik Sokolowski, SPT in 2011; Updated by Karen McCulloch, PT, PhD, NCS and the TBI EDGE task force of the Neurology Section of the APTA in 2012; Updated with references for Alzheimer's Disease, Dementia, Parkinson's Disease, and stroke by Joe Frjelich, SPT, Michael Santa Maria, SPT, and Jordan Miller, SPT in 11/2012; Reviewed for PD by Rosemary Gallagher, PR, DPT, GCs and the PD EDGE Taskforce fo the neurology Section of the APTA in 2013.

Updated in 2019 by Alexandra Garcia, OTS; Asha Rao, OTS; Mariana Reyes, OTS; and Yarelly Velazquez, OTS from the University of Illinois at Chicago

Updated in July 2020 by Tri Pham, UT Southwestern Medical School

ICF Domain

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:  

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

LS/UR

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

NR

NR

NR

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

No

No

Yes

Not reported

TBI EDGE

No

No

No

Not reported

Considerations

  • MMSE is more prone to ceiling effects than the MoCA and may therefore may not be as sensitive to mild cognitive impairment in PD (Zadikoff et al, 2007)

  • When used alone the MMSE is limited in its ability to detect dementia, but can be significantly improved by the addition of a short evaluation of memory, executive function and IADL (Dujardin et al, 2010)

  • Order of administration of the MMSE and MoCA did not affect test performance (MMSE: t = -0.03, degrees of freedonm(df) = 0.98, P = 0.79) and (MoCA t-1.8, df = 98, P = 0.07). (Nazem et al 2009)

  • The MMSE has been criticized as suffering from "low reliability, too many easy items, too many cutoff points, and a lack of standardized scores" (Lopez et al, 2005)

  • Physical impairment can interfere with interpretation of the measure if not properly noted
  • Age, education, cultural and socioeconomic background (but NOT gender) can result in biased MMSE scores
  • Not sensitive to change in patients with severe dementia so it should not be used by itself as a diagnostic tool
  • Mean MMSE scores are highly correlated with baseline age and education attainment (Jacqmin-Gadda, 1997)
  • Review of stroke related outcome measures (Salter et al, 2005)
  • Prior research has cautioned that the MMSE may have low sensitivity among patients with:
    • Mild cognitive impairment
    • Right-sided lesions "within a general neurological patient population"
    • Stroke
  • If you need to administer over the telephone, you can use the Telephone Interview for Cognitive Status (TICS) over the MSSE (Fong et al, 2009)

 

Parkinson’s Disease:

(Hoops et al, 2009; = 132, mean age no disorder = 63.9(9.7), mean age PDD = 68.1 (9.2), Parkinson's Disease)

  • The optimal screening cutoff point for detection of any cognitive disorder for the MoCA had greater specificity (0.53), PPV (0.46), and percent correctly diagnosed (64%) than the optimal MMSE screening cutoff point (specificity = 0.38; PPV = 0.39; percent correctly diagnosed = 54%).

 

Stroke:

(Toglia et al, 2011; n = 72; mean age = 70 (17.0) years; mean time post CVA = 8.5 days, Stroke)

  • The MMSE classi?ed fewer patients as having cognitive de?cits than the MoCA
  • Sixty-seven percent of persons who scored at or higher than a conservative cutoff of 27 on the MMSE scored abnormally on the MoCA. None of the patients with a score less than 27 on the MMSE scored at or higher than the cutoff value of 26 on the MoCA

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Alzheimer's Disease and Progressive Dementia

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Standard Error of Measurement (SEM)

础濒锄丑别颈尘别谤’蝉/顿别尘别苍迟颈补:

(Ashford, J.W., Schmitt, F.A., 2001 ; n = 981, Alzheimer’s/Dementia)

  • As the severity of dementia increases, the standard error of measurement begins to decreases exponentially until 5 years and increases exponentially after 5 years. 

 

 

Minimally Clinically Important Difference (MCID)

Alzheimer’s and Dementia: (Andrews et al, 2019); n=19,566 (normal cognition=8,404; MCI-Alzheimer’s Disease=2,815; mild AD dementia=3,163; moderate-to-severe AD dementia=1,509; remaining 3,675 did not meet criteria for cohorts)

  • Across participants whose cognitive ability ranged from normal to moderate-severe AD dementia (n=15,891), on average, a 1-3 point decrease in MMSE was indicative of a meaningful decline.

Cut-Off Scores

Dementia: (Mitchell, 2009); 39 studies reviewed (dementia=34; MCI=5)

  • Most commonly favored cutoff score for dementia was 23v24 (n=18)

Normative Data

础濒锄丑别颈尘别谤’蝉/顿别尘别苍迟颈补:

(Brugnolo, A., Nobili, F. et al, 2009); n = 524; mean age = 78.02 (6.07) years, Alzheimer's Disease/Dementia)

The main features of the 524 AD patients in our study pool

 

 

 

 

MMSE Score

Number

Females n (%)

Age (years) Mean(SD)

29

9

6 (66.7)

76.00 (4.03)

28

17

4 (23.5)

78.47 (5.07)

27

26

17 (65.4)

76.46 (6.76)

26

26

19 (73.1)

76.92 (4.73)

25

36

19 (52.8)

76.19(5.32)

24

38

24 (63.2)

77.84 (6.58)

23

42

29 (69.1)

76.31 (8.82)

22

49

37 (75.5)

78.31 (5.98)

21

23

18 (78.3)

78.91 (9.38)

20

34

25 (73.5)

78.38 (6.44)

19

35

25 (71.4)

80.06 (5.46)

18

30

23 (76.7)

78.57 (4.78)

17

18

11 (61.1)

78.94 (4.90)

16

30

23 (76.7)

78.57 (4.78)

15

25

18 (72.0)

