The Mini-mental State Examination revisited: ceiling and floor effects after score adjustment for educational level in an aging Mexican population

2009 ◽  
Vol 22 (1) ◽  
pp. 72-81 ◽  
Author(s):  
Francisco Franco-Marina ◽  
Jose Juan García-González ◽  
Fernando Wagner-Echeagaray ◽  
Joseph Gallo ◽  
Oscar Ugalde ◽  
...  
Keyword(s):  
Cognitive Impairment ◽  
Mental State ◽  
Educational Level ◽  
Mini Mental State Examination ◽  
Community Sample ◽  
Epidemiological Studies ◽  
Cognitive Test ◽  
Ceiling Effects ◽  
Floor Effects ◽  
State Examination

ABSTRACTBackground: The Mini-mental State Examination (MMSE) is the most widely used cognitive test, both in clinical settings and in epidemiological studies. However, correcting its score for education may create ceiling effects when used for poorly educated people and floor effects for those with higher education.Methods: MMSE and a recent cognitive test, the seven minute screen (7MS), were serially administered to a community sample of Mexican elderly. 7MS test scores were equated to MMSE scores. MMSE-equated 7MS differences indicated ceiling or floor effects. An ordinal logistic regression model was fitted to identify predictors of such effects.Results: Poorly educated persons were more prevalent on the side of MMSE ceiling effects. Concentration (serial-sevens), orientation and memory were the three MMSE subscales showing the strongest relationship to MMSE ceiling effects in the multivariate model.Conclusion: Even when MMSE scores are corrected for educational level they still have ceiling and floor effects. These effects should be considered when interpreting data from longitudinal studies of cognitive decline. When an education-adjusted MMSE test is used to screen for cognitive impairment, additional testing may be required to rule out the possibility of mild cognitive impairment.

Educational level differences on the Mini-Mental State: the role of test bias

1988 ◽  
Vol 18 (3) ◽  
pp. 727-731 ◽  
Author(s):  
A. F. Jorm ◽  
R. Scott ◽  
A. S. Henderson ◽  
D. W. K. Kay
Keyword(s):  
Cognitive Impairment ◽  
Elderly People ◽  
Mental State ◽  
Educational Level ◽  
Mini Mental State Examination ◽  
Community Sample ◽  
Test Bias ◽  
Level Difference ◽  
State Examination

SynopsisLess educated elderly people are commonly found to perform more poorly on the Mini-Mental State Examination (MMSE). This educational level difference has been attributed by some research workers to test bias. To assess whether the MMSE is biased against the poorly educated, its validity was assessed separately in the more- and less-educated members of a community sample. No evidence was found to indicate that the test is a biased measure of cognitive impairment.

scholarly journals Can the MMSE help clinicians predict progression from mild cognitive impairment to dementia?

2015 ◽  
Vol 21 (6) ◽  
pp. 363-366 ◽  
Author(s):  
Alex J. Mitchell
Keyword(s):  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Risk Prediction ◽  
Mental State ◽  
Mini Mental State Examination ◽  
Case Finding ◽  
Cognitive Test ◽  
Prediction Tool ◽  
State Examination

SummaryThe Mini-Mental State Examination (MMSE) is the most widely used bedside cognitive test. It has previously been shown to be poor as a case-finding tool for both dementia and mild cognitive impairment (MCI). This month's Cochrane Corner review examines whether the MMSE might be used as a risk prediction tool for later dementia in those with established MCI. From 11 studies of modest quality, it appears that the MMSE alone should not be relied on to predict later deterioration in people with MCI. As this is the case, it is likely that only a combination of predictors would be able to accurately predict progression from MCI to dementia.

Relationship of health and demographic characteristics to Mini-Mental State Examination score among community residents

1988 ◽  
Vol 18 (3) ◽  
pp. 719-726 ◽  
Author(s):  
G. G. Fillenbaum ◽  
D. C. Hughes ◽  
A. Heyman ◽  
L. K. George ◽  
D. G. Blazer
Keyword(s):  
Mental Health ◽  
Cognitive Impairment ◽  
Functional Status ◽  
Mental State ◽  
Mini Mental State Examination ◽  
Community Sample ◽  
Demographic Characteristics ◽  
Community Residents ◽  
Relationship Of ◽  
State Examination

SynopsisMini-Mental State findings from an age 60+ random community sample (N = 1681) indicate that score is related to education, age and race (but not sex) and to functional status, but not to selected aspects of physical or mental health. Adjustment for demographic characteristics, particularly education, is recommended lest cognitive impairment be overestimated.

scholarly journals Formal education, health literacy and Mini-Mental State Examination

