Explore the vast range of titles available.

Background Hypertension remains one of the most important preventable risk factors for diseases and death. Identifying clustered patterns of modifiable lifestyle risk factors for hypertension and demographics factors related to these clustered patterns allows for targeting health prevention interventions. Therefore, this study aims to identify latent classes of hypertensive patients’ lifestyle risk factors based on the clustering of four modifiable lifestyle risk factors: eating, physical activity patterns, smoking habits, and blood pressure control. Methods A total of 750 patients ( M age  = 65.38 years, SD age  = 9.2 years) with diagnosed hypertension in urban and rural primary health care centers in Takab (Iran) were recruited randomly from August 2016 to February 2017. Latent class analysis was performed by using proc. LCA in SAS 9.2. Results Three classes of lifestyle patterns were identified. About 14.4% of hypertensive patients were categorized in a low-risk class (I), 54.6% in an intermediate-risk class (II), and 31% in a high-risk class (III) of lifestyle. A one-year increase in age significantly increases the risk of membership in classes II and III. Similarly, being widowed or divorced increases the risk of membership in classes II and III. Also, having a higher education level decreases the risk of membership in classes II and III. Conclusions This study contributes to the literature on lifestyle behaviors among older adults and provides evidence that there are considerable differences in lifestyle behaviors between subgroups of older adult patients. The three profiles of hypertensive patients’ conditions suggest that because behaviors often occur simultaneously within an individual level, a latent-class approach helps cluster co-occurrence risk behaviors and focuses on interventions targeted to several healthy behaviors among high-risk patients.

Research on digital technology to change health behavior has increased enormously in recent decades. Due to the interdisciplinary nature of this topic, knowledge and technologies from different research areas are required. Up to now, it is not clear how the knowledge from those fields is combined in actual applications. A comprehensive analysis that systematically maps and explores the use of knowledge within this emerging interdisciplinary field is required. This study aims to provide an overview of the research area around the design and development of digital technologies for health behavior change and to explore trends and patterns. A bibliometric analysis is used to provide an overview of the field, and a scoping review is presented to identify the trends and possible gaps. The study is based on the publications related to persuasive technologies and health behavior change in the last 18 years, as indexed by the Web of Science and Scopus (317 and 314 articles, respectively). In the first part, regional and time-based publishing trends; research fields and keyword co-occurrence networks; influential journals; and collaboration network between influential authors, countries, and institutions are examined. In the second part, the behavioral domains, technological means and theoretical foundations are investigated via a scoping review. The literature reviewed shows a clear and emerging trend after 2001 in technology-based behavior change, which grew exponentially after the introduction of the smartphone around 2009. Authors from the United States, Europe, and Australia have the highest number of publications in the field. The three most active research areas are computer science, public and occupational health, and psychology. The keyword \"mhealth\" was the dominant term and predominantly used together with the term \"physical activity\" and \"ehealth\". A total of three strong clusters of coauthors have been found. Nearly half of the total reported papers were published in three journals. The United States, the United Kingdom, and the Netherlands have the highest degree of author collaboration and a strong institutional network. Mobile phones were most often used as a technology platform, regardless of the targeted behavioral domain. Physical activity and healthy eating were the most frequently targeted behavioral domains. Most articles did not report about the behavior change techniques that were applied. Among the reported behavior change techniques, goal setting and self-management were the most frequently reported. Closer cooperation and interaction between behavioral sciences and technological areas is needed, so that theoretical knowledge and new technological advancements are better connected in actual applications. Eventually, this could result in a larger societal impact, an increase of the effectiveness of digital technologies for health behavioral change, and more insight in the relationship between behavioral change strategies and persuasive technologies' effectiveness.