76.40 (7.24)

14

30

22 (73.3)

78.37 (6.05)

13

18

11 (61.1)

78.78 (7.20)

12

13

10 (76.9)

78.54 (6.76)

11

11

8 (72.7)

79.55 (5.64)

10

12

9 (75.0)

78.61 (6.97)

Internal Consistency

Alzheimer’s and Dementia: (Mougias et al., 2018); n=210 (AD=114; VaD=24; other/not-specified dementias=63); mean age=81.48±7.06 years

  • Excellent internal consistency: Cronbach’s alpha 0.76

Criterion Validity (Predictive/Concurrent)

础濒锄丑别颈尘别谤’蝉/顿别尘别苍迟颈补:

(Freidl et al, 1996; n = 1947; ages 50-80 years; mean time post CVA = 8.5 days, Alzheimer’s/Dementia)

  • The MMSE showed poor concurrent validity when compared to the Mattis Dementia Rating Scale (MDRS) (r = 0.29, p = 0.000)

Alzheimer’s and Dementia: (Mougias et al., 2018)

  • Comparison of the SMMSE and MMSE showed excellent concurrent validity (r =0.820; p<0.001)

Construct Validity

Convergent Validity:

Alzheimer’s and Dementia: (Mougias et al., 2018)

  • Excellent convergent validity between MMSE and Global Deterioration Scale (r = -0.671)

 

Dementia: (Trzepacz et al., 2015; n = 100)

  • Excellent convergent validity between MMSE and MOCA (r = 0.86)

 

Discrminant Validity

Alzheimer’s and Dementia: (Mougias et al., 2018)

  • Adequate discriminant validity between MMSE and Katz Activities of Daily Living (r = 0.465)

Floor/Ceiling Effects

Alzheimer’s and Dementia: (Mougias et al., 2018)

Poor floor effects: To evaluate floor effect, a variance index was calculated for the three groups, divided based on severity of cognitive decline as classified by MMSE scores. Group 1 (n=61; MMSE=0-6) and group 3 (n=37; MMSE=17-22) had the lowest variance index, (3.77 and 2.38). When considering the percentage of participants who scored into 0-6 (lowest MMSE quartile), 29% achieved these scores on the MMSE, indicating poor floor effects.

Responsiveness

“Our findings reflect an inherent limitation of the MMSE to detect longitudinal changes in short‐term intervals in patients with severe dementia, which has been also reported even in long‐term intervals when functional decline is examined.” (Mougias et al., 2018)

Older Adults and Geriatric Care

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Standard Error of Measurement (SEM)

Non-demented older adults:

(Jacqmin-Gadda, 1997; n = 2,537; mean age of participants = 74.4 (6.8) years, Non-demented older adults) 

  • For patients aged 65 at initial assessment: SEM = 2.4 points at baseline and 2.0 points at 1, 3 and 5 years 
  • For patients aged 85 at initial assessment: SEM = 3.5 points at baseline and 3.2 at year 1; 3.3 year 3 and 3.4 at year 5

Middle Aged and Older Adults  (Feeney, Savva, O’Regan, King-Kallimanis, Cronin & Kenny, 2016; n= 128; median age= 71)

  • SEM for entire group (n=128): 1.02

Minimal Detectable Change (MDC)

Community Dwelling Older Adults:

(Rockwood et al, 2008; n = 3255; all participants older than 65 years; version = Modified MMSE (3MS), Community Dwelling Older Adults)

  • 5 point change (or less) over a 5 to 10 year period

Middle Aged and Older Adults  (Feeney et al., 2016)

  • MDC for entire group (n=128): 2.38 (90%); 2.84 (95%)

Cut-Off Scores

Elderly Patients:

(Lopez et al, 2005; n = 418, mean age = 77.73 (6.89) years; mean education = 12.53 (3.20) years; all patients were being screened for cognitive deficits, Elderly Patients)

  • Lopez suggests that MMSE score should only be used to make one of two conclusions:
    • “needs no further evaluation” 
    • “needs a more extensive examination to determine if cognitive deficits exist

 

Cut-off scores suggested by prior research:

(Lopez et al, 2005)

  • ≥ 24 = no impairment
  • 18-23 = mild impairment
  • ≤ 17 = severe impairment
  • ≥ 27 = no impairment
  • 21–26 = mild impairment
  • 11–20 = moderate impairment
  • ≤ 10 = severe impairment
  • < 23 is generally accepted as indicating cognitive impairment and was associated with the diagnosis of dementia in at least 79% of cases (Lancu & Olmer, 2006)

Several sources of bias are known to exist with MMSE including: age, education, cultural and socioeconomic background. Various adjustments to MMSE scores have been suggested. (Mungas et al., 1996, n = 2983 individuals evaluated for possible dementia) For Hispanic individuals, a formula is MMSAdj = Raw MMS - (0.471 X [Education-12]) + (0.131 * [Age-70])

(Pedraza et al., 2011; n=3254 adults, 2819 Caucasian and 435 African-American, mean age 76.4 (7.3) years including 2048 cognitively normal and 1206 with some form of dementia)

  • African American older adults had lower levels of education and significantly lower MMSE scores. A cut score of 23/24 was recommended for African-Americans to maximize classification accuracy (.96), with 92% sensitivity and 98% specificity.
  • Attempts to identify an ideal cut point for patients with stroke have not been successful (Blake et al, 2002)

Mixed Population: (Tsai, Chen, Chu, Yang, Chung, Liao & Chou & 2016; n= 140; age range= 65 or older; MCI (59), Dementia (57), normal cognitive functioning (26));

  • Optimal cutoff score for MCI and dementia were 27 and 24 respectively

 

Mixed Population: (Boban et al., 2012) n=344; age range= 45 or older; MCI or dementia (127), cognitively healthy without neurological and psychiatric disorders (217)