2011 ◽  
Vol 5 (1) ◽  
pp. 26-30 ◽  
Author(s):  
Sonia Maria Dozzi Brucki ◽  
Letícia Lessa Mansur ◽  
Maria Teresa Carthery-Goulart ◽  
Ricardo Nitrini
Keyword(s):  
Cognitive Impairment ◽  
Health Literacy ◽  
Mental State ◽  
Educational Level ◽  
Formal Education ◽  
Mini Mental State Examination ◽  
Indirect Measure ◽  
Great Heterogeneity ◽  
State Examination ◽  
Years Of Schooling

Abstract The Mini-Mental State Examination (MMSE) is a widely used screening test for cognitive impairment, but is heavily biased by education. Educational level has frequently been ranked using years of schooling, which may not be a good indirect measure of educational level because there is great heterogeneity in standards of schooling among populations and across regions of the same country. S-TOFHLA is a measure of health literacy with some results indicating that it is a good measure for literacy level. Objective: To evaluate the correlations between years of schooling and scores on the S-TOFHLA and the MMSE. Methods: Healthy subjects without cognitive impairment were submitted to the S-TOFHLA and the MMSE. Correlations and regression analysis were performed to determine possible associations among variables. Results: Both years of schooling and S-TOFHLA scores were strongly correlated with MMSE scores, but the strongest association was reached by the S-TOFHLA (r=0.702, p<0.01), where the S-TOFHLA was the best predictor of MMSE scores (R2=0.494, p<0.001). Conclusions: A stronger association between S-TOFHLA scores and MMSE performance was found than between years of education and MMSE scores. This finding justifies further studies incorporating years of schooling together with S-TOFHLA score, to evaluate cognitive performance.

Zur Anwendung der CES-D bei älteren Menschen: Dimensionsstruktur und Meßartefakte

Diagnostica ◽  
2000 ◽  
Vol 46 (1) ◽  
pp. 29-37 ◽  
Author(s):  
Herbert Matschinger ◽  
Astrid Schork ◽  
Steffi G. Riedel-Heller ◽  
Matthias C. Angermeyer
Keyword(s):  
Mental State ◽  
Latent Class ◽  
Mini Mental State Examination ◽  
Depression Scale ◽  
Epidemiological Studies ◽  
Partial Credit ◽  
Examination Score ◽  
State Examination

Zusammenfassung. Beim Einsatz der Center for Epidemiological Studies Depression Scale (CES-D) stellt sich das Problem der Dimensionalität des Instruments, dessen Lösung durch die Konfundierung eines Teilkonstruktes (“Wohlbefinden”) mit Besonderheiten der Itemformulierung Schwierigkeiten bereitet, da Antwortartefakte zu erwarten sind. Dimensionsstruktur und Eignung der CES-D zur Erfassung der Depression bei älteren Menschen wurden an einer Stichprobe von 663 über 75-jährigen Teilnehmern der “Leipziger Langzeitstudie in der Altenbevölkerung” untersucht. Da sich die Annahme der Gültigkeit eines partial-credit-Rasch-Modells sowohl für die Gesamtstichprobe als auch für eine Teilpopulation als zu restriktiv erwies, wurde ein 3- bzw. 4-Klassen-latent-class-Modell für geordnete Kategorien berechnet und die 4-Klassen-Lösung als den Daten angemessen interpretiert: Drei Klassen zeigten sich im Sinne des Konstrukts “Depression” geordnet, eine Klasse enthielt jene Respondenten, deren Antwortmuster auf ein Antwortartefakt hinwiesen. In dieser Befragtenklasse wird der Depressionsgrad offensichtlich überschätzt. Zusammenhänge mit Alter und Mini-Mental-State-Examination-Score werden dargestellt. Nach unseren Ergebnissen muß die CES-D in einer Altenbevölkerung mit Vorsicht eingesetzt werden, der Summenscore sollte nicht verwendet werden.

Mini-Mental State Examination (MMSE) for the early detection of dementia in people with mild cognitive impairment (MCI)

2021 ◽  
Vol 2021 (7) ◽  
Author(s):  
Ingrid Arevalo-Rodriguez ◽  
Nadja Smailagic ◽  
Marta Roqué-Figuls ◽  
Agustín Ciapponi ◽  
Erick Sanchez-Perez ◽  
...  
Keyword(s):  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Early Detection ◽  
Mental State ◽  
Mini Mental State Examination ◽  
State Examination

scholarly journals Preoperative Cognitive Impairment as a Predictor of Postoperative Outcomes in Elderly Patients Undergoing Spinal Surgery for Degenerative Spinal Disease

2021 ◽  
Vol 10 (7) ◽  
pp. 1385
Author(s):  
Hyung Cheol Kim ◽  
Seong Bae An ◽  
Hyeongseok Jeon ◽  
Tae Woo Kim ◽  
Jae Keun Oh ◽  
...  
Keyword(s):  
Cognitive Impairment ◽  
Elderly Patients ◽  
Mental State ◽  
Mini Mental State Examination ◽  
Operation Time ◽  
Cognitive Status ◽  
Blood Analysis ◽  
Spinal Disease ◽  
Degenerative Spinal Disease ◽  
State Examination

