Evaluating a Novel, Portable, Self-Administrable Device ("Beacon") That Measures Critical Flicker Frequency as a Test for Hepatic Encephalopathy.

INTRODUCTION: We compared critical flicker frequency (CFF) thresholds obtained using a novel portable device "Beacon" with thresholds from the commercially available Lafayette Flicker Fusion System (Lafayette-FFS) in patients with cirrhosis. METHODS: One hundred fifty-three participants with chronic liver disease underwent CFF testing using Beacon and Lafayette-FFS with a method-of-limits and/or forced-choice protocol. RESULTS: Beacon demonstrated excellent test-retest reliability (intraclass correlation 0.91-0.97) and good correlation with the Lafayette-FFS values (intraclass correlation 0.77-0.84). Forced-choice CFF were on average 4.1 Hz higher than method-of-limits descending CFFs. DISCUSSION: Beacon can be self-administered by patients with chronic liver disease and cirrhosis to measure CFF, a validated screening test for minimal hepatic encephalopathy.

MigraineTracker: Examining Patient Experiences with Goal-Directed Self-Tracking for a Chronic Health Condition.

Self-tracking and personal informatics offer important potential in chronic condition management, but such potential is often undermined by difficulty in aligning self-tracking tools to an individual's goals. Informed by prior proposals of goal-directed tracking, we designed and developed MigraineTracker, a prototype app that emphasizes explicit expression of goals for migraine-related self-tracking. We then examined migraine patient experiences in a deployment study for an average of 12+ months, including a total of 50 interview sessions with 10 patients working with 3 different clinicians. Patients were able to express multiple types of goals, evolve their goals over time, align tracking to their goals, personalize their tracking, reflect in the context of their goals, and gain insights that enabled understanding, communication, and action. We discuss how these results highlight the importance of accounting for distinct and concurrent goals in personal informatics together with implications for the design of future goal-directed personal informatics tools.

Role of alcohol taxes in moderating alcohol consumption: Current and future potential impacts.

INTRODUCTION: There is a substantial literature on the price elasticity of demand for alcoholic beverages, but the literature on the tax elasticity and the way tax rates impact the evolution of alcohol consumption through time is more limited. METHODS: A two-level Bayesian hierarchical model is used to estimate tax and income elasticity values. The estimates from five different forecast methods are then averaged, and combined with the tax elasticity estimate, to investigate consumption for different scenarios. The sample consists of 30 high-income and upper-middle-income countries. RESULTS: The alcohol tax elasticity estimate is approximately -0.4 and the alcohol income elasticity estimate approximately 0.2. If alcohol taxes evolve the way they have in the past, there is little evidence to suggest that per capita alcohol consumption will be higher in 2027, relative to 2017; but if alcohol taxes remain constant over the next decade, it is likely that per capita alcohol consumption will be notably higher in 2027, relative to 2017, for the sample of countries considered. DISCUSSION AND CONCLUSIONS: There is a natural tendency for alcohol consumption to increase with income. A working rule of thumb that can be used by policy makers to mitigate this effect is to increase alcohol tax rates at approximately half the long-run gross national income growth rate. For rich countries, this implies annual increases of approximately 1.0-1.5% in alcohol taxes.

The spatiotemporal dynamics, distribution, and characteristics of beached plastics along the remote south coast of Western Australia.

Understanding the accumulation mechanism for beached plastics is important for marine debris research. Similar to the global accumulation pattern for beached plastics, we find that along the remote south coast of Western Australia (SCWA) white, hard, microplastics dominate the microplastic pollution accumulating on beaches. We estimate that along the SCWA, plastics are present at a density of 2.01 items·m-2, but also find that the density of plastic pollution is higher at the eastern end of bays. Significantly fewer plastics were found after easterly winds (austral summer-prevailing winds), and regional physical ocean process, including the Leeuwin Current, and the Ekman transport effect may be relevant to the rate of plastic accumulation on SCWA beaches.

Using Health Concept Surveying to Elicit Usable Evidence: Case Studies of a Novel Evaluation Methodology.

