164 research outputs found
HCI and Health: Learning from Interdisciplinary Interactions
HCI has multidisciplinary roots and has drawn from and contributed to different disciplines, including computer science, psychology, sociology, and medicine. There is a natural overlap between health and HCI researchers, given their joint focus on utilising technologies to better support people’s health and wellbeing. However, the best digital health interventions are not simply the result of the ‘application’ of HCI to the domain of healthcare, but emerge when researchers from both camps seek to overcome differences in disciplinary practices, traditions, and values in order to collaborate more effectively and productively. We propose a special interest group (SIG) to include interdisciplinary researchers (i.e., participants active in both communities) as well as researchers from either discipline, but with interests in the other field
The Evolution of SIGCHI conferences and the future of CHI
The ACM Conference on Human Factors in Computing Systems(CHI) was born in 1982 and has been held annually since 1985. Specialized conferences (such as IUI, CSCW, MobileHCI, and UIST) gradually emerged and have now become a significant part of the conference program that ACM SIGCHI offers the global HCI community
Strategies for conducting situated studies of technology use in hospitals
Ethnographic methods are widely used for understanding situated practices with technology. When authors present their data gathering methods, they almost invariably focus on the bare essentials. These enable the reader to comprehend what was done, but leave the impression that setting up and conducting the study was straightforward. Text books present generic advice, but rarely focus on specific study contexts. In this paper, we focus on lessons learnt by non-clinical researchers studying technology use in hospitals: gaining access; developing good relations with clinicians and patients; being outsiders in healthcare settings; and managing the cultural divide between technology human factors and clinical practice. Drawing on case studies across various hospital settings, we present a repertoire of ways of working with people and technologies in these settings. These include engaging clinicians and patients effectively, taking an iterative approach to data gathering and being responsive to the demands and opportunities provided by the situation. The main contribution of this paper is to make visible many of the lessons we have learnt in conducting technology studies in healthcare, using these lessons to present strategies that other researchers can take up
Turning to Peers: Integrating Understanding of the Self, the Condition, and Others’ Experiences in Making Sense of Complex Chronic Conditions
People are increasingly involved in the self-management of their own health, including chronic conditions. With technology advances, the choice of self-management practices, tools, and technologies has never been greater. The studies reported here investigated the information seeking practices of two different chronic health populations in their quest to manage their health conditions. Migraine and diabetes patients and clinicians in the UK and the US were interviewed about their information needs and practices, and representative online communities were explored to inform a qualitative study. We found that people with either chronic condition require personally relevant information and use a broad and varied set of practices and tools to make sense of their specific symptoms, triggers, and treatments. Participants sought out different types of information from varied sources about themselves, their medical condition, and their peers' experiences of the same chronic condition. People with diabetes and migraine expended great effort to validate their personal experiences of their condition and determine whether these experiences were 'normal'. Based on these findings, we discuss the need for future personal health technologies that support people in engaging in meaningful and personalised data collection, information seeking, and information sharing with peers in flexible ways that enable them to better understand their own condition
The new SIGCHI EC's values and strategic initiatives.
The SIGCHI EC has articulated the following 10 values. Specifically, these are instrumental values: They are our preferred methods of behavior. They are not an end goal, but they translate into a means by which an end goal is accomplished
Future Opportunities for IoT to Support People with Parkinson’s
Recent years have seen an explosion of internet of things (IoT) technologies being released to the market. There has also been an emerging interest in the potentials of IoT devices to support people with chronic health conditions. In this paper, we describe the results of engagements to scope the future potentials of IoT for supporting people with Parkinson’s. We ran a 2-day multi-disciplinary event with professionals with expertise in Parkinson’s and IoT, to explore the opportunities, challenges and benefits. We then ran 4 workshops, engaging 13 people with Parkinson’s and caregivers, to scope out the needs, values and desires that the community has for utilizing IoT to monitor their symptoms. This work contributes a set of considerations for future IoT solutions that might support people with Parkinson’s in better understanding their condition, through the provision of objective measurements that correspond to their, currently unmeasured, subjective experiences
High genetic diversity of measles virus, World Health Organization European region, 2005-2006
During 2005-2006, nine measles virus (MV) genotypes were identified throughout the World Health Organization European Region. All major epidemics were associated with genotypes D4, D6, and B3. Other genotypes (B2, D5, D8, D9, G2, and H1) were only found in limited numbers of cases after importation from other continents. The genetic diversity of endemic D6 strains was low; genotypes C2 and D7, circulating in Europe until recent years, were no longer identified. The transmission chains of several indigenous MV strains may thus have been interrupted by enhanced vaccination. However, multiple importations from Africa and Asia and virus introduction into highly mobile and unvaccinated communities caused a massive spread of D4 and B3 strains throughout much of the region. Thus, despite the reduction of endemic MV circulation, importation of MV from other continents caused prolonged circulation and large outbreaks after their introduction into unvaccinated and highly mobile communities
