The essence of accommodating older adults into the social care sector in Malaysia

Population ageing puts pressure on the workforce and increase the demands for aged workforce. The demographic shifts have made the issue of healthier workers, especially those of advanced age and physically related job scopes, a fundamental aspect to employing older workers. Hence, this study aimed to explore the best practices to employ older adults into the social care sector. The social care sector was chosen in view of the nature of job and declining demand among younger workers. A qualitative study was conducted involving series of focus group discussions (FGD) with social care workers of long-term care centers in the peninsular Malaysia. Data was collected using a validated and pre-tested semi-structured interview protocol. Each focus group discussions and in-depth interviews were lasted between 45 min to 1 h. A total of 57 workers were consented for the study which was divided into young and old workers based on the mean age of 41.43 [SD ± 9.97] years old. The content of the interviews was transcribed verbatim and thematic analysis was performed to inductively identify the coding and themes within the data related to the challenges employing older workers into the social care sector. Three categories of coding were identified (individual, environmental and management factors), leading to the identification of two important themes which are healthy workplace and work autonomy. The findings indicate the needs for work culture transformations to cultivate healthy working environment and freedom of speech particularly among the older workers

Effectiveness of a community-based muscle strengthening exercise program to increase muscle strength among pre-frail older persons in Malaysia: a pilot study

Deterioration in muscle mass and muscle strength is common among the frail older persons, cause functional dependence and decrease in the quality of life. Therefore, the identification of cost-effective interventions to prevent or ameliorate frailty is crucially needed. The aim of this study is to determine the effectiveness of a Community-based Muscle Strengthening Exercise (COME) program to increase muscle strength among pre-frail older persons. This study was a quasi-experimental study. A total of 32 older persons aged 60 years and older with pre-frail symptoms were recruited from the community center. The COME was developed based on the Growing Stronger program and the Otago Home Exercise Program. COME was designed to strengthen all of the major muscle groups in the upper and lower extremities. The exercise program was conducted for 12 weeks and divided into 3 parts; (1) to strengthen the body slowly and gently, using only body weight, (2) to introduce dumbbells and ankle weights to increase strength and (3) to add various new ways to boost strength even more. Functional tests were measured before and after the intervention. The results revealed non-significant p-value for pre- and post-intervention comparison for all study outcomes. Observing the values of mean difference, the study intervention was shown to have slightly improved the time up and go (Mean difference = -0.25), and sit-to-stand duration (Mean difference = -0.41) as well as the handgrip strength (Mean difference = 0.68) among the participants. On the assessment of Cohen ES, all three improvements exhibited small effect sizes. Sit-to-stand duration was shown to have most benefited from the intervention with highest ES among the outcome variables (ES = 0.20). COME intervention program among pre-frail older persons showed favorable trend toward improvement of upper and lower extremities muscle strength. This study should be further tested in randomized control trial to confirm its effectiveness

Characteristics of COVID-19-related deaths among older adults in Malaysia

In response to the rising number of COVID-19-related deaths among older adults in Malaysia, observation concerning COVID-19-related mortality among older adults is of urgent public health importance. This study presents a review of the COVID-19-related death cases among older adults in Malaysia. Clinical and social demographic data of death cases officially released by the Ministry of Health Malaysia were reviewed. As of 12 June 2020, 81 older adult death cases were identified and included in this study. The mean age of the death cases was 71.88 years old. Even though 79% of these cases were male, gender was not likely to be associated with mortality. A substantial difference between the prevalence of diabetes among death cases and the nationwide population indicated that diabetes was more likely to be associated with mortality. Most of the studied deaths were individuals with pre-existing medical conditions, predominantly diabetes and hypertension, and those aged 70 years old or above. The mean time from hospitalisation to death was 11.83 days. Extra focus should be given to older adults in the prevention and control of COVID-19

Gender analyses on knowledge and awareness of COVID-19 on wearing face mask behaviour for self-protection among elderly Malaysians

