Personal Health Management with Digital Solutions

Permanent URI for this collectionhttps://hdl.handle.net/10125/107486

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Now showing 1 - 9 of 9

Design of Personal Health Libraries for People Returning from Incarceration in the United States
(2024-01-03) Mccall, Terika; Levi, Amanda; Peng, Mary; Zhou, Kristal; Swaminath, Meera; Harikrishnan, Vignesh; Workman, T Elizabeth; Fooladi, Hadi; Saunders, Monya; Foumakoye, Marisol; Campbell Britton, Meredith; Teng, Sarah; Zeng-Treitler, Qing; Yin, Ying; Wang, Emily A; Puglisi, Lisa B; Shavit, Shira; Brandt, Cynthia A; Wang, Karen H
Individuals with a history of incarceration face many barriers to accessing resources to meet their basic needs when returning to community settings. Digital health tools have potential to reduce health inequities by facilitating connections to health and social services, and peer support. This study aimed to employ a user-centered design approach to create a digital Personal Health Library (PerHL) for previously incarcerated individuals. The design process included in-depth interviews followed by rapid analysis, interpretation sessions, and user experience/user interface (UX/UI) design of a high-fidelity prototype. Semi-structured interviews were conducted with individuals with a history of incarceration (n=20) to understand their experience rejoining their communities. Findings highlight the need for an app that allows users to easily access resources for employment, housing, healthcare and medical needs, formal and informal support, and legal counsel.
Healthy but at Home: A Taxonomy to Structure the Opaque Remote Patient Monitoring Market
(2024-01-03) Kegel, Felix; Diesterhöft, Till; Braun, Marvin; Schierholt, Christoph; Kolbe, Lutz
The Covid-19 pandemic has resulted in overburdened hospitals and patients’ inability to access appropriate healthcare services. In inpatient care, patients are being monitored for extended periods of time, especially in the case of emerging diseases, further straining hospital capacities. According to current literature, Remote Patient Monitoring Systems (RPMS) can help address and reduce this burden. However, in practice, RPMS adoption has been slow. We argue that there exists a lack of transparency in the current RPMS landscape which results in a mismatch between RPMS offerings on the market and users’ need for these systems. Aiming to structure the opaque RPMS market, we develop a taxonomy that describes the characteristics and nuances of RPMS based on 39 existing systems. Drawing on the taxonomy, we derive five archetypes that help both practitioners and scholars to differentiate between system types and thus support future RPMS deployment to improve healthcare accessibility and quality.
Predicting Adolescent Suicide Risk From Cellphone Usage Data and Self-Report Assessments
(2024-01-03) Stemmer, Maya; Barzilay, Shira; Efrati, Itamar; Friedman, Talia; Carmi, Lior; Zohar , Mishael; Brunstein Klomek, Anat; Apter, Alan; Fine, Shai
As suicide is a leading cause of adolescent death, innovative evaluation of imminent suicide risk factors is needed. This study followed high-risk adolescents who presented with recent suicidal thoughts and behaviors (STB) for six months. They were digitally monitored and periodically observed during in-clinic visits. We aimed to classify their STB levels and identify severe cases based on two types of digital monitoring: (1) weekly self-reported questionnaires by patients and (2) and continuously collected cellphone use data. We present a novel approach for utilizing the immense amounts of unlabeled cellular logs in a supervised classification problem. Satisfying prediction results from both data types showed the feasibility of using digital monitoring for STB prediction. Such a capability may enrich periodic clinical assessments with frequent digital follow-ups and raise awareness whenever necessary.
Uncovering the facilitating influence of shared technology use on working alliance in Type-2 diabetes management with Indigenous Australian patients and healthcare providers.
(2024-01-03) Nazneen, Noor E; Alam, Sultana Lubna; Nguyen, Lemai
Addressing the prevalence of chronic diseases among Indigenous populations remains a critical global challenge. The ongoing COVID-19 pandemic has accelerated the adoption of digital health technologies (DHTs) among Indigenous patients and their healthcare providers, enabling remote chronic care delivery. To ensure culturally safe and patient-centred care through these digital channels, it is imperative that the use of DHTs fosters a collaborative patient-provider relationship. This research-in-progress paper incorporates the indigenous perspectives and draws upon the concepts of the working alliance from psychology and the information systems affordance theory to explore how the shared use of technology facilitates a collaborative patient-provider relationship (i.e., working alliance) in the context of managing type-2 diabetes among Indigenous Australian patients.
The Impact of Digital Voice Assistants on the Everyday Life of Physically Disabled Users: Barriers, Drivers and Potential for Improvement