  • An ideal cut off score to indicate a cognitively healthy individual without MCI and/or dementia was 26/27 within a general population. In the population ≥ 65 years, the cut-off score is 24/25. A higher cut-off score of 26/27 should be used for highly educated persons (≥ 14 years of education + ≥65 years)

Normative Data

Norms for the MMSE and 3MS:

(Bravo & Herbert, 1997; n = 7754; mean age = 74.9 (6.8) years; 97.9% community dwelling, 2.1% institutionalized)

MMSE and 3MS norms by years of education:

 

 

 

 

 

 

 

 

 

 

 

Education (yrs)

65-69

 

70-74

 

75-79

 

80-84

 

85 and over

 

 

n

mean (SD)

n

mean (SD)

n

mean (SD)

n

mean (SD)

n

mean (SD

0-4

78

25.7 (3.4)

85

25.7 (2.7)

93

25.4 (1.9)

78

24.5 (2.8)

65

24.3 (2.6)

5-8

495

26.9 (2.8)

422

27.0 (2.5)

556

26.4 (2.0)

277

25.8 (2.0)

239

25.2 (1.8)

9-12

942

27.9 (2.2)

752

27.7 (2.1)

921

27.3 (1.5)

455

26.8 (1.7)

332

26.2 (1.4)

> 13

581

28.4 (1.9)

375

28.2 (2.0)

535

27.7 (1.8)

236

27.3 (1.7)

208

26.9 (1.3)

All

2098

27.7 (2.5)

1638

27.5 (2.3)

2112

27.1 (1.8)

1051

26.5 (2.0)

853

25.9 (1.8)

3MS

 

 

 

 

 

 

 

 

 

 

0-4

78

82.0 (8.7)

85

82.6 (7.5)

93

81.0 (5.4)

78

79.6 (8.1)

65

77.0 (8.8)

5-8

495

87.1 (7.7)

422

87.1 (8.1)

556

85.7 (5.8)

277

84.0 (6.0)

239

82.6 (5.1)

9-12

942

91.7 (6.5)

752

90.7 (6.3)

921

89.8 (4.7)

455

87.5 (5.1)

332

85.6 (4.3)

> 13

581

93.9 (5.7)

375

92.9 (6.4)

535

91.3 (5.2)

236

89.8 (5.3)

208

88.0 (4.2)

All

2098

90.9 (7.6)

1638

89.9 (7.6)

2112

88.6 (5.7)

1051

86.5 (6.2)

853

84.5 (5.5)

 

MMSE Score Pre & Post Rehab:

(Ozdemir et al, 2001; n = 43; mean age = 60.49 (8.1) years; mean rehab = 64.09 (18.27) days)

  • Before Rehab: MMSE mean = 18.95; SD = 6.49 
  • After Rehab MMSE mean = 22.79; SD = 5.46

 

Community Dwelling Older Adults:

(Andrew et al, 2008; version = Modified MMSE (3MS), Community Dwelling Older Adults)

  • Longitudinal Modified MMSE scores:

    • 1 year mean = 90.4 (6.9)

    • 5 year mean = 89.1 (8.2)

    • 10 year mean = 85.8 (13.0) 

 

Non-demented Older Adults:

(Jacqmin-Gadda, 1997, Non-demented Older Adults)

  • Mean MMSE score = 26.1 (3.1) points

  • 20.2% had an MMSE score < 24 points

 

Participants 75 and Older:

(Aguero-Torres et al, 1998; n = 1745, Sweedish sample, Participants 75 and Older)

MMSE Norms by Diagnosis: 

 

 

 

 

Disease

n

Mean (SD) age

MMSE Mean (SD) Score

Dementia (Yes)

210

84.9 (5.5)

12.6 (8.2)

Dementia (No)

1535

81.2 (4.7)

26.8 (3.3)

Heart Disease (Yes)

305

83.0 (5.3)

22.8 (7.2)

Heart Disease (No)

1440

81.4 (4.8)

25.0 (7.2)

Cancer (Yes)

206

81.6 (5.1)

24.3 (6.2)

Cancer (No)

1539

81.6 (4.9)

24.7 (6.1)

Hip Fracture (Yes)

190

84.9 (5.3)

19.0 (9.7)

Hip Fracture (Yes)

1555

81.2 (4.7)

25.3 (5.2)

 

Interrater/Intrarater Reliability

Older Adults:

(Molloy and Standish, 1997; n = 48 participants recruited from a nursing home and chronic care facility, assessed 3 times with 1 week intervals between testing -- age not reported, Older Adults)

  • Adequate Interrater reliability (ICC = 0.69)

Middle Aged and Older Adults (Feeney et al., 2016)

  • Excellent inter-/intra-rater reliability (ICC=0.75)

Criterion Validity (Predictive/Concurrent)

Community-Dwelling Patients (Brodaty et al., 2002; n = 283. Those >75 were included regardless of cognitive status. Subjects aged 50-74 had to have memory problems, but no existing diagnosis of depression or delirium)

  • Adequate predictive validity for dementia (area under the curve of ROC was 0.85)

 

Community-Based Black Individuals: (Callahan et al., 2002; n = 344)

  • Adequate predictive validity for cognitive impairment (area under the curve of the ROC was 0.85)
  • Excellent predictive validity for dementia (area under the curve of the ROC was 0.96)

 

Referrals from Alzheimer Disease Center (Callahan et al., 2002; n = 651)

  • Excellent predictive validity for cognitive impairment (area under the curve of the ROC was 0.93)
  • Excellent predictive validity for dementia (area under the curve of the ROC was 0.95)

Construct Validity

Convergent Validity

MCI Patients: (Trzepacz et al., 2015; n = 299)

