Sharing our Research and Scholarship

We explored how nurses and students can use AI language models to help run statistical analyses, lowering the barrier to doing research.

This study tested short, culturally tailored videos to help Hispanic family caregivers feel more confident and capable in caring for a loved one with dementia.

This paper examines “moral reckoning,” a nursing theory about how nurses respond when their values clash with difficult workplace situations, and weighs how useful and sound the theory is.

Exploring the quality of TikTok-based diabetes self-management education in English and Spanish: A digital health study.

This study reviewed diabetes advice on TikTok in English and Spanish to see how accurate and trustworthy it is, since many people now turn to social media for health information.

Continuous glucose monitoring for glycemic control in non-insulin-treated patients with type 2 diabetes.

This study looked at whether wearable continuous glucose monitors help people with type 2 diabetes who do not use insulin keep their blood sugar in a healthier range.

Navigating type 2 diabetes care: Asian American perspectives on self-management education and support.

We asked Asian Americans with type 2 diabetes what helps and what gets in the way when they try to use diabetes education and support programs, so those programs can serve them better.

Colonial mentality and diabetes self-management in Filipino Americans with type 2 diabetes.

This study explored how “colonial mentality” (internalized beliefs rooted in a colonial past) relates to how Filipino Americans manage their type 2 diabetes.

This study followed workers over four years to see whether the stress of juggling work and family was linked to changes in health markers such as blood pressure, weight, and blood sugar.

Filipino Americans’ social and cultural experiences of type 2 diabetes management: Cultural paradox, ownership, and success definition.

We talked with Filipino Americans about what living with and managing type 2 diabetes is really like day to day: how family, food, faith, and cultural expectations can either help or get in the way. The goal is care that respects and works with their culture.

We looked at how everyday life circumstances, such as income, housing, and access to care, were associated with Californians’ mental health during the COVID-19 pandemic.

We looked at the factors associated with U.S. adults using health apps and devices, and with their willingness to share health information with doctors, family, or on social media. This helps designers build digital health tools that people actually trust and use.

This study explored why some patients stop short of completing the weight-loss (bariatric) surgery process. Understanding what gets in their way can help clinics support people better and keep them from falling through the cracks.

Economic burden, financial stress, and cost-related coping among people with uncontrolled diabetes.

This study examined the financial strain of living with hard-to-control diabetes, and the difficult tradeoffs people make, such as skipping medication, to cope with the cost.

Experiences of Filipino Americans with type 2 diabetes during COVID-19: A qualitative study.

We asked Filipino Americans with type 2 diabetes how the COVID-19 pandemic affected their health, including the added stress, disrupted routines and care, and what helped them cope, so that future support can be ready for hard times like these.

This study mapped how nurses actually work in newborn intensive care units (NICUs). Knowing the real workflow lets hospitals design computer alerts and decision-support tools that fit how nurses work, instead of slowing them down.

We documented the unexpected problems nurses run into with electronic health record (EHR) systems, including the workarounds, extra clicks, and frustrations, to point the way toward safer, easier-to-use systems.

We used data from the electronic health record itself to study how nurses move through their digital tasks. It offers a new way to understand, and ultimately improve, the everyday computer work that takes nurses away from patients.

We evaluated a smartphone app (Meducation) designed to help patients take their medicines correctly, and showed why health apps need to be tested after they are rolled out, not just before.

Type 2 diabetes self-management interventions among Asian Americans in the United States: A scoping review.

We reviewed existing programs that help Asian Americans manage type 2 diabetes to see what has been tried, what works, and where the gaps are.

We summarized the research on what makes electronic health records easy or frustrating for nurses to use, to guide better, safer system design.

This commentary argues that research on young (millennial) family caregivers must account for their complex, overlapping identities in order to truly understand and support them.

This commentary makes the case that nurses’ frontline expertise should have a stronger voice in shaping public health policy, a lesson underscored by COVID-19.

This commentary calls on nurses to recognize and oppose police violence and unjust policing as threats to health and to their patients.

Filipino healthcare workers were hit especially hard by COVID-19, facing high exposure, racist rhetoric, and inadequate protection, often hidden because data lump Filipinos into a broad “Asian” category. This study found their culture was both a source of strength and a channel through which inequities reached them, pointing to a need for culturally responsive support.

Most older adults live with more than one chronic condition, and wearables are often suggested to help. Using a national survey of 910 adults aged 65 and older, this study examined whether wearable use was associated with more physical activity and greater confidence in managing one’s health. As a snapshot in time, it describes associations rather than cause and effect.

Filipino Americans often face health challenges despite social advantages. Drawing on interviews with 23 Filipino American adults, this study explores how “colonial mentality,” internalized beliefs left by a history of colonization, shapes their healthcare experiences and can create barriers to care.

Artificial intelligence in diabetes self-management: An integrative review.

