Scaling Cognitive Domains of the Montreal Cognitive Assessment: An Analysis Using the Partial Credit Model

Montreal Cognitive Assessment (MoCA): A validation study among prisoners

BACKGROUND

There are numerous scales for screening cognitive performance and thus identification of any potential deficits, but in spite of the vulnerability of the prison population to such problems, there has been no adequate validation of screening tools specifically for use with prisoners or others in the criminal justice system.

AIM

To validate the Montreal Cognitive Assessment (MoCA) for use with prisoners.

METHODS

100 adult prisoners in one Portuguese prison were randomly invited by clinicians to take part in this study. A same size sample of community-living adult non-offenders of similar age was selected from the MoCA's normative study database in Portugal. For both groups, the key inclusion criterion was fluency in the Portuguese language. All participants completed the Mini Mental State Examination (MMSE) and the MoCA, both in Portuguese translation. Cronbach's alpha coefficient was calculated as an index of internal consistency and Pearson's r correlations calculated. Group performances were compared using independent samples t-test. Covariance analysis (ANCOVA) was computed with level of education as covariate. To measure the magnitude of the effect,η p 2 ${\eta }_{p}^{2}$ was used. A receiver operating characteristics curve analysis was computed to evaluate the discriminatory accuracy of MoCA and MMSE.

RESULTS

The MoCA showed a 'reasonable' internal consistency index (α = 0.75) as well as positive and significant correlations with the MMSE. As a cognitive measure, however, the MoCA showed consistently superior psychometric properties and higher discriminatory accuracy (MoCA = 89%) than the MMSE (65%). According to the Youden index, the optimal cut-off point for the MoCA is below 24 points, whereas for the MMSE, it is below 27.

CONCLUSIONS

The MoCA is a valid cognitive screening tool for use with prisoners. Further validations against detailed cognitive evaluation would be a useful next step.

Montreal Cognitive Assessment (MoCA): An update normative study for the Portuguese population

The Montreal Cognitive Assessment (MoCA) is a brief cognitive screening instrument that is known for its good psychometric properties and sensitivity to detect mild cognitive impairment (MCI). After ten years, it became relevant to update the previous Portuguese normative study due to changes in the population and some limitations present in the study itself. The study sample was composed of 860 cognitively healthy adults, stratified according to verified distribution of the Portuguese population across several sociodemographic variables. All participants completed a neuropsychological assessment battery, in which the MoCA was included. The analysis of the relationships between the sociodemographic variables and the MoCA show that age and educational level had a significant effect on MoCA scores, with educational level being the better predictor. These results foster the consideration of age and educational level in the development of normative data. The present study contributes to a reliable update of the normative data of MoCA. The new age groups and more stratified norms comply with the natural changes on the Portuguese population, providing an increase of power and clinical accuracy. The presented norms consider the cognitive domains subscores, consequently improving the comprehension and utility of the results obtained from the MoCA test.

Interitem Psychometric Validation of the Stanford Integrated Assessment for Transplant Scale Among Thoracic Transplant Candidates

BACKGROUND

Psychosocial evaluations are mandatory for transplant listing, however the methodology for creating psychosocial risk stratifications is unclear. The Standford Psychosocial Integrated Psychosocial Assessment for Transplant Scale is the most commonly used instrument, however its interitem validity has never been examined.

OBJECTIVE

To investigate the interitem validity of a psychosocial assessment tool for transplant candidates among a sample of thoracic transplant candidates.

METHODS

Clinic data consisting of Stanford Integrated Psychosocial Assessment for Transplant administrations from 173 heart and lung transplant candidates were fit to a partial credit model. Data were subsequently fit to 4 separate partial credit models based on subscale categories, demonstrating the discrimination parameter estimate of each item. Differential item functioning analyses were conducted on the data within each subscale by sex to investigate potential bias produced by each item.

RESULTS

The initial partial credit model using the full scale did not converge, indicating the subscales possibly did not measure the same underlying construct. Subscale discrimination parameter estimates demonstrated that most items were adequately or highly discriminative. The item measuring history of substance use demonstrated poor fit and differential item functioning.

CONCLUSIONS

While the Stanford Integrated Psychosocial Assessment for Transplant has demonstrated strong potential as a standardized framework for psychosocial assessments in transplant, this study identified some areas for improvement in the scoring system. The subscale scores appeared to show greater construct validity when utilized individually than when aggregated to form a total score. The substance use/abuse/dependence item did not fit well into its respective subscale. Future studies should aim to optimize the scoring system and re-asses its construct validity to improve its accuracy in discriminating between high-risk candidates and those needing psychosocial assistance.

A cross-sectional study exploring cognitive impairment in kidney failure

BACKGROUND

Little is known of the prevalence or associated factors of cognitive impairment in people with kidney failure. Assessment of cognition is necessary to inform comprehension of healthcare information, aptitude for dialysis modality and informed decision making.

OBJECTIVES

This study sought to determine the prevalence and factors associated with cognitive impairment in people with kidney failure.

DESIGN

Prospective cross-sectional.

PARTICIPANTS

Participants (n = 222) with chronic kidney disease grade 5 (CKD G5) including those not treated with dialysis, those undertaking dialysis independently or in a facility (CKD 5D), and those with a kidney transplant (CKD 5T).

MEASUREMENTS

Data were collected using the Montreal Cognitive Assessment tool, the Hospital Anxiety and Depression Scale (only the depression subscale), and a demographic questionnaire. Type of kidney disease and comorbidities were extracted from participants' hospital records.

