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 Table of Contents  
Year : 2020  |  Volume : 7  |  Issue : 1  |  Page : 45-50

Cognitive impairment among Hindi mental state examination positive community-dwelling rural older adults

Department of Geriatric Mental Health, King George's Medical University, Lucknow, Uttar Pradesh, India

Date of Submission18-Nov-2019
Date of Decision06-Dec-2019
Date of Acceptance01-Feb-2020
Date of Web Publication29-Jun-2020

Correspondence Address:
Dr. Rakesh Kumar Tripathi
Department of Geriatric Mental Health, King George's Medical University, Lucknow, Uttar Pradesh
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Source of Support: None, Conflict of Interest: None

DOI: 10.4103/jgmh.jgmh_40_19

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Background: Cognitive impairment is emerging as one of the greatest mental health challenges in older adults. Its proper screening is required primarily. This article aimed to determine the usefulness of cognitive screening and assessment tools for ascertaining cognitive impairments among community-dwelling rural older adults. Methods: Lucknow rural elderly project was funded by the Indian Council of Medical Research, carried out in randomly selected rural areas of Lucknow district. The present article is based on the archived data of the same project. We have analyzed 1243 patients' data, who participated in the referred study. Data related to sociodemographic details, Hindi Mental State Examination (HMSE), were extracted. There were 81 patients who screened as HMSE positives (scored ≤23). These patients were then assessed using the Cambridge Examination for Mental Disorders of the Elderly-Revised to reach to a diagnostic category as per the International Classification of Diseases-10th Revision DCR criteria. Further, a triad of Brief Cognitive Rating Scale (BCRS), Functional Assessment Staging (FAST), and Global Deterioration Scale (GDS) administered on the cognitively impaired patients. The data were analyzed by employing SPSS version 15. Results: Among HMSE positives, 81.5% (66) had a diagnosable cognitive impairment and 18.5% (15) non-cases. FAST, BCRS, and GDS had concordant findings and were found to be effective instruments for the assessment of severity of cognitive decline. Conclusion: HMSE is a useful cognitive screening tool for rural older adults. A triad of BCRS, and GDS is found to be useful in determining the severity of cognitive impairment.

Keywords: BCRS, cognitive impairment, dementia, FAST, GDS, HMSE, memory, rural older adults

How to cite this article:
Pandey NM, Tripathi RK, Tripathi SM, Singh B, Tiwari SC. Cognitive impairment among Hindi mental state examination positive community-dwelling rural older adults. J Geriatr Ment Health 2020;7:45-50

How to cite this URL:
Pandey NM, Tripathi RK, Tripathi SM, Singh B, Tiwari SC. Cognitive impairment among Hindi mental state examination positive community-dwelling rural older adults. J Geriatr Ment Health [serial online] 2020 [cited 2023 Jan 30];7:45-50. Available from:

  Introduction Top

The prevalence of cognitive decline and dementia is on the rise in the elderly population. Studies indicate that the cases of dementia will increase rapidly in low- and middle-income countries.[1] Public awareness about dementia is low in India, and at times, people are unable to differentiate between dementia and age-related decline.[2] It is well-documented that dementia begins imperceptibly and therefore is remained unrecognized at its early stages. Epidemiological studies in geriatric mental health focusing on dementia are few and limited to some of the states of the country. However, the available studies report the variable prevalence of dementia in India, i.e., between 1.4% to 9.1%.[3],[4],[5],[6],[7],[8],[9],[10],[11],[12],[13] It is estimated that about 3.6% of older adults are suffering from one or other kinds of dementia.[14] As per this statistics, in India, around 3.50 million older adults (aged 60 years and above) have one or other kinds of cognitive impairment. For optimum channelization of the resources, there is a need of adequate understanding of the prevalence of the disease burden. At the same time, considerations for developing proper assessment tools and establishing the usefulness of available screening and assessment tools are also needed to be studied. This will help in understanding the disease, its burden, and status of the disease in a comprehensive manner, which further may in making strategies for care, management, and prevention plans.

