Publications
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Udeh-Momoh CT, Watermeyer T, Price G, et al., 2021, Protocol of the cognitive health in ageing register: investigational, observational and trial studies in dementia research (CHARIOT): prospective readiness cOhort (PRO) SubStudy., BMJ Open, Vol: 11, Pages: 1-12, ISSN: 2044-6055
INTRODUCTION: The Cognitive Health in Ageing Register: Investigational, Observational and Trial Studies in Dementia Research (CHARIOT): Prospective Readiness cOhort (PRO) SubStudy (CPSS), sponsored by Janssen Pharmaceutical Research & Development LLC, is an Alzheimer's disease (AD) biomarker enriched observational study that began 3 July 2015 CPSS aims to identify and validate determinants of AD, alongside cognitive, functional and biological changes in older adults with or without detectable evidence of AD pathology at baseline. METHODS AND ANALYSIS: CPSS is a dual-site longitudinal cohort (3.5 years) assessed quarterly. Cognitively normal participants (60-85 years) were recruited across Greater London and Edinburgh. Participants are classified as high, medium (amnestic or non-amnestic) or low risk for developing mild cognitive impairment-Alzheimer's disease based on their Repeatable Battery for the Assessment of Neuropsychological Status performance at screening. Additional AD-related assessments include: a novel cognitive composite, the Global Preclinical Alzheimer's Cognitive Composite, brain MRI and positron emission tomography and cerebrospinal fluid analysis. Lifestyle, other cognitive and functional data, as well as biosamples (blood, urine, and saliva) are collected. Primarily, study analyses will evaluate longitudinal change in cognitive and functional outcomes. Annual interim analyses for descriptive data occur throughout the course of the study, although inferential statistics are conducted as required. ETHICS AND DISSEMINATION: CPSS received ethical approvals from the London-Central Research Ethics Committee (15/LO/0711) and the Administration of Radioactive Substances Advisory Committee (RPC 630/3764/33110) The study is at the forefront of global AD prevention efforts, with frequent and robust sampling of the well-characterised cohort, allowing for detection of incipient pathophysiological, cognitive and functional changes that could inform therape
Reitsma MB, Kendrick PJ, Ababneh E, et al., 2021, Spatial, temporal, and demographic patterns in prevalence of smoking tobacco use and attributable disease burden in 204 countries and territories, 1990–2019: a systematic analysis from the Global Burden of Disease Study 2019, The Lancet, Vol: 397, Pages: 2337-2360, ISSN: 0140-6736
BackgroundEnding the global tobacco epidemic is a defining challenge in global health. Timely and comprehensive estimates of the prevalence of smoking tobacco use and attributable disease burden are needed to guide tobacco control efforts nationally and globally.MethodsWe estimated the prevalence of smoking tobacco use and attributable disease burden for 204 countries and territories, by age and sex, from 1990 to 2019 as part of the Global Burden of Diseases, Injuries, and Risk Factors Study. We modelled multiple smoking-related indicators from 3625 nationally representative surveys. We completed systematic reviews and did Bayesian meta-regressions for 36 causally linked health outcomes to estimate non-linear dose-response risk curves for current and former smokers. We used a direct estimation approach to estimate attributable burden, providing more comprehensive estimates of the health effects of smoking than previously available.FindingsGlobally in 2019, 1·14 billion (95% uncertainty interval 1·13–1·16) individuals were current smokers, who consumed 7·41 trillion (7·11–7·74) cigarette-equivalents of tobacco in 2019. Although prevalence of smoking had decreased significantly since 1990 among both males (27·5% [26·5–28·5] reduction) and females (37·7% [35·4–39·9] reduction) aged 15 years and older, population growth has led to a significant increase in the total number of smokers from 0·99 billion (0·98–1·00) in 1990. Globally in 2019, smoking tobacco use accounted for 7·69 million (7·16–8·20) deaths and 200 million (185–214) disability-adjusted life-years, and was the leading risk factor for death among males (20·2% [19·3–21·1] of male deaths). 6·68 million [86·9%] of 7·69 million deaths attributable to smoking tobacco use were among current smokers.Int
Lall P, Dutta O, Tan WS, et al., 2021, "I decide myself"- A qualitative exploration of end of life decision making processes of patients and caregivers through Advance Care Planning, PLOS ONE, Vol: 16, ISSN: 1932-6203
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- Citations: 3
Lo ZJ, Surendra NK, Saxena A, et al., 2021, Clinical and economic burden of diabetic foot ulcers: A 5-year longitudinal multi-ethnic cohort study from the tropics, INTERNATIONAL WOUND JOURNAL, Vol: 18, Pages: 375-386, ISSN: 1742-4801
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- Citations: 22
Fadahunsi P, O'Connor S, Akinlua J, et al., 2021, Information quality frameworks for digital health technologies: systematic review, Journal of Medical Internet Research, Vol: 23, ISSN: 1438-8871
