Mohd Fadzly Amar Jamil

Introduction: Falls are highly prevalent among individuals with dementia, largely due to the cognitive and physical impairments associated with the condition. Understanding the barriers and challenges to fall prevention in community-dwelling individuals with dementia is essential for developing tailored strategies that address their unique risks. Despite the existing evidence on fall prevention in older adults, few reviews specifically examine the obstacles faced by persons with dementia and their caregivers in community settings. This scoping review, therefore, aims to map the barriers and challenges to preventing falls among community-dwelling individuals with dementia. Methods and analysis: This review will follow Arksey and O’Malley’s five-stage framework and be reported in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses—Extension for Scoping Reviews checklist. Six electronic databases (PsycINFO, PubMed, Web of Science, Cumulative Index to Nursing and Allied Health Literature, Scopus and Embase) will be searched for relevant studies published between 2014 and 2024. Grey literature sources, including dissertations and conference proceedings, will also be included. Data will be charted and synthesised thematically to provide an overview of barriers and contextual factors influencing fall prevention. The study commenced in August 2025 and is expected to be completed by February 2026. Ethics and dissemination: As this review involves the analysis of existing literature, ethical approval is not required. Findings will be disseminated through peer-reviewed publications, conference presentations and summaries tailored for healthcare providers and caregiver groups. Registration details: The protocol is registered with the Open Science Framework: https://osf.io/gnw47/ (dataset).

Introduction: Hospital patients are at an increased risk of falls, which are a significant safety concern within healthcare settings. ¹ Understanding how the COVID-19 pandemic has influenced fall risks is essential for identifying key factors that could inform future fall prevention strategies. ² This scoping review aims to explore the barriers and challenges associated with preventing inpatient falls in the context of the post-COVID-19 environment. Methods and analysis: The methodology for this scoping review follows the framework established by Arksey and O’Malley. A comprehensive literature search will be conducted using specific keywords to identify relevant published studies. Searches will be performed across selected electronic databases, including PubMed/MEDLINE, CINAHL, Scopus, ProQuest and Web of Science, covering publications from 2014 to 2024. This review will focus on a global perspective. Two authors will independently screen titles and abstracts to identify potential studies for inclusion. Studies meeting the inclusion criteria will be retrieved for full-text review, and their references will be assessed for relevance using the same criteria. The PRISMA flow diagram will guide the review process. Data will be extracted, analysed and charted according to categories from the selected publications. Ethics and dissemination: This scoping review will provide a comprehensive overview of the barriers and challenges in preventing inpatient falls in the post-pandemic context. The findings will be disseminated through submission for publication in a scientific journal. Registration details: This scoping review protocol is registered with Open Science Framework (OSF) available at https://osf.io/ .

As COVID-19 dispersion occurs at different levels of gradients across geographies, the application of spatiotemporal science via computational methods can provide valuable insights to direct available resources and targeted interventions for transmission control. This ecological-correlation study evaluates the spatial dispersion of COVID-19 and its temporal relationships with crucial demographic and socioeconomic determinants in Malaysia, utilizing secondary data sources from public domains. By aggregating 51,476 real-time active COVID-19 case-data between 22 January 2021 and 4 February 2021 to district-level administrative units, the incidence, global and local Moran indexes were calculated. Spatial autoregressive models (SAR) complemented with geographical weighted regression (GWR) analyses were executed to determine potential demographic and socioeconomic indicators for COVID-19 spread in Malaysia. Highest active case counts were based in the Central, Southern and parts of East Malaysia regions of Malaysia. Countrywide global Moran index was 0.431 (p = 0.001), indicated a positive spatial autocorrelation of high standards within districts. The local Moran index identified spatial clusters of the main high–high patterns in the Central and Southern regions, and the main low–low clusters in the East Coast and East Malaysia regions. The GWR model, the best fit model, affirmed that COVID-19 spread in Malaysia was likely to be caused by population density (β coefficient weights = 0.269), followed by average household income per capita (β coefficient weights = 0.254) and GINI coefficient (β coefficient weights = 0.207). The current study concluded that the spread of COVID-19 was concentrated mostly in the Central and Southern regions of Malaysia. Population’s average household income per capita, GINI coefficient and population density were important indicators likely to cause the spread amongst communities.

The rapid transmission of highly contagious infectious diseases within communities can yield potential hotspots or clusters across geographies. For COVID-19, the impact of population density on transmission models demonstrates mixed findings. This study aims to determine the correlations between population density, clusters, and COVID-19 incidence across districts and regions in Malaysia. This countrywide ecological study was conducted between 22 January 2021 and 4 February 2021 involving 51,476 active COVID-19 cases during Malaysia’s third wave of the pandemic, prior to the reimplementation of lockdowns. Population data from multiple sources was aggregated and spatial analytics were performed to visualize distributional choropleths of COVID-19 cases in relation to population density. Hierarchical cluster analysis was used to synthesize dendrograms to demarcate potential clusters against population density. Region-wise correlations and simple linear regression models were deduced to observe the strength of the correlations and the propagation effects of COVID-19 infections relative to population density. Distributional heats in choropleths and cluster analysis showed that districts with a high number of inhabitants and a high population density had a greater number of cases in proportion to the population in that area. The Central region had the strongest correlation between COVID-19 cases and population density (r = 0.912; 95% CI 0.911, 0.913; p < 0.001). The propagation effect and the spread of disease was greater in urbanized districts or cities. Population density is an important factor for the spread of COVID-19 in Malaysia.

