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ORIGINAL ARTICLE
Year : 2023  |  Volume : 26  |  Issue : 1  |  Page : 44-53
 

Normative scores for malayalam cognitive screening test battery among older adults in Kerala, India


1 Government College of Nursing, Govt. Medical College, Thiruvananthapuram, Kerala, India
2 ICMR- National Institute of Virology, Microbial Containment Complex, 130/1, Sus Road, Pashan, Pune (Current), Govt. Medical College, Thiruvananthapuram, Kerala, India
3 Jeffrey Cheah School of Medicine and Health Sciences Monash University Malaysia (Current), Govt. Medical College Thiruvananthapuram, Kerala, India
4 Excise Headquarters, Nandavanam Road, Thiruvananthapuram (Current), Govt. Medical College Thiruvananthapuram, Kerala, India
5 Government Medical College, Thiruvananthapuram, Kerala, India

Date of Submission13-Apr-2022
Date of Decision23-Oct-2022
Date of Acceptance08-Nov-2022
Date of Web Publication04-Jan-2023

Correspondence Address:
Thomas Iype
GNRA A16, Kowdiar Post, Thiruvananthapuram - 695 003, Kerala
India
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/aian.aian_695_22

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   Abstract 


Background: Many neuropsychological tests are primarily developed in high-income countries, and normative data are not readily available for low- and middle-income countries (LMICs). We need culturally appropriate cognitive screening tests for India. Objective: Hence, we decided to translate the Hindi cognitive screening test battery (HCSTB) tool to Malayalam and establish the age and education-stratified norms for a Malayalam cognitive screening test battery (MCSTB). Material and Methods: HCSTB was translated to Malayalam, back-translated by bilinguals conversant in Malayalam and English, and pretested on 30 older normal adults. Using a multistage sampling technique, we conducted a descriptive cross-sectional survey in the Thiruvananthapuram district of Kerala, India. We approached older adults aged ≥60 years for informed and written consent. We excluded subjects with depression, functional impairment, cognitive impairment, history of stroke, psychosis, and visual/hearing loss that impaired cognitive assessment. Results: The normative data were derived from 441 older adults: 226 (51%) from rural areas and 215 (49%) from urban areas. Age and education affected the cognitive scores. The time to administer MCSTB among normal adults was approximately 17 minutes. Discussion and Conclusion: The derived normative data showed lower values than the published literature. A limitation of our study was the small number of older people with ≥12 years of education and the lack of neuroimaging of the subjects.


Keywords: Aged, cognition, developing countries, India, neuropsychological tests


How to cite this article:
Radhakrishnan PJ, Raghunath SP, Mohan D, Rajan R, Iype T. Normative scores for malayalam cognitive screening test battery among older adults in Kerala, India. Ann Indian Acad Neurol 2023;26:44-53

How to cite this URL:
Radhakrishnan PJ, Raghunath SP, Mohan D, Rajan R, Iype T. Normative scores for malayalam cognitive screening test battery among older adults in Kerala, India. Ann Indian Acad Neurol [serial online] 2023 [cited 2023 Feb 1];26:44-53. Available from: https://www.annalsofian.org/text.asp?2023/26/1/44/367043





   Introduction Top


Fifty million people worldwide live with dementia: this number is projected to increase to 82 million by 2030 and 152 million by 2050.[1] Currently, the majority (63%) of people with dementia live in low- and middle-income countries (LMICs).[2]

India is a very culturally diverse country. Kerala is unique in India's southern part, with a higher literacy rate (96.2%), than the national average, and life expectancy (74.9 years). Malayalam is the official language of Kerala, spoken by 34 million people worldwide. There is a wide variation in the prevalence of dementia in India.[3] 'The prevalence of cognitive impairment among persons 60 years and above is high in Kerala: dementia is 5.63%, and mild cognitive impairment (MCI) is 26.06%.[4] With meta-analysis showing community care coordination reducing nursing home admissions,[5] detecting MCI and mild dementia is crucial. The diagnosis of MCI, based on neuropsychological tests, predicts progression to dementia.[6],[7] To screen for cognitive decline in a vast population of LMICs, we need standardized neuropsychological tests that are brief to use in the community.

A wide range of neuropsychological tests is available for the assessment of cognition. However, they are primarily developed in high-income countries, and their normative data are not readily available for the LMIC setting. They are very time-consuming, limiting their use as community-based screening tools. We need culturally appropriate cognitive screening tests for a limited-resource country like India, with enormous linguistic and cultural diversity and varying education levels.