·&苍产蝉辫;&苍产蝉辫;&苍产蝉辫;&苍产蝉辫;&苍产蝉辫;&苍产蝉辫;&苍产蝉辫;&苍产蝉辫; Excellent convergent validity between MMSE and MOCA (r = 0.60)

Healthy Controls: (Trzepacz et al., 2015; n = 219)

·&苍产蝉辫;&苍产蝉辫;&苍产蝉辫;&苍产蝉辫;&苍产蝉辫;&苍产蝉辫;&苍产蝉辫;&苍产蝉辫; Adequate convergent validity between MMSE and MOCA (r = 0.43)

Mixed Population: (Trzepacz et al., 2015; n = 618. Of this 618, n = 219 healthy controls, n = 299 MCI, and n = 100 dementia)

·&苍产蝉辫;&苍产蝉辫;&苍产蝉辫;&苍产蝉辫;&苍产蝉辫;&苍产蝉辫;&苍产蝉辫;&苍产蝉辫; Excellent convergent validity between MMSE and MOCA (r = 0.84)

Community-Dwelling Patients (Brodaty et al., 2002; n = 283. Those >75 were included regardless of cognitive status. Subjects aged 50-74 had to have memory problems, but no existing diagnosis of depression or delirium)

·&苍产蝉辫;&苍产蝉辫;&苍产蝉辫;&苍产蝉辫;&苍产蝉辫;&苍产蝉辫;&苍产蝉辫;&苍产蝉辫; Excellent convergent validity between MMSE and GPCOG patient section (r = 0.683)

Community-Based Black Individuals: (Callahan et al., 2002; n = 344)

·&苍产蝉辫;&苍产蝉辫;&苍产蝉辫;&苍产蝉辫;&苍产蝉辫;&苍产蝉辫;&苍产蝉辫;&苍产蝉辫; Excellent convergent validity between MMSE and number of errors on Six-Item Screener (r = 0.77)

Referrals from Alzheimer Disease Center (Callahan et al., 2002; n = 651)

·&苍产蝉辫;&苍产蝉辫;&苍产蝉辫;&苍产蝉辫;&苍产蝉辫;&苍产蝉辫;&苍产蝉辫;&苍产蝉辫; Excellent convergent validity between MMSE and number of errors on Six-Item Screener (r = 0.87)

Chinese Older Adults: (Tsai et al., 2016; n = 142)

  • Adequate predictive validity for MCI (area under the curve of ROC was 0.88)
  • Adequate predictive validity for dementia (area under the curve of ROC was 0.89)

Floor/Ceiling Effects

Mixed Population: (Trzepacz et al., 2015); 618 cases: 219 cognitively normal healthy control, 299 MCI, and 100 AD dementia cases

  • Poor ceiling effects: Ceiling effect of 28-30 points accounted for 71.4% of the healthy control and MCI group.

Parkinson's Disease

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Standard Error of Measurement (SEM)

Neurocognitive Disorders and Parkinson's (Lucza et al., 2015; mild neurocognitive disorder due to PD- n=60; median age= 71; major neurocognitive disorder due to PD- n= 53; median age= 74)

  • SEM for mild neurocognitive disorders due to PD= 2.32
  • SEM for major neurocognitive disorders due to PD= 2.22

Minimal Detectable Change (MDC)

Neurocognitive Disorders and Parkinson's (Lucza et al., 2015);

  • MDC (95% CI) for mild neurocognitive disorders due to PD=6.43
  • MDC (95% CI) for major neurocognitive disorders due to PD= 6.16

Cut-Off Scores

Parkinson’s Disease:

(Hoops et al, 2009; = 132, mean age = 63.9(9.7), mean age PDD = 68.1(9.2), Parkinson’s Disease) 

  • The optimal screening cutoff points were 29/30 (sensitivity = 0.90, specificity = 0.38) for the MMSE

MMSE

 

 

 

 

 

 

 

Cutoff

24/25

25/26

26/27

27/28

28/29

29/30

Sensitivity

20

28

38

53

78

90

Specificity

99

96

88

83

63

38

 

Parkinson’s Disease:

(Djuradin et al, 2010)

  • The best cut-off for distinguishing between demented and non-demented patients with PD was 26/30 for the MMSE.

Neurocognitive Disorders and Parkinson's (Lucza et al., 2015);

  • For mild neurocognitive disorder due to PD= 27.5 (with a sensitivity of 0.602 and specificity of 0.706)
  • For major neurocognitive disorder due to PD= 26.5 (with a sensitivity of 0.692 and specificity of 0.806)

This study determined cut-off scores being 27.5 and 26.5 for the MMSE when detecting mild and major neurocognitive disorders in PD respectively. These numbers represent an absence of mild and major NCDs.

 

Dementia in Parkinson’s Patients (Kaszas et al., 2012; PD patients with dementia- n=51; mean age= 62.7; SD= 8.4; PD patients without dementia- n=22; mean age= 64.6; SD= 10.6; )

  • 26 points with sensitivity of 79.9% and specificity of 74.0%

This study found that most patients scored 26 points on the MMSE (which demonstrates an absence of dementia), with the support of the instrument having a higher ability to detect serious concerns.