(2024-01-03) Fota, Anne; Schramm-Klein, Hanna
To date, there is little research literature on the adoption and use of smart technology, like digital voice assistants by vulnerable user groups, such as physically disabled users. In particular, physically disabled users face different everyday obstacles that can be overcome by using digital voice assistants. Therefore, 18 interviews with users having physical disabilities (all wheelchair users) are conducted and evaluated by means of qualitative content analysis to identify the barriers and drivers of use, but above all the potential for improvement especially for this user group. The results show the potential for facilitating everyday tasks and increasing individual mobility offered by digital voice assistants, but also that financial barriers, lack of necessity, and the desire to maintain independence inhibit their use. To minimize these barriers for users with physical disabilities, financial support, better education, and improved functionality of the devices should be ensured.
Coupling Neural Networks Between Clusters for Better Personalized Care
(2024-01-03) Kraus, Mathias; Hambauer, Nico; Müller, Kristina; Kröckel, Pavlina; Ulapane, Nalika; De Caigny, Arno; De Bock, Koen; Coussement, Kristof
Personalized healthcare powered by machine learning (ML) is at the forefront of modern medicine, promising to optimize treatment outcomes, reduce adverse effects, and improve patient satisfaction. However, simple ML models generally lack the complexity to accurately model individual characteristics, while powerful ML models require large amounts of data, which are often unavailable in the healthcare domain. We address this problem with cluster-level personalization. In this method, similar patients are grouped into clusters and a local ML model is trained for each cluster. Since the amount of patient data to train ML models naturally decreases for each cluster, we introduce a novel objective function called "coupling" that allows information to be shared between clusters, so that smaller clusters can also benefit from information from larger clusters, thereby improving patient outcome prediction. Our method provides a compromise between a single global model for all patients and completely independent local cluster models. We show that coupling leads to statistically significant improvements on a simulated and a real-world dataset in the context of diabetes.
Harnessing Technology for Mental Well-being: An EEG Comparison of VR and Mobile-Based Mindfulness Meditation Interventions
(2024-01-03) Kim, Yeongseo; Boo, Chaeeun; Suh, Ayoung
As digital technology becomes increasingly integrated into daily life, its potential to enhance mental well-being is transforming the landscape of mental health care. Of particular interest is the rise of virtual reality (VR) technology. However, empirical research exploring VR’s influence on mental well-being is limited. This study aimed to fill this gap by conducting a one-factor, between-subject experiment involving 60 participants, comparing the effects of VR and mobile-based mindfulness meditation interventions. Data were collected using self-report assessments and electroencephalograms. The findings suggest that VR-based mindfulness meditation significantly enhances subjective well-being by reducing anxiety and nervousness. However, mobile-based mindfulness meditation was found to be more effective than VR-based mindfulness meditation in improving psychological well-being. These results not only contribute to the growing research in digital mental health care, but also provide new insights into the therapeutic potential of VR technology, underscoring its importance for future interventions in mental health care.
A Stressful Explanation: The Dual Effect of Explainable Artificial Intelligence in Personal Health Management
(2024-01-03) Grüning, Maximilian; Wolf, Tobias; Trenz, Manuel
Artificial intelligence (AI) is increasingly incorporated into innovative personal health apps to improve the decision-making of its users. To facilitate the understanding and to increase usage of such AI-based personal health apps, firms are progressively turning to explainable artificial intelligence (XAI) designs. However, we argue that explanations of the AI-based recommendations have not only positive but also negative consequences. Based on a socio-technical lens, we develop a model that relates XAI to technostress - both eustress and distress - and its downstream consequences. To test our model, we conducted an online experiment, in which participants interact with XAI or black-box AI. Our results show that (1) XAI causes both eu- and distress, and (2) simultaneously exerts differential influence on objective performance, satisfaction, and intention to use. Our findings contribute to information systems research and practice by uncovering the dual effect of XAI on decision processes in the health context.
Introduction to the Minitrack on Personal Health Management with Digital Solutions
(2024-01-03) Ma, Tuan Huy; Bodendorf, Freimut; Wickramasinghe, Nilmini

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