Cognitive assessments include screening as well as a thorough investigation of various higher functions of the brain including memory, attention, orientation, language, executive functions (planning activities), and praxis (sequencing of activities). Various assessment tools are available for these examinations. The Mini Mental State Examination (MMSE) is a widely acknowledged and practiced tool for cognitive assessment of older adults.[15],[16],[17],[18] This is an appreciated instrument and is being applied globally as a screening tool to rule out cognitive impairment whether it is age-associated cognitive decline, mild cognitive impairment (MCI), or dementia. It also gives a detailed map of the higher cognitive function of older adults and is therefore translated and modified in several languages including Hindi.[17],[18] Hindi Mental State Examination (HMSE)[17] is a standardized and widely used tool in the Hindi-speaking belt of the country. To assess the magnitude of cognitive impairment and determine stages of dementia in older adults, a triad of Brief Cognitive Rating Scale (BCRS),[19] Global Deterioration Scale (GDS),[20] and Functional Assessment Staging (FAST)[21] is also widely used and recommended. The GDS staging procedure is used to assist family members and professionals around the world in understanding the nature and course of Alzheimer's disease (AD).[22] The FAST staging procedure is mandated by the US government for certain purposes.[23] All of the elements of GDS/BCRS/FAST staging system have been used worldwide and have been used in clinical trials of two of the drugs currently marketed for Alzheimer's management.[24] However, these tools are also being used to assess the magnitude and stage of cognitive impairment in hospital settings or epidemiological studies.

To screen and determine cognitive impairment/decline in the elderly, a large epidemiological study [13] applied HMSE to screen suspects of cognitive impairment; screened cases were further evaluated on Cambridge Examination for Mental Disorders of the Elderly-Revised (CAMDEX-R)[25] and diagnosed cases of dementia were further assessed on BCRS,[19] GDS [20] and FAST.[21] This study was titled ”an epidemiological study of prevalence of neuropsychiatric disorders with special reference to cognitive disorders amongst rural elderly”[11] and funded by the Indian Council of Medical Research (ICMR). The present article is based on the archived data of the same study and describes the details of cognitive assessment in probable cases (HMSE positives) of cognitively impaired older adults. The study provides an analytical overview about precision of the tools, and the data were analyzed with the objectives to (i) find out usefulness of the HMSE tool by observing the prevalence of true (patients with any cognitive impairment/disorder or psychiatric illness) and false-positive cases (no cognitive impairment/disorder or psychiatric illness) in HMSE positive and also (ii) to determine the usefulness of various tools applied in the study, i. e., BCRS,[19] FAST,[21] and GDS.[20]

  Methods Top

This article is based on the archived data of Bakshi Ka Talab of Lucknow rural elderly study,[11] which was an exploratory study and detailed methodology has been published in the year 2013.[13] Ethical clearance of the study was obtained (vide letter no. 1532/R; Cell-06 dated December 5, 2006). The study was carried out by a trained research staff with fair inter-rater reliability on the tools applied. Villages of Bakshi Ka Talab were selected in consultation with the block officials to yield elderlies aged 55 years and above. A total of 17 villages were identified and selected for the study and a total of 11260 population were covered. Data obtained on the following tools were extracted and used for the present article:

  • Household screening form to identify households where individuals aged 55 years and above were residing
  • Socioeconomic status (SES) Scale:[26] SES of the persons was determined through a detailed assessment on the SES Scale “A scale for the assessment of socioeconomic status.” There are seven domains investigated in the scale for determining the SES of a family which are as follows: 1 – house, 2 – material possessions, 3 – education, 4 – occupation, 5 – economic, 6 – possessed land/house cost, and 7 – social profile. A maximum of 10 points are awarded in each domain totaling up to maximum of 70. The scores categorize persons into five SES classes, i.e., score 0–18: lower class; 18–33: lower middle class; 33–48: middle class; 48–63: upper middle class; and 63–70: upper class. For this study, lower middle (18–33) and upper middle (48–63) classes are merged in middle class (33–48) as there are a large number of middle-class persons in India, especially in Northern region
  • Screening schedules for “in” individuals aged 55 years and above:

    • Informed consent form for index patients and their caregivers
    • Hindi Mental State Examination (HMSE):[17] The Indo-U. S. project developed a modified version of MMSE, known as the Hindi Mental State Examination (HMSE), specifically to overcome educational and language bias when screening rural illiterate elderly people for cognitive impairment in India. HMSE has a high sensitivity (0.81) and specificity (0.60).[27] This examination was used in pilot phase of the study only to assess applicability of the MMSE and the HMSE to the urban elderly of India, and a high correlation (r = 0.86) with MMSE score for literate elderly was established.[18]