BACKGROUND: Developers, designers, and researchers use rapid prototyping methods to project the adoption and acceptability of their health intervention technology (HIT) before the technology becomes mature enough to be deployed. Although these methods are useful for gathering feedback that advances the development of HITs, they rarely provide usable evidence that can contribute to our broader understanding of HITs. OBJECTIVE: In this research, we aim to develop and demonstrate a variation of vignette testing that supports developers and designers in evaluating early-stage HIT designs while generating usable evidence for the broader research community. METHODS: We proposed a method called health concept surveying for untangling the causal relationships that people develop around conceptual HITs. In health concept surveying, investigators gather reactions to design concepts through a scenario-based survey instrument. As the investigator manipulates characteristics related to their HIT, the survey instrument also measures proximal cognitive factors according to a health behavior change model to project how HIT design decisions may affect the adoption and acceptability of an HIT. Responses to the survey instrument were analyzed using path analysis to untangle the causal effects of these factors on the outcome variables. RESULTS: We demonstrated health concept surveying in 3 case studies of sensor-based health-screening apps. Our first study (N=54) showed that a wait time incentive could influence more people to go see a dermatologist after a positive test for skin cancer. Our second study (N=54), evaluating a similar application design, showed that although visual explanations of algorithmic decisions could increase participant trust in negative test results, the trust would not have been enough to affect people's decision-making. Our third study (N=263) showed that people might prioritize test specificity or sensitivity depending on the nature of the medical condition. CONCLUSIONS: Beyond the findings from our 3 case studies, our research uses the framing of the Health Belief Model to elicit and understand the intrinsic and extrinsic factors that may affect the adoption and acceptability of an HIT without having to build a working prototype. We have made our survey instrument publicly available so that others can leverage it for their own investigations.

Making waves: Creating water sensitive cities in Australia.

Creating water sensitive cities is a stated goal of Australia's National Water Initiative; however, most Australian cities have made only limited progress toward this goal. This paper summarises an in-depth collaborative research project that sought to understand what is holding back investment in water sensitive cities and identify a road map to address the constraints. The project involved research academics, industry participants, and economic regulation agencies from all major Australian jurisdictions. The reforms identified that will move Australia towards a nation of water sensitive cities are: (i) strengthening government policy support for water sensitive urban design to ensure it has equal standing with other policy objectives; (ii) increased government investment for outcomes valued by the community (funded through general taxation or broad-based charges), accompanied by charges for those services used and valued by water utility customers; (iii) improvements to system-level accountability to ensure objectives are met; (iv) changes to the regulatory incentives faced by water utilities to ensure the services valued by customers and community are delivered; (v) removal of barriers to private sector participation in service delivery; and (vi) improved information systems and analytical capabilities to ensure appropriate water sensitive solutions are identified and delivered efficiently.

Accumulation and potential for transport of microplastics in stormwater drains into marine environments, Perth region, Western Australia.

Stormwater drains are important sinks for microplastics and potentially aid the transport of microplastics from terrestrial to marine environments. Samples were collected from sediments in five stormwater drainage systems with different land uses, area, population, and sediment characteristics. Microplastic concentrations within the drainage network varied between 0 and 3500 microplastics per kg of dry sediment, with a mean concentration of 664 particles per kg. The majority of microplastics found were fibres. Polyethylene and polypropylene were the dominant polymer types (µ-FTIR). Based on a Generalized Linear Mixed Model, the expected number of microplastics for a representative urban drain was 760 particles per kg, with 245 particles per kg expected for an agricultural drain. Sediment grain size was a predictor for microplastic abundance, with sandier sediments containing more microplastics. This study is the first to quantify microplastic pollution in stormwater drainage systems in Western Australia.

"They don't always think about that": Translational Needs in the Design of Personal Health Informatics Applications.

Personal health informatics continues to grow in both research and practice, revealing many challenges of designing applications that address people's needs in their health, everyday lives, and collaborations with clinicians. Research suggests strategies to address such challenges, but has struggled to translate these strategies into design practice. This study examines translation of insights from personal health informatics research into resources to support designers. Informed by a review of relevant literature, we present our development of a prototype set of design cards intended to support designers in re-thinking potential assumptions about personal health informatics. We examined our design cards in semi-structured interviews, first with 12 student designers and then with 12 health-focused professional designers and researchers. Our results and discussion reveal tensions and barriers designers encounter, the potential for translational resources to inform the design of health-related technologies, and a need to support designers in addressing challenges of knowledge, advocacy, and evidence in designing for health.