The neuropsychological assessment battery[8] by the Consortium to Establish a Registry for Alzheimer's Disease (CERAD) is a comprehensive, brief, and easy tool with good psychometric properties for cognitive assessment of geriatric subjects.[9],[10] It is often combined with a screening tool to assess global cognitive function like mini-mental state examination (MMSE). This cognitive battery was modified to adapt to Indian culture and translated to Hindi (a local language in India).[11] Age- and education-appropriate normative data of the Hindi cognitive screening test battery (HCSTB) for the elderly were documented from a rural area near Delhi.[11]

Cognitive performance is known to be affected by sociodemographic factors.[12],[13] The cognitive performance scores developed for a predominantly illiterate rural Hindi-speaking population may not be appropriate for a Malayalam-speaking people from a different culture, with a different level of education, and different urban areas. Hence, we decided to translate the HCSTB tool into Malayalam and establish the age- and education-stratified norms for a Malayalam cognitive screening test battery (MCSTB).


   Material and Methods Top


The HCSTB consisted of the following four tests:

  1. Memory Test


    1. Word List Memory (WLM)


    2. This test consists of 10 Malayalam words: butter, arm, corner, letter, queen, ticket, grass, stone, book, and stick. The participants were presented with these words and asked to recall them. This process was repeated thrice, but the ten words were presented in a different order [Appendix 1].



      The maximum possible score is 30.

    3. Word List Recall (WLR)


    4. Subjects are again asked to recall 10 words read from the green paper five minutes after administration of the 10-word list.

      The maximum score is 10.

    5. Wordlist recognition (WLRec)


    6. This test consists of 10 original words intermingled with 10 new words. The words are read out to the subject in a predetermined order. The participants are asked to identify each word as original or new.

      One point is given for each correctly recognized old and new word. Misclassified words get zero points. The maximum score is 20.


  2. Object Naming Test


  3. This test consists of 15 objects, including five high-frequency objects (flower, lock, bottle, elephant, rolling pin), five medium-frequency objects (syringe, comb, scissors, spectacles, basket), and five low-frequency objects (flute, airplane, funnel, telephone, necklace). The subject must name the 15 objects shown to them without handling them.

    Each correct response receives one point. The maximum score is 15.

  4. Verbal fluency


  5. The subject must enumerate as many fruits and animals separately in 60 seconds for each category.

    The correct response receives one point. The sum of the scores in both categories is utilized (no maximum score).

  6. Praxis


  7. This test consists of circles, diamonds, overlapping rectangles, and box line drawings. The subject must copy this.

    The maximum score for the circle is two, for the diamond is five, for the overlapping rectangles is two, and for the box is four. The maximum total score for praxis is 13.


  1. Steps used in the development of MCSTB


    1. Translation and back-translation: HCSTB [11] was translated to the local Malayalam language and back-translated by bilingual experts.
    2. Pre-testing of items: This tool was pretested on 30 persons aged 60 years and older.
    3. Face validity and content validity: Expert review established the face validity and content validity.
    4. Reliability assessment: Internal consistency reliability was done on the final 441 samples.


  2. Procedure of deriving normative scores:


We conducted a descriptive cross-sectional survey in Thiruvananthapuram district, Kerala, India. We used the multistage sampling technique. One taluk was randomly selected from the four taluks in Thiruvananthapuram. One village was selected randomly from the five rural areas and one out of the 26 urban areas. Three wards each were randomly selected from the selected rural and urban areas. Each ward was divided into four clusters; from each cluster, 17 to 20 samples were selected proportionately.

The target sample size was calculated based on the verbal fluency item (fruits and animals) in the HCSTB, which yielded the maximum sample size. A mean score of 19.9 in verbal fluency, SD of 5.6, an alpha error of 5%, precision of 1.96 times the standard error of mean, and design effect of 2 was used to calculate the sample size.[11] The total sample size was 440, distributed between rural and urban areas proportionate to the population. The rural sample size was 200, and the urban area sample size was 240. We collected data between September 2016 and August 2017 after obtaining approval from the Institutional Human Ethics Committee of Government Medical College, Thiruvananthapuram. Four field investigators (with a minimum bachelor's degree in allied health sciences) conducted a door-to-door survey and approached persons aged 60 years and older for informed and written consent.

In the study, we included persons aged 60 years and above residing in the selected rural and urban areas of Thiruvananthapuram district. We excluded subjects with depression (scoring 8 or higher in the depression part of the Hospital Anxiety and Depression Scale)[14] and functional impairment (scoring 3 or higher on the Everyday Abilities Scale for India).[15] We also excluded persons with cognitive impairment (scoring at or below the 10th percentile on education-stratified population norms according to the Malayalam Addenbrooke's Cognitive Examination),[16] history of stroke, psychosis, and visual/hearing loss that impaired cognitive assessment.

The MCSTB was administered by field investigators who were trained for a period of one week.

