The reliability and validity of a Japanese version of symptom checklist 90 revised

<p>Abstract</p> <p>Objective</p> <p>To examine the validity and reliability of a Japanese version of the Symptom Checklist 90 Revised (SCL-90-R (J)).</p> <p>Methods</p> <p>The English SCL-90-R was translated to Japanese and the Japanese version confirmed by back-translation. To determine the factor validity and internal consistency of the nine primary subscales, 460 people from the community completed SCL-90-R(J). Test-retest reliability was examined for 104 outpatients and 124 healthy undergraduate students. The convergent-discriminant validity was determined for 80 inpatients who replied to both SCL-90-R(J) and the Minnesota Multiphasic Personality Inventory (MMPI).</p> <p>Results</p> <p>The correlation coefficients between the nine primary subscales and items were .26 to .78. Cronbach's alpha coefficients were from .76 (Phobic Anxiety) to .86 (Interpersonal Sensitivity). Pearson's correlation coefficients between test-retest scores were from .81 (Psychoticism) to .90 (Somatization) for the outpatients and were from .64 (Phobic Anxiety) to .78 (Paranoid Ideation) for the students. Each of the nine primary subscales correlated well with their corresponding constructs in the MMPI.</p> <p>Conclusion</p> <p>We confirmed the validity and reliability of SCL-90-R(J) for the measurement of individual distress. The nine primary subscales were consistent with the items of the original English version.</p

Usability and feasibility of PreventS-MD webapp for stroke prevention

Background: Most strokes and cardiovascular diseases (CVDs) are potentially preventable if their risk factors are identified and well controlled. Digital platforms, such as the PreventS-MD webapp (PreventS-MD) may aid health care professionals (HCPs) in assessing and managing risk factors and promoting lifestyle changes for their patients.Methods: This is a mixed methods cross-sectional 2-phase survey using a largely positivist (quantitative and qualitative) framework. During phase 1, a prototype of PreventS-MD was tested internationally by 59 of 69 consenting HCPs of different backgrounds, age, sex, working experience and specialities using hypothetical data. Collected comments/suggestions from the study HCPs in phase 1 were reviewed and implemented. In phase 2, a near-final version of PreventS-MD was developed and tested by 58 of 72 consenting HCPs using both hypothetical and real patient (n=10) data. Qualitative semi-structured interviews with real patients (n=10) were conducted, and 1-month adherence to the preventative recommendations was assessed by self-reporting. The four System Usability Scale (SUS) groups of scores (0-50 unacceptable; 51-68 poor, 68-80.3 good; >80.3 excellent) were used to determine usability of PreventS-MD.Findings: 99 HCPs from 27 countries (45% from low- to middle-income countries) participated in the study, out of whom 10 HCPs were involved in the development of PreventS before the study, and therefore were not involved in the survey. Of the remaining 89 HCPs 69 consented to the first phase of the survey, out of whom 59 completed the first phase of the survey (response rate 86%) and 58 HCPs completed the second phase of the survey (response rate 84%). The SUS scores supported good usability of the prototype (mean score=80.2; 95% CI [77.0-84.0]) and excellent usability of the final version of PreventS-MD (mean score=81.7; 95%CI [79.1-84.3]) in the field. Scores were not affected by the age, sex, working experience or speciality of the HCPs. One month follow-up of the patients confirmed the high level of satisfaction/acceptability of PreventS-MD and (100%) adherence to the recommendations. Interpretation: The PreventS-MD webapp has a high level of usability, feasibility and satisfaction by HCPs and individuals at risk of stroke/CVD. Individuals at risk of stroke/CVD demonstrated a high level of confidence and motivation in following and adhering to preventative recommendations generated by PreventS-MD

Defining neurotrauma in administrative data using the International Classification of Diseases Tenth Revision

Abstract Background It is essential to use a definition that is precise and accurate for the surveillance of traumatic brain injuries (TBI) and spinal cord injuries (SCI). This paper reviews the International Classification of Diseases 10th revision (ICD-10) definitions used internationally to inform the definition for neurotrauma surveillance using administrative data in Ontario, Canada. Methods PubMed, Web of Science, Medline and the grey literature were searched for keywords "spinal cord injuries" or "brain injuries" and "international classification of diseases". All papers and reports that used an ICD-10 definition were included. To determine the ICD-10 codes for inclusion consensus across papers and additional evidence were sought to look at the correlation between the condition and brain or spinal injuries. Results Twenty-four articles and reports were identified; 15 unique definitions for TBI and 7 for SCI were found. The definitions recommended for use in Ontario by this paper are F07.2, S02.0, S02.1, S02.3, S02.7, S02.8, S02.9, S06, S07.1, T90.2, and T90.5 for traumatic brain injuries and S14.0, S14.1, S24.0, S24.1, S34.1, S34.0, S34.3, T06.0, T06.1 and T91.3 for spinal cord injuries. Conclusions Internationally, inconsistent definitions are used to define brain and spinal cord injuries. An abstraction study of data would be an asset in understanding the effects of inclusion and exclusion of codes in the definition. This paper offers a definition of neurotrauma for surveillance in Ontario, but the definition could be applied to other countries that have mandated administrative data collection

