Engaging the disability community in informatics research: rationales and practical steps

Designing an infographic webtool for public health

OBJECTIVE

To create and evaluate a public health informatics tool, Florence, for communicating information to the public.

MATERIALS AND METHODS

This user-centered design study included 3 phases: (1) an interview and survey study with public health practitioners to assess needs for creating infographics; (2) the application of assessment findings and public health-motivated design guidelines to the design and development of a public health-specific infographic design tool; and (3) a feasibility and usability study to evaluate the feasibility and usability of the tool.

RESULTS

In phase 1, participants noted the importance of tailoring infographics to an audience and wanted flexible tools along with design guidance to help make fewer design decisions. In phase 2, we developed a prototype tool with: (1) layout and functionality familiar to PH users, (2) quick and intuitive ways to add and modify data in visualizations, and (3) health-focused visual elements. In phase 3, participants found Florence to be usable, providing an intuitive and straightforward experience, and that the focus on public health was useful.

DISCUSSION

Based on needs assessments and existing literature, we created Florence along with public health practitioners to address their domain specific needs, ultimately leading to a tool that participants in our study deemed useful. Future research can build on our work to develop user-centered tools to meet their needs.

CONCLUSION

Infographics are important for public health communication. Creating user-centered solutions to address the unique needs of public health can support communication efforts.

Characterization of Adult Patients with Autism Spectrum Disorder that Use Patient Portal

Patients with autism spectrum disorder (ASD) access healthcare frequently, yet little is known about their interactions with patient portals. To describe adults with ASD using patient portal, we conducted regression analyses of visit history, demographics, co-occurring conditions and diagnoses, and patient portal use to determine factors most indicative of whether a patient 1) has sent at least one message (via patient or proxy) and 2) has at least one message sent on their behalf via a proxy account after they turned 18 years old. The 2,412-person cohort had 996 (41.3%) patients who had sent at least one message on their account with 129 (5.3%) of patients having at least one proxy message. This study found that adults with ASD are less likely to use messaging functionality and more likely to have a message sent via proxy than other patient populations. Comorbid mental illness was correlated with using messaging functionality.

Achieving trust in health-behavior-change artificial intelligence apps (HBC-AIApp) development: a multi-perspective guide

OBJECTIVE

Trust determines the success of Health-Behavior-Change Artificial Intelligence Apps (HBC-AIApp). Developers of such apps need theory-based practical methods that can guide them in achieving such trust. Our study aimed to develop a comprehensive conceptual model and development process that can guide developers how to build HBC-AIApp in order to support trust creation among the app's users.

METHODS

We apply a multi-disciplinary approach where medical informatics, human-centered design, and holistic health methods are integrated to address the trust challenge in HBC-AIApps. The integration extends a conceptual model of trust in AI developed by Jermutus et al., whose properties guide the extension of the IDEAS (integrate, design, assess, and share) HBC-App development process.

RESULTS

The HBC-AIApp framework consists of three main blocks: (1) system development methods that study the users' complex reality, hence, their perceptions, needs, goals and environment; (2) mediators and other stakeholders who are important for developing and operating the HBC-AIApp, boundary objects that examine users' activities via the HBC-AIApp; and (3) the HBC-AIApp's structural components, AI logic, and physical implementation. These blocks come together to provide the extended conceptual model of trust in HBC-AIApps and the extended IDEAS process.

DISCUSSION

The developed HBC-AIApp framework drew from our own experience in developing trust in HBC-AIApp. Further research will focus on studying the application of the proposed comprehensive HBC-AIApp development framework and whether applying it supports trust creation in such apps.

Designing mobile health to align with the social determinants of health

The maternal health crisis in the United States is becoming increasingly worse, with disparities continuing to escalate among marginalized populations. mHealth can contribute to addressing the Social Determinants of Health (SDOH) that produce inequities in maternal morbidity and mortality. Reducing inequities through mHealth can be achieved by designing these technologies to align with SDOH. As mHealth developed to support maternal health has primarily supported the extension of clinical care, there is an opportunity to integrate frameworks and methods from human factors/ergonomics and public health to produce thorough comprehension of SDOH through intentional partnerships with marginalized populations. Potential for this opportunity is presented through a case study derived from a community-based participatory research process focused on transportation access to maternal health services. Through multi-faceted, interdisciplinary, and community-based approaches to designing mHealth that attends to the systemic factors that generate and escalate inequities, improvements in the maternal health crisis could be realized.

The lived experience of people with disabilities during the COVID-19 pandemic on Twitter: Content analysis

Objective

People with disabilities (PWDs) are at greater risk of COVID-19 infection, complications, and death, and experience more difficulty accessing care. We analyzed Twitter tweets to identify important topics and investigate health policies' effects on PWDs.

Methods

Twitter's application programming interface was used to access its public COVID-19 stream. English-language tweets from January 2020 to January 2022 containing a combination of keywords related to COVID-19, disability, discrimination, and inequity were collected and refined to exclude duplicates, replies, and retweets. The remaining tweets were analyzed for user demographics, content, and long-term availability.

Results

The collection yielded 94,814 tweets from 43,296 accounts. During the observation period, 1068 (2.5%) accounts were suspended and 1088 (2.5%) accounts were deleted. Account suspension and deletion among verified users tweeting about COVID-19 and disability were 0.13% and 0.3%, respectively. Emotions were similar among active, suspended, and deleted users, with general negative and positive emotions most common followed by sadness, trust, anticipation, and anger. The overall average sentiment for the tweets was negative. Ten of the 12 topics identified (96.8%) related to pandemic effects on PWDs; "politics that rejects and leaves the disabled, elderly, and children behind" (48.3%) and "efforts to support PWDs in the COVID crisis" (31.8%) were most common. The sample of tweets by organizations (43.9%) was higher for this topic than for other COVID-19-related topics the authors have investigated.

Conclusions

The primary discussion addressed how pandemic politics and policies disadvantage PWDs, older adults, and children, and secondarily expressed support for these populations. The increased level of Twitter use by organizations suggests a higher level of organization and advocacy within the disability community than in other groups. Twitter may facilitate recognition of increased harm to or discrimination against specific populations such as people living with disability during national health events.