Statistical Analysis: Age- and education-stratified norms were prepared. The range, mean and standard deviation, and 5th, 10th, and 50th (median) percentile scores for each cognitive test were determined. Comparison of age, education, gender, and area of living in each domain of the MCSTB were identified using analysis of variance (ANOVA) and t-test, and the effect of age, education, and area of living on the MCSTB scores was determined by multiple linear regression.


   Results Top


Translation and back-translation ensured that the meaning of items had not changed. The items were finalized after expert review and respondent review. Expert review established the face validity and content validity. Internal consistency reliability Cronbach's alpha for MCSTB was 0.82.

To obtain the required sample size, we approached 509 elderly aged 60 years and older. We excluded 68 subjects with visual or hearing impairment (two subjects), who refused to participate (two subjects), with functional impairment (17 subjects), cognitive impairment (18 subjects), and severe depression (29 subjects). The normative data were derived from the remaining 441 elderly considered to represent healthy subjects. Of the total sample size of 441 individuals aged 60 years and older, 51% (226 individuals) were sampled from rural areas, and 49% (215 individuals) were sampled from urban areas.

We present the demographic characteristics for MCSTB from 441 non-demented subjects aged 60–96 years recruited from rural and urban communities [Appendix 2].



[Table 1] shows the overall distribution of test scores for each subtest of the MCSTB. The sample size differs slightly in some tests as some subjects did not complete all the tests. The median values for constructional praxis [Appendix 3] were higher among the urban subjects (P = 0.001) [Appendix 4]. The median values for wordlist learning immediate, wordlist learning delayed recall, verbal fluency for fruits, verbal fluency for animals, and object naming were significantly higher among the urban subjects [Appendix 4].
Table 1: Overall distribution of test scores

Click here to view



[Table 2], [Table 3], [Table 4], [Table 5] show age- and education-stratified norms for the entire test battery. For each item of the MCSTB, mean (SD), 5th, 10th, and 50th percentile scores are given. The median values for word list memory immediate, word list recall, word list recognition of foils, praxis, and verbal fluency in fruits and animals were marginally lower among elderly aged 80 years and older.
Table 2: Distribution of test scores - WLL* Immediate and WLL Delayed based on age and education

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Table 3: Distribution of test scores .Word list recognition (WLR) based on age and education

Click here to view
Table 4: Distribution of test scores . Object naming and constructional praxis based on age and education

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Table 5: Distribution of test scores .Verbal Fluency (Fruits & Animals) based on age and education

Click here to view


[Appendix 4] shows that age significantly affected all tests (P < 0.01) except word list recognition originals and verbal fluency fruits. Also, education has a significant effect on all test scores (P < 0.001). Gender significantly affects constructional praxis and verbal fluency for animals (P < 0.01).

[Appendix 5] shows the effect of age, education, and area of living on all test scores. Education had a significant direct impact on all tests. The effect of area of living is significant for all tests except word list recall, word list recognition, and verbal fluency fruits. There was a significant inverse effect of age on word list learning immediate and word list recall. The area of living, age, and education interaction effect was significant for word list learning immediately. The effect of demographic variables on variations in the test results differs. The education, age, and area of living explain 33.2% of word list learning immediate. The 18.7% of variation in word list recall is explained by education and age. Education alone contributed 45.3% of the variation in praxis score, 9.8% of the variation in word list recognition (originals and foils), and 7.9% in verbal fluency fruits. A combination of education and area of living contributed to 13.6% of the variation in the scores of object naming, 25.2% of the variation in verbal fluency in animal scores, and 24.4% in verbal fluency scores for both animals and fruit.



The time taken by a trained administrator to complete the MCSTB was approximately 13 minutes.


   Discussion Top


The MCSTB possesses satisfactory psychometric properties, reliability, and validity. The internal consistency reliability Cronbach's alpha was 0.82. We present the population-derived normative data of the elderly with the 5th, 10th, and 50th percentile of the MCSTB. Our data is normative as we have excluded persons with cognitive impairment: scoring 10th percentile or less on education-stratified population norms of Malayalam Addenbrooke's Cognitive Examination[16] and scoring 3 or higher on the Everyday Abilities Scale for India.[15] The data mimic real-life situations since it is a population-based study and have not excluded patients with comorbid diseases like hypertension or diabetes. The older person was defined as people 60 years and older, as defined in the national policy of India. We have stratified the normative data based on two important confounding factors: age and education.