The escalated burden of diabetes on the population’s health has catalyzed rigorous scientific research to produce appropriate evidence for treatment and control. Malaysia suffers from the leading diabetes epidemic within the Western Pacific region. It is crucial to map the scientific landscape of diabetes research for the country to identify trends in productivity and determine whether research efforts are directed toward the needs-gaps priority for evidence synthesis that could be used for the drafting of policies and guidelines. This systematic scientometrics study was conducted to map the scientific research output (trends and distribution, citation frequency, keywords link visualization, and thematic cluster conceptualization) related to diabetes between 2000–2018 in Malaysia. Using three international databases (PubMed, EMBASE, Scopus) and one local database (MyCite), scientific publication records related to diabetes in Malaysia between 2000 and 2018 were retrieved and analyzed using quantitative and qualitative methodologies. Microsoft Excel 2016, EndNote X9.2, BibExcel 2016, GraphPad Prism 8.0.1, VOS viewer software 1.6.13, and R software version 1.3.959 were used to analyze the trend and contents of diabetes publications. A total of 2094 publication records that accounted for 35,497 citations were analyzed. Kuala Lumpur was the most scientifically productive state in Malaysia, contributing 754 papers. Medical Journal of Malaysia had the highest number of publications. The inflection point of the Malaysian diabetes research output was in 2013, with most publications being non-collaborative research works. Most publications originated from academia, especially from local public universities. The overall publication productivity of diabetes research in Malaysia was conceptualized into eleven thematic clusters, with clinical and animal studies being the most prevalent themes. The diabetes literature in Malaysia has grown steadily over the past 19 years. However, the cumulative evidence remains inadequate and is insufficiently powered to guide policymaking and the control of diabetes. It does not yet seem feasible to direct the diabetes epidemic curve to a plateau for the Malaysian population based on Malaysian diabetes publications.

Diabetes causes significant disabilities, reduced quality of life and mortality that imposes huge economic burden on societies and governments worldwide. Malaysia suffers a high diabetes burden in Asia, but the magnitude of healthcare expenditures documented to aid national health policy decision-making is limited. This systematic review aimed to document the economic burden of diabetes in Malaysia, and identify the factors associated with cost burden and the methods used to evaluate costs. Studies conducted between 2000 and 2019 were retrieved using three international databases (PubMed, Scopus, EMBASE) and one local database (MyCite), as well as manual searches. Peer reviewed research articles in English and Malay on economic evaluations of adult type 2 diabetes conducted in Malaysia were included. The review was registered with PROSPERO (CRD42020151857), reported according to PRISMA and used a quality checklist adapted for cost of illness studies. Data were extracted using a data extraction sheet that included study characteristics, total costs, different costing methods and a scoring system to assess the quality of studies reviewed. The review identified twelve eligible studies that conducted cost evaluations of type 2 diabetes in Malaysia. Variation exists in the costs and methods used in these studies. For direct costs, four studies evaluated costs related to complications and drugs, and two studies were related to outpatient and inpatient costs each. Indirect and intangible costs were estimated in one study. Four studies estimated capital and recurrent costs. The estimated total annual cost of diabetes in Malaysia was approximately USD 600 million. Age, type of hospitals or health provider, length of inpatient stay and frequency of outpatient visits were significantly associated with costs. The most frequent epidemiological approach employed was prevalence-based (n = 10), while cost analysis was the most common costing approach used. The current review offers the first documented evidence on cost estimates of diabetes in Malaysia.

The uncertainties around disease management and control measures have not only motivated clinicians to keep abreast of new evidence available in the scholarly literature, but also to be rigorously engaged in medical research, dissemination and knowledge transfer. We aimed to explore clinicians’ publication output from the Malaysian perspective. A self-report survey and bibliometric analysis was conducted. A total of 201/234 clinicians participated in the survey. Items consisted of demographics, researching habits, publication output and level of importance of journal selection metrics. Descriptive, bivariate and multivariate analyses were conducted. Bibliometric analysis using retrieved records from PubMed between 2009 and October 2019 was conducted and co-occurrence and co-authorship analyses were executed. Self-reported publication output was 16.9%. In the logistic regression model, publication output was significantly higher amongst consultants or clinical specialists (aOR = 2.5, 95% CI 1.1–10.0, p = 0.023); clinicians previously involved in research (aOR = 4.2, 95% CI 1.5–11.4, p = 0.004); clinicians who ever used reference citation managers (aOR = 3.2, 95% CI 1.3–7.7, p = 0.010); and journal publication speed (aOR = 2.9, 95% CI 1.2–7.1, p = 0.019). Most clinicians published original research papers (76.4%) in international journals (78.2%). Published papers were mostly observational studies, genetic, stroke and health services or systems research. In conclusion, socio-demographics, researching habits and journal selection metrics were significantly associated with self-reported publication output. Real outputs from bibliometrics were predominantly focused across five clusters.