Online Behavioral Screener with Tailored Obesity Prevention Messages: Application to a Pediatric Clinical Setting

Obesity prevention involves promoting healthy eating and physical activity across all children. Can we leverage technology to feasibly survey children’s health behaviors and deliver theory-based and user-tailored messages for brief clinical encounters? We assessed the acceptability and utility of an online pediatric-adapted liking survey (PALS) and tailored messages among children receiving non-urgent care in a pediatric emergency department (PED). Two hundred and forty-five children (average age = 10 years, racially/ethnically diverse, 34% overweight/obese from measured indices, 25% of families reporting food insecurity) and their parents/caregivers participated. Each reported the child’s activity and behaviors using the online PALS and received two to three messages tailored to the responses (aligned with elaboration likelihood and transtheoretical models) to motivate behavioral improvements or reinforce healthy behaviors. Most children and parents (>90%) agreed the PALS was easy to complete, encouraging thought about their own/child’s behaviors. The child’s PALS responses appeared reasonable (fair-to-good child–parent intraclass correlations). Most children and parents (≥75%) reported the tailored messages to be helpful and favorable for improving or maintaining the targeted behavior. Neither message type (motivating/reinforcing) nor favorability responses varied significantly by the child’s weight or family’s food security status. In summary, children and parents found the PALS with tailored messages acceptable and useful. The message types and responses could help focus brief clinical encounters.     

Interpersonal influences on self-management in the eHealth era: Predicting the uses of eHealth tools for self-care in America

Drawing on the social cognitive theory and the comprehensive model of information seeking, this study proposes a theoretical framework that systematically examines the role of interpersonal factors in individuals' self-management in the eHealth context. The framework was tested with a sample of 965 eHealth users drawn from the National Cancer Institute's 2018 Health Information National Trends Survey. Structural equation modelling was performed to model the relationships among patient-centred communication, social support, self-efficacy, perceptions of eHealth tools and eHealth behaviours. The results established social support and patient-centred communication as two important sources of self-efficacy. Self-efficacy together with characteristics of eHealth tools were associated with higher utility of eHealth tools, which further predicted higher levels of eHealth behaviours. The results show that incorporating interpersonal factors in health interventions may enhance the targets' self-efficacy in self-management and indirectly motivates eHealth behaviours.     

COVID-19 Surveillance in the Biobank at the Colorado Center for Personalized Medicine: Observational Study

BackgroundCharacterizing the experience and impact of the COVID-19 pandemic among various populations remains challenging due to the limitations inherent in common data sources, such as electronic health records (EHRs) or cross-sectional surveys.ObjectiveThis study aims to describe testing behaviors, symptoms, impact, vaccination status, and case ascertainment during the COVID-19 pandemic using integrated data sources.MethodsIn summer 2020 and 2021, we surveyed participants enrolled in the Biobank at the Colorado Center for Personalized Medicine (CCPM; N=180,599) about their experience with COVID-19. The prevalence of testing, symptoms, and impacts of COVID-19 on employment, family life, and physical and mental health were calculated overall and by demographic categories. Survey respondents who reported receiving a positive COVID-19 test result were considered a “confirmed case” of COVID-19. Using EHRs, we compared COVID-19 case ascertainment and characteristics in EHRs versus the survey. Positive cases were identified in EHRs using the International Statistical Classification of Diseases, 10th revision (ICD-10) diagnosis codes, health care encounter types, and encounter primary diagnoses.ResultsOf the 25,063 (13.9%) survey respondents, 10,661 (42.5%) had been tested for COVID-19, and of those, 1366 (12.8%) tested positive. Nearly half of those tested had symptoms or had been exposed to someone who was infected. Young adults (18-29 years) and Hispanics were more likely to have positive tests compared to older adults and persons of other racial/ethnic groups. Mental health (n=13,688, 54.6%) and family life (n=12,233, 48.8%) were most negatively affected by the pandemic and more so among younger groups and women; negative impacts on employment were more commonly reported among Black respondents. Of the 10,249 individuals who responded to vaccination questions from version 2 of the survey (summer 2021), 9770 (95.3%) had received the vaccine. After integration with EHR data up to the time of the survey completion, 1006 (4%) of the survey respondents had a discordant COVID-19 case status between EHRs and the survey. Using all longitudinal EHR and survey data, we identified 11,472 (6.4%) COVID-19-positive cases among Biobank participants. In comparison to COVID-19 cases identified through the survey, EHR-identified cases were younger and more likely to be Hispanic.ConclusionsWe found that the COVID-19 pandemic has had far-reaching and varying effects among our Biobank participants. Integrated data assets, such as the Biobank at the CCPM, are key resources for population health monitoring in response to public health emergencies, such as the COVID-19 pandemic.     

Digital Disparities

ABSTRACT

There is a vast amount of health information on the Internet, although certain underserved U.S. populations still lack equal access to this information. This digital divide pertains not only to computer and Internet access, but also to issues related to appropriate content. Some view the Internet as one solution to eliminating health disparities, although barriers such as education, income and cost, age, location, literacy, and content contribute to a persistent digital divide. Many solutions to this problem have been proposed, but the situation still warrants further study before eHealth strategies and interventions can be effectively implemented to a wider community.     

Aplicaciones móviles en la enfermedad de Parkinson: una revisión sistemática

Introduction

Parkinson's disease (PD) is the second most common neurodegenerative disease. However, diagnosing, assessing, and treating these patients is a complex process requiring continuous monitoring. In this context, smartphones may be useful in the management of patients with PD.