Background Mobile health (mHealth) provides a unique modality for improving access to and awareness of palliative care among patients, families, and caregivers from diverse backgrounds. Some mHealth palliative care apps exist, both commercially available and established by academic researchers. However, the elements of family support and family caregiving tools offered by these early apps is unknown. Objective The objective of this scoping review was to use social convoy theory to describe the inclusion and functionality of family, social relationships, and caregivers in palliative care mobile apps. Methods Using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Review guidelines, a systematic search of palliative care mHealth included (1) research-based mobile apps identified from academic searches published between January 1, 2010, and March 31, 2019 and (2) commercially available apps for app stores in April 2019. Two reviewers independently assessed abstracts, app titles, and descriptions against the inclusion and exclusion criteria. Abstracted data covered app name, research team or developer, palliative care element, target audience, and features for family support and caregiving functionality as defined by social convoy theory. Results Overall, 10 articles describing 9 individual research-based apps and 22 commercially available apps were identified. Commercially available apps were most commonly designed for both patients and social convoys, whereas the majority of research apps were designed for patient use only. Conclusions Results suggest there is an emerging presence of apps for patients and social convoys receiving palliative care; however, there are many needs for developers and researchers to address in the future. Although palliative care mHealth is a growing field, additional research is needed for apps that embrace a team approach to information sharing, target family- and caregiver-specific issues, promote access to palliative care, and are comprehensive of palliative needs.
This study explores the effects of habitual health risk behaviors and self-activation on resistance to narrative persuasion. In two experiments, heavier drinkers were more resistant to an anti-binge-drinking narrative public service announcement (PSA) in which a binge drinker suffers a negative outcome. Specifically, heavier drinkers were more likely to generate counterarguments, unrealism judgments, and negative evaluations about the message compared to lighter drinkers or nondrinkers. However, activating self-concept when processing the persuasive narrative reduced unrealism judgments and negative evaluations, particularly among heavier drinkers. Self-activation also decreased perceived freedom threat among both heavier and lighter drinkers, which further led to higher perceived risk of binge drinking. Theoretical and practical implications are discussed.
Background Although patient portals are widely used for health promotion, little is known about the use of palliative care and end-of-life (PCEOL) portal tools available for patients and caregivers. Objective This study aims to identify and assess the user perspectives of PCEOL portal tools available to patients and caregivers described and evaluated in the literature. Methods We performed a scoping review of the academic literature directed by the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-analyses) extension for Scoping Review and searched three databases. Sources were included if they reported the development or testing of a feature, resource, tool, or intervention; focused on at least one PCEOL domain defined by the National Coalition for Hospice and Palliative Care; targeted adults with serious illness or caregivers; and were offered via a patient portal tethered to an electronic medical record. We independently screened the titles and abstracts (n=796) for eligibility. Full-text (84/796, 10.6%) sources were reviewed. We abstracted descriptions of the portal tool name, content, targeted population, and reported user acceptability for each tool from included sources (n=19). Results In total, 19 articles describing 12 tools were included, addressing the following PCEOL domains: ethical or legal (n=5), physical (n=5), and psychological or psychiatric (n=2). No tools for bereavement or hospice care were identified. Studies have reported high acceptability of tools among users; however, few sources commented on usability among older adults. Conclusions PCEOL patient portal tools are understudied. As medical care increasingly moves toward virtual platforms, future research should investigate the usability and acceptability of PCEOL patient portal resources and evaluate their impact on health outcomes.
Objective Our goal is to establish the feasibility of using an artificially intelligent chatbot in diverse healthcare settings to promote COVID-19 vaccination. Methods We designed an artificially intelligent chatbot deployed via short message services and web-based platforms. Guided by communication theories, we developed persuasive messages to respond to users’ COVID-19-related questions and encourage vaccination. We implemented the system in healthcare settings in the U.S. between April 2021 and March 2022 and logged the number of users, topics discussed, and information on system accuracy in matching responses to user intents. We regularly reviewed queries and reclassified responses to better match responses to query intents as COVID-19 events evolved. Results A total of 2479 users engaged with the system, exchanging 3994 COVID-19 relevant messages. The most popular queries to the system were about boosters and where to get a vaccine. The system's accuracy rate in matching responses to user queries ranged from 54% to 91.1%. Accuracy lagged when new information related to COVID emerged, such as that related to the Delta variant. Accuracy increased when we added new content to the system. Conclusions It is feasible and potentially valuable to create chatbot systems using AI to facilitate access to current, accurate, complete, and persuasive information on infectious diseases. Such a system can be adapted to use with patients and populations needing detailed information and motivation to act in support of their health.
The proliferation of technology enthuses clinicians, researchers, and entrepreneurs to revolutionize health care and care delivery. Intersecting in the field of digital health, academicindustry collaboration (AIC) play a critical role in advancing evidence-based innovations into real world application. AIC models vary, but historically have not included the strong emphasis on rapid research and discovery that the digital health field demands. Due to the voluminous availability of real time patient and client data, academic health centers offer a rich interdisciplinary environment to develop, pilot and evaluate innovations in pragmatic settings. Despite the opportunity between academic health centers and industry to advance digital health innovation through rapid research, limited evidence exists of such collaboration. The purpose of this case report is to examine an AIC facilitating research of new health technologies within an academic health center. This paper presents a case report involving collaboration between diverse technology industry partners and an academic health center that encompasses a university health system (UCHealth), a university technology transfer office (CU Innovations), an innovation center (CARE Innovation Center), and research collaborators (mHealth Impact Laboratory). Case assertions discuss the lessons learned and recommendations when implementing such collaboration in practice. The principal finding is that academic health centers offer an innovative environment for AIC in digital health. Collaborations between academia and industry provide much promise in ensuring health innovations are scientifically sound while meeting the needs of a rapidly evolving technical climate.
One crucial factor that leads to disparities in smoking cessation between groups with higher and lower socioeconomic status is more prevalent socioenvironmental smoking cues in low-income communities. Little is known about how these cues influence socioeconomically disadvantaged smokers in real-world scenarios and how to design interventions, especially mobile phone–based interventions, to counteract the impacts of various types of smoking cues. We interviewed 15 current smokers living in low-income communities and scanned their neighborhoods to explore smoking-related experiences and identify multilevel cues that may trigger them to smoke. Findings suggest four major types of smoking cues influence low-income smokers—internal, habitual, social, and environmental. We propose an ecological model of smoking cues to inform the design of mobile health (mHealth) interventions for smoking cessation. We suggest that user-triggered strategies will be most useful to address internal cues; server-triggered strategies will be most suitable in changing perceived social norms of smoking and routine smoking activities to address social and habitual cues; and context-triggered strategies will be most effective for counteracting environmental cues. The pros and cons of each approach are discussed regarding their cost-effectiveness, the potential to provide personalized assistance, and scale.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.