Influence of Social and Demographic Factors on the Montreal Cognitive Assessment (MoCA) Test in Rural Population of North-Eastern Greece

Ιnnovative Health Promotion Strategies: A 6-Month Longitudinal Study on Computerized Cognitive Training for Older Adults with Minor Neurocognitive Disorders

Minor neurocognitive disorders (NCDs) represent a transitional phase between normal cognitive aging and dementia, highlighting the importance of early interventions. This study assessed the efficacy of a structured 6-month computerized cognitive training (CCT) program in stabilizing cognitive decline among older adults with minor NCDs. One hundred participants were randomly assigned to an intervention group or a non-intervention group. The intervention group underwent weekly, personalized CCT sessions using the MeMo program, which targeted memory, attention, and adaptability. Cognitive performance was measured at baseline and after six months using the Cambridge Cognitive Examination (CAMCOG). Statistical analysis showed significant cognitive decline in the non-intervention group in orientation (p = 0.032), language expression (p = 0.008), praxis (p = 0.008), and memory (p = 0.01). In contrast, the intervention group showed no significant changes, except for a minor decline in perception (p = 0.003). These results suggest that CCT may help delay cognitive deterioration in minor NCDs. However, while cognitive decline was stabilized, no significant improvement was observed. Further research is recommended to investigate the long-term benefits and the transferability of cognitive gains. The findings support the use of CCT as a non-pharmacological health promotion strategy for enhancing cognitive resilience in aging populations. The novelty of this research lies in its focus on adaptive CCT as a non-pharmacological intervention, highlighting the potential role of neuroplasticity in delaying cognitive decline and offering new insights into personalized cognitive health strategies for aging populations.

Predictive Markers of Post-Stroke Cognitive Recovery and Depression in Ischemic Stroke Patients: A 6-Month Longitudinal Study

The growing number of stroke survivors face physical, cognitive, and psychosocial impairments, making stroke a significant contributor to global disability. Various factors have been identified as key predictors of post-stroke outcomes. The aim of this study was to develop a standardized predictive model that integrates various demographic and clinical factors to better predict post-stroke cognitive recovery and depression in patients with ischemic stroke (IS). We included IS patients during both the acute phase and six months post-stroke and considered neuropsychological measures (screening scales, individual tests, functional cognitive scales), stroke severity and laterality, as well as functional disability measures. The study identified several key predictors of post-stroke cognitive recovery and depression in IS patients. Higher education and younger age were associated with better cognitive recovery. Lower stroke severity, indicated by lower National Institutes of Health Stroke Scale (NIHSS) scores, also contributed to better cognitive outcomes. Patients with lower modified Rankin Scale (mRS) scores showed improved performance on cognitive tests and lower post-stroke depression scores. The study concluded that age, education, stroke severity and functional status are the most critical predictors of cognitive recovery and post-stroke emotional status in IS patients. Tailoring rehabilitation strategies based on these predictive markers can significantly improve patient outcomes.

Cultural Effects on the Performance of Older Haitian Immigrants on Timed Cognitive Tests

Background

Ignoring the cultural factors that can affect performance on cognitive tests may result in use of tests that have not been validated for that group. One example is testing of Haitian Creole speaking adults who are increasingly affected by Alzheimer's disease and related dementias, for whom few tests have been validated.

Aims

Our purpose is to describe differences in timed test performance between Haitian Creole and English-speaking participants and explore factors that may account for any differences in results found.

Methods

Data was obtained from an ongoing longitudinal driving and cognition study "In Vehicle Sensors to Detect Cognitive Change in Older Drivers." Two groups consisting of 12 Creole speaking and 12 English speaking older adults were matched by age and gender. Test scores were selected from the battery of tests administered in the parent study. The measures were translated by two bilingual Creole-English researchers. Group performance on five timed cognitive tests commonly used in research was compared.

Results

The English-speaking group's mean scores were significantly higher than the Creole speaking group on the MoCA and the timed Animal category fluency, letter P fluency, Stroop Color Test, and Trail Making Test A and B. The most significant effects were noted in Letter P fluency, Trail Making Test A and B and Animal category fluency where the differences had large effect sizes. However, the Creole speaking group had higher mean scores than the English-Speaking group on the Stroop Color Word Test, although the difference was not statistically significant. It was not feasible to match education levels due to the differences in years of education across the groups. These results highlight the significant role of culture and linguistic context in cognitive task performance.

Conclusions

The results suggest performance in cognitive testing among non-English speaking groups may be impacted by cultural factors related to time perception and the testing approach employed, leading to misinterpretation and misdiagnosis. Future studies should explore the fairness of various cognitive testing approaches with Haitian older adults and other societies with cultures and educational approaches different from those of Western cultures.

Optimal cutoff scores of the Montreal Cognitive Assessment to detect mild cognitive impairment and dementia in Costa Rican older adults

BACKGROUND

The burden of Alzheimer's disease and related dementias (AD/ADRD) in Costa Rica is expected to become one of the highest in the region. Early detection will help optimize resources and improve primary care interventions. The Montreal Cognitive Assessment (MoCA) has shown good sensitivity for detecting mild cognitive impairment (MCI), but specificity varies depending on the population. This motivated the analysis of different cutoffs to minimize false-positive classifications in a Costa Rican sample for its use in clinical settings.