Normative Data

Parkinson’s Disease: 

  • MMSE score (= 1120 PD with Dementia (= 43): 19.6 (4.6), no dementia (= 87): 28.5 (2.0) < 0.001(Aarsland et al, 2001) 
  • Patients with PD and Dementia had an annual decline from year 1 to year 4 of 2.3 (95% CI, 2.1 to 2.5; 9.1% change from year 1) (Aarsland et al, 2004) 
  • Mean (SD) MMSE Score for PD and no dementia at year 1 was 27.3(3.7), was 23.8(8.0) at year 4, and 19.2(9.8) at year 8 (all P-values < 0.001). (Aarsland et al, 2004) 
  • Mean (SD) Scores for PD with dementia at year 1 was 25.4(4.9), were 16.2(8.0) at year 4, and 7.2(6.5) at year 8. (Aarsland et al, 2004) 
  • Comparison of Mean MMSE (28.8 + 1.1 and MoCA scores (24.9 + 3.1) in a chort of patients with PD who scored normal on the MMSE as part of the eligibility criteria- 52% met criteria for cognitive impairment based on the MoCA score (< 26). (Nazem et al 2009)

Test/Retest Reliability

Parkinson’s Disease with Dementia and Parkinson’s Disease:

(Pagonabarraga et al, 2010; n = 70 for PD-ND and n = 32 for PDD, Parkinson’s Disease with Dementia & Parkinson’s Disease)

  • Total scores were significantly lower in the PDD population
  • MMSE scores: PD-ND = 27.9(2.1), PDD = 23(2.8) 
  • P < 0.001

Criterion Validity (Predictive/Concurrent)

Parkinson’s Disease:

(Aarsland et al, 2004): 129 patients with PD (57%F)Mean age 70.0(8.1)yrs, duration of disease mean 8.6(4.9) yrs, H&Y stage mean 2.4(0.9). 

  • MMSE negatively correlated with age (P < 0.001) and motor score B of the UPDRS (P < 0.001) 
  • Also sig interaction of age by time (P < 0.01) and motor score B by time implying more rapid cognitive decline with higher age and higher levels of motor score B. 
  • Predictors of more rapid cognitive decline in PD were: old age at study entry, hallucinations, and more severe motor symptoms, in particular, symptoms not associated with dopaminergic motor symptoms such as gait, speech, and postural disturbances. 
  • In the model including UPDRS scores of bradykinesia and rigidity, age (P < 0.001) and rigidity score (P < 0.01) were negatively related to MMSE 
  • Independent risk factors at baseline for dementia development in PD were age (OR, 1.2;95% CI, 1.1 to 1.2)/ MMSE Score < 29 (OR 3.3; 95%CI, 1.3 to 8.2) and H&Y Stage > 2 (OR, 3.4; 95% CI, 1.3 to 8.6). 
  • At MMSE score < 24 at baseline the incidence of dementia in the PD was 74.8% (95% CI, 48.6 to 101.0) per 1000 persons. The OR associated with PD was 5.3 ((%% CI, 3.2 to 8.6) after adjustment for age, gender and education. 

Djudardin et al 2010: 

  • Coefficient of the MMSE Scores < 26 was 2.21 (OR = 1 (reference), 95% CI, 3.03-27.28, p < 0.0001) for predicting PDD (parkinson’ s disease dementia) 

(Harvey, P.D., Ferris, S.H., et al, 2009, Parkinson’s Disease)

Study demonstrated criterion related validity for the ADAS-cog in people with PDD and showed strong correlation with the MMSE. This supports the validity of a previous clinical study’s results of patients with PDD that have used these measures. It also suggests that they are useful for future studies.

 

(Zadikoff et al, 2008):

  • MMSE correlated slightly more with the UPDRS I item 1 (Spearmen correlation coefficients -0.34, P = 0.0013) than the MoCA (Spearman correlation coefficients -0.26, P = 0.0153) 
  • More pronounced ceiling effect of the MMSE (27/88 subjects scored 30) compared to the MoCA (4.88 scored 30)

Dementia in Parkinson’s Patients (Kaszas et al., 2012); PD patients with dementia- n=51; mean age= 62.7; SD= 8.4; PD patients without dementia- n=22; mean age= 64.6; SD= 10.6; )

  • Receiver Operating Characteristic (ROC) analysis- area under the curve: Adequate= 0.867 for dementia

 

Neurocognitive Disorders and Parkinson's (Lucza et al., 2015);

  • Receiver Operating Characteristic (ROC) analysis- area under the curve: Adequate= 0.82 for mild neurocognitive disorder due to PD
  • Receiver Operating Characteristic (ROC) analysis- area under the curve: Excellent = 0.90 for major neurocognitive disorder due to PD

Construct Validity

Parkinson’s Disease:

(Aarslsand et al, 2004)

  • Pearson correlation between MMSE and Dementia Rating Sale = 0.87 (P < 0.001) 

(Hoops et al, 2009, Parkinson’s Disease) 

  • MoCA was superior to the MMSE as a screening instrument

Convergent Validity

Dementia in Parkinson’s Patients: (Kaszas et al., 2012)

  • Adequate convergent validity between MMSE and Frontal Assessment Battery (r = 0.419)
  • Excellent convergent validity between MMSE and Addenbrooke’s Cognitive Examination (r = 0.717)

 

Discriminant Validity

Dementia in Parkinson’s Patients: (Kaszas et al., 2012)

  • Poor discriminant validity between MMSE and verbal fluency + language/orientation + memory (r = -0.251)

 

Content Validity

Parkinson’s Disease:

(Kandiah et al, 2009; n = 106, mean age = 61.2, Parkinson's Disease)

  • The rate for those with no cognitive decline was 10.41 (SD = 0.97) points/year whereas the rate for patients with cognitive decline was 22.39 (SD = 2.07) points/year (Fig. 1)

Face Validity

Parkinson’s Disease:

(Lessig et al, 2012; = 98, mean age = 68.8 (1.02), Parkinson's Disease)

  • There were significant declines on the MMSE for both individuals with disease duration ≥ 10 and < 10 years (P < 0.001 and P = 0.01)
  • This demonstrates that the MMSE measures cognitive decline over a prolonged period of time

Stroke

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Cut-Off Scores

Stroke: (Morris, Hacker, & Lincoln, 2011; n = 101; mean age = 76 years; mean time post stroke = 15 -18 months, Acute Stroke)

  • At a cut-off score of 27 the MMSE showed good sensitivity (sensitivity, 0.80), low specificity (specificity, 0.20; positive predictive value, 0.84; negative predictive value, 0.16).