Can AI safely help people manage diabetes? Our team reviewed 25 studies on patient-facing AI tools, like chatbots and large language models. These tools show real promise, but some give inaccurate or unsafe advice, and many were never tested with older adults, people with limited tech access, or non-English speakers. AI tools need more careful, inclusive testing before everyday diabetes care.

A machine learning approach integrating social determinants of health and allostatic load to predict type 2 diabetes.

Diabetes risk tools usually rely on clinical numbers and ignore people’s social circumstances and chronic stress. This study built a machine-learning model that added social determinants of health and “allostatic load” (the body’s cumulative stress) to predict dysglycemia. It predicted risk well, and the social and stress factors added meaningful value, pointing toward whole-person risk tools.

Gender differences in diabetes distress within a digital intervention.

Diabetes distress, the emotional burden of diabetes, often weighs more on women. This study examined gender differences in distress over 12 months and whether a digital program addressing unmet social needs (CareAvenue) worked differently by gender, using data from a randomized trial of 598 adults with diabetes.

Implementation of a culturally tailored outpatient case management program for Filipino Americans with type 2 diabetes.

Filipino Americans face a high burden of type 2 diabetes, yet standard education rarely addresses cultural values like pakikisama, hiya, and tiwala. This DNP project evaluated a six-week culturally tailored outpatient case management program, compared with usual care, to improve patient activation, medication adherence, and blood sugar control.

Bridging the gap: opportunities and barriers in diabetes self-management education.

This study asked Asian Americans with type 2 diabetes what helps and what gets in the way when using diabetes education and support. Barriers included cost, logistics, stigma, and negative provider experiences; family, community, and online resources helped. It points to a need for culturally responsive programs, including online options.

Filipino healthcare workers were hit especially hard by COVID-19, facing high exposure, racist rhetoric, and inadequate protection, often hidden because data lump Filipinos into a broad “Asian” category. This study found their culture was both a source of strength and a channel through which inequities reached them, pointing to a need for culturally responsive support.

Chronic stress wears on the body (measured as “allostatic load”) and raises diabetes risk. This study asks whether a strong “sense of coherence,” feeling that life is understandable, manageable, and meaningful, helps buffer that physical toll. Part of the lab’s NIH AIM-AHEAD and Bridge2AI work.

Filipino healthcare workers were hit especially hard by COVID-19, facing high exposure, racist rhetoric, and inadequate protection, often hidden because data lump Filipinos into a broad “Asian” category. This study found their culture was both a source of strength and a channel through which inequities reached them, pointing to a need for culturally responsive support.

Stress from systemic disadvantages can leave a physical mark. Using the AI-READI dataset, this study examines whether perceived stress is associated with higher “allostatic load” (the body’s cumulative wear and tear) among people with type 2 diabetes. Part of the lab’s NIH AIM-AHEAD and Bridge2AI work.

Cost-related maladaptive coping and diabetes distress among adults with diabetes.

Diabetes is expensive, and some people cope in harmful ways like skipping medications. This study examined whether such cost-related coping is associated with “diabetes distress” (the emotional weight of diabetes) among adults with uncontrolled diabetes, to help clinicians spot and support those struggling.

Can an AI chatbot analyze research data as reliably as standard software? We compared ChatGPT-4 with SPSS on the same dataset (n = 1,339) to assess how similar and reliable the results were, testing rather than assuming its trustworthiness for nursing research.

Geospatial mapping of diabetes programs and equity index among Asian Americans in Los Angeles.

Diabetes hits Asian Americans hard, yet fewer than one in ten join diabetes education and support programs. This study mapped where those programs sit across Los Angeles County alongside population and community-health data, and found they cluster unevenly, which can leave some communities underserved and can guide where to focus outreach.

Digital health tools can help, but use and data-sharing are uneven. We analyzed a national survey of 3,865 U.S. adults to identify which personal, health, and technology factors are linked to using digital health tools and to sharing health information with providers, family and friends, or social media.

The electronic health record works best when it fits the nurse and the task. Surveying 95 nurses, this study measured that “task-technology fit” and how it relates to workload, time in the system, and performance, to help improve the everyday computer work that pulls nurses away from patients.

Every click in the electronic health record leaves a trace. We mined EHR audit logs using sequential pattern mining and Markov chain analysis to map how nurses actually navigate the system, a faster, data-driven alternative to traditional workflow analysis that can guide EHR redesign.

Hospitals invest heavily in tools like the electronic health record, but they only help if nurses have a good experience using them. This poster offers a framework linking nurses’ user experience to whether a system is truly adopted, and argues for designing around real workflows.

An early poster exploring how sequential pattern analysis could reveal the way nurses navigate and document in the electronic health record. This preliminary work set the stage for the lab’s later computational ethnography studies of EHR workflow.