METHODS: Online databases (PubMed, Ovid MEDLINE and Scopus), reference lists of articles identified, and grey literature (Malaysian Ministry of Health website, WHO website) were systematically searched for relevant literature on pneumococcal serotype distribution across Malaysia up to 10th November 2020. No lower date limit was set to maximise the number of target reports returned. Results of serotypes were split by age categories, including ≤5 years, > 5 years and unreported for those that did not specify.
RESULTS: The search returned 18 relevant results, with a total of 2040 isolates. The most common serotypes across all disease types were 19F (n = 313, 15.3% [95%CI: 13.8-17.0]), 23F (n = 166, 8.1% [95%CI: 7.0-9.4]), 14 (n = 166, 8.1% [95%CI: 7.0-9.4]), 6B (n = 163, 8.0% [95%CI: 6.9-9.2]) and 19A (n = 138, 6.8% [95%CI: 5.8-7.9]).
CONCLUSION: Four of the most common serotypes across all isolate sources in Malaysia are covered by PCV10, while PCV13 provides greater serotype coverage in comparison to PCV10. There is still a need for surveillance studies, particularly those investigating serotypes in children under 5 years of age, to monitor vaccine effectiveness and pneumococcal population dynamic following implementation of PCV10 into routine immunisation.
OBJECTIVE: This scientometric investigation aims to examine collaborative research networks, dominant research themes and disciplines, and seminal research studies that have contributed most to the field of telemedicine. This information is vital for scientists, institutions, and policy stakeholders to evaluate research areas where more infrastructural or scholarly contributions are required.
METHODS: For analyses, we used CiteSpace (version 4.0 R5; Drexel University), which is a Java-based software that allows scientometric analysis, especially visualization of collaborative networks and research themes in a specific field.
RESULTS: We found that scholarly activity has experienced a significant increase in the last decade. Most important works were conducted by institutions located in high-income countries. A discipline-specific shift from radiology to telestroke, teledermatology, telepsychiatry, and primary care was observed. The most important innovations that yielded a collaborative influence were reported in the following medical disciplines, in descending order: public environmental and occupational health, psychiatry, pediatrics, health policy and services, nursing, rehabilitation, radiology, pharmacology, surgery, respiratory medicine, neurosciences, obstetrics, and geriatrics.
CONCLUSIONS: Despite a continuous rise in scholarly activity in telemedicine, we noticed several gaps in the literature. For instance, all the primary and secondary research central to telemedicine was conducted in the context of high-income countries, including the evidence synthesis approaches that pertained to implementation aspects of telemedicine. Furthermore, the research landscape and implementation of telemedicine infrastructure are expected to see exponential progress during and after the COVID-19 era.
METHODS AND RESULTS: From January to March 2015, we conducted focus group discussions with 30 Japanese retirees who live in Kuala Lumpur and Ipoh. Guided by the social-ecological model, we discovered seven pertinent themes: 'language barriers','healthcare decisions', 'medical check-ups','healthcare insurance', 'nursing and palliative care', 'trust and distrust of healthcare services', and 'word-of-mouth information'.
DISCUSSION: We identified seven pertinent issues related to healthcare services among Japanese retirees in Malaysia, of which four are especially important. These issues are explained as integrated themes within the social-ecological model. Language barriers prohibit them from having difficulty accessing to healthcare in Malaysia, but lack of will to improve their language skills exist among them. For that reason, they rely heavily on word-of-mouth information when seeking for healthcare. As a consequence, some develop feelings of trust and distrust of healthcare services. In addition, we have identified the needs for provide nursing and palliative care among Japanese retirees in Malaysia.
CONCLUSION: Based on the magnitude of the discussion, we concluded that there are four crucial healthcare issues among Japanese retirees; 'language barriers', 'trust and distrust of healthcare services', 'word-of-mouth information' and 'nursing and palliative care'. We propose that further dialogue by healthcare stakeholders should be carried out to improve further the healthcare service provisions for Japanese retirees in Malaysia.
METHOD: Two categories of participants, i.e., medical doctors (n = 11) and final year medical students (Group 1, n = 5; Group 2, n = 10) participated in four separate focus group discussions. Nielsen's 5 dimensions of usability (i.e. learnability, effectiveness, memorability, errors, and satisfaction) and Pentland's narrative network were adapted as the framework to study the usability and the implementation of the checklist in a real clinical setting respectively.
RESULTS: Both categories (medical doctors and medical students) of participants found that the TWED checklist was easy to learn and effective in promoting metacognition. For medical student participants, items "T" and "W" were believed to be the two most useful aspects of the checklist, whereas for the doctor participants, it was item "D". Regarding its implementation, item "T" was applied iteratively, items "W" and "E" were applied when the outcomes did not turn out as expected, and item "D" was applied infrequently. The one checkpoint where all four items were applied was after the initial history taking and physical examination had been performed to generate the initial clinical impression.
CONCLUSION: A metacognitive checklist aimed to check cognitive errors may be a useful tool that can be implemented in the real clinical setting.
METHODS: This bibliometric work investigated the academic publication trends in medical image segmentation technology. These data were collected from the Web of Science (WoS) Core Collection and the Scopus. In the quantitative analysis stage, important visual maps were produced to show publication trends from five different perspectives including annual publications, countries, top authors, publication sources, and keywords. In the qualitative analysis stage, the frequently used methods and research trends in the medical image segmentation field were analyzed from 49 publications with the top annual citation rates.
RESULTS: The analysis results showed that the number of publications had increased rapidly by year. The top related countries include the Chinese mainland, the United States, and India. Most of these publications were conference papers, besides there are also some top journals. The research hotspot in this field was deep learning-based medical image segmentation algorithms based on keyword analysis. These publications were divided into three categories: reviews, segmentation algorithm publications, and other relevant publications. Among these three categories, segmentation algorithm publications occupied the vast majority, and deep learning neural network-based algorithm was the research hotspots and frontiers.
CONCLUSIONS: Through this bibliometric research work, the research hotspot in the medical image segmentation field is uncovered and can point to future research in the field. It can be expected that more researchers will focus their work on deep learning neural network-based medical image segmentation.