  • Assessment tools for cognitive decline/impairment: Hindi-translated version of the standardized English tools was administered
  • CAMDEX-R:[25] CAMDEX-R consists of eight sections for complete assessment of an older adults: Section A – clinical information about the current condition, past history, and family history of the patient; B – Cognitive function Cambridge cognitive ; C – interviewer's observation on the patients' appearance and behavior; D – physical and neurological examination; E – results of laboratory tests; F – medication received by the patient; G – additional information; H – structured interview with the relative/caregiver. Inter-rater reliability of the CAMDEX ranged from 0.83 to 0.94 for the patient interview. It also gives diagnosis based on the criteria of the International Classification of Diseases-10th Revision (ICD-10) and Diagnostic and Statistical Manual of Mental Disorders-4th Edition
  • ICD-10[28]
  • Assessment tools for the severity of cognitive decline/deterioration:

    • BCRS:[19] Reisberg and Ferris developed the BCRS in 1988. It is divided into five axes: concentration, recent memory, past memory, orientation, and function/self-care. The validity of the scale has been assessed and it was found to be satisfactory. Reliability is generally about 0.9 for the total score and is more than 0.8 for all five axes taken together. Inter-rater reliability is more than 0.9 for all axes. Specificity and sensitivity of BCRS is 100% at cutoff score 4. BCRS is a seven-point rating scale. Rating 1 denotes no subjective or objective impairment in cognitive function, 2 – subjective impairment/dysfunction, and 3–7 – objective impairment
    • GDS:[20] The GDS, developed by Dr. Barry Reisberg, provides caregivers an overview of the stages of cognitive function for those suffering from a primary degenerative dementia such as AD. It is broken down into seven different stages. Stages 1–3 are the pre-dementia stages. Stages 4–7 are the dementia stages. Beginning in Stage 5, an individual can no longer survive without assistance. Within the GDS, each stage is numbered (1–7), given a short title (i.e., forgetfulness, early confusional, etc.) followed by a brief listing of the characteristics for that stage. Caregivers can get a rough idea of where an individual is at in the disease process by observing that individual's behavioral characteristics and comparing them to the GDS. The correlation of the GDS with the Mini Mental Status Examination was 0.9 (P < 0.001)[29]
    • FAST:[21] The FAST is a rating scale which assesses in detail the progression of functional change in aging and AD in seven major stages and a total of 16 successive stages and substages. The researches support the optimal concordance of the FAST stages and substages with the GDS and BCRS. The FAST demonstrated intraclass rater consistency as 0.86 and intraclass rater agreement as 0.87. A strong correlation (r = 0.9) was found between stages of FAST and GDS.[30]

Procedure of translation of the tools

Three translators, well versed in English and Hindi, had translated the original English versions of BCRS, GDS, FAST, and CAMDEX-R into Hindi independently. To agree on a pre-final translated Hindi version (PFHV) and preserve the originality of the tools, translated items were compared item by item. PFHV tools were administered to 10 literate and 10 illiterate persons aged 60 years and above, drawn from a nearby community to know the comprehensibility of the items. The final translated Hindi versions of the tools were validated by three bilingual mental health professionals.


Families with individuals aged 55 years and above living in the identified villages were listed and screened as “in families” for the study. Adequate precautions were taken to ascertain the age of the patients. Consent to participate in the study was obtained from “in families” and family details were recorded on SDP and SES was assessed. To identify suspects for probable cognitive problems, participants were screened on HMSE. CAMDEX-R [26] was further applied by a trained research staff on HMSE-positive patients (patients scores 23 or less) to ascertain the diagnosis. The diagnosis was made according to the diagnostic criteria of ICD-10 DCR based on the findings of CAMDEX-R. Patients diagnosed as cases of MCI and dementia were further assessed on BCRS, FAST, and GDS. Data were analyzed by applying SPSS-15.

