Background Many individuals with suicide risk present to acute care settings such as emergency departments (EDs). However, staffing and time constraints mean that many EDs are not well equipped to deliver evidence-based interventions for patients experiencing suicidality. An existing intervention initiated in the ED for patients with suicide risk (Emergency Department Safety Assessment and Follow-up Evaluation [ED-SAFE]) has been found to be effective but faces trenchant barriers for widespread adoption. Objective On the basis of the ED-SAFE intervention, we aimed to develop 2 apps for patients with suicide risk: a web app guiding patients through safety planning in the ED (ED app) and a smartphone app providing patients components of the ED-SAFE program on their phones after discharge (patient app). We then tested the usability of these apps with patients presenting to the ED with suicide risk. Methods Using a user-centered design framework, we first developed user personas to explore the needs and characteristics of patients who are at risk for suicide using inputs from clinicians (n=3) and suicidologists (n=4). Next, we validated these personas during interviews with individuals with lived experience of suicidality (n=6) and used them to inform our application designs. We field-tested the apps with ED patients presenting with suicide risk (n=14) in 2 iterative cycles to assess their usability and engagement using a mixed methods approach. We also rated the quality and fidelity of the safety plans created. Results We developed 2 interoperable and complementary apps. The first is a web app designed for use on a tablet device during ED admission that guides the patient by creating a safety plan using a chatbot-style interface. The second is a smartphone app for use after discharge and allows the patient to view, edit, and share their completed safety plan; access self-care education, helplines, and behavioral health referrals; and track follow-up appointments with the study clinician. The initial prototype usability testing (n=9) demonstrated satisfactory scores (ED app System Usability Scale [SUS], mean 78.6/100, SD 24.1; User Engagement Scale, mean 3.74/5, SD 0.72; patient app SUS, mean 81.7/100, SD 20.1). After refining the apps based on participant feedback, the second cycle testing (n=5) showed improvement (ED app SUS, mean 90.5/100, SD 9.9; User Engagement Scale, mean 4.07/5, SD 0.36; patient app SUS, mean 97.0/100, SD 1.9). The quality ratings for completed safety plans were satisfactory (Safety Planning Intervention Scoring Algorithm-Brief, mean 27.4, SD 3.4). Conclusions By adopting a user-centered approach and creating personas to guide development, we were able to create apps for ED patients with suicide risk and obtain satisfactory usability, engagement, and quality scores. Developing digital health tools based on user-centered design principles that deliver evidence-based intervention components may help overcome trenchant implementation barriers in challenging health care settings.

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ReachCare Mobile Apps for Patients Experiencing Suicidality in the Emergency Department: Development and Usability Testing Using Mixed Methods

Developing Personas for Designing Health Interventions

Chronic pain is a multifaceted complex experience that is often captured with self reported measures. While subjective selfreported measures capture pain from a patients point of view, they are limited in information richness. Collecting eye movements when completing self reported subjective pain measures provides valuable insight about information processing and decision behavior. This information can improve the information richness of self reported pain measures by providing a broader view of an individuals pain experience. How people process information and make decisions when completing pain measures can also help to investigate the cognitive evaluative aspects of chronic pain, which in turn can provide insight for developing eye tracking biomarkers of chronic pain, and by doing so help develop smart clinician support technologies. Our preliminary results show that people with chronic pain expended significantly more cognitive effort than their pain free counterparts when completing three self reported pain measures that are widely used in clinical settings. These results are promising because they suggest that eye movements may serve as valuable information to accompany self reported pain scores and thus enable effective assessment and management of chronic pain. The results also suggest that eye movements may serve as suitable biomarkers of chronic pain.

/pdf/examining-the-impact-of-chronic-pain-on-information-2le439mt.pdf

Examining the Impact of Chronic Pain on Information Processing Behavior: An Exploratory Eye-tracking Study

Eye tracking has become the gold standard in measuring human attention and information-processing behavior. As such, eye tracking in mixed-methods user experience (UX) research serves as an invaluable tool to learn about user needs and to create actionable insights for improving product and service design during the development cycle. Here, we discuss the iterative process that we used to improve the design of a decision aid (DA) developed to facilitate shared decision making. We explain the use of eye tracking during this process to examine how users processed the information provided by the DA. We also explain how we used eye tracking in a retrospective “think-aloud” protocol to gain insight about users’ needs. Our results show that user reactions captured by eye tracking can not only be used to optimize design decisions but also to gather user feedback about their information processing needs. 

Gaayathri Sankar

Papers

Developing Personas for Designing Health Interventions

Examining the Impact of Chronic Pain on Information Processing Behavior: An Exploratory Eye-tracking Study

Using Eye Tracking to Measure User Engagement with a Decision Aid

Impact of Anxiety on Information Processing Among Young Adults: An Exploratory Eye-tracking Study

Extended Review on the User Evaluation of Teleoperation Interfaces for Professional Service Robots