Background: Digital health technologies (DHTs) generate a large volume of information used in health care for administrative, educational, research, and clinical purposes. The clinical use of digital information for diagnostic, therapeutic, and prognostic purposes has multiple patient safety problems, some of which result from poor information quality (IQ).Objective: This systematic review aims to synthesize an IQ framework that could be used to evaluate the extent to which digital health information is fit for clinical purposes.Methods: The review was conducted according to the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis) guidelines. We searched Embase, MEDLINE, PubMed, CINAHL, Maternity and Infant Care, PsycINFO, Global Health, ProQuest Dissertations and Theses Global, Scopus, and HMIC (the Health Management Information Consortium) from inception until October 2019. Multidimensional IQ frameworks for assessing DHTs used in the clinical context by health care professionals were included. A thematic synthesis approach was used to synthesize the Clinical Information Quality (CLIQ) framework for digital health.Results: We identified 10 existing IQ frameworks from which we developed the CLIQ framework for digital health with 13 unique dimensions: accessibility, completeness, portability, security, timeliness, accuracy, interpretability, plausibility, provenance, relevance, conformance, consistency, and maintainability, which were categorized into 3 meaningful categories: availability, informativeness, and usability.Conclusions: This systematic review highlights the importance of the IQ of DHTs and its relevance to patient safety. The CLIQ framework for digital health will be useful in evaluating and conceptualizing IQ issues associated with digital health, thus forestalling potential patient safety problems.Trial Registration: PROSPERO International Prospective Register of Systematic Reviews CRD42018097142; https://www.crd.york.ac.uk/pros
Nazeha N, Sathish T, Soljak M, et al., 2021, A Comparative Study of International and Asian Criteria for Overweight or Obesity at Workplaces in Singapore, ASIA-PACIFIC JOURNAL OF PUBLIC HEALTH, Vol: 33, Pages: 404-410, ISSN: 1010-5395
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- Citations: 3
Martinengo L, Stona A-C, Tudor Car L, et al., 2021, Education on Depression in Mental Health Apps: Systematic Assessment of Characteristics and Adherence to Evidence-Based Guidelines (Preprint)
<sec> <title>BACKGROUND</title> <p>Suboptimal understanding of depression and mental health disorders by the general population is an important contributor to the wide treatment gap in depression. Mental health literacy encompasses knowledge and beliefs about mental disorders and supports their recognition, management, and prevention. Besides knowledge improvement, psychoeducational interventions reduce symptoms of depression, enhance help-seeking behavior, and decrease stigma. Mental health apps often offer educational content, but the trustworthiness of the included information is unclear.</p> </sec> <sec> <title>OBJECTIVE</title> <p>The aim of this study is to systematically evaluate adherence to clinical guidelines on depression of the information offered by mental health apps available in major commercial app stores.</p> </sec> <sec> <title>METHODS</title> <p>A systematic assessment of the educational content regarding depression in the apps available in the Apple App Store and Google Play was conducted in July 2020. A systematic search for apps published or updated since January 2019 was performed using 42matters. Apps meeting the inclusion criteria were downloaded and assessed using two smartphones: an iPhone 7 (iOS version 14.0.1) and a Sony XPERIA XZs (Android version 8.0.0). The 156-question assessment checklist comprised general characteristics of apps, appraisal of 38 educational topics and their adherence to evidence-based clinical guidelines, as well as technical aspects and quality assurance. The results were tabulated and reported as a narrative review, using descriptive statistics.</p> </sec>
Meinert E, Eerens J, Banks C, et al., 2021, Exploring the Cost of eLearning in Health Professions Education: Scoping Review, JMIR MEDICAL EDUCATION, Vol: 7, ISSN: 2369-3762
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- Citations: 8
Surendran S, De Foo C, Tam CH, et al., 2021, The Missed Opportunity of Patient-Centered Medical Homes to Thrive in an Asian Context, INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH, Vol: 18
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- Citations: 5
Ho AHY, Lall P, Tan WS, et al., 2021, Sustainable implementation of advance care planning in Asia: An interpretive-systemic framework for national development, PALLIATIVE & SUPPORTIVE CARE, Vol: 19, Pages: 82-92, ISSN: 1478-9515
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- Citations: 5
Martinengo L, Stona A-C, Griva K, et al., 2021, Self-guided Cognitive Behavioral Therapy Apps for Depression: Systematic Assessment of Features, Functionality, and Congruence With Evidence (Preprint)