To rule out false-negative cases, 3% of the total HMSE-negative patients were also assessed on CAMDEX-R. These assessments were done within 1 month after the screening on HMSE. However, no one of these patients had a symptom profile to lead to a diagnosis. Following this, the older adults were categorized as per their mental and physical health status in different categories. MCI was diagnosed in individuals who had cognitive impairments over the expected range of scores as per their age and education but did not interfere significantly with their daily activities.[31]

The detailed flowchart of the procedure right from population screening to assessment is provided as following [Figure 1].
Figure 1: Flow chart of the study

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  Results Top

A total of 1320 (11.7%) individuals were at the age of 55 years and above, of these 1243 (94.2%) individuals gave consent to participate in the study and there households were labeled as “in families.” After getting the sociodemographic details, the HMSE was applied on all the participants. Among the total participants, 81 (6.5%) were found to be HMSE positive. Moreover, these + ves were further assessed on CAMDEX-R for making ICD-10-based diagnosis. Of these, only 66 were diagnosed as a case of cognitive impairment (MCI or dementia). The remaining 15 were non case. The detailed sociodemographic profile of these patients is described in [Table 1].
Table 1: Details of sociodemographic profile of the Hindi Mental State Examination-positive patients

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Majority of the patients were aged between 70 and 79 years, female, and belonged to lower SES as well as widowed/widower and illiterate.

Cognitive impairment, Alzheimer's' dementia, and other problems were present in 81.5% of the HMSE-positive patients. Age-wise description of positive cases is given in [Table 2].
Table 2: Age-wise description of Hindi Mental State Examination-positive patients and magnitude of cognitive impairment on triad (Brief Cognitive Rating Scale, Functional Assessment Staging, and Global Deterioration Scale)

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With the advancement in age, there was a significant decline in all areas of cognition; however, most deterioration is present in the recent memory. Further, analysis of variance (ANOVA) was also performed to observe the level of significance in the severity of cognitive decline with the advancement in age with various domains of BCRS, FAST, and GDS. The number of patients with cognitive impairment increased with the advancement in age, but ANOVA did not reveal any significant indication except for GDS and age code (p ≤ 0.01;.03;.03). Other sociodemographic variables such as SES, marital status, and sex do not reveal any significant results. Further, education-wise analysis was also not done as the number and proportion of literate patients was less, i. e., 18.5% (15).

An overall analysis of all HMSE positives was done to determine the association of various cognitive disorders on magnitude and stage of cognitive impairment. The details are shown in [Table 3] and [Table 4].
Table 3: Details of Hindi Mental State Examination+ves and its impact on magnitude and stage of cognitive impairment

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Table 4: Analysis of variance table on Hindi Mental State Examination+ves and magnitude of cognitive impairment

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[Table 3] portrays that patients with AD had more problems on all the axis of BCRS, FAST, and GDS.

[Table 4] reveals that there is a positive association between the magnitude of cognitive impairment and MCI and dementias. There is a progressive deterioration in all cognitive functions in MCI and dementias consistent with the disorder category. The mean scores obtained in the AD group show that all spheres of cognitive functioning are about two times poorer than those in MCI or other groups of disorders category. The ANOVA also reveals the same.

  Discussion Top

Majority of the patients diagnosed as a case of cognitive impairment were within the age range of 70–79 years. It indicates that advancing age makes one more prone for worsening of cognitive functions. Hence, a person approaching the age group of 70–79 years should regularly undergo assessments for cognitive functions. The proportion of females (n = 51) outnumbered males (n = 30) indicating the current trend of feminization among the elderly population which supports earlier estimates.[12],[32],[33] Majority of the studied patients were illiterate (n = 66), which is also as per the current statistics.[34]

It can be observed that majority of the patients with cognitive impairment were aged 80 years and above, and minimum cognitive impairment was in the age range of 55–59 years. This supports previous findings that cognitive decline increases with the advancement in age.[2] HMSE when employed as a screening tool on 81 patients, 81.5% (n = 66) were diagnosed to be suffering from either MCI or Alzheimer's dementia or other cognitive disorders, whereas 18.5% (n = 15) were found as “non-case” (without any diagnosable cognitive disorder). Among the persons diagnosed as “cases,” MCI, dementia, and other disorders were diagnosed in 53.1% (n = 43), 22.2% (n = 18), and 6.2% (n = 5), respectively. The present findings support some of the previous studies [15],[16],[17] and also advocate the use of HMSE as a screening tool in rural areas. A triad of BCRS, FAST, and GDS was also found to be useful tools and precisely points out the deterioration and magnitude of cognitive impairment.