In spring 2020, the first Covid-19-related lockdown included the closing of kindergartens and schools. Home schooling, the lack of social contacts with peers and the care of the children at home posed an enormous challenge for many families. The present study investigated the leisure behavior of 285 one- to 10-year-old German children at two time points (t1 and t2) during the Covid-19-related lockdown in spring 2020. In the subsample of primary school children (n = 102), we also explored children's attitudes towards schoolwork at home. Analyses focused on the change of behavior from t1 to t2, on differences in these changes depending on socio-economic status (SES), and on associations of behavior with SES, the number of children at home, and the frequency of receiving learning materials from school. While the frequency of playing outside increased significantly from t1 to t2, the frequency of handicrafts, playing board games, indoor sports, and motivation to do schoolwork decreased. The observed changes between t1 and t2 did not differ depending on SES. However, a lower SES was associated with higher media use, less outdoor activity, and (though only marginally significant) a reduced time doing schoolwork and a reduced ability to concentrate on schoolwork at t1. In households with more children, children played outside more often, but were read to less frequently and (though only marginally significant) watched movies and series less frequently. Children receiving learning materials from school on a regular basis spent significantly more time doing schoolwork at home than children receiving materials only irregularly. A continuing loss of childcare in day-care facilities and schools entails the danger of declining education in the form of (inter)active indoor activities and schoolwork.

Vietnam's burden of liver cancer is largely due to its high prevalence of chronic hepatitis B virus (HBV) infection. This study aimed to examine healthcare workers' (HCWs) knowledge, attitude and practices regarding HBV prevention and management. A cross-sectional survey among health care workers working at primary and tertiary facilities in two Northern provinces in Vietnam in 2017. A standardized questionnaire was administered to randomly selected HCWs. Multivariate regression was used to identify predictors of the HBV knowledge score. Among the 314 participants, 75.5% did not know HBV infection at birth carries the highest risk of developing chronic infection. The median knowledge score was 25 out of 42 (59.5%). About one third (30.2%) wrongly believed that HBV can be transmitted through eating or sharing food with chronic hepatitis B patients. About 38.8% did not feel confident that the hepatitis B vaccine is safe. Only 30.1% provided correct answers to all the questions on injection safety. Up to 48.2% reported they consistently recap needles with two hands after injection, a practice that would put them at greater risk of needle stick injury. About 24.2% reported having been pricked by a needle at work within the past 12 months. More than 40% were concerned about having casual contact or sharing food with a person with chronic hepatitis B infection (CHB). In multivariate analysis, physicians scored significantly higher compared to other healthcare professionals. Having received training regarding hepatitis B within the last two years was also significantly associated with a better HBV knowledge score. Findings from the survey indicated an immediate need to implement an effective hepatitis B education and training program to build capacity among Vietnam's healthcare workers in hepatitis B prevention and control and to dispel hepatitis B stigma.

Background The World Health Organization (WHO) International Classification of Diseases and Related Health Problems (ICD) is used globally by 194 WHO member nations. It is used for assigning clinical diagnoses, providing the framework for reporting public health data, and to inform the organization and reimbursement of health services. Guided by overarching principles of increasing clinical utility and global applicability, the 11th revision of the ICD proposes major changes that incorporate empirical advances since the previous revision in 1992. To test recommended changes in the Mental, Behavioral, and Neurodevelopmental Disorders chapter, multiple vignette-based case-controlled field studies have been conducted which examine clinicians’ ability to accurately and consistently use the new guidelines and assess their overall clinical utility. This manuscript reports on the results from the study of the proposed ICD-11 guidelines for feeding and eating disorders (FEDs). Method Participants were 2288 mental health professionals registered with WHO’s Global Clinical Practice Network. The study was conducted in Chinese, English, French, Japanese, and Spanish. Clinicians were randomly assigned to apply either the ICD-11 or ICD-10 diagnostic guidelines for FEDs to a pair of case vignettes designed to test specific clinical questions. Clinicians selected the diagnosis they thought was correct for each vignette, evaluated the presence of each essential feature of the selected diagnosis, and the clinical utility of the diagnostic guidelines. Results The proposed ICD-11 diagnostic guidelines significantly improved accuracy for all FEDs tested relative to ICD-10 and attained higher clinical utility ratings; similar results were obtained across all five languages. The inclusion of binge eating disorder and avoidant-restrictive food intake disorder reduced the use of residual diagnoses. Areas needing further refinement were identified. Conclusions The proposed ICD-11 diagnostic guidelines consistently outperformed ICD-10 in distinguishing cases of eating disorders and showed global applicability and appropriate clinical utility. These results suggest that the proposed ICD-11 guidelines for FEDs will help increase accuracy of public health data, improve clinical diagnosis, and enhance health service organization and provision. This is the first time in the revision of the ICD that data from large-scale, empirical research examining proposed guidelines is completed in time to inform the final diagnostic guidelines.

