INTRODUCTION
Aging is a global phenomenon. Worldwide, the proportion of older adult population consisting of people aged ≥60 years is growing faster than any other age group.1) According to the World Health Organization, the 703 million older adult individuals in the world today is expected to increase to 1.5 billion by 2050.2) In Malaysia, the older adult population (age ≥65 years) is also the fastest-growing age group. In 2017, 6.2% of 32.3 million people in Malaysia were aged over 65 years. In terms of ethnicity, 7% of Malaysian older adults are from the Malay population. The Malaysian Healthy Ageing Society reported that the proportion of Malaysians aged 60 years and older had increased from 6.2% in 2000 and is predicted to reach 13.6% by 2030.3) This increasing trend of aging population implies that Malaysia is moving towards an aging population. Based on data reported by the National Population and Family Development Board (LPPKN), Malaysia is predicted to reach aging population status by 2035, in which citizens aged 60 years and older will comprise 15% of the total population (5.6 million).4)
The occurrence of a variety of conditions and disorders unique to this age group has increased notably in recent years, in line with the rapidly aging society. Older adults experience progressive declines in their biological and psychological functions. A comprehensive assessment is thus required to ensure a holistic approach in their care plans. Comprehensive Geriatric Assessment (CGA) is a multidimensional and interdisciplinary diagnostic process to determine the medical, psychological, and functional capabilities of older adults. CGA has been applied widely in many medical contexts including orthopedic5), coronary artery disease6), and multimorbidity.7) Its purpose is tailored towards developing a coordinated and integrated plan for treatment and long-term follow-up. The basic components of the CGA include functional status, co-morbidity, cognition, depression, polypharmacy, nutrition, presence of geriatric syndromes, and socioeconomic factors. While integrating standard medical diagnostic evaluation, CGA emphasizes the quality of life (QOL) and functional status, prognosis, and outcome that entail a workup with more depth and breadth.8-10)
Most of the standardized questionnaires in CGA that are developed in English-speaking countries are not applicable in Malaysia, which is a country with a multi-ethnic population and more than one spoken language. Thus, the questionnaires must be translated into the local Malay language, adapted to the local culture, and validated against the original version while also considering important cultural differences. The Malay language is the language of knowledge and union and it is the national language in Malaysia.11) This language is related to the Austronesian family of Malay, which has spread across nearly half of the world, with more than 300 million speakers, making it the fourth-largest language globally in terms of the number speakers.12) Thus, the objectives of this study were to translate the original English version of CGA questionnaires into the Malay language and determine the reliability and validity of this Malay version among the Malaysian older adult population.
MATERIALS AND METHODS
Instrument Translation
The CGA questionnaire consists of five sections (A to E): Section A enquires about participant socio-demographic data, medical conditions, and health and nutritional risk factors, while Sections B–E comprise the screening tools to assess nutritional status (Mini Nutritional Assessment-Short Form [MNA-SF]), QOL (36-items Short Form Health Survey version 2.0 [SF-36 Health Survey v2]), functional capability (activities of daily living [ADLs] and instrumental activities of daily living [IADLs]), and depression status (Geriatric Depression Scale-Short Form [GDS-SF]). All five sections were translated together according to the international guidelines after obtaining permission from the respective original authors of the questionnaires.
The first step of the translation involved the forward translation of the original English questionnaire into the Malay language by two qualified and independent linguistic translators fluent in both languages. The translators were requested to produce a forward translation that was conceptually equivalent to the original English-version questionnaire. Each translator produced a forward translation version without mutual consultation. The translations were then reviewed and reconciled by the researchers to create a preliminary version of the forward translation. This version was subsequently given to a third translator, who translated the questionnaire back into English. The backward translation version was compared to the original English questionnaire by the researchers, with consideration regarding whether the items were rewritten using the same words (literal assessment) or if the original meaning had been retained (semantic equivalence). When discrepancies between backward translation and original versions arose, the word choices were discussed among the researchers and translators until a final forward translation version was reconciled. The comprehensibility and appropriateness of the language in the Malaysian cultural context were emphasized during the translation procedure.
Ethical Clearance
This study was approved by the Malaysia Research Ethics Committee (MREC) of the Ministry of Health Malaysia (Registration No. (2)dlm.KKM/NIHSEC/08/0804/P10-337) and the Human Research Ethics Committee (HREC) of USM (No. USMKK/PPP/JEPeM (228.4[1.6])).
Content and Face Validity
An expert team comprising seven geriatricians, physicians, dietitian, and lecturers assessed the final forward translation questionnaire for its content. They made their judgments about the relevance of the questionnaire and suggested the use of better terms and format.