[Table 4] suggests that various AXIS of BCRS have definite usefulness for assessing the severity of cognitive decline. On BCRS AXIS I (concentration), the mean scores for patients with MCI were found to be 2.14, which indicates that majority of the MCI patients either showed subjective decrement in concentration ability or minor objective signs of poor concentration, whereas in patients of dementia, the mean score was 3.22 which indicates that most responses were either minor objective signs of poor concentration or definite concentration deficit for persons of their background. BCRS AXIS II (recent memory)-mean score of 2.7 was indicative of subjective impairment only or deficit in recall of specific events evident on detailed questioning and no deficit in the recall of major recent events, whereas in patients of dementia, the mean score was 4.30, indicative of the fact that they cannot recall major events of previous weekend or week. They had scanty knowledge (general fund) or were unsure of the current president or current address. AXIS III (past memory)-MCI mean score of 2.35 means subjective impairment only where can recall two or more primary school teachers or some gaps in the past memory on the detailed questioning and persons are able to recall at least one childhood teacher and/or one childhood friend, whereas the mean for dementias 4.13 suggests clear-cut deficit as the spouse recalls more of the patient's past than the patient himself/herself. They were unable to recall childhood friends and/or teachers but knew the names of most schools attended. They confused chronology in reciting personal history or major past events were sometimes not recalled (e.g., names of schools attended). On AXIS IV (orientation), the MCI mean 2.26 indicates subjective impairment only in orientation, he/she knows the time of the nearest hour, and the location may make a mistake in time >2 h, day of week >1 day, and date >3 days. In dementia, the mean score was 3.91 which is suggestive of mistakes in time >2 h, day of week >1 day, and date >3 days or mistakes in month >10 days of year >1 month. On AXIS V (functioning and self-care), the mean on MCI 2.42 suggests that the person complains of forgetting the location of objects and has subjective work difficulties, decreased job functioning evident to coworkers, and difficulty in traveling to new locations. In dementia, the mean score of 4.17 was suggestive of decreased ability to perform complex tasks (e.g., planning dinner for guests, handling finances, and marketing) requiring assistance in choosing the proper clothing. On each AXIS of the BCRS, the mean scores were found to be highest (AXIS I – 3.22; AXIS II – 4.30; AXIS III – 4.13; AXIS IV – 3.91; and AXIS V – 4.17) for dementia, followed by that for MCI (AXIS I – 2.14; AXIS II – 2,70; AXIS III – 2.35; AXIS IV – 2.26; and AXIS V – 2.42) and then for others group of psychiatric disorders (AXIS I – 1.89; AXIS II – 2.11; AXIS III – 1.22; AXIS IV – 1.22; and AXIS V – 1.22).

The mean scores of FAST and GDS and analysis from ANOVA as well also suggest that functional impairment and global deterioration were found to be significantly higher in patients of dementia when compared to MCI and other groups of psychiatric disorders. The mean scores of FAST and GDS were found to be highest for dementia (FAST – 4.26; GDS – 3.22) followed by that for MCI (FAST – 2.16 and GDS – 2.14) and other groups (FAST – 1.22 and GDS – 1.89). The findings suggest that the triad of tools effectively assesses the extent of cognitive decline, functions, and global deterioration and is useful for epidemiological studies.

  Conclusion Top

The results of the study demonstrate that HMSE is an effective and relevant screening tool for the rural community using cutoff 23 and it is worthy of application in epidemiological studies. On further evaluation, 81% of HMSE positives were found to be cognitively impaired. A triad of BCRS, FAST, and GDS was found to be useful in determining the severity of cognitive impairment. The article describes HMSE is an effective tool to screen cognitive impairment of community-dwelling rural older adults. However, further research may be done to determine score range for HMSE positives, which can be applied in the rural community of older adults and enable the researchers, clinicians, and academicians in the assessment of cognitive impairment/decline status (age-related memory impairment, MCI, mild cognitive disorder, and dementia).


