METHODOLOGY: We conducted a cross-sectional study using a validated self-administered questionnaire among tuberculosis patients attending primary care clinics in Johor Bahru district. A total of 208 tuberculosis patients were enrolled in this study through convenience sampling. We assessed the general knowledge, transmission, causes, and prevention of tuberculosis, where higher scores indicated better knowledge. For the perception of treatment, a higher mean score indicated a more negative perception.
RESULTS: The mean score for knowledge on tuberculosis was 54.33 ± 12.78, ranging from 25 to 88.9%. The mean score for perception was 2.75±0.52, ranging from 2.15-3.39. We found that although 88.9% of respondents knew a person could be infected with TB through inhalation of tuberculosis bacilli, a majority believed that smoking (68.2%), sharing food (69.2%), and eating from the same plate (66.8%) are causes of tuberculosis. Moreover, there was still a negative perception regarding the treatment of tuberculosis with the highest mean score for the statement 'I am afraid if I am told I am tuberculosis positive'.
CONCLUSIONS: We found that there were gaps in knowledge among tuberculosis patients. Intermittent counseling during the treatment re-enforces the knowledge of tuberculosis. An updated standardized counseling sheet of tuberculosis Health Education should be included along with staff training to update their knowledge as part of their important role in health education in tuberculosis prevention.
AIMS: This review is aimed to identify the prevalence of Long Covid-19 in the workplace and to determine the various symptoms of Long Covid-19 experienced by the workers.
METHODS: A meta-analysis was conducted to calculate the pooled estimates for the prevalence of Long Covid-19. Heterogeneity among the estimates was evaluated using the I² statistic.
RESULTS: The pooled prevalence of Long Covid-19 among workers across the 11 studies was 38% (95% CI 23-56). A total of 43 symptoms associated with Long Covid-19 were identified in the workplace, with the top five symptoms being dyspnoea at moderate activity (51%, 95% CI 39-62), mental symptoms (38%, 95% CI 6-87), dyspnoea at mild activity (35%, 95% CI 25-47), fatigue (26%, 95% CI 3-78) and effort intolerance (24%, 95% CI 15-35).
CONCLUSIONS: The review indicates a significant burden of long-lasting symptoms within the workforce. The top five reported symptoms of Long Covid-19 were dyspnoea during mild and moderate activities, mental symptoms, fatigue and effort intolerance.
METHODS AND ANALYSIS: Arksey and O'Malley's scoping review methodology framework will guide the conduct of this scoping review. The search strategy will involve electronic databases including PubMed, Excerpta Medica Database, Cumulative Index of Nursing and Allied Health Literature, Cochrane Library, Google Scholar and ScienceDirect, in addition to grey literature sources and hand-searching of reference lists. Two reviewers will independently screen all abstracts and full-text studies for inclusion. Data will be charted and sorted through an iterative process by the research team. The extracted data will undergo a descriptive analysis and simple quantitative analysis will be conducted using descriptive statistics. Engagement with relevant stakeholders will be carried out to gain more insights into our data from different perspectives.
ETHICS AND DISSEMINATION: Since the data used are from publicly available sources, this study does not require ethical approval. Results will be disseminated through academic journals, conferences and seminars. We anticipate that our findings will aid technology developers and health professionals working in the area of ageing and rehabilitation.
DESIGN: Scoping review.
DATA SOURCE: PubMed, Embase, CINAHL, Cochrane Library, Google Scholar and Science Direct (January 2009-December 2020).
STUDY SELECTION: Studies that describe older adults' perspectives with regard to their willingness, barriers or motivators towards the use of mobile applications in monitoring and managing their health condition were included.
DATA EXTRACTION: Titles and abstracts were initially screened by two reviewers. Articles agreed by both reviewers were proceeded to full-text screening. One reviewer extracted the data, which were verified by a second reviewer. Findings were further classified according to the 14 TDF domains by two researchers.