While considerable efforts have been made to understand the neurobiological basis of substance addiction, the potentially “addictive” qualities of repetitive behaviors, and whether such behaviors constitute “behavioral addictions,” is relatively neglected. It has been suggested that some conditions, such as gambling disorder, compulsive stealing, compulsive buying, compulsive sexual behavior, and problem Internet use, have phenomenological and neurobiological parallels with substance use disorders. This review considers how the issue of “behavioral addictions” has been handled by latest revisions of the Diagnostic and Statistical Manual of Mental Disorders (DSM) and the International Classification of Diseases (ICD), leading to somewhat divergent approaches. We also consider key areas for future research in order to address optimal diagnostic classification and treatments for such repetitive, debilitating behaviors.

Rigorous analysis of levels and trends in exposure to leading risk factors and quantification of their effect on human health are important to identify where public health is making progress and in which cases current efforts are inadequate. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 provides a standardised and comprehensive assessment of the magnitude of risk factor exposure, relative risk, and attributable burden of disease. GBD 2019 estimated attributable mortality, years of life lost (YLLs), years of life lived with disability (YLDs), and disability-adjusted life-years (DALYs) for 87 risk factors and combinations of risk factors, at the global level, regionally, and for 204 countries and territories. GBD uses a hierarchical list of risk factors so that specific risk factors (eg, sodium intake), and related aggregates (eg, diet quality), are both evaluated. This method has six analytical steps. (1) We included 560 risk–outcome pairs that met criteria for convincing or probable evidence on the basis of research studies. 12 risk–outcome pairs included in GBD 2017 no longer met inclusion criteria and 47 risk–outcome pairs for risks already included in GBD 2017 were added based on new evidence. (2) Relative risks were estimated as a function of exposure based on published systematic reviews, 81 systematic reviews done for GBD 2019, and meta-regression. (3) Levels of exposure in each age-sex-location-year included in the study were estimated based on all available data sources using spatiotemporal Gaussian process regression, DisMod-MR 2.1, a Bayesian meta-regression method, or alternative methods. (4) We determined, from published trials or cohort studies, the level of exposure associated with minimum risk, called the theoretical minimum risk exposure level. (5) Attributable deaths, YLLs, YLDs, and DALYs were computed by multiplying population attributable fractions (PAFs) by the relevant outcome quantity for each age-sex-location-year. (6) PAFs and attributable burden for combinations of risk factors were estimated taking into account mediation of different risk factors through other risk factors. Across all six analytical steps, 30 652 distinct data sources were used in the analysis. Uncertainty in each step of the analysis was propagated into the final estimates of attributable burden. Exposure levels for dichotomous, polytomous, and continuous risk factors were summarised with use of the summary exposure value to facilitate comparisons over time, across location, and across risks. Because the entire time series from 1990 to 2019 has been re-estimated with use of consistent data and methods, these results supersede previously published GBD estimates of attributable burden. The largest declines in risk exposure from 2010 to 2019 were among a set of risks that are strongly linked to social and economic development, including household air pollution; unsafe water, sanitation, and handwashing; and child growth failure. Global declines also occurred for tobacco smoking and lead exposure. The largest increases in risk exposure were for ambient particulate matter pollution, drug use, high fasting plasma glucose, and high body-mass index. In 2019, the leading Level 2 risk factor globally for attributable deaths was high systolic blood pressure, which accounted for 10·8 million (95% uncertainty interval [UI] 9·51–12·1) deaths (19·2% [16·9–21·3] of all deaths in 2019), followed by tobacco (smoked, second-hand, and chewing), which accounted for 8·71 million (8·12–9·31) deaths (15·4% [14·6–16·2] of all deaths in 2019). The leading Level 2 risk factor for attributable DALYs globally in 2019 was child and maternal malnutrition, which largely affects health in the youngest age groups and accounted for 295 million (253–350) DALYs (11·6% [10·3–13·1] of all global DALYs that year). The risk factor burden varied considerably in 2019 between age groups and locations. Among children aged 0–9 years, the three leading detailed risk factors for attributable DALYs were all related to malnutrition. Iron deficiency was the leading risk factor for those aged 10–24 years, alcohol use for those aged 25–49 years, and high systolic blood pressure for those aged 50–74 years and 75 years and older. Overall, the record for reducing exposure to harmful risks over the past three decades is poor. Success with reducing smoking and lead exposure through regulatory policy might point the way for a stronger role for public policy on other risks in addition to continued efforts to provide information on risk factor harm to the general public. Bill & Melinda Gates Foundation.