For face validity, we tested the questionnaire in 10 geriatric patients aged ≥65 years who were admitted to the medical wards in Hospital Universiti Sains Malaysia (HUSM) after obtaining informed consent from all participants. The researcher went through each item and allowed the patients to clarify their doubts and comment on the questions and response choices. The researchers discussed these comments and developed the final Malay version of the CGA questionnaire, which was then evaluated for its reliability and validity among Malaysian geriatric patients.
Internal Consistency Reliability and Construct Validity
Study design and participants
A cross-sectional study was conducted using convenience sampling at the Medical Outpatients Department (MOPD) and medical wards of Hospital Sultanah Nur Zahirah (HSNZ), Kuala Terengganu, Malaysia. This study was approved by the MREC of Ministry of Health, Malaysia in November 2010.
The inclusion criteria were geriatric patients aged ≥65 years and admitted to the medical wards or who visited the MOPD. We identified eligible participants from the patient admission list at the admission counter of the medical wards and the patient appointment list located at the registration counter of daily MOPD. A trained interviewer collected data collection via face-to-face interviews.
Measures
This study integrated a revised MNA-SF13) in the CGA tool to screen the patients’ nutritional status. The revised MNA-SF consisted of six items and included the calf circumference (CC) parameter as a substitute for body mass index (BMI). This change enabled its application to immobile individuals or in circumstances where the weight and height could not be measured. A total score ranging from 0–14 distinguishes patients into those with normal nutritional status (12–14 points), risk of malnutrition (8–11 points), and who are malnourished (0–7 points).
The CGA applies the SF-36 Health Survey v214) with standard 4-week recall periods to assess the health-related QOL among the participants. It contained 36 items across eight different scales of health; namely: physical functioning (PF), role limitations due to physical problems (RP), bodily pain (BP), general health (GH), vitality (VT), social functioning (SF), role limitations due to emotional problems (RE), and mental health (MH). These eight scales were further aggregated into two summary measures; namely, physical (21 items: PF, RP, BP, GH) and mental (14 items: VT, SF, RE, MH) components. The survey additionally included a single-item scale on health translation (HT) to describe the comparison between current health status and health status 1 year prior. The response choices of these 36 items based on 3-, 5-, or 6-point scales, with item scores of 1–3, 5, or 6 points. We recoded the scores for 11 items so that all 36 items would score in the same direction, with higher values indicating better health status.
The functional capacity of patients was measured as the ability to perform both the ADL and IADL. This entailed the use of the 10-item Barthel Index15,16) for the ADL; and 7-item IADL subscale of the Older Americans Resources and Services (OARS)17) for the IADL assessment.
The Barthel Index15,16) measures patients’ level of independence using 10 basic activities rated with scores ranging between 0 and 3 and a maximum total score of 20 points. Scores of 15–19 and <14 points indicated mild and moderate to severe functional disabilities, respectively.
The IADL subscale of the OARS17) assesses patients’ level of independence on seven instrumental activities. The questionnaire used three levels of scoring (0=fully dependent; 1=requiring some help; 2=fully independent) for a total score ranging from 0–14 points. Scores <10 points indicated functional disability.
The GDS-SF18) is modified from the original GDS and used to screen patient depression levels. As a 15-item scale with a “yes/no” format, 10 items suggest probable depression for negative responses (negative items); the remaining 5 items suggest probable depression when answered positively (positive items). The scores ranged from 0–15, whereby 1 point was given for each response suggestive of probable depression. Points ≥5 were indicative of the risk of depression.
Along with MNA-SF, SF-36, GDS-SF, ADL, and IADL assessment, the questionnaire also integrated variables on socio-demographic characteristics, medical conditions, and health and nutritional risk factors. Patients’ medical records were reviewed for other related information besides the interview.
Statistical analysis
Data entry and analysis were performed using SPSS Statistics for Windows, version 18.0 (SPSS Inc., Chicago, IL, USA). This study assessed the reliability of the CGA questionnaire based on the internal consistency from the item-total correlation (ITC) and Cronbach’s alpha coefficient for each of the screening tools (MNA-SF, SF-36, ADL, IADL, and GDS-15).
The corrected ITC consisted of the Pearson correlation coefficient between the score for the individual item and the sum of the scores on the remaining items, which was computed to assess the extent to which an individual item was related to the remainder of its scale. Values >0.30 indicated item appropriateness.
