Clinician Needs for Electronic Health Record Pediatric and Adolescent Weight Management Tools: A Mixed-Methods Study.

BACKGROUND: Clinicians play an important role in addressing pediatric and adolescent obesity, but their effectiveness is restricted by time constraints, competing clinical demands, and the lack of effective electronic health record (EHR) tools. EHR tools are rarely developed with provider input. OBJECTIVES: We conducted a mixed method study of clinicians who provide weight management care to children and adolescents to determine current barriers for effective care and explore the role of EHR weight management tools to overcome these barriers. METHODS: In this mixed-methods study, we conducted three 1-hour long virtual focus groups at one medium-sized academic health center in Missouri and analyzed the focus group scripts using thematic analysis. We sequentially conducted a descriptive statistical analysis of a survey emailed to pediatric and family medicine primary care clinicians (n = 52) at two private and two academic health centers in Missouri. RESULTS: Surveyed clinicians reported that they effectively provided health behavior lifestyle counseling at well-child visits (mean of 60 on a scale of 1-100) and child obesity visits (63); however, most felt the current health care system (27) and EHR tools (41) do not adequately support pediatric weight management. Major themes from the clinician focus groups were that EHR weight management tools should display data in a way that (1) improves clinical efficiency, (2) supports patient-centered communication, (3) improves patient continuity between visits, and (4) reduces documentation burdens. An additional theme was (5) clinicians trust patient data entered in real time over patient recalled data. CONCLUSION: Study participants report that the health care system status quo and currently available EHR tools do not sufficiently support clinicians working to manage pediatric or adolescent obesity and provide health behavior counseling. Clinician input in the development and testing of EHR weight management tools provides opportunities to address barriers, inform content, and improve efficiencies of EHR use.

Virtual Reality and Neurofeedback for Management of Cancer Symptoms: A Feasibility Pilot.

Background: Evidence suggests the usefulness of complementary and alternative medicine approaches, like neurofeedback and virtual reality, for the management of cancer-related pain and mood. It is not well-understood whether neurofeedback delivered through virtual reality is feasible and acceptable to patients actively undergoing cancer treatment. Objective: The purpose of this study was to explore the feasibility and acceptability of a nature-based virtual reality combined with neurofeedback as a non-pharmacologic strategy for managing cancer-related pain and anxiety. Methods: This study utilized a mixed-methods approach. Participants included 15 cancer patients undergoing treatment. Patients engaged in a 22-minute nature-based virtual reality experience, wearing a virtual reality headset with a Brainlink headband measuring EEG activity. Participants were asked to complete the Edmonton Symptom Assessment System revised version (ESAS-r) before (T1) and after (T3) the experience to measure pain and anxiety. They were asked their level of pain midway through the experience (T2) and completed a follow-up interview afterward. Results: This study revealed feasible delivery of a virtual reality intervention combined with neurofeedback for patients seeking cancer treatment. All participants (100%) completed the intervention experience. Patients report this is an acceptable approach to managing cancer-related pain and anxiety. Comparisons between patients' pain scores at T1, T2, and T3 reveal statistically significant reductions in pain (p .001). Patients also report decreased depression and anxiety. Conclusion: This is the first study examining virtual reality combined with neurofeedback as a non-pharmacologic intervention for managing cancer symptoms during treatment. The study reveals it is a promising for managing cancer-symptoms.

Mixed-methods study of development and design needs for CommitFit, an adolescent mHealth App.

Background: Adolescent obesity remains a significant public health issue within the United States. Mobile application technology growth and popularity offer new opportunities for research and health improvement. The development of a consolidated mobile health application (mHealth app) for adolescents on these platforms has the potential to improve health outcomes. Thus, this study describes the co-development process working with adolescent users. The aims are as follows: (I) to explore the visual design and functional requirements when developing the CommitFit mHealth app, (II) to uncover the gamification techniques that incentivize adolescents to set and achieve healthy lifestyle goals, and (III) to identify adolescent expectations when using the CommitFit mHealth application. Methods: In this mixed method study, we used semi-structured interviews/task analysis and surveys of adolescents (aged 13 to 15 years) to understand their user requirements and design preferences during the development of the CommitFit mHealth app. Interviews were conducted online, via Zoom. The survey included the user design industry-standard System Usability Scale (SUS) paired with a supplemental questionnaire on the specific features and functionalities of the CommitFit mHealth app. Participants were recruited from the electronic health record from the University of Missouri Healthcare system. Results: Ten adolescents, aged 13 to 15 years (average of 13.6 years), were interviewed and surveyed to explore adolescent preferences with visual app design and functionality. Our inductive thematic analysis found that adolescents preferred colorful, user-friendly interfaces paired with gamification in the CommitFit mHealth app. Our analysis of SUS survey data validated our user-centered and human-system design and adolescents confirmed their design, feature, and functionality preferences. Overall, adolescent users were able to confirm their preference to have educational resources, goal recommendations, leaderboard, points, reminders, and an avatar in the app. Conclusions: Adolescent feedback is crucial in the successful development of our adolescent-targeted mHealth app, CommitFit. Adolescents preferred vibrant colors, easy-to-use interface, gamification, customizable and personalized, and mature graphics. Adolescents were especially motivated by gamification techniques to maintain their interest in the application and their health behavior goals. Additional research is now needed to explore the clinical effectiveness of the CommitFit mHealth app, as a health and lifestyle intervention.

Analytical Estimation of Data-Motivated Time-Dependent Disease Transmission Rate: An Application to Ebola and Selected Public Health Problems.

Obtaining reasonable estimates for transmission rates from observed data is a challenge when using mathematical models to study the dynamics of ?infectious? diseases, like Ebola. Most models assume the transmission rate of a contagion either does not vary over time or change in a fixed pre-determined adhoc ways. However, these rates do vary during an outbreak due to multitude of factors such as environmental conditions, social behaviors, and public-health interventions deployed to control the disease, which are in-part guided by changing size of an outbreak. We derive analytical estimates of time-dependent transmission rate for an epidemic in terms of either incidence or prevalence using a standard mathematical SIR-type epidemic model. We illustrate applicability of our method by applying data on various public health problems, including infectious diseases (Ebola, SARS, and Leishmaniasis) and social issues (obesity and alcohol drinking) to compute transmission rates over time. We show that time-dependent transmission rate estimates can have a large variation, depending on the type of available data and other epidemiological parameters. Time-dependent estimation of transmission rates captures the dynamics of the problem better and can be utilized to understand disease progression more accurately.