Aim Quality of life (QoL) among the older persons provides valuable insights into the potential modifiable risk factors that affect well‐being in later life. This study aimed to describe the QoL and psychosocial factors of QoL of older persons in Malaysia. Methods We used the 19‐item Control, Autonomy, Self‐realization and Pleasure scale, a validated instrument that measures psychological well‐being related to QoL in older persons. Scores range from 0 to 57, and higher scores indicate better QoL. We included several factors as covariates. Analysis of complex samples was carried out using Stata 15. Descriptive analysis was carried out to determine QoL by sociodemographic characteristics and other factors. Linear regression analysis was used to identify psychosocial factors that influence QoL. Results A total of 3444 individuals aged ≥60 years completed all 19‐item Control, Autonomy, Self‐realization and Pleasure items. The estimated mean QoL score was 47.01 (95% CI 46.30–47.72). Adjusted for confounders, QoL was lower among individuals with no formal education (−2.554, 95% CI −3.684, −1.424), probable depression (−1.042, 95% CI −1.212, −0.871) and food insecurity (−0.815, 95% CI −1.083, −0.548). QoL continued to improve with improved ADL score (0.302, 95% CI 0.052, 0.552), IADL score (0.646, 95% CI 0.382, 0.909) and better social support (0.308, 95% CI 0.187, 0.429). Conclusions Lower education, depression, food insecurity, presence of limited functional status and poor social support negatively influenced QoL in older Malaysians. This study identified potentially modifiable factors that could be targeted for interventions to enhance QoL of older persons in Malaysia. Geriatr Gerontol Int 2020; 20: 92–97.
Background According to the World Bank, Malaysia reported an estimated 97 tuberculosis cases per 100,000 people in 2021. Chest x-ray (CXR) remains the best conventional method for the early detection of pulmonary tuberculosis (PTB) infection. The intervention of artificial intelligence (AI) in PTB diagnosis could efficiently aid human interpreters and reduce health professionals’ work burden. To date, no AI studies have been evaluated in Malaysia. Objective This study aims to evaluate the performance of Putralytica and Qure.ai software for CXR screening and PTB diagnosis among the Malaysian population. Methods We will conduct a retrospective case-control study at the Respiratory Medicine Institute, National Cancer Institute, and Sungai Buloh Health Clinic. A total of 1500 CXR images of patients who completed treatments or check-ups will be selected and categorized into three groups: (1) abnormal PTB cases, (2) abnormal non-PTB cases, and (3) normal cases. These CXR images, along with their clinical findings, will be the reference standard in this study. All patient data, including sociodemographic characteristics and clinical history, will be collected prior to screening via Putralytica and Qure.ai software and readers’ interpretation, which are the index tests for this study. Interpretation from all 3 index tests will be compared with the reference standard, and significant statistical analysis will be computed. Results Data collection is expected to commence in August 2023. It is anticipated that 1 year will be needed to conduct the study. Conclusions This study will measure the accuracy of Putralytica and Qure.ai software and whether their findings will concur with readers’ interpretation and the reference standard, thus providing evidence toward the effectiveness of implementing AI in the medical setting. International Registered Report Identifier (IRRID) PRR1-10.2196/36121
BACKGROUND Soil-transmitted helminth (STH) infection is one of the 13 notable Neglected Tropical Diseases (NTDs) according to the CDC and WHO. In 2010, it is estimated that 1.73 billion people are infected with STH globally of which 70% of cases occur in Asia. To date, there is a dearth of published literature on the prevalence of STH infection throughout Malaysia. OBJECTIVE The objectives of this study are to review research activity on STH infection in Malaysia, to estimate the prevalence of STH infection among Malaysian, and to identify significant risk factors associated with the infection. METHODS We will conduct a scoping review based on the 6-stages structured framework of Arksey and O’Malley’s (2005) methodology. A comprehensive search strategy focusing on STH infection will be executed using electronic databases (Scopus, PubMed, Web of Science and EMBASE). A systematic approach to searching, screening, reviewing and data extraction will be applied based on Preferred Reporting Items for Systematic Reviews and Meta-Analyses for Scoping Review (PRISMA-ScR). Mendeley software and Microsoft Excel programmes will be used to manage the references and to remove duplicates. Relevant data from selected articles will be extracted using a standardized data extraction form using the Google Form application. Results will be summarized descriptively in tabular form including types of interventions, study design, settings, tools used, and the outcomes of each study. RESULTS We would like to provide further evidence on the prevalence of STH in terms of parasite species that predominately cause the infection and the intensity of the infection. Finally, we will present the significant risk factors that contribute to STH infection and discuss prevention taken by considering the government or private sectors involvement towards curbing this issue. CONCLUSIONS We hope that the findings of this scoping review will provide information for policymakers and strengthen policy guidelines to eradicate STH infection, and for researchers to further study and investigate any STH-related issue in Malaysia.