Global, regional, and national comparative risk assessment of 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks, 1990-2015: a systematic analysis for the Global Burden of Disease Study 2015

SummaryBackground The Global Burden of Diseases, Injuries, and Risk Factors Study 2015 provides an up-to-date synthesis of the evidence for risk factor exposure and the attributable burden of disease. By providing national and subnational assessments spanning the past 25 years, this study can inform debates on the importance of addressing risks in context. Methods We used the comparative risk assessment framework developed for previous iterations of the Global Burden of Disease Study to estimate attributable deaths, disability-adjusted life-years (DALYs), and trends in exposure by age group, sex, year, and geography for 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks from 1990 to 2015. This study included 388 risk-outcome pairs that met World Cancer Research Fund-defined criteria for convincing or probable evidence. We extracted relative risk and exposure estimates from randomised controlled trials, cohorts, pooled cohorts, household surveys, census data, satellite data, and other sources. We used statistical models to pool data, adjust for bias, and incorporate covariates. We developed a metric that allows comparisons of exposure across risk factors—the summary exposure value. Using the counterfactual scenario of theoretical minimum risk level, we estimated the portion of deaths and DALYs that could be attributed to a given risk. We decomposed trends in attributable burden into contributions from population growth, population age structure, risk exposure, and risk-deleted cause-specific DALY rates. We characterised risk exposure in relation to a Socio-demographic Index (SDI). Findings Between 1990 and 2015, global exposure to unsafe sanitation, household air pollution, childhood underweight, childhood stunting, and smoking each decreased by more than 25%. Global exposure for several occupational risks, high body-mass index (BMI), and drug use increased by more than 25% over the same period. All risks jointly evaluated in 2015 accounted for 57·8% (95% CI 56·6–58·8) of global deaths and 41·2% (39·8–42·8) of DALYs. In 2015, the ten largest contributors to global DALYs among Level 3 risks were high systolic blood pressure (211·8 million [192·7 million to 231·1 million] global DALYs), smoking (148·6 million [134·2 million to 163·1 million]), high fasting plasma glucose (143·1 million [125·1 million to 163·5 million]), high BMI (120·1 million [83·8 million to 158·4 million]), childhood undernutrition (113·3 million [103·9 million to 123·4 million]), ambient particulate matter (103·1 million [90·8 million to 115·1 million]), high total cholesterol (88·7 million [74·6 million to 105·7 million]), household air pollution (85·6 million [66·7 million to 106·1 million]), alcohol use (85·0 million [77·2 million to 93·0 million]), and diets high in sodium (83·0 million [49·3 million to 127·5 million]). From 1990 to 2015, attributable DALYs declined for micronutrient deficiencies, childhood undernutrition, unsafe sanitation and water, and household air pollution; reductions in risk-deleted DALY rates rather than reductions in exposure drove these declines. Rising exposure contributed to notable increases in attributable DALYs from high BMI, high fasting plasma glucose, occupational carcinogens, and drug use. Environmental risks and childhood undernutrition declined steadily with SDI; low physical activity, high BMI, and high fasting plasma glucose increased with SDI. In 119 countries, metabolic risks, such as high BMI and fasting plasma glucose, contributed the most attributable DALYs in 2015. Regionally, smoking still ranked among the leading five risk factors for attributable DALYs in 109 countries; childhood underweight and unsafe sex remained primary drivers of early death and disability in much of sub-Saharan Africa. Interpretation Declines in some key environmental risks have contributed to declines in critical infectious diseases. Some risks appear to be invariant to SDI. Increasing risks, including high BMI, high fasting plasma glucose, drug use, and some occupational exposures, contribute to rising burden from some conditions, but also provide opportunities for intervention. Some highly preventable risks, such as smoking, remain major causes of attributable DALYs, even as exposure is declining. Public policy makers need to pay attention to the risks that are increasingly major contributors to global burden. Funding Bill & Melinda Gates Foundation

Global and regional burden of disease and injury in 2016 arising from occupational exposures : a systematic analysis for the Global Burden of Disease Study 2016