<sec> <title>BACKGROUND</title> <p>Mental health disorders affect 1 in 10 people globally, of whom approximately 300 million are affected by depression. At least half of the people affected by depression remain untreated. Although cognitive behavioral therapy (CBT) is an effective treatment, access to mental health specialists, habitually challenging, has worsened because of the COVID-19 pandemic. Internet-based CBT is an effective and feasible strategy to increase access to treatment for people with depression. Mental health apps may further assist in facilitating self-management for people affected by depression; however, accessing the correct app may be cumbersome given the large number and wide variety of apps offered by public app marketplaces.</p> </sec> <sec> <title>OBJECTIVE</title> <p>This study aims to systematically assess the features, functionality, data security, and congruence with evidence of self-guided CBT-based apps targeting users affected by depression that are available in major app stores.</p> </sec> <sec> <title>METHODS</title> <p>We conducted a systematic assessment of self-guided CBT-based apps available in Google Play and the Apple App Store. Apps launched or updated since August 2018 were identified through a systematic search in the 42matters database using CBT-related terms. Apps meeting the inclusion criteria were downloaded and assessed using a Samsung Galaxy J7 Pro (Android 9) and iPhone 7 (iOS 13.3.1). Apps were appraised using a 182-question checklist developed by the research team, assessing their general characteristics, technical aspects and quality assurance, and CBT-related features, including 6 evidence-based CBT tech
Jimenez G, Matchar D, Koh CHG, et al., 2021, The Role of Health Technologies in Multicomponent Primary Care Interventions: Systematic Review, JOURNAL OF MEDICAL INTERNET RESEARCH, Vol: 23, ISSN: 1438-8871
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- Citations: 4
Udeh-Momoh CT, Watermeyer T, Sindi S, et al., 2021, Associations of Health, Lifestyle and Psycho-Social Factors With Sleep Quality During the Early Phase of the COVID-19 Pandemic: A Focus on UK Older Adults Deemed Clinically Extremely Vulnerable, SSRN Electronic Journal
Meinert E, Eerens J, Banks C, et al., 2021, Exploring the cost of eLearning within the field of health professions education: Scoping review, JMIR Medical Education, Vol: 7, ISSN: 2369-3762
Background:Existing research on the costs associated with the design and deployment of eLearning in health professions education is limited. The relative costs of these learning platforms to those of face-to-face learning are also not well understood. The lack of predefined costing models used for eLearning cost data capture has made it difficult to complete cost evaluation.Objective:The key aim of this scoping review was to explore the state of evidence concerning cost capture within eLearning in health professions education. The review explores the available data to define cost calculations related to eLearning.Methods:The scoping review was performed using a search strategy with Medical Subject Heading terms and related keywords centered on eLearning and cost calculation with a population scope of health professionals in all countries. The search was limited to articles published in English. No restriction was placed on literature publication date.Results:In total, 7344 articles were returned from the original search of the literature. Of these, 232 were relevant to associated keywords or abstract references following screening. Full-text review resulted in 168 studies being excluded. Of these, 61 studies were excluded because they were unrelated to eLearning and focused on general education. In addition, 103 studies were excluded because of lack of detailed information regarding costs; these studies referred to cost in ways either indicating cost favorability or unfavorability, but without data to support findings. Finally, 4 studies were excluded because of limited cost data that were insufficient for analysis. In total, 42 studies provided data and analysis of the impact of cost and value in health professions education. The most common data source was total cost of training (n=29). Other sources included cost per learner, referring to the cost for individual students (n=13). The population most frequently cited was medical students (n=15), although 12 article
Pavagadhi D, Car J, 2021, Pedometer-based walking interventions provide sustained increases in physical activity levels, as well as reductions in cardiovascular events and fractures., Evid Based Nurs, Vol: 24
Jimenez G, Matchar D, Koh GC-H, et al., 2021, Multicomponent interventions for enhancing primary care: a systematic review, BRITISH JOURNAL OF GENERAL PRACTICE, Vol: 71, Pages: E10-E21, ISSN: 0960-1643
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- Citations: 7
De Foo C, Surendran S, Tam CH, et al., 2021, Perceived facilitators and barriers to chronic disease management in primary care networks of Singapore: a qualitative study, BMJ OPEN, Vol: 11, ISSN: 2044-6055