Normative Data

Stroke:

(Blake et al, 2002; mean age = 70.8 (12.2) years; < 4 weeks post stroke; mean Barthel Index score at recruitment = 10.5 (5.8); UK sample, Acute Stroke)

Assessment

Mean

SD

Range

% impaired

MMSE

21.0

8.9

0-30

31

SST

14.0

6.0

0-20

37

RCPM

19.1

9.3

1-36

28

MMSE = Mini-Mental State Exam

SST = Sheffield Screening Test

RCPM = Raven's Colored Progressive Matrices

 

 

 

 

 

Internal Consistency

Stroke:

(Toglia et al, 2011; n = 72; mean age = 70 (17.0 years; mean time post CVA = 8.5 days), Stroke)

  • The internal consistency of 11 MMSE items showed Cronbach alpha of 0.60, indicating that the items may not be measuring a unidimensional construct in persons with mild subacute stroke
  • The internal consistency of 10 MoCA items showed stronger internal consistency with Cronbach alpha of 0.78, suggesting that it is a more reliable measure for persons with mild cognitive de?cits

Criterion Validity (Predictive/Concurrent)

Stroke:

(Nys et al, 2005, Acute Stroke)

  • Scores on the MMSE were no better than chance at detecting cognitive impairment

Stroke: (Morris, Hacker, & Lincoln, 2011; n = 101; mean age = 76 years; mean time post stroke = 15 -18 months, Acute Stroke)

  • MMSE AUC = 0.53
  • In the acute stroke population, the MMSE is not able to accurately discriminate between people with and without cognitive impairment.

 

Predictive Validity

Stroke: (Cumming et al., 2013; n = 60)

  • Adequate predictive validity for cognitive impairment after stroke (area under the curve of ROC was 0.84)

After altering the criterion standard threshold to require 2 or more domain z-scores of <1.5 resulted in a classification of 32 of 60 (53%) patients as cognitively impaired, adequate predictive validity for cognitive impairment after stroke (area under the curve of ROC was 0.89)

Construct Validity

Stroke:

(Godefroy et al, 2011; n = 95; mean age = 68.2 (13.7) years; mean time post CVA < 3 weeks, Stroke)

  • Using raw scores, MoCA was more frequently impaired (P = 0.0001) than MMSE. MoCA showed good sensitivity (sensitivity, 0.94) but moderate specificity (specificity, 0.42; positive predictive value, 0.77; negative predictive value, 0.76), whereas an inverse profile was observed for MMSE (sensitivity, 0.66; specificity, 0.97; positive predictive value, 0.98; negative predictive value, 0.58) 

 

(Agrell & Dehlin, 2000, Acute Stroke)

  • MMSE scores were found to significantly correlate with the BI, MADRS and Zung Depression Scale (p > 0.05)

Stroke: (Cumming et al., 2013; n = 60)

  • Adequate reliability between MMSE and criterion standard which is determined on basis of neuropsychological battery (ICC = 0.57, CCC = 0.57, k = 0.57)
  • After altering the criterion standard threshold to require 2 or more domain z-scores of <1.5 resulted in a classification of 32 of 60 (53%) patients as cognitively impaired, adequate reliability between the MMSE and criterion standard (ICC = 0.70. CCC = 0.70, k = 0.70)

Floor/Ceiling Effects

Stroke:

(Toglia et al, 2011; n = 72; mean age = 70 (17.0) years; mean time post CVA = 8.5 days, Stroke)

  • Compared to the MOCA, a more pronounced ceiling effect was noted for the MMSE

Responsiveness

Stroke:

(Nys et al, 2005; n = 34; mean age = 64.7 (11.5) years; Dutch sample, Acute Stroke)

  • MMSE AUC = 0.67* (standard error = 0.11)

    • Results indicate that the MMSE performed no better than chance at differentiating cognitive impairment from cognitively intact patients

*A measure with an AUC = 1 can be interpreted as having 100% sensitivity and specificity

The MMSE was NOT useful to assess memory problems or overall cognitive impairment after stroke. (Blake et al, 2002)

Mixed Populations

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Test/Retest Reliability

Meta-analytic Evidence:

(Tombaugh & McIntyre, 1992)

  • Poor to Excellent test-retest reliability in MMSE's administered < 2 months (= 0.38 - 0.99)

 

Mixed Diagnoses:

(Folstein et al, 1975; n = 63 normal elderly and 206 elderly with cognitive or emotional disorders, Mixed Diagnoses)

  • Excellent 24 hour test-retest (same examiner) reliability (r = 0.88)
  • Excellent 24 hour test-retest reliability (with different examiner; r = 0.827)
  • Excellent 28 day (mean time between assessments) test-retest reliability (r = 0.988)

Internal Consistency

Meta-analytic Evidence:

(Tombaugh & McIntyre, 1992)

  • Adequate to Excellent internal consistency (Cronbach's alpha = 0.54 to 0.96)

Criterion Validity (Predictive/Concurrent)

  • Poor to Adequate MMSE and FIM correlations (Ozdemir et al, 2001; mean rehab = 64.09 (18.27) days)

 

Motor FIM Score Improvement

Functional Ambulation Score Improvement

Baseline MMSE

r = 0.31

(adequate)

r = 0.23

(poor)

Construct Validity

Mixed diagnosis:(Folstein et

  • Excellent convergent validity with:
    • WAIS (Wechsler Adult Intelligence Scale) Verbal IQ (r = 0.78) 
    • WAIS (Wechsler Adult Intelligence Scale) Performance IQ (r = 0.66) 

Brain Injury

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Criterion Validity (Predictive/Concurrent)

Traumatic Brain Injury:

(Srivastava et al, 2006; n = 43; mean age 66 (7.2) years; one year post TBI, mild to moderate severity; 60.5% sample mild, TBI) 

  • Scores on MMSE were not useful to identify those with cognitive impairment, possible utility of attention items in identifying those who are not impaired. 