RESULTS: Six studies were included in the final scoping review. Barriers to adopting mobile applications for health-related interventions among older adults were the most common topic identified in the included studies. Barriers included being unaware of the existence of mobile health applications, lack of technological skills, lack of perceived ability and time, absence of professional involvements, and violation of trust and privacy. With regard to willingness, older adults are willing to use mobile applications if the apps incorporated features from a trusted source and have valid credentials. Motivators included continuous improvements of mobile applications' design interface and personalised features tailored to older adults' needs.
CONCLUSIONS: With the constant research for more diversified technology, the development of mobile applications to help older adults to manage and monitor health is seen as feasible, but barriers have to be addressed. The most prominent barriers linked to TDF domains were: (1) technological skills, (2) belief about consequences, and (3) memory, attention and decision process. Future interventions should use behaviour change techniques that target these three TDF domains in order to improve the ability to engage older adults with mobile technology.
DESIGN: A population-based cross-sectional study.
SETTING: 13 states and 3 Federal Territories in Malaysia.
PARTICIPANTS: A total of 3966 adults aged 60 years and above were extracted from the nationwide National Health and Morbidity Survey (NHMS) 2018 data set.
PRIMARY OUTCOME MEASURES: Multimorbidity was defined as co-occurrence of at least two known chronic non-communicable diseases in the same individual. The chronic diseases included hypertension, type 2 diabetes mellitus, dyslipidaemia and cancer.
RESULTS: The prevalence of multimorbidity among Malaysian older adults was 40.6% (95% CI: 37.9 to 43.3). The factors associated with multimorbidity were those aged 70-79 years (adjusted OR (AOR)=1.30; 95% CI=1.04 to 1.63; p=0.019), of Indian (AOR=1.69; 95% CI=1.14 to 2.52; p=0.010) and Bumiputera Sarawak ethnicities (AOR=1.81; 95% CI=1.14 to 2.89; p=0.013), unemployed (AOR=1.53; 95% CI=1.20 to 1.95; p=0.001), with functional limitation from activities of daily livings (AOR=1.66; 95% CI=1.17 to 2.37; p=0.005), physically inactive (AOR=1.28; 95% CI=1.03 to 1.60; p=0.026), being overweight (AOR=1.62; 95% CI=1.11 to 2.36; p=0.014), obese (AOR=1.88; 95% CI=1.27 to 2.77; p=0.002) and with abdominal obesity (AOR=1.52; 95% CI=1.11 to 2.07; p=0.009).
CONCLUSION: This study highlighted that multimorbidity was prevalent among older adults in the community. Thus, there is a need for future studies to evaluate preventive strategies to prevent or delay multimorbidity among older adults in order to promote healthy and productive ageing.
METHODS: Data were obtained from the National Health and Morbidity (NHMS) 2018 survey on the health of older Malaysian adults and analyzed. This cross-sectional population-based study used a two-stage stratified random sampling design. Sociodemographic characteristics, smoking status, and social support data were collected from respondents aged 60 years and more. A validated Malay language interviewer-administered questionnaire of 11-items, the Duke Social Support Index, was utilized to assess the social support status. A multivariable logistic regression analysis was used to assess the association of social support and smoking status among the respondents.
RESULTS: The prevalence of good social support was significantly higher among the 60-69 years old (73.1%) compared to the ≥80 years old respondents (50%). Multivariate logistic regression analysis showed that respondents aged ≥80 years old were 1.7 times more likely to have poor social support compared to those aged 60-69 years. Respondents with no formal education were 1.93 times more likely to have poor social support compared to respondents who had tertiary education. Respondents with an income of MYR 3000. Former smokers had good social support compared to current smokers (73.6% vs. 78.7%). For current smokers, they had poor social support, which is almost 1.42 times higher than that for non-smokers.
CONCLUSION: There was poor social support among older people who were current smokers, had an increased age, had no formal education and had a low income. The findings obtained from this study could assist policymakers to develop relevant strategies at the national level to enhance the social support status among older smokers and aid in their smoking cessation efforts.