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  1. Tey NP, Siraj SB, Kamaruzzaman SB, Chin AV, Tan MP, Sinnappan GS, et al.
    Gerontologist, 2016 08;56(4):603-9.
    PMID: 26553738 DOI: 10.1093/geront/gnv153
    Multiethnic Malaysia provides a unique case study of divergence in population aging of different sociocultural subgroups within a country. Malaysia represents 3 major ethnicities in Asia-the Malay, Chinese, and Indian. The 3 ethnic groups are at different stages of population aging, as they have undergone demographic transition at different pace amidst rapid social and economic changes. Between 1991 and 2010, the Malaysian population aged 60 and over has more than doubled from about 1 million to 2.2 million, and this is projected to rise to about 7 million or 17.6% of the projected population of 40 million by 2040. In 2010, the aging index ranged from 22.8% among the Bumiputera (Malays and other indigenous groups), to 31.4% among the Indians and 55.0% among the Chinese. Population aging provides great challenges for Malaysia's social and economic development. The increasing prevalence of noncommunicable diseases in older adults, coupled with the erosion of the traditional family support system has increased demands on health care services with an overwhelming need for multidisciplinary and specialized geriatric care. Following the adoption of the National Policy for the Elderly in 1995, issues of population aging have gained increasing attention, especially among researchers. There is an urgent need to increase public awareness, develop infrastructure, as well as support action oriented research that will directly translate to comprehensive and cohesive social strategies, policies, and legislation to protect not just the current older Malaysians but the future of all Malaysians.
  2. Albahri AS, Alnoor A, Zaidan AA, Albahri OS, Hameed H, Zaidan BB, et al.
    Complex Intell Systems, 2022;8(2):1781-1801.
    PMID: 34777975 DOI: 10.1007/s40747-021-00503-w
    Topical treatments with structural equation modelling (SEM) and an artificial neural network (ANN), including a wide range of concepts, benefits, challenges and anxieties, have emerged in various fields and are becoming increasingly important. Although SEM can determine relationships amongst unobserved constructs (i.e. independent, mediator, moderator, control and dependent variables), it is insufficient for providing non-compensatory relationships amongst constructs. In contrast with previous studies, a newly proposed methodology that involves a dual-stage analysis of SEM and ANN was performed to provide linear and non-compensatory relationships amongst constructs. Consequently, numerous distinct types of studies in diverse sectors have conducted hybrid SEM-ANN analysis. Accordingly, the current work supplements the academic literature with a systematic review that includes all major SEM-ANN techniques used in 11 industries published in the past 6 years. This study presents a state-of-the-art SEM-ANN classification taxonomy based on industries and compares the effort in various domains to that classification. To achieve this objective, we examined the Web of Science, ScienceDirect, Scopus and IEEE Xplore ® databases to retrieve 239 articles from 2016 to 2021. The obtained articles were filtered on the basis of inclusion criteria, and 60 studies were selected and classified under 11 categories. This multi-field systematic study uncovered new research possibilities, motivations, challenges, limitations and recommendations that must be addressed for the synergistic integration of multidisciplinary studies. It contributed two points of potential future work resulting from the developed taxonomy. First, the importance of the determinants of play, musical and art therapy adoption amongst autistic children within the healthcare sector is the most important consideration for future investigations. In this context, the second potential future work can use SEM-ANN to determine the barriers to adopting sensing-enhanced therapy amongst autistic children to satisfy the recommendations provided by the healthcare sector. The analysis indicates that the manufacturing and technology sectors have conducted the most number of investigations, whereas the construction and small- and medium-sized enterprise sectors have conducted the least. This study will provide a helpful reference to academics and practitioners by providing guidance and insightful knowledge for future studies.
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