Objective: This study examined research productivity of NSAIDs in Malaysia.
Materials and Methods: This bibliometric study included all published research articles on NSAIDs from 1979 to 2018, which were conducted in Malaysia. The search databases such as Google Scholar, PubMed, ScienceDirect, and Scopus were used. Search terms included NSAIDs and specific drug names such as ibuprofen, celecoxib, and naproxen. Growth of publication, authorship pattern, citation analysis, journal index, type of studies, and geographical distribution of institutions publishing articles on NSAIDs were measured.
Results: Overall, 111 articles were retrieved from 1979 to 2018. The annual productivity of articles throughout the study fluctuated in which the highest productivity was in 2018, 12.61% (n = 14). Majority of articles were multiple authored, 99.10% (n = 109), and University of Science Malaysia (USM) produced the highest number of articles (30 articles). Most of the articles were International Scientific Indexing-indexed, 52.25% (n = 58), and the main issue studied in most of the articles was the drug formulation of NSAIDs.
Conclusion: The growth of NSAID research in Malaysia was slow, and the majority of research involved laboratory studies. Clinical studies evaluating the clinical outcomes of NSAIDs in patients, particularly using large healthcare databases are still lacking.
METHODS AND ANALYSIS: This scoping review will be guided by the smart technology adoption behaviours of elder consumers theoretical model (Elderadopt) by Golant and reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses for Scoping Reviews. First, we will conduct an internet search for nursing homes and websites and databases related to the stakeholders to retrieve the definitions, concepts and criteria of a smart nursing home (phase 1). Second, we will conduct an additional systematic electronic database search for published articles on any measures of technological feasibility and integration of medical services in nursing home settings and their acceptability by nursing home residents and caregivers (phase 2). The electronic database search will be carried out from 1999 to 30 September 2020 and limited to works published in English and Chinese languages. For phase 2, the selection of literature is further limited to residents of nursing homes aged ≥60 years old with or without medical needs but are not terminally ill or bed-bound. Qualitative data analysis will follow the Framework Methods and thematic analysis using combined inductive and deductive approaches, conducted by at least two reviewers.
ETHICS AND DISSEMINATION: This protocol is registered on osf.io (URL: https://osf.io/qtwz2/). Ethical approval is not necessary as the scoping review is not a primary study, and the information is collected from selected articles that are publicly available sources. All findings will be disseminated at conferences and published in peer-reviewed journals.
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.
OBJECTIVES: Due to this discrepancy between the academic curriculum and the skills needed in the healthcare industry, the objectives of this study are to define the career pathway for eHealth professions and identify the challenges experienced by academic institutions and the industry in describing digital health professionals.
METHODS: We elicited qualitative data by conducting six focus groups with individuals from different professional backgrounds, including healthcare workers, information managers, computer sciences professionals, and workers in the revenue cycle who participated in a workshop on November 2-3, 2019, in Dubai. All focus group sessions were audio-recorded and transcribed, and participants were de-identified before analysis. An exploratory method was used to identify themes and subthemes. Saturation was reached when similar responses were found during the analysis. In this study, we found that respondents clearly defined eHealth career pathways based on criteria that included qualifications, experience, job scope, and competency. We also explored the challenges that the respondents encountered, including differences in the required skill sets and training and the need to standardize the academic curriculum across the GCC region, to recognize the various career pathways, and to develop local training programs. Additionally, country-specific projects have been initiated, such as the competency-based Digital Health framework, which was developed by the Saudi Commission of Healthcare Specialties (SCFHS) in 2018. Competency-based digital health frameworks generally include relevant job definitions, roles, and recommended competencies. Both the GCC taskforce and the Saudi studies capitalized on previous efforts by professional organizations, including Canada's Digital Health formerly known as (COACH), the U.S. Office of the National Coordinator for Health Information Technology (ONC), the American Medical Informatics Association (AMIA), and the Health Information and Management Systems Society (HIMSS).
RESULTS: In this study, we found that respondents defined eHealth career pathways based on different criteria such as: qualifications; various background of health and IT in the HI field; work experiences; job scope and competency. We also further explore the challenges that the respondents encountered which delineates four key aspects such as need of hybrid skills to manage the digital transformation, need of standardization of academic curriculum across GCC, recognition of the career pathways by the industry in order to open up career opportunity and career advancement, and availability of local training programs for up-skilling the current health workforce.
