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Question 1
Psychometric Analysis of the Montreal Cognitive Assessment in South Africa
Aim of the Study and Description of the Instrument
The study by van Wijk et al. (2024) aimed to replicate and extend earlier South African research on
the Montreal Cognitive Assessment (MoCA), providing an expanded description of its psychometric
properties in a workplace sample. The MoCA is a widely used screening tool for mild cognitive
impairment (MCI), designed to detect early neurocognitive difficulties before dementia develops. It
is brief, inexpensive, and covers six domains of cognition: visuospatial, executive functioning,
attention, language, memory, and orientation. The test yields a maximum score of 30, with a
traditional cut-off of ≤26 indicating possible impairment. Its purpose is to guide clinical
decision-making in resource-constrained contexts where advanced neuropsychological testing is not
feasible (Foxcroft & Roodt, 2023; van Wijk et al., 2024).
Sampling Strategy and Sample Evaluation
Comparison to the Standardization Sample
The original MoCA was standardized on North American adults, primarily English- and
French-speaking Canadians, with validation studies reporting high sensitivity (90%) and specificity
(87%) for detecting MCI. In contrast, van Wijk et al. (2024) used a South African workplace sample
of 402 neurocognitively healthy adults and 42 individuals diagnosed with mild neurocognitive
disorders. Unlike the standardization sample, which was culturally and linguistically homogeneous,
the South African sample was multilingual and diverse, with participants reporting home languages
such as Afrikaans, isiXhosa, isiZulu, Sesotho, and Setswana, though all were proficient in English.
This difference highlights the challenge of applying a universal cut-off score across heterogeneous
populations.
Representation of the General Population
The workplace sample consisted of highly skilled workers with at least Grade 12 education plus
vocational training, drawn from fields such as engineering, administration, security, hospitality, and
radar/sonar operations. While this ensured a controlled and educated group, it does not fully
represent the broader South African population, which includes individuals with lower educational
attainment and varying levels of English proficiency. Thus, the findings may not generalize to rural
or less-educated communities, where dementia prevalence is higher and language barriers are more
pronounced (Foxcroft & Roodt, 2023).
Importance of Demographic Characteristics
Demographic variables played a crucial role in the study’s findings. Age was negatively correlated
with MoCA scores, consistent with international and local research. Language significantly
influenced performance, with non-English first-language speakers scoring lower, raising concerns
about cultural and linguistic bias. Interestingly, gender did not show consistent effects, aligning with
mixed findings in prior South African studies. These demographic insights are vital for future use of
the MoCA in South Africa: they underscore the need for context-specific adaptations, such as
lowering the cut-off score (e.g., ≤24) or introducing grey-zone thresholds to reduce false positives.
Without such adjustments, cognitively healthy individuals risk being misclassified as impaired
simply due to language or cultural differences (van Wijk et al., 2024).
Question 1
Psychometric Analysis of the Montreal Cognitive Assessment in South Africa
Aim of the Study and Description of the Instrument
The study by van Wijk et al. (2024) aimed to replicate and extend earlier South African research on
the Montreal Cognitive Assessment (MoCA), providing an expanded description of its psychometric
properties in a workplace sample. The MoCA is a widely used screening tool for mild cognitive
impairment (MCI), designed to detect early neurocognitive difficulties before dementia develops. It
is brief, inexpensive, and covers six domains of cognition: visuospatial, executive functioning,
attention, language, memory, and orientation. The test yields a maximum score of 30, with a
traditional cut-off of ≤26 indicating possible impairment. Its purpose is to guide clinical
decision-making in resource-constrained contexts where advanced neuropsychological testing is not
feasible (Foxcroft & Roodt, 2023; van Wijk et al., 2024).
Sampling Strategy and Sample Evaluation
Comparison to the Standardization Sample
The original MoCA was standardized on North American adults, primarily English- and
French-speaking Canadians, with validation studies reporting high sensitivity (90%) and specificity
(87%) for detecting MCI. In contrast, van Wijk et al. (2024) used a South African workplace sample
of 402 neurocognitively healthy adults and 42 individuals diagnosed with mild neurocognitive
disorders. Unlike the standardization sample, which was culturally and linguistically homogeneous,
the South African sample was multilingual and diverse, with participants reporting home languages
such as Afrikaans, isiXhosa, isiZulu, Sesotho, and Setswana, though all were proficient in English.
This difference highlights the challenge of applying a universal cut-off score across heterogeneous
populations.
Representation of the General Population
The workplace sample consisted of highly skilled workers with at least Grade 12 education plus
vocational training, drawn from fields such as engineering, administration, security, hospitality, and
radar/sonar operations. While this ensured a controlled and educated group, it does not fully
represent the broader South African population, which includes individuals with lower educational
attainment and varying levels of English proficiency. Thus, the findings may not generalize to rural
or less-educated communities, where dementia prevalence is higher and language barriers are more
pronounced (Foxcroft & Roodt, 2023).
Importance of Demographic Characteristics
Demographic variables played a crucial role in the study’s findings. Age was negatively correlated
with MoCA scores, consistent with international and local research. Language significantly
influenced performance, with non-English first-language speakers scoring lower, raising concerns
about cultural and linguistic bias. Interestingly, gender did not show consistent effects, aligning with
mixed findings in prior South African studies. These demographic insights are vital for future use of
the MoCA in South Africa: they underscore the need for context-specific adaptations, such as
lowering the cut-off score (e.g., ≤24) or introducing grey-zone thresholds to reduce false positives.
Without such adjustments, cognitively healthy individuals risk being misclassified as impaired
simply due to language or cultural differences (van Wijk et al., 2024).