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- Citations: 4
Roth GA, Mensah GA, Johnson CO, et al., 2020, Global burden of cardiovascular diseases and risk factors, 1990-2019: update from the GBD 2019 study., Journal of the American College of Cardiology, Vol: 76, Pages: 2982-3021, ISSN: 0735-1097
Cardiovascular diseases (CVDs), principally ischemic heart disease (IHD) and stroke, are the leading cause of global mortality and a major contributor to disability. This paper reviews the magnitude of total CVD burden, including 13 underlying causes of cardiovascular death and 9 related risk factors, using estimates from the Global Burden of Disease (GBD) Study 2019. GBD, an ongoing multinational collaboration to provide comparable and consistent estimates of population health over time, used all available population-level data sources on incidence, prevalence, case fatality, mortality, and health risks to produce estimates for 204 countries and territories from 1990 to 2019. Prevalent cases of total CVD nearly doubled from 271 million (95% uncertainty interval [UI]: 257 to 285 million) in 1990 to 523 million (95% UI: 497 to 550 million) in 2019, and the number of CVD deaths steadily increased from 12.1 million (95% UI:11.4 to 12.6 million) in 1990, reaching 18.6 million (95% UI: 17.1 to 19.7 million) in 2019. The global trends for disability-adjusted life years (DALYs) and years of life lost also increased significantly, and years lived with disability doubled from 17.7 million (95% UI: 12.9 to 22.5 million) to 34.4 million (95% UI:24.9 to 43.6 million) over that period. The total number of DALYs due to IHD has risen steadily since 1990, reaching 182 million (95% UI: 170 to 194 million) DALYs, 9.14 million (95% UI: 8.40 to 9.74 million) deaths in the year 2019, and 197 million (95% UI: 178 to 220 million) prevalent cases of IHD in 2019. The total number of DALYs due to stroke has risen steadily since 1990, reaching 143 million (95% UI: 133 to 153 million) DALYs, 6.55 million (95% UI: 6.00 to 7.02 million) deaths in the year 2019, and 101 million (95% UI: 93.2 to 111 million) prevalent cases of stroke in 2019. Cardiovascular diseases remain the leading cause of disease burden in the world. CVD burden continues its decades-long rise for almost al
Surendra NK, Lo ZJ, Saxena A, et al., 2020, CLINICAL AND ECONOMIC BURDEN OF DIABETIC FOOT ULCERS: A 5-YEAR LONGITUDINAL INSTITUTIONAL POPULATION HEALTH REVIEW, Publisher: ELSEVIER SCIENCE INC, Pages: S513-S513, ISSN: 1098-3015
Osman T, Lew E, Lum EP-M, et al., 2020, PreAnaesThesia computerized health (PATCH) assessment: development and validation, BMC ANESTHESIOLOGY, Vol: 20, ISSN: 1471-2253
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- Citations: 12
Nazeha N, Pavagadhi D, Kyaw BM, et al., 2020, Digitally competent health workforce: a scoping review of educational frameworks, Journal of Medical Internet Research, Vol: 22, Pages: 1-20, ISSN: 1438-8871
Background: Digital health technologies can be key to improving health outcomes, provided health workers are adequately trained to utilize these technologies. There have been efforts to identify digital competencies for different health worker groups, however, an overview of these efforts has yet to be consolidated and analysed.Objective: The objective of this review is to identify and study the existing digital health competency frameworks for health workers and provide recommendations for future digital health training initiatives and framework development.Methods: A literature search was performed to collate digital health competency frameworks published from year 2000. Six databases, including grey literature sources such as OpenGrey, ResearchGate, Google Scholar, Google, and websites of relevant associations were searched in November 2019. Screening and data extraction were performed in parallel by reviewers. The included evidence is narratively described in terms of characteristics, evolution, and structural composition of frameworks. A thematic analysis was also performed to identify common themes across the included frameworks. Findings: Thirty frameworks were included in this review, a majority of which aimed at nurses, originated from high-income countries, published since 2016 and developed via literature reviews, followed by expert consultations. The thematic analysis uncovered 28 digital health competency domains across the included frameworks. The most prevalent domains were pertaining to basic IT literacy, health information management, digital communication, ethical/legal/regulatory requirements, and data privacy/security. The HITCOMP framework was found to be the most comprehensive framework, as it presented 21 out of the 28 identified domains, had the highest number of competencies, and targeted a wide variety of health workers.Conclusions: Digital health training initiatives should focus on competencies relevant to a particular health worker grou
Thach T-Q, Mahirah D, Sauter C, et al., 2020, Associations of perceived indoor environmental quality with stress in the workplace, INDOOR AIR, Vol: 30, Pages: 1166-1177, ISSN: 0905-6947