The study allowed us to explore the usefulness of various tools in the community in a cost-effective manner. There were some limitations of the study which could have enhanced the quality of the study. It did not try to investigate the pattern of individual physical illness that commonly coexists with neuropsychiatric disorders and cognitive impairment. Since it was a part of cross-sectional study based archived data, the temporality of the evolution of each disorder/s could not be investigated. Education and recall bias may be present at the time of assessment which we may fail to address during the analysis. Limited data relating to social and behavioral factors allowed inadequate analysis of factors determining distribution patterns of cognitive impairment.


The authors would like to thank ICMR, New Delhi, for funding support, study sample for participation, and research staff for their cooperation.

Financial support and sponsorship

This study was funded by ICMR, New Delhi, India.

Conflicts of interest

There are no conflicts of interest.

  References Top

Prince M. The need for research on dementia in developing countries. Trop Med Int Health 1997;2:993-1000.  Back to cited text no. 1
Shaji KS, Sumesh TP, Nakulan A. Early detection and diagnosis of dementia. In: Tiwari SC, Pandey NM, editors. Geriatric Mental Health at a Glance. Delhi, India: Ahuja Publishing House; 2014. p. 61-8.  Back to cited text no. 2
Ramachandran V, Menon MS, Ramamurthy B. Family structure and mental illness in old age. Indian J Psychiatry 1981;23:21-6.  Back to cited text no. 3
[PUBMED]  [Full text]  
Chandra V, Ganguli M, Pandav R, Johnston J, Belle S, DeKosky ST. Prevalence of Alzheimer's disease and other dementias in rural India: The Indo-US study. Neurology 1998;51:1000-8.  Back to cited text no. 4
Vas CJ, Rajkumar S, Tanyakitpisal R, Chandra V. Alzheimer's Disease: The Brain Killer. New Delhi: WHO; 2001. p. 50.  Back to cited text no. 5
Shaji S, Promodu K, Abraham T, Roy KJ, Verghese A. An epidemiological study of dementia in a rural community in Kerala, India. Br J Psychiatry 1996;168:745-9.  Back to cited text no. 6
Shaji KS, Kishore NR, Lal KP, Pinto C, Trivedi JK. Better mental health care for older people in India. Indian J Psychiatry 2004;46:367-72.  Back to cited text no. 7
[PUBMED]  [Full text]  
Shaji KS, Jithu VP, Jyothi KS. Indian research on aging and dementia. Indian J Psychiatry 2010;52:148-52.  Back to cited text no. 8
[PUBMED]  [Full text]  
Tiwari SC. Geriatric psychiatric morbidity in rural northern India: Implications for the future. Int Psychogeriatr 2000;12:35-48.  Back to cited text no. 9
Tiwari SC, Kar AM, Singh R, Kohli VK, Agarwal GG. An Epidemiological Study of Prevalence of Neuro-psychiatric Disorders with Special Reference to Cognitive Disorders, Amongst (Urban) Elderly- Lucknow Study. ICMR Report, New Delhi; 2009.  Back to cited text no. 10
Tiwari SC, Kar AM, Singh R, Kohli VK, Agarwal GG. An Epidemiological Study of Prevalence of Neuro-psychiatric Disorders with Special Reference to Cognitive Disorders, Amongst (Rural) Elderly- Lucknow Study. ICMR Report, New Delhi; 2010.  Back to cited text no. 11
Tiwari SC, Pandey NM, Singh N. Mental health morbidity in North Indian rural elderly: Issues and challenges. Indian J Geriatr Ment Health 2011;7:68-82.  Back to cited text no. 12
Tiwari SC, Srivastava G, Tripathi RK, Pandey NM, Agarwal GG, Pandey S, et al. Prevalence of psychiatric morbidity amongst the community dwelling rural older adults in Northern India. Indian J Med Res 2013;138:504-14.  Back to cited text no. 13
[PUBMED]  [Full text]  
Tiwari SC, Pandey NM. Status and requirements of geriatric mental health services in India: An evidence-based commentary. Indian J Psychiatry 2012;54:8-14.  Back to cited text no. 14
  [Full text]  