Objectives This study provides an overview of the influence of occupational risk factors on the global burden of disease as estimated by the occupational component of the Global Burden of Disease (GBD) 2016 study. Methods The GBD 2016 study estimated the burden in terms of deaths and disability-adjusted life years (DALYs) arising from the effects of occupational risk factors (carcinogens; asthmagens; particulate matter, gases and fumes (PMGF); secondhand smoke (SHS); noise; ergonomic risk factors for low back pain; risk factors for injury). A population attributable fraction (PAF) approach was used for most risk factors. Results In 2016, globally, an estimated 1.53 (95% uncertainty interval 1.39-1.68) million deaths and 76.1 (66.3-86.3) million DALYs were attributable to the included occupational risk factors, accounting for 2.8% of deaths and 3.2% of DALYs from all causes. Most deaths were attributable to PMGF, carcinogens (particularly asbestos), injury risk factors and SHS. Most DALYs were attributable to injury risk factors and ergonomic exposures. Men and persons 55 years or older were most affected. PAFs ranged from 26.8% for low back pain from ergonomic risk factors and 19.6% for hearing loss from noise to 3.4% for carcinogens. DALYs per capita were highest in Oceania, Southeast Asia and Central sub-Saharan Africa. On a per capita basis, between 1990 and 2016 there was an overall decrease of about 31% in deaths and 25% in DALYs. Conclusions Occupational exposures continue to cause an important health burden worldwide, justifying the need for ongoing prevention and control initiatives

Mapping disparities in education across low- and middle-income countries

Educational attainment is an important social determinant of maternal, newborn, and child health1–3. As a tool for promoting gender equity, it has gained increasing traction in popular media, international aid strategies, and global agenda-setting4–6. The global health agenda is increasingly focused on evidence of precision public health, which illustrates the subnational distribution of disease and illness7,8; however, an agenda focused on future equity must integrate comparable evidence on the distribution of social determinants of health9–11. Here we expand on the available precision SDG evidence by estimating the subnational distribution of educational attainment, including the proportions of individuals who have completed key levels of schooling, across all low- and middle-income countries from 2000 to 2017. Previous analyses have focused on geographical disparities in average attainment across Africa or for specific countries, but—to our knowledge—no analysis has examined the subnational proportions of individuals who completed specific levels of education across all low- and middle-income countries12–14. By geolocating subnational data for more than 184 million person-years across 528 data sources, we precisely identify inequalities across geography as well as within populations

Serum cytokine and glucose levels as predictors of poststroke fatigue in acute ischemic stroke patients

Fatigue is a common but often overlooked symptom after stroke. This study investigated whether stroke type, infarct volume, and laterality, as well as the levels of various cytokines and other blood components in the acute phase of acute ischemic stroke (AIS), can predict the level of fatigue at 6, 12, and 18 months after its onset. In 45 patients with acute stroke, serum levels of C-reactive protein, hemoglobin, glucose, and 13 cytokines were measured within 72 h of stroke onset. The cytokine measurements were performed using BioPlex XMap technology (Luminex). The acute serum levels of interleukin (IL)-1β and glucose were positively correlated with the score on the Fatigue Severity Scale (FSS) at 6 months after the stroke (r = 0.37, p = 0.015, and r = 0.37, p = 0.017, respectively). The acute serum levels of IL-ra and IL-9 were negatively correlated with FSS score at 12 months after the stroke (r = −0.38, p = 0.013, and r = −0.36, p = 0.019, respectively). The FSS score at 12 months after stroke was significantly lower in patients with radiologically confirmed infarction than in those without such confirmation (p = 0.048). The FSS score at 18 months was not correlated with any of the measured variables. High acute serum levels of glucose and IL-1β, and low IL1-ra and IL-9 may predict fatigue after AIS, indicating that the development of poststroke fatigue can be accounted for by the proinflammatory response associated with AIS. These novel findings support a new cytokine theory of fatigue after stroke. However, more research is needed to validate the results of this study

Use of multidimensional item response theory methods for dementia prevalence prediction: an example using the Health and Retirement Survey and the Aging, Demographics, and Memory Study

Background: Data sparsity is a major limitation to estimating national and global dementia burden. Surveys with full diagnostic evaluations of dementia prevalence are prohibitively resource-intensive in many settings. However, validation samples from nationally representative surveys allow for the development of algorithms for the prediction of dementia prevalence nationally. Methods: Using cognitive testing data and data on functional limitations from Wave A (2001–2003) of the ADAMS study (n = 744) and the 2000 wave of the HRS study (n = 6358) we estimated a two-dimensional item response theory model to calculate cognition and function scores for all individuals over 70. Based on diagnostic information from the formal clinical adjudication in ADAMS, we fit a logistic regression model for the classification of dementia status using cognition and function scores and applied this algorithm to the full HRS sample to calculate dementia prevalence by age and sex. Results: Our algorithm had a cross-validated predictive accuracy of 88% (86–90), and an area under the curve of 0.97 (0.97–0.98) in ADAMS. Prevalence was higher in females than males and increased over age, with a prevalence of 4% (3–4) in individuals 70–79, 11% (9–12) in individuals 80–89 years old, and 28% (22–35) in those 90 and older. Conclusions: Our model had similar or better accuracy as compared to previously reviewed algorithms for the prediction of dementia prevalence in HRS, while utilizing more flexible methods. These methods could be more easily generalized and utilized to estimate dementia prevalence in other national surveys