Parallel Journeys of Patients with Cancer and Depression: Challenges and Opportunities for Technology-Enabled Collaborative Care.

Depression is common but under-treated in patients with cancer, despite being a major modifiable contributor to morbidity and early mortality. Integrating psychosocial care into cancer services through the team-based Collaborative Care Management (CoCM) model has been proven to be effective in improving patient outcomes in cancer centers. However, there is currently a gap in understanding the challenges that patients and their care team encounter in managing co-morbid cancer and depression in integrated psycho-oncology care settings. Our formative study examines the challenges and needs of CoCM in cancer settings with perspectives from patients, care managers, oncologists, psychiatrists, and administrators, with a focus on technology opportunities to support CoCM. We find that: (1) patients with co-morbid cancer and depression struggle to navigate between their cancer and psychosocial care journeys, and (2) conceptualizing co-morbidities as separate and independent care journeys is insufficient for characterizing this complex care context. We then propose the parallel journeys framework as a conceptual design framework for characterizing challenges that patients and their care team encounter when cancer and psychosocial care journeys interact. We use the challenges discovered through the lens of this framework to highlight and prioritize technology design opportunities for supporting whole-person care for patients with co-morbid cancer and depression.

DreamCatcher: Exploring How Parents and School-Age Children Can Track and Review Sleep Information Together.

Parents and their school-age children can impact one another's sleep. Most sleep-tracking tools, however, are designed for adults and make it difficult for parents and children to track together. To examine how to design a family-centered sleep tracking tool, we designed DreamCatcher. DreamCatcher is an in-home, interactive, shared display that aggregates data from wrist-worn sleep sensors and self-reported mood. We deployed DreamCatcher as a probe to examine the design space of tracking sleep as a family. Ten families participated in the study probe between 15 and 50 days. This study uses a family systems perspective to explore research questions regarding the feasibility of children actively tracking health data alongside their parents and the effects of tracking and sharing on family dynamics. Our results indicate that children can be active tracking contributors and that having parents and children track together encourages turn-taking and working together. However, there were also moments when family members, in particular parents, felt discomfort from sharing their sleep and mood with other family members. Our research contributes to a growing understanding of designing family-centered health-informatics tools to support the combined needs of parents and children.

Data-Driven Implications for Translating Evidence-Based Psychotherapies into Technology-Delivered Interventions.

Mobile mental health interventions have the potential to reduce barriers and increase engagement in psychotherapy. However, most current tools fail to meet evidence-based principles. In this paper, we describe data-driven design implications for translating evidence-based interventions into mobile apps. To develop these design implications, we analyzed data from a month-long field study of an app designed to support dialectical behavioral therapy, a psychotherapy that aims to teach concrete coping skills to help people better manage their mental health. We investigated whether particular skills are more or less effective in reducing distress or emotional intensity. We also characterized how an individual's disorders, characteristics, and preferences may correlate with skill effectiveness, as well as how skill-level improvements correlate with study-wide changes in depressive symptoms. We then developed a model to predict skill effectiveness. Based on our findings, we present design implications that emphasize the importance of considering different environmental, emotional, and personal contexts. Finally, we discuss promising future opportunities for mobile apps to better support evidence-based psychotherapies, including using machine learning algorithms to develop personalized and context-aware skill recommendations.

The Importance of Starting With Goals in N-of-1 Studies.

N-of-1 tools offer the potential to support people in monitoring health and identifying individualized health management strategies. We argue that elicitation of individualized goals and customization of tracking to support those goals are a critical yet under-studied and under-supported aspect of self-tracking. We review examples of self-tracking from across a range of chronic conditions and self-tracking designs (e.g., self-monitoring, correlation analyses, self-experimentation). Together, these examples show how failure to elicit goals can lead to ineffective tracking routines, breakdowns in collaboration (e.g., between patients and providers, among families), increased burdens, and even designs that encourage behaviors counter to a person's goals. We discuss potential techniques for eliciting and refining goals, scaffolding an appropriate tracking routine based on those goals, and presenting results in ways that advance individual goals while preserving individual agency. We then describe open challenges, including how to reconcile competing goals and support evolution of goals over time.

A Patient-Centered Proposal for Bayesian Analysis of Self-Experiments for Health.