(de Guise et al, 2011; n = 162, 102 mild TBI, 30 moderate, 30 severe; see abstract below, TBI) 

  • Other measures (clock drawing test and Trail Making Test - B) offered better utility for predicting outcome than the MMSE when tested early in inpatient rehabilitation

Bibliography

Aarsland, D., Andersen, K., et al. (2001). "Risk of dementia in Parkinson’s disease A community-based, prospective study." Neurology 56(6): 730-736.

Aarsland, D., Andersen, K., et al. (2004). "The rate of cognitive decline in Parkinson disease." Archives of Neurology 61(12): 1906.

Agrell, B. and Dehlin, O. (2000). "Mini mental state examination in geriatric stroke patients. Validity, differences between subgroups of patients, and relationships to somatic and mental variables." Aging (Milano) 12(6): 439-444.

Andrew, M. K. and Rockwood, K. (2008). "A five-point change in Modified Mini-Mental State Examination was clinically meaningful in community-dwelling elderly people." Journal of Clinical Epidemiology 61(8): 827-831.

Ashford, J. W. and Schmitt, F. A. (2001). "Modeling the time-course of Alzheimer dementia." Curr Psychiatry Rep 3(1): 20-28.

Blake, H., McKinney, M., et al. (2002). "An evaluation of screening measures for cognitive impairment after stroke." Age Ageing 31: 451-456.

Bravo, G. and Hebert, R. (1997). "Age- and education-specific reference values for the Mini-Mental and modified Mini-Mental State Examinations derived from a non-demented elderly population." International Journal of Geriatric Psychiatry 12(10): 1008-1018.

Brugnolo, A., Nobili, F., et al. (2009). "The factorial structure of the mini mental state examination (MMSE) in Alzheimer's disease." Arch Gerontol Geriatr 49(1): 180-185.

de Guise, E., Gosselin, N., et al. (2011). "Clock drawing and mini-mental state examination in patients with traumatic brain injury." Appl Neuropsychol 18(3): 179-190.

Dick, J. P., Guiloff, R. J., et al. (1984). "Mini-mental state examination in neurological patients." Journal of Neurology, Neurosurgery and Psychiatry 47(5): 496-499.

Dujardin, K., Dubois, B., et al. (2010). "Parkinson's disease dementia can be easily detected in routine clinical practice." Movement Disorders 25(16): 2769-2776.

Folstein, M. F., Folstein, S. E., et al. (1975). ""Mini-mental state". A practical method for grading the cognitive state of patients for the clinician." Journal of Psychiatric 嫩B研究院 12(3): 189-198.

Fong, T. G., Fearing, M. A., et al. (2009). "Telephone interview for cognitive status: Creating a crosswalk with the Mini-Mental State Examination." Alzheimers Dement 5(6): 492-497.

Freidl, W., Schmidt, R., et al. (1996). "Sociodemographic predictors and concurrent validity of the Mini Mental State Examination and the Mattis Dementia Rating Scale." Eur Arch Psychiatry Clin Neurosci 246(6): 317-319.

Godefroy, O., Fickl, A., et al. (2011). "Is the Montreal Cognitive Assessment superior to the Mini-Mental State Examination to detect poststroke cognitive impairment? A study with neuropsychological evaluation." Stroke 42(6): 1712-1716.

Harvey, P. D., Ferris, S. H., et al. (2010). "Evaluation of dementia rating scales in Parkinson's disease dementia." Am J Alzheimers Dis Other Demen 25(2): 142-148.

Hoops, S., Nazem, S., et al. (2009). "Validity of the MoCA and MMSE in the detection of MCI and dementia in Parkinson disease." Neurology 73(21): 1738-1745.

Jacqmin-Gadda, H., Fabrigoule, C., et al. (1997). "A 5-year longitudinal study of the Mini-Mental State Examination in normal aging." American Journal of Epidemiology 145(6): 498-506.

Kandiah, N., Narasimhalu, K., et al. (2009). "Cognitive decline in early Parkinson's disease." Mov Disord 24(4): 605-608.

Lancu, I. and Olmer, A. (2006). "[The minimental state examination--an up-to-date review]." Harefuah 145(9): 687-690, 701.

Lessig, S., Nie, D., et al. (2012). "Changes on brief cognitive instruments over time in Parkinson's disease." Mov Disord 27(9): 1125-1128.

Molloy, D. W. and Standish, T. I. (1997). "A guide to the standardized Mini-Mental State Examination." International Psychogeriatrics 9 Suppl 1: 87-94; discussion 143-150.

Mungas, D., Marshall, S. C., et al. (1996). "Age and education correction of Mini-Mental State Examination for English and Spanish-speaking elderly." Neurology 46(3): 700-706.

Nazem, S., Siderowf, A. D., et al. (2009). "Montreal Cognitive Assessment Performance in Patients with Parkinson's Disease with “Normal” Global Cognition According to Mini‐Mental State Examination Score." Journal of the American Geriatrics Society 57(2): 304-308.

Nys, G. M. S., van Zandvoort, M. J. E., et al. (2005). "Restrictions of the Mini-Mental State Examination in acute stroke." Arch Clin Neuropsychol 20: 623-629.

Ozdemir, F., Birtane, M., et al. (2001). "Cognitive evaluation and functional outcome after stroke." Am J Phys Med Rehabil 80: 410-415.

Pagonabarraga, J., Kulisevsky, J., et al. (2010). "PDD-Short Screen: a brief cognitive test for screening dementia in Parkinson's disease." Mov Disord 25(4): 440-446.