METHODS

Data was analyzed from 516 memory clinic outpatients (148 cognitively normal, 260 MCI, 108 mild AD/ADRD; mean age 66.3 ± 10.8 years) who underwent complete neurological and neuropsychological assessment and were diagnosed by consensus. Optimal MoCA cutoff scores were identified using a multiple cutoff approach.

RESULTS

Overall, a cutoff score of ≥ 23 showed better accuracy to distinguish between normal cognition (NC) and MCI (sensitivity 73%, specificity 83%). When analyzed by educational levels, a cutoff score of ≥ 21 showed better accuracy for ≤ 6 years (sensitivity 80%, specificity 76%), ≥23 for 7-12 years (sensitivity 86%, specificity 76%) and ≥ 24 for > 12 years (sensitivity 70%, specificity 85%). For distinguishing MCI from mild AD/ADRD, the optimal overall cutoff score was ≥ 15 (sensitivity 66%, specificity 85%). When stratified by years of education, cutoff scores of ≥ 14 showed better accuracy for ≤ 6 years (sensitivity 70%, specificity 88%), ≥15 for 7-12 years (sensitivity 46%, specificity 95%) and ≥ 17 for > 12 years (sensitivity 67%, specificity 93%).

CONCLUSIONS

A MoCA cutoff score of ≥ 23 in the Costa Rican population showed better diagnostic accuracy for detecting MCI and may reduce the false positive rate. Our findings may be helpful for primary care clinical settings and further referral criteria.

Predictive Models for the Transition from Mild Neurocognitive Disorder to Major Neurocognitive Disorder: Insights from Clinical, Demographic, and Neuropsychological Data

Neurocognitive disorders (NCDs) are progressive conditions that severely impact cognitive function and daily living. Understanding the transition from mild to major NCD is crucial for personalized early intervention and effective management. Predictive models incorporating demographic variables, clinical data, and scores on neuropsychological and emotional tests can significantly enhance early detection and intervention strategies in primary healthcare settings. We aimed to develop and validate predictive models for the progression from mild NCD to major NCD using demographic, clinical, and neuropsychological data from 132 participants over a two-year period. Generalized Estimating Equations were employed for data analysis. Our final model achieved an accuracy of 83.7%. A higher body mass index and alcohol drinking increased the risk of progression from mild NCD to major NCD, while female sex, higher praxis abilities, and a higher score on the Geriatric Depression Scale reduced the risk. Here, we show that integrating multiple factors-ones that can be easily examined in clinical settings-into predictive models can improve early diagnosis of major NCD. This approach could facilitate timely interventions, potentially mitigating the progression of cognitive decline and improving patient outcomes in primary healthcare settings. Further research should focus on validating these models across diverse populations and exploring their implementation in various clinical contexts.

Usefulness of the Montreal Cognitive Assessment in Older Adults With Type 1 Diabetes

Objective

Older adults with type 1 diabetes are at high risk for cognitive impairment, yet the usefulness of common cognitive screening instruments has not been evaluated in this population.

Methods

A total of 201 adults ≥60 years of age with type 1 diabetes completed a battery of neuropsychological measures and the Montreal Cognitive Assessment (MoCA). Receiver operating characteristic (ROC) curves and Youden indices were used to evaluate overall screening test performance and to select an optimal MoCA cutoff score for detecting low cognitive performance, as defined as two or more neuropsychological test performances ≥1.5 SD below demographically corrected normative data.

Results

The ROC area under the curve (AUC) was 0.745 (P < 0.001). The publisher-recommended cutoff score of <26 resulted in sensitivity of 60.4% and specificity of 71.4%, whereas a cutoff score of <27 resulted in sensitivity of 75.0% and specificity of 61.0%. The Youden indices for these cutoff scores were 0.318 and 0.360, respectively. Minimally acceptable sensitivity (i.e., >0.80) was obtained when using a cutoff score of <28, whereas >0.80 specificity was obtained with a cutoff score of <25.

Conclusions

The MoCA has modest overall performance (AUC 0.745) as a cognitive screening instrument in older adults with type 1 diabetes. The standard cutoff score of <26/30 may not adequately detect individuals with neuropsychological testing-defined abnormal cognition. The optimal MoCA cutoff score (based on the Youden index) was <27/30. A score of <28 resulted in acceptable sensitivity but was accompanied by low specificity (42%). Future studies with a more diverse population are needed to confirm these findings.

Optimal cut-off MoCA score for screening for mild cognitive impairment in elderly individuals in China: A systematic review and meta-analysis

AIM

To evaluate the optimal cut-off MoCA score for elderly individuals with MCI.

DESIGN

A systematic review and meta-analysis.