Cognitive status has been reported to affect the peri-operative and post-operative outcomes of certain surgical procedures. This prospective study investigated the effect of preoperative cognitive impairment on the postoperative course of elderly patients (n = 122, >65 years), following spine surgery for degenerative spinal disease. Data on demographic characteristics, medical history, and blood analysis results were collected. Preoperative cognition was assessed using the mini-mental state examination, and patients were divided into three groups: normal cognition, mild cognitive impairment, and moderate-to-severe cognitive impairment. Discharge destinations (p = 0.014) and postoperative cardiopulmonary complications (p = 0.037) significantly differed based on the cognitive status. Operation time (p = 0.049), white blood cell count (p = 0.022), platelet count (p = 0.013), the mini-mental state examination score (p = 0.033), and the Beck Depression Inventory score (p = 0.041) were significantly associated with the length of hospital stay. Our investigation demonstrated that improved understanding of preoperative cognitive status may be helpful in surgical decision-making and postoperative care of elderly patients with degenerative spinal disease.

scholarly journals Education does not equally influence all the Mini Mental State Examination subscales and items: inferences from a Brazilian community sample

2010 ◽  
Vol 32 (3) ◽  
pp. 223-230 ◽  
Author(s):  
Jerson Laks ◽  
Evandro Silva Freire Coutinho ◽  
Washington Junger ◽  
Heitor Silveira ◽  
Raphael Mouta ◽  
...  
Keyword(s):  
Mental State ◽  
Mini Mental State Examination ◽  
Community Sample ◽  
Community Dwelling ◽  
Delayed Recall ◽  
Functional Activities ◽  
Key Factor ◽  
Z Scores ◽  
The Impact ◽  
State Examination

OBJECTIVE: Mini-Mental State Examination cutoffs have been presented for schooling levels to screen cognitive impairment. However, items may behave differently with regards to education. The objective of this study was to examine the impact of education on MMSE subscales and items. METHOD: Community-dwelling participants aged 65 years or more (n = 990, females = 637, age = 74.1 years, range 65-108) were stratified as illiterate (n = 373), 1-8 (n = 540), 9-12 (n = 63), and more than 12 years of schooling (n = 14) and were screened with MMSE and Pfeffer Functional Activities Questionnaire. To make the Mini-Mental State Examination items comparable, each item was transformed into z scores. Multiple linear regression was used to estimate the effect of schooling on MMSE subs and items controlling for age, sex, and activities of daily life. RESULTS: Temporal and space orientation, attention/calculation, repetition, reading, writing, and drawing scores improved as education increased, but not memory registration, three step command, and naming. Reading and writing displayed the largest coefficients, whereas education exerted no influence on naming and three step command tasks. CONCLUSION: Education does not exert an important effect on naming, three step command, memory registration, and delayed recall. As memory is a key factor for diagnosing dementia, these items could be considered despite education.

scholarly journals Random Forest Model in the Diagnosis of Dementia Patients with Normal Mini-Mental State Examination Scores

2022 ◽  
Vol 12 (1) ◽  
pp. 37
Author(s):  
Jie Wang ◽  
Zhuo Wang ◽  
Ning Liu ◽  
Caiyan Liu ◽  
Chenhui Mao ◽  
...  
Keyword(s):  
Machine Learning ◽  
Cognitive Impairment ◽  
Random Forest ◽  
Mental State ◽  
Mini Mental State Examination ◽  
Machine Learning Algorithms ◽  
Assessment Model ◽  
Test Time ◽  
Cognitive Screening ◽  
State Examination

Background: Mini-Mental State Examination (MMSE) is the most widely used tool in cognitive screening. Some individuals with normal MMSE scores have extensive cognitive impairment. Systematic neuropsychological assessment should be performed in these patients. This study aimed to optimize the systematic neuropsychological test battery (NTB) by machine learning and develop new classification models for distinguishing mild cognitive impairment (MCI) and dementia among individuals with MMSE ≥ 26. Methods: 375 participants with MMSE ≥ 26 were assigned a diagnosis of cognitively unimpaired (CU) (n = 67), MCI (n = 174), or dementia (n = 134). We compared the performance of five machine learning algorithms, including logistic regression, decision tree, SVM, XGBoost, and random forest (RF), in identifying MCI and dementia. Results: RF performed best in identifying MCI and dementia. Six neuropsychological subtests with high-importance features were selected to form a simplified NTB, and the test time was cut in half. The AUC of the RF model was 0.89 for distinguishing MCI from CU, and 0.84 for distinguishing dementia from nondementia. Conclusions: This simplified cognitive assessment model can be useful for the diagnosis of MCI and dementia in patients with normal MMSE. It not only optimizes the content of cognitive evaluation, but also improves diagnosis and reduces missed diagnosis.

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