Traditional self-injurious behavior (SIB) management can place compliance demands on the caregiver and have low ecological validity and accuracy. To support an SIB monitoring system for autism spectrum disorder (ASD), we evaluated machine learning methods for detecting and distinguishing diverse SIB types. SIB episodes were captured with body-worn accelerometers from children with ASD and SIB. The highest detection accuracy was found with k-nearest neighbors and support vector machines (up to 99.1% for individuals and 94.6% for grouped participants), and classification efficiency was quite high (offline processing at ~ 0.1 ms/observation). Our results provide an initial step toward creating a continuous and objective smart SIB monitoring system, which could in turn facilitate the future care of a pervasive concern in ASD.

Background The importance of behaviour change in improving health is illustrated by the increasing investment by funding bodies in the development and evaluation of complex interventions to change population, patient, and practitioner behaviours. The development of effective interventions is hampered by the absence of a nomenclature to specify and report their content. This limits the possibility of replicating effective interventions, synthesising evidence, and understanding the causal mechanisms underlying behaviour change. In contrast, biomedical interventions are precisely specified ( e.g. , the pharmacological 'ingredients' of prescribed drugs, their dose and frequency of administration). For most complex interventions, the precise 'ingredients' are unknown; descriptions ( e.g. , 'behavioural counseling') can mean different things to different researchers or implementers. The lack of a method for specifying complex interventions undermines the precision of evidence syntheses of effectiveness, posing a problem for secondary, as well as primary, research. We aim to develop a reliable method of specifying intervention components ('techniques') aimed at changing behaviour. Methods/Design The research will be conducted in three phases. The first phase will develop the nomenclature. We will refine a preliminary list of techniques and definitions. Using a formal consensus method, experts will then define the key attributes of each technique and how it relates to, and differs from, others. They will evaluate the techniques and their definitions until they achieve an agreed-upon list of clearly defined, nonredundant techniques. The second phase will test the nomenclature. Trained experts (primary researchers and systematic reviewers), equipped with a coding manual and guidance, will use the nomenclature to code published descriptions of complex interventions. Reliability between experts, over time, and across types of users will be assessed. We will assess whether using the nomenclature to write intervention descriptions enhances the clarity and replicability of interventions. The third phase will develop a web-based users' resource of clearly specified and nonredundant techniques, which will aid the scientific understanding of, and development of, effective complex interventions. Dissemination throughout the project will be through stakeholder meetings, targeted multidisciplinary workshops, conference presentation, journal publication, and publication in an interactive web-based platform (a Wiki). Discussion The development of a reliable method of specifying intervention components aimed at changing behaviour will strengthen the scientific basis for developing, evaluating, and reporting complex interventions. It will improve the precision of evidence syntheses of effectiveness, thus enhancing secondary, as well as primary, research.