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- Citations: 16
Xu X, Olsson M, Bajpai R, et al., 2020, Concordance Between Physician-rated and Caregiver-perceived Disease Severity in Children with Atopic Dermatitis: A Cross-sectional Study, ACTA DERMATO-VENEREOLOGICA, Vol: 100, ISSN: 0001-5555
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- Citations: 3
Jimenez G, Spinazze P, Matchar D, et al., 2020, Digital health competencies for primary healthcare professionals: A scoping review, INTERNATIONAL JOURNAL OF MEDICAL INFORMATICS, Vol: 143, ISSN: 1386-5056
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- Citations: 28
Su Y, Roberts AC, Yap HS, et al., 2020, White- and Blue- collar workers responses' towards underground workspaces, TUNNELLING AND UNDERGROUND SPACE TECHNOLOGY, Vol: 105, ISSN: 0886-7798
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- Citations: 4
Xu X, Griva K, Koh M, et al., 2020, Creating a Smartphone App for Caregivers of Children With Atopic Dermatitis With Caregivers, Health Care Professionals, and Digital Health Experts: Participatory Co-Design, JMIR MHEALTH AND UHEALTH, Vol: 8, ISSN: 2291-5222
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- Citations: 10
Car J, Koh GC-H, Foong PS, et al., 2020, Video consultations in primary and specialist care during the covid-19 pandemic and beyond, BMJ-BRITISH MEDICAL JOURNAL, Vol: 371, ISSN: 0959-535X
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- Citations: 95
Murray CJL, Abbafati C, Abbas KM, et al., 2020, Five insights from the Global Burden of Disease Study 2019, The Lancet, Vol: 396, Pages: 1135-1159, ISSN: 0140-6736
The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 provides a rules-based synthesis of the available evidence on levels and trends in health outcomes, a diverse set of risk factors, and health system responses. GBD 2019 covered 204 countries and territories, as well as first administrative level disaggregations for 22 countries, from 1990 to 2019. Because GBD is highly standardised and comprehensive, spanning both fatal and non-fatal outcomes, and uses a mutually exclusive and collectively exhaustive list of hierarchical disease and injury causes, the study provides a powerful basis for detailed and broad insights on global health trends and emerging challenges. GBD 2019 incorporates data from 281 586 sources and provides more than 3·5 billion estimates of health outcome and health system measures of interest for global, national, and subnational policy dialogue. All GBD estimates are publicly available and adhere to the Guidelines on Accurate and Transparent Health Estimate Reporting. From this vast amount of information, five key insights that are important for health, social, and economic development strategies have been distilled. These insights are subject to the many limitations outlined in each of the component GBD capstone papers.
Tan BY, Pereira MJ, Yang S-Y, et al., 2020, Collaborative model of care between Orthopaedics and allied healthcare professionals in knee osteoarthritis (CONNACT): study protocol for an effectiveness-implementation hybrid randomized control trial, BMC MUSCULOSKELETAL DISORDERS, Vol: 21
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- Citations: 1
Rykov Y, Thach T-Q, Bojic I, et al., 2020, Digital Biomarkers for Depression Screening With Wearable Devices: Cross-sectional Study With Machine Learning Modeling (Preprint)
<sec> <title>BACKGROUND</title> <p>Depression is a prevalent mental disorder that is undiagnosed and untreated in half of all cases. Wearable activity trackers collect fine-grained sensor data characterizing the behavior and physiology of users (ie, digital biomarkers), which could be used for timely, unobtrusive, and scalable depression screening.</p> </sec> <sec> <title>OBJECTIVE</title> <p>The aim of this study was to examine the predictive ability of digital biomarkers, based on sensor data from consumer-grade wearables, to detect risk of depression in a working population.</p> </sec> <sec> <title>METHODS</title> <p>This was a cross-sectional study of 290 healthy working adults. Participants wore Fitbit Charge 2 devices for 14 consecutive days and completed a health survey, including screening for depressive symptoms using the 9-item Patient Health Questionnaire (PHQ-9), at baseline and 2 weeks later. We extracted a range of known and novel digital biomarkers characterizing physical activity, sleep patterns, and circadian rhythms from wearables using steps, heart rate, energy expenditure, and sleep data. Associations between severity of depressive symptoms and digital biomarkers were examined with Spearman correlation and multiple regression analyses adjusted for potential confounders, including sociodemographic characteristics, alcohol consumption, smoking, self-rated health, subjective sleep characteristics, and loneliness. Supervised machine learning with statistically selected digital biomarkers was used to predict risk of depression (ie, symptom severity and screening status). We used varying cutoff scores from an acceptable PHQ-9 score range to def
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