Accessibility testing is often focused on compliance with standards rather than ensuring a smooth experience for end users. This webinar examines how to develop and harness user journeys to connect…

Background: Young adults in the United States are experiencing accelerating rates of suicidal thoughts and behaviors but have the lowest rates of formal mental health care. Digital suicide prevention ...

Background: Social isolation and weakened intergenerational ties pose significant threats to the emotional well-being and social support networks of older adults. Although structured intergenerational programs can reduce age-related stereotypes and promote connectedness, their accessibility is often hindered by physical and logistical constraints. The increasing digital literacy among older populations presents new opportunities for technology-based interventions to support meaningful cross-generational engagement. Objective: This study aimed to design and evaluate a mobile app that fosters intergenerational communication and enhances perceived social support in older adults using a user-centered design framework grounded in the double diamond model. Methods: The development process followed the 4 phases of the double diamond model. In the discover phase, surveys with older and younger adults identified distinct usability preferences. The define phase synthesized these insights into key design principles. In the develop phase, a prototype was created and iteratively refined through usability testing. Finally, in the deliver phase, a 2-week experimental study involving 39 participants (20 older adults aged 68-82 years and 19 younger adults aged 22-39 years) assessed changes in intergenerational interaction, perceived social support, and user satisfaction. Results: The app appeared to enhance intergenerational communication and perceived social support, particularly among older participants. Users reported increased comfort and emotional connection in cross-generational conversations. Accessibility features and engaging content were noted as contributing to positive user experiences across age groups. Conclusions: This study suggests the potential of user-centered digital platforms to promote social well-being among older adults. By addressing the unique needs of multiple generations, such interventions may help foster inclusive digital environments and contribute to age-friendly, connected societies. Despite limitations related to sample size, duration, and cultural context, the study provides preliminary evidence for the potential of co-designed digital tools in supporting intergenerational communication and aging-in-place.

Background: Digital health measurement offers opportunities to address several primary health care challenges, but health care professionals encounter significant implementation barriers. Therefore, resources need to be developed to facilitate the integration of digital health measurement into daily practice. Objective: We aim to identify the most appropriate format and content for an intervention to support primary health care professionals in adopting digital health measurement. In addition, we describe and reflect on the development process. Methods: We used a participatory action research approach as well as user-centered design principles. A total of 19 primary health care professionals from 4 disciplines—physical therapy, occupational therapy, speech and language therapy, and general practitioner practice assistance—participated in intervention development as end users. External experts were consulted to broaden perspectives. Data were collected across 3 iterative stages (concept, design, and testing and trials) between January 2022 and December 2023 during cocreative meetings, individual interviews, focus group discussions, #usability testing, and prototype use in daily practice. Data were analyzed using content analysis and descriptive statistics. Results: A web-based, stepwise intervention combining theoretical information, practical aids, examples, and experiences proved most suitable. Key features were concise content, intuitive and attractive graphic design, and flexible navigation and functionalities. Iterative improvements led to an increase in #usability ratings from “okay” to “good to excellent.” Conclusions: Different health care disciplines benefit from similar support strategies; yet, this requires a careful balancing of intervention design and content. Combining participatory action research and user-centered design principles was useful to tailor the intervention to end users’ daily routines. The described development process offers a replicable framework for creating support strategies for digital health measurement in various health care settings.

The Institute on Digital Health and Innovation invites you to join a comprehensive three-day academic workshop focused on the development, implementation and evaluation of digital health…

Background: The rising prevalence of dementia is a major concern, with approximately 45% of cases linked to 14 modifiable risk factors. The European project LETHE aims to develop a personalized digital intervention model to delay or prevent cognitive decline through risk factor management. Objective: The objective of our study was to design a clinical trial platform for older individuals at risk of cognitive decline, including a mobile app for study participants and a clinical trial management system (CTMS) for health professionals. Methods: Using a user-centered design approach, workshops and feedback rounds involved potential participants representing the target group and professionals. The LETHE app’s usability was assessed among 156 older adults enrolled in a 2-year multinational randomized controlled trial evaluating the feasibility of a digitally supported lifestyle program for dementia risk reduction. The randomized controlled trial is currently ongoing; the System Usability Scale (SUS) was administered 1 month after baseline to map first user experiences. Feedback on the LETHE CTMS was collected from 21 users. Results: Of the 78 participants in the trial intervention group, 66 (85%) provided responses for the mobile app, with a median SUS score of 70 (IQR 55-82). Within the control group, 73% (57/78) of responses were received, with a median SUS score of 73 (IQR 63-90). For the CTMS, we received 71% (15/21) of responses, and the feedback was mostly positive. A ranking of the features that could be considered beyond state of the art showed that the integration of personalized activities (mean 2.23, SD 1.17) and real-time appointments (mean 2.46, SD 1.51) were considered the most novel ones. Conclusions: The LETHE app and CTMS were developed to support a personalized digital intervention method within a study involving 156 participants. Limitations include participants having digital literacy and internet access, potentially impacting the generalizability of the findings. Despite these limitations, positive feedback and high usability scores suggest promising potential for the LETHE app and CTMS in supporting personalized interventions to prevent cognitive decline in older adults.

