Psychometric Properties of the Persian Montreal Cognitive Assessment in Mild Cognitive Impairment and Alzheimer Disease

Rashedi, Vahid; Foroughan, Mahshid; Chehrehnegar, Negin

doi:10.1159/000514673

Cited by 18 publications

(9 citation statements)

References 37 publications

(55 reference statements)

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“…The patients' cognitive status was assessed using the Montreal Cognitive Assessment (MoCA) battery ( 23 ) and Functional Assessment Staging (FAST) scale ( 24 ).…”

Section: Methodsmentioning

confidence: 99%

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Relationship Between Psychological Impacts of COVID-19 and Loneliness in Patients With Dementia: A Cross-Sectional Study From Iran

et al. 2022

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ObjectivesAlthough the COVID-19 pandemic has affected people all around the world, the elderly is at a higher risk of suffering from its consequences. One of the serious concerns is developing loneliness and post-traumatic stress symptoms, which may contribute to cognitive decline at older ages. This study aimed to examine the psychological responses and loneliness in elderly patients diagnosed with dementia.MethodsTwenty-one patients diagnosed with dementia, with ages older than 40, and 19 caregivers were enrolled in the study. The patients have undergone a comprehensive neuropsychiatric interview and were assessed with De Jong Gierveld Scale for loneliness and Impact of Event Scale—Revised (IES-R). The severity of dementia was assessed by Functional Assessment Staging Tool (FAST Scale) and the Montreal Cognitive Assessment (MoCA).ResultsNo significant difference was seen in patients and caregivers in the IES-R and loneliness scales. A higher level of avoidance and social and total loneliness were seen in higher FAST levels (p-value: 0.046). There was a negatively significant correlation between MoCA score and avoidance. Hyperarousal was significantly correlated with emotional loneliness in patients.ConclusionWe found a direct relationship between cognitive decline and the psychological impacts of COVID-19. Our results highlight the need for more comprehensive studies to further investigate the influence of the pandemic on the worsening of cognitive impairment and loneliness in patients with dementia.

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“…The patients' cognitive status was assessed using the Montreal Cognitive Assessment (MoCA) battery ( 23 ) and Functional Assessment Staging (FAST) scale ( 24 ).…”

Section: Methodsmentioning

confidence: 99%

“…Patients with scores of 26 or higher did not have any cognitive impairments (normal MoCA), whereas patients with scores lower than 26 probably had cognitive impairments ( 28 ). Rashedi et al found a sensitivity of 94% and a specificity of 90% for MCI and Alzheimer's disease, with a cutoff score of 20 ( 23 ).…”

Section: Methodsmentioning

confidence: 99%

Relationship Between Psychological Impacts of COVID-19 and Loneliness in Patients With Dementia: A Cross-Sectional Study From Iran

et al. 2022

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“…Cognitive tests are time consuming, their reliability is disputable. According to the previous studies, the accuracy of the tests distinguishing MCI from healthy aging ranges from 58 to 90% (Tóth et al, 2018;Müller et al, 2019;Fernández-Fleites et al, 2021;Rashedi et al, 2021). Because of the inconsistent findings clinicians cannot rely on cognitive scores as a single diagnostic modality (Statsenko et al, 2021e,f).…”

Section: Accuracy Of Unimodal Approach Cognitive Testsmentioning

confidence: 99%

Patterns of structure-function association in normal aging and in Alzheimer's disease: Screening for mild cognitive impairment and dementia with ML regression and classification models

Statsenko

Meribout

Habuza

et al. 2023

Front. Aging Neurosci.