The rise of affordable sensors and apps has enabled people to monitor various health indicators via self-tracking. This trend encourages self-experimentation, a subset of self-tracking in which a person systematically explores potential causal relationships to try to answer questions about their health. Although recent research has investigated how to support the data collection necessary for self-experiments, less research has considered the best way to analyze data resulting from these self-experiments. Most tools default to using traditional frequentist methods. However, the US Agency for Healthcare Research and Quality recommends using Bayesian analysis for n-of-1 studies, arguing from a statistical perspective. To develop a complementary patient-centered perspective on the potential benefits of Bayesian analysis, this paper describes types of questions people want to answer via self-experimentation, as informed by 1) our experiences engaging with irritable bowel syndrome patients and their healthcare providers and 2) a survey investigating what questions individuals want to answer about their health and wellness. We provide examples of how those questions might be answered using 1) frequentist null hypothesis significance testing, 2) frequentist estimation, and 3) Bayesian estimation and prediction. We then provide design recommendations for analyses and visualizations that could help people answer and interpret such questions. We find the majority of the questions people want to answer with self-tracking data are better answered with Bayesian methods than with frequentist methods. Our results therefore provide patient-centered support for the use of Bayesian analysis for n-of-1 studies.

Examining Opportunities for Goal-Directed Self-Tracking to Support Chronic Condition Management.

Although self-tracking offers potential for a more complete, accurate, and longer-term understanding of personal health, many people struggle with or fail to achieve their goals for health-related self-tracking. This paper investigates how to address challenges that result from current self-tracking tools leaving a person's goals for their data unstated and lacking explicit support. We examine supporting people and health providers in expressing and pursuing their tracking-related goals via goal-directed self-tracking, a novel method to represent relationships between tracking goals and underlying data. Informed by a reanalysis of data from a prior study of migraine tracking goals, we created a paper prototype to explore whether and how goal-directed self-tracking could address current disconnects between the goals people have for data in their chronic condition management and the tools they use to support such goals. We examined this prototype in interviews with 14 people with migraine and 5 health providers. Our findings indicate the potential for scaffolding goal-directed self-tracking to: 1) elicit different types and hierarchies of management and tracking goals; 2) help people prepare for all stages of self-tracking towards a specific goal; and 3) contribute additional expertise in patient-provider collaboration. Based on our findings, we present implications for the design of tools that explicitly represent and support an individual's specific self-tracking goals.

Identifying and Planning for Individualized Change: Patient-Provider Collaboration Using Lightweight Food Diaries in Healthy Eating and Irritable Bowel Syndrome.

Identifying and planning strategies that support a healthy lifestyle or manage a chronic disease often require patient-provider collaboration. For example, people with healthy eating goals often share everyday food, exercise, or sleep data with health coaches or nutritionists to find opportunities for change, and patients with irritable bowel syndrome (IBS) often gather food and symptom data as part of working with providers to diagnose and manage symptoms. However, a lack of effective support often prevents health experts from reviewing large amounts of data in time-constrained visits, prevents focusing on individual goals, and prevents generating correct, individualized, and actionable recommendations. To examine how to design photo-based diaries to help people and health experts exchange knowledge and focus on collaboration goals when reviewing the data together, we designed and developed Foodprint, a photo-based food diary. Foodprint includes three components: (1) A mobile app supporting lightweight data collection, (2) a web app with photo-based visualization and quantitative visualizations supporting collaborative reflection, and (3) a pre-visit note communicating an individual's expectations and questions to experts. We deployed Foodprint in two studies: (1) with 17 people with healthy eating goals and 7 health experts, and (2) with 16 IBS patients and 8 health experts. Building upon the lens of boundary negotiating artifacts and findings from two field studies, our research contributes design principles to (1) prepare individuals to collect data relevant to their health goals and for collaboration, (2) help health experts focus on an individual's eating context, experiences, and goals in collaborative review, and (3) support individuals and experts to develop individualized, actionable plans and strategies.

Supporting Patient-Provider Collaboration to Identify Individual Triggers using Food and Symptom Journals.