Discover user-centered design (UCD), its principles, steps to implementation, benefits, real-life use cases, challenges, solutions, and the future.

Background: The potential of digital mental health to transform care delivery in low and middle-income countries is well established. However, one barrier is the need to clinically and culturally adapt current tools to local needs. This article explores one example of this process by creating a novel data visualization system for a digital mental health app and outlines the necessary steps in the process. Objective: Our objective is to develop tools to make inferences from the data obtained from digital phenotyping for schizophrenia. The tool is specific in its scope of being extendible from an already existing mindLAMP platform, and it allows exploratory analysis for sparse data from digital phenotyping. While the data is voluminous when collected passively from sensors on the mobile phone, the number of engaged users providing active data is sparse. Particularly, the data on relapses has uncertainties. Altogether, the proposed tool should appropriately handle data, and provide exploratory visualizations to compare the behavior of a patient across different modalities or time instances, and also trends across different patients. Also, the tool is designed to accommodate the requirements put forth by the teams in Bangalore and Boston involved in this work. Methods: We adapted the mindLAMP app, already used in many countries today, to offer a new data visualization portal, mindLAMPVis. The portal is designed to improve clinical integration for use in India. After building the new portal, we corroborate insights from this new portal with known clinical observations of relapse, to support the use of comparative visualization. We then worked to visualize these insights by taking data from the mindLAMP app and using multivariate analysis and dimensionality reduction to make the data easy for clinicians and patients to interact with. We integrate these techniques in a novel interactive visualization tool, mindLAMPVis, a locally co-designed, developed, and deployed tool. Results: To assess the system, we preloaded data of 24 patients with schizophrenia, including those with relapses. Through case examples focusing on relapse risk prediction in schizophrenia, we utilized mindLAMP vis to identify different visualization methods to compare different analytical results for each patient. In partnership with clinicians, we then explored the clinical potential of mindLAMPvis to inform care. As an example of reverse translation, we found that mindLAMPvis offers new features that complement to original features in mindLAMP – highlighting the mutual benefit of software adaptation and co-design. Conclusions: mindLAMPVis is a tailored tool designed for use in India, but it can aid in identifying and comparing behavioral patterns that may indicate clinical risk for patients in any country. mindLAMPVis offers an example of how through technical, design, feedback, and real-world clinical testing it is feasible to adapt current software tools to meet local needs and even exceed the use cases of the original technology. Clinical Trial: Not applicable

Sanjay K Mohindroo

Sanjay K Mohindroo

Background: It is challenging to design usable and effective digital health interventions (DHIs). The person-based approach (PBA) has been proposed to incorporate users’ perspectives for the design of DHIs. However, it does not explicitly describe the iterative stages of design and evaluation that are essential in moving from early planning to deployment. For this, we draw on methods from human computer interaction (HCI) that have been developed for various situations. Objective: This study aimed to reflect on the adaptation and synthesis of PBA and HCI approaches to developing DHIs. We present a case study applying both approaches to develop Empowering People through Informed Choices for HIV (EPIC-HIV1), a DHI designed for men living in rural KwaZulu-Natal, South Africa, intended to support them in making an informed choice about whether to take an HIV test and, if necessary, engage in care. Methods: We conducted a retrospective analysis of the documentation generated during the development of EPIC-HIV1 including findings about requirements, design representations, and the results of iterative rounds of testing. We developed an account of the process, the outcomes, and the strengths and limitations of the design and evaluation techniques applied. We also present the design of EPIC-HIV1 and summarize considerations when designing for hard-to-reach people in such settings. Results: The PBA was applied to deliver a first prototype. This helped identify key messages to convey and how to manage issues such as user privacy, but the resulting prototype was judged by the team not to be engaging for potential users, and it was unclear whether the design was inclusive of people with low digital or health literacy. We therefore introduced methods from HCI to iteratively test and refine the app. Working with local community representatives, we conducted four refinement cycles with 29 participants, adapting and retesting the app until no further changes were needed. Key changes included making it clearer what the consequences of selecting options in the app were and changing wording to minimize misconceptions (eg, that the app would test for HIV) while addressing common concerns about testing and emphasizing long-term benefits of engaging with care, if needed. Conclusions: Techniques for developing DHIs need to be situationally appropriate. The PBA enabled us to establish both empirical data and theory to design the content of EPIC-HIV1, but it did not directly inform interaction design to make the app usable and effective for the intended users; HCI techniques tailored to the setting enabled us to refine the app to be easy for men with little familiarity with digital technologies to use within the constraints of the setting. Iterative testing ensured the app was easy to use and that the intended clinical messages were communicated effectively.