Laboratory capability and surveillance testing for middle east respiratory syndrome coronavirus infection in the who european region, June 2013
Turning to Peers: Integrating Understanding of the Self, the Condition, and Others’ Experiences in Making Sense of Complex Chronic Conditions
Global burden and strength of evidence for 88 risk factors in 204 countries and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021
Background: Understanding the health consequences associated with exposure to risk factors is necessary to inform public health policy and practice. To systematically quantify the contributions of risk factor exposures to specific health outcomes, the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 aims to provide comprehensive estimates of exposure levels, relative health risks, and attributable burden of disease for 88 risk factors in 204 countries and territories and 811 subnational locations, from 1990 to 2021. Methods: The GBD 2021 risk factor analysis used data from 54 561 total distinct sources to produce epidemiological estimates for 88 risk factors and their associated health outcomes for a total of 631 risk–outcome pairs. Pairs were included on the basis of data-driven determination of a risk–outcome association. Age-sex-location-year-specific estimates were generated at global, regional, and national levels. Our approach followed the comparative risk assessment framework predicated on a causal web of hierarchically organised, potentially combinative, modifiable risks. Relative risks (RRs) of a given outcome occurring as a function of risk factor exposure were estimated separately for each risk–outcome pair, and summary exposure values (SEVs), representing risk-weighted exposure prevalence, and theoretical minimum risk exposure levels (TMRELs) were estimated for each risk factor. These estimates were used to calculate the population attributable fraction (PAF; ie, the proportional change in health risk that would occur if exposure to a risk factor were reduced to the TMREL). The product of PAFs and disease burden associated with a given outcome, measured in disability-adjusted life-years (DALYs), yielded measures of attributable burden (ie, the proportion of total disease burden attributable to a particular risk factor or combination of risk factors). Adjustments for mediation were applied to account for relationships involving risk factors that act indirectly on outcomes via intermediate risks. Attributable burden estimates were stratified by Socio-demographic Index (SDI) quintile and presented as counts, age-standardised rates, and rankings. To complement estimates of RR and attributable burden, newly developed burden of proof risk function (BPRF) methods were applied to yield supplementary, conservative interpretations of risk–outcome associations based on the consistency of underlying evidence, accounting for unexplained heterogeneity between input data from different studies. Estimates reported represent the mean value across 500 draws from the estimate's distribution, with 95% uncertainty intervals (UIs) calculated as the 2·5th and 97·5th percentile values across the draws. Findings: Among the specific risk factors analysed for this study, particulate matter air pollution was the leading contributor to the global disease burden in 2021, contributing 8·0% (95% UI 6·7–9·4) of total DALYs, followed by high systolic blood pressure (SBP; 7·8% [6·4–9·2]), smoking (5·7% [4·7–6·8]), low birthweight and short gestation (5·6% [4·8–6·3]), and high fasting plasma glucose (FPG; 5·4% [4·8–6·0]). For younger demographics (ie, those aged 0–4 years and 5–14 years), risks such as low birthweight and short gestation and unsafe water, sanitation, and handwashing (WaSH) were among the leading risk factors, while for older age groups, metabolic risks such as high SBP, high body-mass index (BMI), high FPG, and high LDL cholesterol had a greater impact. From 2000 to 2021, there was an observable shift in global health challenges, marked by a decline in the number of all-age DALYs broadly attributable to behavioural risks (decrease of 20·7% [13·9–27·7]) and environmental and occupational risks (decrease of 22·0% [15·5–28·8]), coupled with a 49·4% (42·3–56·9) increase in DALYs attributable to metabolic risks, all reflecting ageing populations and changing lifestyles on a global scale. Age-standardised global DALY rates attributable to high BMI and high FPG rose considerably (15·7% [9·9–21·7] for high BMI and 7·9% [3·3–12·9] for high FPG) over this period, with exposure to these risks increasing annually at rates of 1·8% (1·6–1·9) for high BMI and 1·3% (1·1–1·5) for high FPG. By contrast, the global risk-attributable burden and exposure to many other risk factors declined, notably for risks such as child growth failure and unsafe water source, with age-standardised attributable DALYs decreasing by 71·5% (64·4–78·8) for child growth failure and 66·3% (60·2–72·0) for unsafe water source. We separated risk factors into three groups according to trajectory over time: those with a decreasing attributable burden, due largely to declining risk exposure (eg, diet high in trans-fat and household air pollution) but also to proportionally smaller child and youth populations (eg, child and maternal malnutrition); those for which the burden increased moderately in spite of declining risk exposure, due largely to population ageing (eg, smoking); and those for which the burden increased considerably due to both increasing risk exposure and population ageing (eg, ambient particulate matter air pollution, high BMI, high FPG, and high SBP). Interpretation: Substantial progress has been made in reducing the global disease burden attributable to a range of risk factors, particularly those related to maternal and child health, WaSH, and household air pollution. Maintaining efforts to minimise the impact of these risk factors, especially in low SDI locations, is necessary to sustain progress. Successes in moderating the smoking-related burden by reducing risk exposure highlight the need to advance policies that reduce exposure to other leading risk factors such as ambient particulate matter air pollution and high SBP. Troubling increases in high FPG, high BMI, and other risk factors related to obesity and metabolic syndrome indicate an urgent need to identify and implement interventions
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