BACKGROUND Tuberculosis (TB) profile in Malaysia showed an average annual growth rate of 2.23%, with an estimated 92 cases per 100,000 people reported in 2018. CXR remains the best conventional method for the early detection of pulmonary TB infection. The intervention of AI in TB diagnosis could efficiently aid human interpreters and reduce health professionals' work burden. To date, no evaluation of AI studies has been carried out in Malaysia. OBJECTIVE This study aims to determine the diagnostic accuracy and evaluate the performance of Qure.ai and Putra Analytica AI software. METHODS We will conduct a retrospective case-control study in Respiratory Medicine Institute (IPR), Kuala Lumpur Health Clinic and Bandar Botanik Klang Health Clinic. Patients' medical reports on TB investigation will be retrieved by accessing electronic and hardcopy medical records and collecting demographic data. Prior to conducting the study, patients' PTB status will be obtained by identifying MTB culture (reference standard) results in order to create a case and a control group. A total of 2000 CXR images will be retrieved, of which 1000 images will be the case (abnormality). Normal and abnormal CXR will be categorized into film and digital CXR, which will be screened onto the said AI software (index tests). RESULTS Results obtained from the AI software will be compared with the reference standard, and significant statistical analysis will be computed CONCLUSIONS We hope that the findings of this evaluation study will provide sufficient information for stakeholders and to implement AI technology in the medical imaging field for better management of TB in hospital and clinic settings.
Background Soil-transmitted helminth (STH) infection is 1 of the 20 notable neglected tropical diseases according to the Centers for Disease Control and Prevention and World Health Organization. In 2010, it is estimated that 1.73 billion people are infected with STH globally, of which 70% of cases occur in Asia. To date, there is a dearth of published literature on the prevalence of STH infection throughout Malaysia. Objective The objectives of this study are to review research activity on STH infection in Malaysia, to estimate the prevalence of STH infection among Malaysians, and to identify significant risk factors associated with the infection. This review aims to provide the current state of evidence pertaining to STH infections, focusing on the main areas, limitations, and biases of research and mapping out the morbidity distribution of the diseases and their causative agents, and to identify significant risk factors for preventive measures. Methods We will conduct a scoping review based on the 6-stage structured framework developed by Arksey and O’Malley. A comprehensive search strategy focusing on STH infection will be executed using electronic databases (Scopus, PubMed, Web of Science, and Embase). A systematic approach for searching, screening, reviewing, and data extraction will be applied based on the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) guidelines. Mendeley software and Microsoft Excel will be used to manage the references and to remove duplicates. Relevant data from selected articles will be extracted using a standardized data extraction form. Results A total of 164 potential manuscripts were retrieved. Data extraction is currently in progress and completion is expected by the end of 2022. Conclusions Our scoping review will summarize the current state of research in this field and provide comprehensive information regarding STH infections in Malaysia for future reference. Trial Registration National Medical Research Register NMRR-20-2889-54348; https://nmrr.gov.my/research-directory/e52ea778-d31c-4eb4-9163-a45bb3680bbf International Registered Report Identifier (IRRID) DERR1-10.2196/36077
Breast cancer is a health problem since so many years ago especially to women. In 2013, Basic Health Research (Riskesdas) showed that the number of national breast cancer prevalence was the second most numerous patients in the world especially attacked women in Indonesia. The common problems experienced by breast cancers patients is the decrease of life quality of the patients. The purpose of this research was to identify factors related to the life quality of the breast cancers patients in Bandung city. This research used cross sectional method. The determination of life quality based on Quality of Life Cancer Survivor Version (QOL-CSV). Accidental sampling was used to choose samples. This research was taken place in four rumah singgah (shelters) of breast cancer located in Bandung city. There were 30 women involved in this study. Inclusive criterion in this research was the patients of breast cancers who are undergoing medications such as surgery, chemotherapy, or radiotherapy, who are willing to be the respondents voluntary. Result of normality test included age factor, marital age and firts time pregnance. Multivariate test used in this research was the linear regression analysis. Based on the result of bivariate analysis, age factor and frequency of pregnancy had positive correlated (p<0.05) to the life quality of breast cancer patients, while menarche had a negative correlated. Regression linear result was determined to life quality factor (p<0,05) including age factor, marital age and pathology anatomy result. Half of the result of coefficient correlation showed a strong relationship in the quality of life of breast cancer patients. This Research showed that some of the reproduction factors related to the quality of life. Some factors are contributed to the quality of life of breast cancer patients such as age of the patient, marital age and result of pathology anatomy (cancer stage). This research needs more in-depths studies toward the quality of life of breast cancers patients as well as efforts of intervention to increase the quality of life of breast cancers patients.Keywords: breast cancer, quality of life, reproductive factors
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.