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BackgroundThe combined analysis of imaging and functional modalities is supposed to improve diagnostics of neurodegenerative diseases with advanced data science techniques.ObjectiveTo get an insight into normal and accelerated brain aging by developing the machine learning models that predict individual performance in neuropsychological and cognitive tests from brain MRI. With these models we endeavor to look for patterns of brain structure-function association (SFA) indicative of mild cognitive impairment (MCI) and Alzheimer's dementia.Materials and methodsWe explored the age-related variability of cognitive and neuropsychological test scores in normal and accelerated aging and constructed regression models predicting functional performance in cognitive tests from brain radiomics data. The models were trained on the three study cohorts from ADNI dataset—cognitively normal individuals, patients with MCI or dementia—separately. We also looked for significant correlations between cortical parcellation volumes and test scores in the cohorts to investigate neuroanatomical differences in relation to cognitive status. Finally, we worked out an approach for the classification of the examinees according to the pattern of structure-function associations into the cohorts of the cognitively normal elderly and patients with MCI or dementia.ResultsIn the healthy population, the global cognitive functioning slightly changes with age. It also remains stable across the disease course in the majority of cases. In healthy adults and patients with MCI or dementia, the trendlines of performance in digit symbol substitution test and trail making test converge at the approximated point of 100 years of age. According to the SFA pattern, we distinguish three cohorts: the cognitively normal elderly, patients with MCI, and dementia. The highest accuracy is achieved with the model trained to predict the mini-mental state examination score from voxel-based morphometry data. The application of the majority voting technique to models predicting results in cognitive tests improved the classification performance up to 91.95% true positive rate for healthy participants, 86.21%—for MCI and 80.18%—for dementia cases.ConclusionThe machine learning model, when trained on the cases of this of that group, describes a disease-specific SFA pattern. The pattern serves as a “stamp” of the disease reflected by the model.

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“…9 Studies have evaluated the effectiveness of MoCA in different settings around the world, and it has been shown to be valid and reliable tool to detect dementia. 9,12 The tool has also been especially praised for its ability to detect subtle changes in the cognitive functioning. 7,11 It has been tested in several settings, including some countries in Africa, and evidence is available for its validity and reliability.…”

Section: Introductionmentioning

confidence: 99%

Psychometric Properties of the Montreal Cognitive Assessment (MoCA) to Detect Major Neurocognitive Disorder Among Older People in Ethiopia: A Validation Study

Daniel¹,

Agenagnew²,

Workicho³

et al. 2022

NDT

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Background: Cognition is one of the most complex functions of the human brain, and major neurocognitive disorders affect this function causing a wide array of problems in an individual's life. Screening for major neurocognitive disorders can be helpful in designing and implementing early interventions. Purpose: This study was designed to assess the reliability and validity of the Montreal Cognitive Assessment (MoCA) tool to detect major neurocognitive disorders among older people in Ethiopia. Methods: One hundred and sixteen randomly selected older adults in Ethiopia were involved in a cross-sectional study. The Diagnostic and Statistical Manual of Mental Disorders criteria for major neurocognitive disorders was used as a gold standard. Data were analyzed using STATA v16 statistical software. Receiver operating curve analysis was performed, and inter-rater, internal consistency reliabilities, content, criterion and construct validities were determined. Statistically significance was declared at a p-value of <0.05. Results:The study had a 100% response rate. The mean age of the study participants was 69.87 ± 7.8. The inter-rater reliability value was 0.96, and Cronbach's alpha was 0.79. The optimal cutoff value was ≤21, and Montreal Cognitive Assessment has an area under curve value of 0.89. The sensitivity, specificity, positive and negative likelihood ratios, and positive and negative predictive values of MoCA are 87.18%, 74.03%, 3.35, 0.17, 63%, and 91.9%, respectively. The tool also has good concurrent and construct validities. Conclusion:The Montreal Cognitive Assessment tool was a reliable and valid tool to detect major neurocognitive disorder. It can be incorporated into the clinical and research practices in developing countries.

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Psychometric Properties of the Persian Montreal Cognitive Assessment in Mild Cognitive Impairment and Alzheimer Disease

Cited by 18 publications

References 37 publications

Relationship Between Psychological Impacts of COVID-19 and Loneliness in Patients With Dementia: A Cross-Sectional Study From Iran

Relationship Between Psychological Impacts of COVID-19 and Loneliness in Patients With Dementia: A Cross-Sectional Study From Iran

Patterns of structure-function association in normal aging and in Alzheimer's disease: Screening for mild cognitive impairment and dementia with ML regression and classification models

Psychometric Properties of the Montreal Cognitive Assessment (MoCA) to Detect Major Neurocognitive Disorder Among Older People in Ethiopia: A Validation Study

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