Patient-generated data can allow patients and providers to collaboratively develop accurate diagnoses and actionable treatment plans. Unfortunately, patients and providers often lack effective support to make use of such data. We examine patient-provider collaboration to interpret patient-generated data. We focus on irritable bowel syndrome (IBS), a chronic illness in which particular foods can exacerbate symptoms. IBS management often requires patient-provider collaboration using a patient's food and symptom journal to identify the patient's triggers. We contribute interactive visualizations to support exploration of such journals, as well as an examination of patient-provider collaboration in interpreting the journals. Drawing upon individual and collaborative interviews with patients and providers, we find that collaborative review helps improve data comprehension and build mutual trust. We also find a desire to use tools like our interactive visualizations within and beyond clinic appointments. We discuss these findings and present guidance for the design of future tools.

When Personal Tracking Becomes Social: Examining the Use of Instagram for Healthy Eating.

Many people appropriate social media and online communities in their pursuit of personal health goals, such as healthy eating or increased physical activity. However, people struggle with impression management, and with reaching the right audiences when they share health information on these platforms. Instagram, a popular photo-based social media platform, has attracted many people who post and share their food photos. We aim to inform the design of tools to support healthy behaviors by understanding how people appropriate Instagram to track and share food data, the benefits they obtain from doing so, and the challenges they encounter. We interviewed 16 women who consistently record and share what they eat on Instagram. Participants tracked to support themselves and others in their pursuit of healthy eating goals. They sought social support for their own tracking and healthy behaviors and strove to provide that support for others. People adapted their personal tracking practices to better receive and give this support. Applying these results to the design of health tracking tools has the potential to help people better access social support.

Feasibility testing of a home-based sensor system to monitor mobility and daily activities in Korean American older adults.

AIMS AND OBJECTIVES: This study aimed to test feasibility of a home-based sensor system that is designed to assess mobility and daily activity patterns among Korean American older adults (KAOAs; n = 6) and explore sensor technology acceptance among participants. BACKGROUND: Home-based sensors have the potential to support older adults' desire to remain at home as long as possible. Despite a growing interest in using home-based sensors for older adults, there have been no documented attempts to apply this type of technology to a group of ethnic minority older adults. DESIGN: The study employed descriptive, quantitative and qualitative approaches. METHODS: The system was deployed for 2 months in four homes of KAOAs. Study procedures included (i) sensor-based data collection, (ii) self-report mobility instruments, (iii) activity logs and (iv) interviews. To explore changes in activity patterns, line graphs and sequence plots were applied to data obtained from a set of sensors. General linear models (GLMs) were used for motion in each space of the home to examine how much variability of activities is explained by several time variables. RESULTS: Sensor data had natural fluctuation over time. Different 24-hr patterns were observed across homes. The GLM estimates showed that effect sizes of the time variables vary across individuals. A hydro sensor deployed in one participant's bathroom inferred various water usage activities. Overall, sensors were acceptable for all participants, despite some privacy concerns. CONCLUSIONS: Study findings demonstrate that sensor technology applications could be successfully used longitudinally in a minority population of older adults that is not often targeted as an end-user group for the use of innovative technologies. IMPLICATIONS FOR PRACTICE: The use of home-based sensors provides nurses with a useful tool to detect deviations from normal patterns and to achieve proactive care for some groups of older adults.

TummyTrials: A Feasibility Study of Using Self-Experimentation to Detect Individualized Food Triggers.

Diagnostic self-tracking, the recording of personal information to diagnose or manage a health condition, is a common practice, especially for people with chronic conditions. Unfortunately, many who attempt diagnostic self-tracking have trouble accomplishing their goals. People often lack knowledge and skills needed to design and conduct scientifically rigorous experiments, and current tools provide little support. To address these shortcomings and explore opportunities for diagnostic self-tracking, we designed, developed, and evaluated a mobile app that applies a self-experimentation framework to support patients suffering from irritable bowel syndrome (IBS) in identifying their personal food triggers. TummyTrials aids a person in designing, executing, and analyzing self-experiments to evaluate whether a specific food triggers their symptoms. We examined the feasibility of this approach in a field study with 15 IBS patients, finding that participants could use the tool to reliably undergo a self-experiment. However, we also discovered an underlying tension between scientific validity and the lived experience of self-experimentation. We discuss challenges of applying clinical research methods in everyday life, motivating a need for the design of self-experimentation systems to balance rigor with the uncertainties of everyday life.