This paper aimed to measure the variable that predicts the likelihood of female respondents to wear face mask. The data were collected (n=501) through online survey using Google Form. The set of questionnaire included the respondents’ background, knowledge about COVID-19, the awareness on COVID-19, and behaviour related to COVID-19 protection especially in wearing a face mask, washing hands, and social distance. Respondents in this study comprised the majority of females, Malay ethnic and from urban areas, at average age=65.55 years old. Majority (75.25%) reported that they are unemployed, married (78.24%), and had tertiary education (74.85%). Knowledge and awareness on COVID-19 significantly predict respondents to wear face mask. High knowledge predicts 19.194 times the likelihood of respondents to wear face mask, and high awareness predicts that less than 95.6% of respondents to wear face mask. Nevertheless, no variable predicts male respondents to wear face mask, and only high knowledge in COVID-19 predicts 41.340 times the likelihood of female respondents to wear a face mask. As conclusion, only high knowledge of COVID-19 predicts the behaviour of wearing face mask. Thus, effort should be focused on providing the public with good knowledge of COVID-19 to sustain good behaviour with regard to COVID-19 protection

Impact of gender on sexual problems and perceptions among urban Malay elderly in Malaysia

Background: Physical and pathological changes associated with advancing age affect sexual behaviours of the elderly. The aim of this study was to explore the impact of gender on sexual problems and perceptions among the urban Malay elderly. Methods: A cross-sectional study was conducted among 160 Malaysian elderly participants aged 60 years and older who live in Kuala Lumpur. Twelve neighbourhood associations were randomly selected using multi-stage cluster sampling. Data was collected using standardized and validated questionnaire by face-to-face interview technique with which was conducted by trained interviewers. Results: Mean age of the participants was 65.33 (5.87) year old with majority were still married. Female (55.7%) reported more sexual problems as evidenced by the higher proportion of those with lacked interest in having sex (72.5%), find sex is unpleasant (34.8%) and unable to come to orgasm (55.1%). Gender was found to have significant impact on every model obtained in the analysis for both sexual problems and perceptions. Female elderly were 10.6 times more likely to have sexual problem compared to male elderly (OR=10.64, P < 0.001, 95% CI 3.61, 31.35) and 033 less likely to have good sexual perception (OR=0.33, P=0.027, 95% CI 0.12,0.88). Conclusion: Gender is a crucial factor towards sexual problem and perceptions among older persons. Older women were reported to have more sexual problems and poor sexual perceptions, reflecting the needs for sexual awareness and education to improve the perceptions and sexuality in later life.

Correlation between hearing handicap inventory for the elderly screening (HHIE-S) and pure tone audiometry (PTA) test among Malaysian elderly

Introduction: The study aims to determine the correlation of the Hearing Handicap Inventory for Elderly Screening (HHIE-S) questionnaire with the pure tone audiometry (PTA) in the Malaysian older adult population. Methods: This cross-sectional study took a random sample of adults ≥60 years in a tertiary hospital. A total of 202 participants completed both the HHIE-S questionnaire and the PTA test. The total HHIE-S score and the PTA result were explored for the correlation using a Kruskal–Wallis and the validity using the receiver operating characteristic curve. Results: A Kruskal–Wallis analysis indicated a significant correlation for the level of hearing impairment (r =.704, p 25db results gave sensitivity: 87.9%, specificity: 78.4%, positive predictive value: 80.3%, and negative predictive value: 86.6%. Conclusion: This study suggests that the HHIE-S questionnaire is a good and valid screening instrument for hearing impairment detection in the Malaysian older adult population

Driver’s fatigue classification based on physiological signals using RNN-LSTM technique

One of the major reasons for road accidents is driver’s fatigue which causes several fatalities every year. Various studies on road accidents have proved that 20% of the accidents are caused mainly due to fatigue among drivers while driving. This paper presents the use of deep learning technique in classifying fatigue in drivers. By using deep neural networks, features are extracted automatically from preprocessed data of physiological signals such as electrocardiogram, heart rate, skin conductance response and body temperature. Public dataset HciLAB was used to train and validate the classification model. In this work, a comparative analysis of using Recurrent Neural Network - Long Short-term Memory (RNN-LSTM) deep learning architecture and the standard artificial neural network (ANN) was proposed and developed to classify fatigue based on the physiological features of the driver. The results revealed the superiority RNN-LSTM (98%) over standard ANN (80%), for driver fatigue classification. The proposed methods, based on RNN-LSTM deep learning architecture introduced elevated average accuracy in comparison with the standard artificial neural network