CONCLUSION: We believe that successful health digital transformation is not limited to technology advancement but requires an adaptive change in: the related competency-based frameworks, the organisation of work and career paths for eHealth professionals, and the development of educational programmes and joint degrees to equip clinicians with understanding of technology, and informaticians with understanding of healthcare. We anticipate that this work will be expanded and adopted by relevant professional and scientific bodies in the GCC region.
MATERIALS AND METHODS: A literature search was done from June 2019 to November 2019 with restrictions to the English language. The search was performed in ScienceDirect, PubMed, and EMBASE databases, using a combination of search terms related to drones, Unmanned Aerial Vehicles (UAV), Unmanned Aerial Systems (UAS), maternal, obstetric, healthcare, medical products transportation and Malaysia. A discourse analysis followed and a narrative review was provided on this subject.
RESULTS AND DISCUSSION: The validated ability of drones in the delivery of blood products is highlighted as a possible application in improving maternal healthcare in Malaysia, particularly in the state of Sabah. Five key challenges are identified: infrastructure, technicalities, regulations, expertise, and social acceptance. Future predictions of drone technology in healthcare were outlined with the suggestion of three principle arms of application.
CONCLUSION: The usage of the medical drone in medical products transportation supports the objectives of WHO MDG 5 for Malaysian maternal health. A study on the impact of drones in reducing the maternal mortality ratio is recommended for further exploration.
METHODS: This study is a pragmatic, cluster-randomised, parallel-group, matched pair, controlled trial with blinded outcome assessment. Randomisation is performed using a computer-generated table with a 1:1 allocation comparing the SIMSP and the POHP involving 28 preschools in the Kampar district, Perak, Malaysia. The intervention consists of preschool visits by a group of dental therapists, in-class oral health lessons and daily toothbrushing conducted by class teacher, child home toothbrushing supervised by parents, and infographic oral health messages to parents. The control consists of the existing POHP that involves preschool visits by a group of dental therapists only. The trial lasts for 6 months. Primary outcome variable is the mean plaque score change after 6 months. To determine the feasibility of the SIMSP, a process evaluation will be conducted using the perspectives of dental therapists, teachers, and parents on the appropriateness, effectiveness, facilitators, and barriers to the SIMSP implementation as well as an audit trail to assess the trial intervention.
DISCUSSION: Cluster randomisation may lead to a random effect and cluster selection bias. These factors will be accounted for when analysing the data and interpreting the outcomes. The effectiveness of the SIMSP will be evaluated by comparing the results with those of the POHP.
TRIAL REGISTRATION: ClinicalTrials.gov NCT04339647 . Registered on 5 April 2020 - Retrospectively registered.
Methods: A double-blinded randomised control trial involving 200 participants between the ages of 20 to 65 years old breast cancer patients was performed. Apart from those who refused participation, patients with chronic diseases and extreme baseline depression scores were also excluded. The control group received standard care twice a week from the social welfare services team facilitator compared to the intervention group that received additional psycho-education intervention programme (PEIP). The coping strategies were measured using the Brief-COPE inventory consisting of 28 items. It was administered on the second and 12th week of trial. The primary end point was compared between pre- and post-intervention. The effect of the intervention between groups, time, and covariates was measured using the generalised linear mixed model (GLMM) analysis.
Results: The mean (SD) of adaptive coping score among the intervention group increased from 5.63 (1.3) at baseline to 6.42 (1.3) at post-intervention. The mean avoidant coping score was 3.87 (1.1) at baseline but reduced to 3.69 (0.8) post-intervention. GLMM showed that women who received the intervention reported significantly higher usage of the adaptive coping strategies after attending the programme (B=0.921, p <0.001).
Conclusion: PEIP significantly improved knowledge of breast cancer patients. Thus, this programme may be considered as a part of the healthcare services in Jordan towards improving the adaptive coping strategies among breast cancer patients, which may point towards the potential for these services to increase adaptive coping strategies among patients in Jordan.
Implications for Public Health: PEIP may be considered as psychosocial intervention in public health and healthcare setting to address rising concerns on quality of care among breast cancer patients.