We performed Principal Component Analysis (PCA; exploratory factor analysis) followed by a varimax rotation to identify whether the items in the questionnaire were structured comparably to the original questionnaires. We first used Bartlett’s test of sphericity (p<0.05) and Kaiser-Meyer-Olkin (KMO) measure of sampling adequacy (with values >0.60 considered acceptable) to measure the appropriateness of the factor analysis. The number of factors was determined by examining the eigenvalues (recommended value ≥1.0) and via a scree plot (recommended to determine the cutoff point at which the slope appeared to change into minor decrement). The ability of the factors to represent the data was expressed by the percentage of explained variance (recommended range, at least 50%–60%). We also examined the factor loading of the items (recommended value >0.4).
RESULTS
General Participant Characteristics
A total of 166 older adult patients (110 and 56 patients from MOPD and the wards, respectively) met the inclusion criteria and agreed to participate in this study with written consent. Table 1 shows the general characteristics of the participants. Their mean age was 70.92±4.64 years (range, 65–92 years). Most respondents were male (73.5%), Malay (98.2%), married (77.1%), literate (had formal education, 74.7%), living with family (93.4%), retired (73.5%), non-smoker/ex-smoker (90.4%), and did not depend on others economically (61.4%).
Validity and Reliability
MNA-SF
The Cronbach’s alpha coefficient was 0.62. Regarding item internal consistency, the corrected ITC of the 6 items in the scale ranged from 0.18 to 0.60, with 2 items not achieving the accepted value. Their corrected ITC values were 0.21 and 0.18 (Table 2).
A PCA of MNA-SF was feasible in this study, as indicated by the significant Bartlett’s test of sphericity (p<0.001) and the KMO measure of 0.63. Factor analysis with no structural restrictions revealed a two-factor solution, which explained 62.0% of the total variance. Four items were grouped under the first factor, the item contents of which were more related to the modifiable nutritional and functional risk factors. Two items were grouped under the second factor, the item contents of which were more related to patient diseases and comorbidities. All factor loadings were above 0.40 and ranged from 0.58 to 0.87 (Table 3).
SF-36 Health Survey v2
All correlation coefficients between the items and the remainders of their own scales were >0.30, except for one item within the GH (“I expect my health to get worse”, corrected ITC=0.23). For all eight subscales of the SF-36 health survey, the Cronbach’s alpha coefficients achieved the minimum criterion of 0.70, ranging from 0.70 to 0.98 (Table 2).
PCA with varimax rotation was performed with 35 items of the SF-36 Health Survey. An item on HT (“Compared to one year ago, how would you rate your health in general now?”) was excluded from the factor analysis as it was not included in the eight scales scores. The Bartlett’s test of sphericity was highly significant (p<0.001), while the KMO measure was high (0.92). An 8-factor solution explaining 76.5% of the observed variance was generated. Table 4 shows the rotated component matrix and total variance explained by factors 1–8 in the whole group. The 10 items of the subscale PF were shared between factors 1 and 6. Factor 2 included all 3 items of the RE subscale and 4 items the MH subscale that explored aspects such as sadness/happiness. Items exploring RP loaded on factor 3, while those exploring BP and SF loaded on factor 5. All 4 items of the VT subscale were distributed between factors 4 and 7, with those positive items being differentiated from the negative items. Besides the items of the VT subscale, factor 2 also loaded with 4 items of the GH subscale and one item of the MH subscale. Factor loading of all items within the eight subscales was satisfactory (above 0.40), ranging from 0.49 to 0.86 (Table 4).
ADL-Barthel Index and IADL-OARS
Both showed good internal consistency reliability, as indicated by their corrected ITC (>0.3) and Cronbach’s alpha coefficient (>0.70) (Table 2).
Table 5 shows the results of the factor analysis. For ADL-Barthel Index, the result of Bartlett’s test of sphericity was significant (p<0.001) and the KMO measure was acceptable (0.85). A two-factor solution explaining 74.0% of the observed variance was generated. Eight items grouped under the first factor, the item contents of which were more related to patient’s self-care functioning. Next, two items grouped under the second factor, the item contents of which were more related to patient physiological needs. All factor loadings were above 0.40, ranging from 0.64 to 0.90 (Table 5).
For IADL-OARS, the result of Bartlett’s test of sphericity was significant (p<0.001) and the KMO measure was acceptable (0.76). A two-factor solution explaining 67.7% of the observed variance was generated. Five items grouped under the first factor, while two items related to domestic chores grouped under the second factor. All factor loadings were above 0.40, ranging from 0.52 to 0.87 (Table 5).
GDS-SF
The Cronbach’s alpha coefficient was 0.75. Regarding item internal consistency, the corrected ITC ranged between 0.12 and 0.56 and three items did not achieve an acceptable value (>0.30) (Table 2).