RESULTS

Participants were 61 ± 13.63 years old; most were male (61.26%), and diabetes was the primary cause of kidney disease (34%). Prevalence of cognitive impairment was 34% although it was significantly higher for those in CKD G5 compared with other groups. A number of factors were found to be associated with cognitive impairment including, age, diabetes, hypertension, education, haemoglobin, albumin, parathyroid hormone, CKD G5, and length of time on treatment.

CONCLUSIONS

Cognitive impairment in kidney failure is common and it has significant implications for informed decision making and treatment choices. Routine assessment of cognitive function is an important part of clinical practice.

The Psychometric Properties of the Montreal Cognitive Assessment (MoCA)

Abstract. The Montreal Cognitive Assessment (MoCA) is a test assessing global cognition in older adults which is often used by researchers and clinicians worldwide, although some of its psychometric properties have yet to be established. We focus on three fundamental aspects: the factorial structure of the MoCA, its general factor saturation, and the measurement invariance of the test. We administered the MoCA to a large sample of Japanese older adults clustered in three cohorts (69–71-year-olds, 79–81-year-olds, and 89–91-year-olds; N = 2,408). Our results show that the test has an overall stable hierarchical factorial structure with a general factor at its apex and satisfactory general-factor saturation. We also found measurement invariance across participants of different ages, educational levels, economic status, and sex. This comprehensive investigation thus supports the idea that the MoCA is a valid tool to assess global cognition in older adults of different socioeconomic status and age ranges.

Studying Individual Differences in Spatial Cognition Through Differential Item Functioning Analysis

Background: In the field of spatial cognition, the study of individual differences represents a typical research topic. Gender and age have been prominently investigated. A promising statistical technique used to identify the different responses to items in relation to different group memberships is the Differential Item Functioning Analysis (DIF). The aim of the present study was to investigate the DIF of the Landmark positioning on a Map (LPM) task, across age groups (young and elderly) and gender, in a sample of 400 healthy human participants. Methods: LPM is a hometown map completion test based on well-known and familiar landmarks used to assess allocentric mental representations. DIF was assessed on LPM items two times: on categorical (i.e., positions) and coordinate (i.e., distances) scores, separately. Results: When positions and distances were difficult to assess with respect to the intended reference point, the probability to endorse the items seemed to get worse for the elderly compared to the younger participants. Instead other features of landmarks (high pleasantness, restorativeness) seemed to improve the elderly performance. A gender-related improvement of probability to endorse distance estimation of some landmarks, favoring women, emerged, probably associated with their repeated experiences with those landmarks. Overall, the complexity of the task seemed to have a differential impact on young and elderly people while gender-oriented activities and places seemed to have a differential impact on men and women. Conclusions: For the first time DIF was applied to a spatial mental representation task, based on the schematic sketch maps of the participants. The application of DIF to the study of individual differences in spatial cognition should become a systematic routine to early detect differential items, improving knowledge, as well as experimental control, on individual differences.

The role of the Montreal Cognitive Assessment (MoCA) and its memory tasks for detecting mild cognitive impairment

To investigate the role of the Montreal Cognitive Assessment (MoCA) (Beijing version) and its memory tasks on detecting different mild cognitive impairment (MCI) subtypes including amnestic MCI (aMCI) and nonamnestic MCI (naMCI) in memory clinics. A total of 121 patients with MCI and 53 healthy controls were included. Fifty-six aMCI-multiple domains (amMCI), 32 aMCI-single domain (asMCI), and 33 naMCI patients were diagnosed according to extensive cognitive tests. All participants were administered by the Mini Mental State Examination (MMSE) and the MoCA. Patients with amMCI performed worse than patients with asMCI, naMCI, and healthy controls on the MMSE and the MoCA (p < 0.001). The area under the curve (AUC) value for the MoCA when comparing the amMCI and control groups was 0.884 (p < 0.001), which was superior to that of the MMSE. The AUC value decreased to 0.687 when applied to the naMCI and control groups (p = 0.007), which was still higher than that of the Rey Auditory Verbal Learning Test (RAVLT) or the Rey-Osterrieth complex figure (ROCF). Delayed free recall or category prompted recall in the MoCA had roles in differentiating asMCI and controls groups with AUC value of 0.717 (p = 0.002) and 0.691 (p = 0.005), respectively. The MoCA is a good screening tool for detecting different types of MCI and is suitable for patients in outpatient clinics.

A Comparison of Magnetic Resonance Imaging and Neuropsychological Examination in the Diagnostic Distinction of Alzheimer's Disease and Behavioral Variant Frontotemporal Dementia

The clinical distinction between Alzheimer's disease (AD) and behavioral variant frontotemporal dementia (bvFTD) remains challenging and largely dependent on the experience of the clinician. This study investigates whether objective machine learning algorithms using supportive neuroimaging and neuropsychological clinical features can aid the distinction between both diseases. Retrospective neuroimaging and neuropsychological data of 166 participants (54 AD; 55 bvFTD; 57 healthy controls) was analyzed via a Naïve Bayes classification model. A subgroup of patients (n = 22) had pathologically-confirmed diagnoses. Results show that a combination of gray matter atrophy and neuropsychological features allowed a correct classification of 61.47% of cases at clinical presentation. More importantly, there was a clear dissociation between imaging and neuropsychological features, with the latter having the greater diagnostic accuracy (respectively 51.38 vs. 62.39%). These findings indicate that, at presentation, machine learning classification of bvFTD and AD is mostly based on cognitive and not imaging features. This clearly highlights the urgent need to develop better biomarkers for both diseases, but also emphasizes the value of machine learning in determining the predictive diagnostic features in neurodegeneration.