METHOD

Articles were retrieved from PubMed, Ovid, Embase, The Cochrane Library, PsycINFO, CBM, CNKI, WanFang and CQVIP and were assessed by using the Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2). Figures of the assessment were made by using Review Manager 5.3, and a meta-analysis of the data was conducted by using Bivariate Random-effects Meta-Analysis (BRMA) via Stata 14.0.

RESULTS

Seventeen articles were retrieved from the database, and when the cut-offs were 24/25 and 25/26, they represented the same diagnostic value; in addition, the AUC was 0.96, which demonstrated high predictive validity for mild cognitive impairment screening. However, the sensitivity was higher with 25/26 (se=0.95, sp=0.80), whereas the specificity was higher with 24/25 (se=0.92, sp=0.89).

Comparison of the Greek Version of the Quick Mild Cognitive Impairment Screen and Montreal Cognitive Assessment in Older Adults

Objective: Cognitive screening instruments (CSIs) are essential for everyday practice. The Quick Mild Cognitive Impairment (Qmci) screen, a short instrument designed to identify mild cognitive impairment, was recently translated into Greek (Qmci-Gr). The present study compared its diagnostic value against the Montreal Cognitive Assessment (MoCA) screen and examined its optimal cutoffs. Method: We recruited consecutive patients aged ≥55 years that presented with cognitive complaints from two outpatient clinics in Greece. The Qmci-Gr and MoCA were completed by all patients. Furthermore, they were assessed independently with a comprehensive flexible neuropsychological battery to establish a diagnostic classification. Results: In the current study, we assessed a total of 145 patients, with a median age of 70 years; 44 were classified as having Subjective Memory Complaints (SMC) but normal cognition, 32 with MCI and 69 with dementia. The Qmci-Gr had a higher accuracy compared to the MoCA in discriminating MCI from dementia, area under the curve (AUC) of 0.81 versus 0.75, respectively; however, this finding was marginally significant (p = 0.08). Its accuracy was marginally higher for distinguishing SMC from dementia, AUC of 0.94 versus 0.89 (p = 0.03). However, Qmci-Gr presented a lower accuracy than MoCa in differentiating SMC from MCI, AUC of 0.76 versus 0.94 (p = 0.006). Conclusions: The Qmci-Gr has comparable diagnostic accuracy to the MoCA regarding MCI and dementia groups. Further research, with larger and more diverse samples, may be necessary to ensure generalizability.

The Effects of Horticultural Therapy on Sense of Coherence among Residents of Long-Term Care Facilities: A Quasi Experimental Design

Promoting positive mental health is crucial for the elderly living in long-term care facilities (LTCFs). This study aims to examine the effectiveness of horticultural therapy on the level of sense of coherence (SOC) among older LTCF residents with relatively normal mental function. With convenient sampling, a total of 86 participants were recruited from 12 LTCFs in northeastern Taiwan. In the experimental group (n = 49), the mean (±standard deviation) score of SOC was 50.45 ± 6.07 at baseline and increased to 56.37 ± 7.20 (p < 0.001) after 12-week horticultural intervention. In contrast, the mean SOC score did not change significantly in the control group (n = 37) during the study period. Generalized estimating equation analysis showed that a significant interaction effect between group and time on the SOC score (p < 0.001). Our findings indicate that horticultural therapy is effective to strengthen the SOC level of older LTCF residents without dementia.

Evaluation of the Accuracy of Cognitive Screening Tests in Detecting Dementia Associated with Alzheimer's Disease: A Hierarchical Bayesian Latent Class Meta-Analysis

BACKGROUND

Montreal Cognitive Assessment (MoCA) and Mini-Mental State Examination (MMSE) are neuropsychological tests commonly used by physicians for screening cognitive dysfunction of Alzheimer's disease (AD). Due to different imperfect reference standards, the performance of MoCA and MMSE do not reach consensus. It is necessary to evaluate the consistence and differentiation of MoCA and MMSE in the absence of a gold standard for AD.

OBJECTIVE

We aimed to assess the accuracy of MoCA and MMSE in screening AD without a gold standard reference test.

METHODS

Studies were identified from PubMed, Web of Science, CNKI, Chinese Wanfang Database, China Science and Technology Journal Database, and Cochrane Library. Our search was limited to studies published in English and Chinese before August 2021. A hierarchical Bayesian latent class model was performed in meta-analysis when the gold standard was absent.

RESULTS

A total of 67 studies comprising 5,554 individuals evaluated for MoCA and 76,862 for MMSE were included in this meta-analysis. The pooled sensitivity was 0.934 (95% CI 0.906 to 0.954) for MoCA and 0.883 (95% CI 0.859 to 0.903) for MMSE, while the pooled specificity was 0.899 (95% CI 0.859 to 0.928) for MoCA and 0.903 (95% CI 0.879 to 0.923) for MMSE. MoCA was useful to rule out dementia associated with AD with lower negative likelihood ratio (LR-) (0.074, 95% CI 0.051 to 0.108). MoCA showed better performance with higher diagnostic odds ratio (DOR) (124.903, 95% CI 67.459 to 231.260).

CONCLUSION

MoCA had better performance than MMSE in screening dementia associated with AD from patients with mild cognitive impairment or healthy controls.