Pedraza, O., Clark, J. H., et al. (2012). "Diagnostic validity of age and education corrections for the Mini-Mental State Examination in older African Americans." J Am Geriatr Soc 60(2): 328-331.

Pendlebury, S. T., Cuthbertson, F. C., et al. (2010). "Underestimation of Cognitive Impairment by Mini-Mental State Examination Versus the Montreal Cognitive Assessment in Patients With Transient Ischemic Attack and Stroke A Population-Based Study." Stroke 41(6): 1290-1293.

Salter, K., Jutai, J. W., et al. (2005). "Issues for selection of outcome measures in stroke rehabilitation: ICF Body Functions." Disability and Rehabilitation 27(4): 191-207.

Srivastava, A., Rapoport, M. J., et al. (2006). "The utility of the mini-mental status exam in older adults with traumatic brain injury." Brain Inj 20(13-14): 1377-1382.

Andrews, J. S., Desai, U., Kirson, N. Y., Zichlin, M. L., Ball, D. E., & Matthews, B. R. (2019). Disease severity and minimal clinically important differences in clinical outcome assessments for Alzheimer’s disease clinical trials. Alzheimer's and Dementia: Translational 嫩B研究院 and Clinical Interventions, 5(1), 354-363. doi:

Boban, M., Malojc?ic?, B., Mimica, N., Vukovic?, S., Zrilic?, I., Hof, P. R., & S?imic?, G. (2012). The Reliability and Validity of the Mini Mental State Examination in the Elderly Croatian Population. Dementia and Geriatric Cognitive Disorders, 33, 385-392. doi: 10.1159/000339596

Brodaty, H., Pond, D., Kemp, N. M., Luscombe, G., Harding, L., Berman, K., & Huppert, F. A. (2002). The GPCOG: a new screening test for dementia designed for general practice. Journal of the American Geriatrics Society50(3), 530-534.

Callahan, C. M., Unverzagt, F. W., Hui, S. L., Perkins, A. J., & Hendrie, H. C. (2002). Six-item screener to identify cognitive impairment among potential subjects for clinical research. Medical care, 771-781.

Cumming, T. B., Churilov, L., Linden, T., & Bernhardt, J. (2013). Montreal Cognitive Assessment and Mini-Mental State Examination are both valid cognitive tools in stroke. Acta Neurologica Scandinavica, 128(2), 122–129. doi: 10.1111/ane.12084

Feeney, J., Savva, G. M., O’Regan, C., King-Kallimanis, B., Cronin, H. & Kenny, R. A. (2016). Measurement error, reliability, and minimum detectable change in the Mini-Mental State Examination, Montreal Cognitive Assessment, and Color Trails Test among community living middle-aged and older adults. Journal of Alzheimer’s Disease, 53(3), 1107-1114. doi: 10.3233/JAD-160248

Kaszas, B., Kovacs, N., Balas, I., Kallai, J., Aschermann, Z., Kerekes, Z., … Karadi, K. (2012). Sensitivity and specificity of Addenbrooke’s Cognitive Examination, Mattis Dementia Rating Scale, Frontal Assessment Battery and Mini Mental State Examination for diagnosing dementia in Parkinson’s disease. Parkinsonism and Related Disorders, 18(5), 553-556. doi:

Lucza, T., Kazmer, K., Kallai, J., Weintraut, R., Janszky, J., Makkos, A., … Kovacs, N. (2015). Screening mild and major neurocognitive disorders in Parkinson’s disease. Behavioural Neurology, 1-10. doi: 10.1155/2015/983606

Mitchell, A. J. (2008). A meta-analysis of the accuracy of the Mini-Mental State Examination in the detection of dementia and mild cognitive impairment. Journal of Psychiatric 嫩B研究院, 43(4), 411-431. doi:

Morris, K., Hacker, V., & Lincoln, N. B. (2011). The validity of the Addenbrooke’s Cognitive Examination-Revised (ACE-R) in acute stroke. Disability and Rehabilitation, 34(3), 189–195. doi: 10.3109/09638288.2011.591884

Mougias, A. A., Christidi, F., Kiosterakis, G., Messinis, L., & Politis, A. (2018). Dealing with severe dementia in clinical practice: A validity and reliability study of Severe Mini-Mental State Examination in Greek Population. International Journal of Geriatric Psychiatry, 33(9), 1236-1242. doi:

Trzepacz, P. T., Hochstetler, H., Wang, S., Walker, B., & Saykin, A. J. (2015). Relationship between the Montreal Cognitive Assessment and Mini-Mental State Examination for assessment of mild cognitive impairment in older adults. BMC Geriatrics, 15, 1-9. doi: 10.1186/s12877-015-0103-3

Tsai, J. C., Chen, C. W., Chu, H., Yang, H. L., Chang, M. H., Liao, Y. M. & Chou, K. R. (2016). Comparing the sensitivity, specificity, and predictive values of the Montreal Cognitive Assessment and Mini-Mental State Examination when screening people for mild cognitive impairment and dementia in chinese population. Archives of Psychiatric Nursing, 30(4), 486-491. doi:

Toglia, J., Fitzgerald, K. A., et al. (2011). "The Mini-Mental State Examination and Montreal Cognitive Assessment in persons with mild subacute stroke: relationship to functional outcome." Arch Phys Med Rehabil 92(5): 792-798.

Tombaugh, T. N. and McIntyre, N. J. (1992). "The mini-mental state examination: a comprehensive review." J Am Geriatr Soc 40: 922-935.

Zadikoff, C., Fox, S. H., et al. (2008). "A comparison of the mini mental state exam to the Montreal cognitive assessment in identifying cognitive deficits in Parkinson's disease." Movement disorders 23(2): 297-299.