Folstein MF, Folstein SE, McHugh PR. “Mini-mental state”. A practical method for grading the cognitive state of patients for the clinician. J Psychiatr Res 1975;12:189-98.  Back to cited text no. 15
Tombaugh TN, McIntyre NJ. The mini-mental state examination: A comprehensive review. J Am Geriatr Soc 1992;40:922-35.  Back to cited text no. 16
Ganguli M, Raicliff G, Chandra V, Sharma S, Gilby J, Pandav R, et a l. A Hindi version of the HMSE: The development of a cognitive screening instrument for a largely illiterate rural elderly population of India. Int J Geriatr Psychiatry 1995;1:367-77.  Back to cited text no. 17
Tiwari SC, Tripathi RK, Kumar A. Applicability of the Mini-Mental State Examination (MMSE) and the Hindi Mental State Examination (HMSE) to the urban elderly in India: A pilot study. Int Psychogeriatr 2009;21:123-8.  Back to cited text no. 18
Reisberg B, Ferris SH. Brief Cognitive Rating Scale (BCRS). Psychopharmacol Bull 1988;24:629-36.  Back to cited text no. 19
Reisberg, Ferris SH, Leon MJD, Crook T. Global Deterioration Scale (GDS). Psychopharmacol Bull 1988;24:661-3.  Back to cited text no. 20
Reisberg B. Functional assessment staging (FAST). Psychopharmacol Bull 1988;24:653-60.  Back to cited text no. 21
Alzheimer's Association 2006. Available from: [Last accessed on 2019 Nov 07].  Back to cited text no. 22
Centers for Medicare & Medicaid Services; 2019. Specifications for the Cross Setting Function Quality Measure Adopted in the Home Health Quality Reporting Program. 2019. Available from: [Last accessed on 2020 Feb 18].  Back to cited text no. 23
Reisberg B. Diagnostic criteria in dementia: A comparison of current criteria, research challenges, and implications for DSM-V. J Geriatr Psychiatry Neurol 2006;19:137-46.  Back to cited text no. 24
Roth M, Tym E, Mountjoy CQ, Huppert FA, Hendrie H, Verma S, et al. CAMDEX. A standardised instrument for the diagnosis of mental disorder in the elderly with special reference to the early detection of dementia. Br J Psychiatry 1986;149:698-709.  Back to cited text no. 25
Tiwari SC, Kumar A, Kumar A. Development standardization of a scale to measure socio-economic status in urban rural communities in India. Indian J Med Res 2005;122:309-14.  Back to cited text no. 26
Pandav R, Fillenbaum G, Ratcliff G, Dodge H, Ganguli M. Sensitivity and specificity of cognitive and functional screening instruments for dementia: The Indo-U.S. Dementia Epidemiology Study. J Am Geriatr Soc 2002;50:554-61.  Back to cited text no. 27
World Health Organisation. ICD-10 Classifications of Mental and Behavioural Disorder: Clinical Descriptions and Diagnostic Guidelines. Geneva: World Health Organisation; 1992.  Back to cited text no. 28
Reisberg B, Sclan SG, Franssen E, deLeon MJ, Kluger A, Torossian C, et al. Clinical stages of normal aging and Alzheimer's disease: The GDS staging system. Neurosci Res Commun 1993;13:S51-4.  Back to cited text no. 29
Sclan SG, Reisberg B. Functional assessment staging (FAST) in Alzheimer's disease: Reliability, validity, and ordinality. Int Psychogeriatr 1992;4 Suppl 1:55-69.  Back to cited text no. 30
Petersen RC, Smith GE, Waring SC, Ivnik RJ, Tangalos EG, Kokmen E. Mild cognitive impairment: Clinical characterization and outcome. Arch Neurol 1999;56:303-8.  Back to cited text no. 31
United Nations. The Woman Ageing Situations. New York: Centre for Social Development and Humanitarian Affairs, United Nations; 1991.  Back to cited text no. 32
Venkatesh S, Vanishree MR. Feminization among elderly population in India: Role of micro financial institutions. Glob J Finance and Manag 2014;6:897-906.  Back to cited text no. 33
Situation Analysis of the Elderly in India; 2011. Available from: [Last accessed on 2020 Jan 17].  Back to cited text no. 34


  [Figure 1]

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

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