Cognitive assessment is the basis of dementia and MCI diagnosis.[6],[7] Hence, there is a need for regional and demographically adjusted normative data for cognitive tests. The tenth and fifth percentile of test items in the MCSTB can be used to screen for cognitive decline in the domains more objectively. The Indian Council of Medical Research Neuro-Cognitive Tool Box (ICMR-NCTB) was devised at the national level to harmonize a common cognitive test battery in five Indian languages. The MCSTB is brief and can be administered in a community by a trained healthcare worker. In contrast, ICMR-NCTB data was derived from OPDs, senior citizen associations, and community centers which has to be administered by a trained psychologist or clinician.[17]

Tests in all four domains except the constructional praxis had an even spread with good fifth and tenth percentiles. There was no floor effect for the tests except for constructional praxis, thus making it useful as a screening tool. The mediocre performance of tests for constructional praxis among the less educated could be due to unfamiliarity with holding a pencil to paper. The observed range touched zero in word list recall, word list recognition of foils, verbal fluency for fruits, and constructional praxis. The observed range touched the maximum in word list recognition of originals and object naming, which may affect the optimal performance grading. ICMR-NCTB used modified tools for illiterates in executive function, memory, visuospatial, and language.[4]

The current study showed that the overall median and fifth percentile scores on word list memory (13, 8), word list recall (4, 2), verbal fluency fruits (7,4), verbal fluency animals (9, 6), and verbal fluency total (17, 11) were low compared to the scores from other countries.[12] The 10/66 study has also noted that Indians do poorly on cognitive tests compared to Chinese and Latin Americans.[18] In the 10/66 study, the education-stratified mean and SD for Indians on word list memory immediate and word list recall were 11 (4.3) and 3.7 (2.0) for zero years of education and 15.5 (4.8) and 5.3 (1.6) for tertiary education, respectively. These results were comparable with the results from our study where education-stratified mean and SD on word list memory immediate and word list recall were 11.03 (2.79) and 3.1 (1.33) for zero years of education and 14.8 (2.97) and 4.6 (1.45) for tertiary education, respectively. In our study, the education-stratified mean and SD for verbal fluency animals were 7.3 (2.13) for zero years of education and 9.9 (2.45) for tertiary education. These results were comparable with the results from the 10/66 study, where the mean and SD for Indians on verbal fluency animals was 7.7 (3.1) for zero years of education and 9.7 (3.03) for tertiary education. Balachandar et al.[19] noted that age and education matched Indian subjects who performed poorly on standard neuropsychological tests like the Tower of Hanoi. Researchers have observed that often verbatim test administration is not enough for Indian subjects.[19],[20]

The normative data for the domains in the current study in a population with higher education was lower for age compared to the data from Ballabgarh. This disparity could suggest that cognitive performance depends not merely on the years of formal education but also on acquired skills. The Ballabgarh study did not find a significant difference in cognitive performance between those who could read and write against those who could not. This lack of difference in cognitive performance in the Ballabgarh population could be due to a primarily illiterate population.[11]

In the current study, a comparison of gender based on test scores showed significant differences only in constructional praxis and verbal fluency for animals. The study from Kolkata[21] in the eastern part of India, where people speak Bengali, also showed the same results. The Kolkata community-based study was conducted on persons aged 50 years and older. The Kolkata Cognitive Screening Battery was similar to ours, except they had additional calculation tests. Comparison of test scores between age groups showed a significant difference in all tests except word list recognition originals and verbal fluency fruits. This result was comparable with the result from the Kolkata study. The current study showed a significant difference in all test scores across educational categories. The study from Kolkata also showed a significant difference in all test scores except the memory test.

In our study, the effect of age, education, and area of living showed that education was significant for all tests. This result was comparable with the result from the Kolkata study, where education was significant for all tests except the memory test.

A limitation to our study was the lack of subjects aged 80 years and older and with 12 or more years of education since we expect a high proportion of subjects in this age group and education in the future. Our data applies only to individuals aged 60 years of age and older in a community setting. We did not use neuroimaging to exclude subjects with cerebral atrophy, hippocampal atrophy, or vascular changes.


   Conclusion Top


The MCSTB is a brief, culturally appropriate cognitive screening battery for Malayalam-speaking people in Kerala. The current study provides age- and education-stratified normative data for MCSTB. Today, optimization of therapy for cognitive impairment demands early diagnosis of cognitive impairment, and the presented normative data for MCSTB will facilitate this by providing accurate information for early diagnosis and decision-making in both the hospital and community setting.

Ethical approval

Human Ethics Committee Medical College, Thiruvananthapuram IEC No. 03/15/2016/MCT dt 21/05.

LMICs: Low- and middle-income countries, HCSTB: Hindi cognitive screening test battery, MCSTB: Malayalam cognitive screening test battery.

Acknowledgements

Lekshmi A. S., Assistant Professor, Government College of Nursing, Thiruvananthapuram.

Financial support and sponsorship

State Board of Medical Research, Government Medical College, Thiruvananthapuram.

Conflicts of interest

There are no conflicts of interest.



 
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    Tables

  [Table 1], [Table 2], [Table 3], [Table 4], [Table 5]



 

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