Blood glucose variance measured by continuous glucose monitors across the menstrual cycle.

Past studies on how blood glucose levels vary across the menstrual cycle have largely shown inconsistent results based on limited blood draws. In this study, 49 individuals wore a Dexcom G6 continuous glucose monitor and a Fitbit Sense smartwatch while measuring their menstrual hormones and self-reporting characteristics of their menstrual cycles daily. The average duration of participation was 79.3 ± 21.2 days, leading to a total of 149 cycles and 554 phases in our dataset. We use periodic restricted cubic splines to evaluate the relationship between blood glucose and the menstrual cycle, after which we assess phase-based changes in daily median glucose level and associated physiological parameters using mixed-effects models. Results indicate that daily median glucose levels increase and decrease in a biphasic pattern, with maximum levels occurring during the luteal phase and minimum levels occurring during the late-follicular phase. These trends are robust to adjustments for participant characteristics (e.g., age, BMI, weight) and self-reported menstrual experiences (e.g., food cravings, bloating, fatigue). We identify negative associations between each of daily estrogen level, step count, and low degrees of fatigue with higher median glucose levels. Conversely, we find positive associations between higher food cravings and higher median glucose levels. This study suggests that blood glucose could be an important parameter for understanding menstrual health, prompting further investigation into how the menstrual cycle influences glucose fluctuation.

VisTA: Integrating Machine Intelligence with Visualization to Support the Investigation of Think-Aloud Sessions.

Think-aloud protocols are widely used by user experience (UX) practitioners in usability testing to uncover issues in user interface design. It is often arduous to analyze large amounts of recorded think-aloud sessions and few UX practitioners have an opportunity to get a second perspective during their analysis due to time and resource constraints. Inspired by the recent research that shows subtle verbalization and speech patterns tend to occur when users encounter usability problems, we take the first step to design and evaluate an intelligent visual analytics tool that leverages such patterns to identify usability problem encounters and present them to UX practitioners to assist their analysis. We first conducted and recorded think-aloud sessions, and then extracted textual and acoustic features from the recordings and trained machine learning (ML) models to detect problem encounters. Next, we iteratively designed and developed a visual analytics tool, VisTA, which enables dynamic investigation of think-aloud sessions with a timeline visualization of ML predictions and input features. We conducted a between-subjects laboratory study to compare three conditions, i.e., VisTA, VisTASimple (no visualization of the ML's input features), and Baseline (no ML information at all), with 30 UX professionals. The findings show that UX professionals identified more problem encounters when using VisTA than Baseline by leveraging the problem visualization as an overview, anticipations, and anchors as well as the feature visualization as a means to understand what ML considers and omits. Our findings also provide insights into how they treated ML, dealt with (dis)agreement with ML, and reviewed the videos (i.e., play, pause, and rewind).

Co-Designing Ambient Assisted Living (AAL) Environments: Unravelling the Situated Context of Informal Dementia Care.

Ambient assisted living (AAL) aims to help older persons "age-in-place" and manage everyday activities using intelligent and pervasive computing technology. AAL research, however, has yet to explore how AAL might support or collaborate with informal care partners (ICPs), such as relatives and friends, who play important roles in the lives and care of persons with dementia (PwDs). In a multiphase codesign process with six (6) ICPs, we envisioned how AAL could be situated to complement their care. We used our codesigned "caregiver interface" artefacts as triggers to facilitate envisioning of AAL support and unpack the situated, idiosyncratic context within which AAL aims to assist. Our findings suggest that AAL should be designed to support ICPs in fashioning "do-it-yourself" solutions that complement tacitly improvised care strategies and enable them to try, observe, and adapt to solutions over time. In this way, an ICP could decide which activities to entrust to AAL support, when (i.e., scheduled or spontaneous) and how a system should provide support (i.e., using personalized prompts based on care experience), and when adaptations to system support are needed (i.e., based alerting patterns and queried reports). Future longitudinal work employing participatory, design-oriented methods with care dyads is encouraged.

Barriers to acceptance of personal digital assistants for HIV/AIDS data collection in Angola.

PURPOSE: Handheld computers have potential to improve HIV/AIDS programs in healthcare settings in low-resource countries, by improving the speed and accuracy of collecting data. However, the acceptability of the technology (i.e., user attitude and reaction) is critical for its successful implementation. Acceptability is particularly critical for HIV/AIDS behavioral data, as it depends on respondents giving accurate information about a highly sensitive topic - sexual behavior. METHODS: To explore the acceptability of handheld computers for HIV/AIDS data collection and to identify potential barriers to acceptance, five focus groups of 8-10 participants each were conducted in Luanda, Angola. Facilitators presented Palm Tungsten E handhelds to the focus groups, probed participants' perceptions of the handheld computer, and asked how they felt about disclosing intimate sexual behavior to an interviewer using a handheld computer. Discussions were conducted in Portuguese, the official language of Angola, and audio-taped. They were then transcribed and translated into English for analysis. RESULTS: In total, 49 people participated in the focus groups. PDAs were understood through the lens of social and cultural beliefs. Themes that emerged were suspicion of outsiders, concern with longevity, views on progress and development, and concern about social status. CONCLUSIONS: The findings from this study suggest that personal and cultural beliefs influence participant acceptance of PDAs in Angola. While PDAs provide great advantages in terms of speed and efficiency of data collection, these barriers, if left unaddressed, may lead to biased reporting of HIV/AIDS risk data. An understanding of the barriers and why they are relevant in Angola may help researchers and practitioners to reduce the impact of these barriers on HIV/AIDS data collection.