We performed PCA with varimax rotation. The result of Bartlett’s test of sphericity was significant (p<0.001) and the KMO measure was acceptable (0.72). A five-factor solution explaining 60.9% of the total variance was generated. The loadings of factors on the items did not reflect an easily interpretable pattern of psychological dimensions. All factor loadings were above 0.40, ranging from 0.45 to 0.89 (Table 6).
DISCUSSION
The translation, cultural adaptation, and validation of questionnaires are time-consuming and demanding tasks. However, these tasks are necessary to be able to compare results from studies performed in different countries and cultures. The results of this study provide preliminary evidence of the psychometric properties behind the Malay translation version of the CGA questionnaire in Malaysia. Due to the good reliability and validity of their original English versions, the current version selected and implemented the MNA-SF, SF-36 Health Survey, Barthel Index, IADL subscales of OARS, and GDS-SF for the comprehensive screening and assessment among geriatric patients. Most of our results suggested that the CGA questionnaire attained good psychometric characteristics in the study population of 166 Malay medical geriatric patients.
The MNA-SF showed moderate reliability, as measured by internal consistency, with a Cronbach’s alpha coefficient of 0.62. Two items of MNA-SF had low corrected ITC, which indicated their poor correlation with the overall scale. This finding is probably due to the item variability of the MNA-SF, which consists of a number of items associated with malnutrition (i.e., food intake, weight loss, mobility, comorbidities, etc.). Omitting these two items from the analysis increased the Cronbach’s alpha coefficient to 0.66 from 0.62. However, the MNA-SF was developed as a comprehensive instrument reflecting a number of factors associated with malnutrition; thus, no items could be omitted from the instrument. The two latent factors solution of the MNA-SF revealed in our factor analysis further supported the results of the reliability test, as the two items mentioned above were separated into a new factor with adequate factor loadings around 0.90.
The Malay version of the SF-36 Health Survey showed satisfactory results in the study population. The reliability, as measured by the Cronbach’s alpha coefficient, ranged from 0.70 for GH and 0.98 for RP. All items passed the tests for item internal consistency, except for one item in GH (“I expect my health to get worse”, corrected ITC=0.23). This finding is supported by the results of a study by Tseng et al.19) that also reported a slightly lower corrected ITC for this item in GH, along with another three items in the PF, RE, and MH. Similarly, another study also reported a lower corrected ITC for that particular item in GH.20) Factor analysis of the SF-36 generally supported the eight-subscale structure of the original SF-36.
In this study, we observed good reliability for both the ADL-Barthel Index and IADL-OARS, indicating that the Malay versions maintained the original scale reliability. For the Barthel Index, the two latent factors revealed by the factor analysis were consistent with those reported previously.21,22) As impairments to the bowels and bladder were not common in the study population, the between-individual variation of participants’ ratings on these two items were small. The relatively high scores and small variances of these two items may explain the two-factor structure of the Malay version of the Barthel Index. For the IADL-OARS, two items related to domestic chores were separated into a new factor with adequate factor loadings (around 0.90). This finding is probably due to the predominance of men (73.5%) in this study, who were not involved in domestic chores.
Three GDS-SF items did not pass the tests for item internal reliability, indicated a lack of discriminatory power in differentiating cases and non-cases of depression in the study population. While the Cronbach’s alpha coefficient increased to 0.78 from 0.75 if these three items were omitted from the analysis, they were not omitted from the tool as the result of this study were inconsistent with those reported in another local study conducted by Teh and Hasanah.23) The prior work reported that only one item (“Do you prefer to stay at home, rather than going out and doing new things?”, corrected ITC=0.09) had no discriminatory power in the local context. The five-factor solution that explained 60.9% of the variance was difficult to interpret; thus, a dimensional structure similar to that in the original English version was not confirmed in the study population.
The CGA questionnaire can be used as a screening tool to identify geriatric syndrome such as medical, psychosocial, and functional issues to allow the subsequent appropriate provision of interventions to older adult patients. The CGA may be used to reduce the length of stay, morbidity, and mortality, maximize overall well-being, and improve QOL.24) However, the present study has some limitations. First, we assessed no parameters related to cognitive and physical performance. Thus, this tool might not be able to be applied to thoroughly assess the nutritional status of older adults. Next, this study has possible issues with selection bias and generalizability as the respondents were sampled only from HSNZ, Terengganu, Malaysia. Therefore, we recommend that future studies include older adult patients from different states (north, south, and west regions) to fully assess the CGA questionnaire applicability in Malaysia.
In conclusion, the Malay version of the CGA questionnaire showed evidence of satisfactory internal consistency reliability and construct validity in the context of the study population comprising 166 medically geriatric patients. Further studies should explore the structural validity and stability of this questionnaire across different diagnostic groups and populations in Malaysia.
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