WeChatting for Health: What Motivates Older Adult Engagement with Health Information.
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ABSTRACT:
SUBMITTER: Zhang X
PROVIDER: S-EPMC8234300 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:OBJECTIVE:Spousal caregiving can have strong implications for health and wellbeing given the strain and burden associated with the role. Maintaining activity engagement is important for late-life health and wellbeing, and may be a possible contributing mechanism to caregiver health and wellbeing. This paper examined longitudinal changes in activity engagement and asks how spousal caregiving status and caregiver age related to longitudinal activity engagement in a sample of older adults. METHOD:Data from four waves of the Health and Retirement study were used to model associations between periods of being a spousal caregiver, age, and engagement in physical, social, self-care, passive, and novel information processing activities over a 6-year period. RESULTS:Caregiving status was associated with declines in physical activity engagement over time. Older age was associated with fewer physical and more self-care and passive activities. DISCUSSION:Caregivers' declines in participation in physical activities may be an important indicator for preservation of health and management of caregiving stress.
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Project description:BackgroundBy 2035, it is expected that older adults (aged 65 years and older) will outnumber children and will represent 78 million people in the US population. As the aging population continues to grow, it is critical to reduce disparities in their representation in medical research.ObjectiveThis study aimed to describe sociodemographic characteristics and health and information behaviors as factors that influence US adults' interest in engaging in medical research, beyond participation as study subjects.MethodsNationally representative cross-sectional data from the 2014 Health Information National Trends Survey (N=3677) were analyzed. Descriptive statistics and weighted multivariable logistic regression analyses were performed to assess predictors of one's interest in patient engagement in medical research. The independent variables included age, general health, income, race and ethnicity, education level, insurance status, marital status, and health information behaviors.ResultsWe examined the association between the independent variables and patient interest in engaging in medical research (PTEngage_Interested). Patient interest in engaging in medical research has a statistically significant association with age (adjusted P<.01). Younger adults (aged 18-34 years), lower middle-aged adults (aged 35-49 years), and higher middle-aged adults (aged 50-64 years) indicated interest at relatively the same frequency (29.08%, 29.56%, and 25.12%, respectively), but older adults (aged ≥65 years) expressed less interest (17.10%) than the other age groups. After the multivariate model was run, older adults (odds ratio 0.738, 95% CI 0.500-1.088) were found to be significantly less likely to be interested in engaging in medical research than adults aged 50 to 64 years. Regardless of age, the strongest correlation was found between interest in engaging in medical research and actively looking for health information (P<.001). Respondents who did not seek health information were significantly less likely than those who did seek health information to be interested in engaging in medical research.ConclusionsPatients' interest in engaging in medical research vary by age and information-seeking behaviors. As the aging population continues to grow, it is critical to reduce disparities in their representation in medical research. Interest in participatory research methods may reflect an opportunity for consumer health informatics technologies to improve the representation of older adults in future medical research.
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Project description:BackgroundUS research organizations increasingly are supporting patient and stakeholder engagement in health research with a goal of producing more useful, relevant and patient-centered evidence better aligned with real-world clinical needs. The Patient-Centered Outcomes Research Institute (PCORI) engages patients, family caregivers and other health-care stakeholders, including clinicians, payers and policymakers, as active partners in prioritizing, designing, conducting and disseminating research as a key strategy to produce useful evidence for health-care decision making.ObjectiveTo inform effective engagement practices and policies, we sought to understand what motivates patients and caregivers to engage as partners on PCORI-funded research projects and how such engagement changed their lives.MethodsWe conducted thematic analysis of open-ended survey responses from 255 patients, family caregivers and individuals from advocacy and community-based organizations who engaged as partners on 139 PCORI-funded research projects focusing on a range of health conditions.ResultsPartners' motivations for engaging in research were oriented primarily towards benefiting others, including a desire to improve patients' lives and to support effective health-care interventions. In addition to feeling they made a positive difference, many partners reported direct benefits from engagement, such as new relationships and improved health habits.Discussion and conclusionsBy identifying patient and caregiver motivations for engaging in research partnerships and what they get out of the experience, our study may help research teams and organizations attract partners and foster more satisfying and sustainable partnerships. Our findings also add to evidence that engagement benefits the people involved as partners, strengthening the case for more widespread engagement.
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Project description:BackgroundWhile digital governance has been adopted by governments around the world to assist in the management of the COVID-19 pandemic, the effectiveness of its implementation relies on the collection and use of personal information. This study examines the willingness of individuals to engage in information-sharing with governments when adopting health technologies during the COVID-19 pandemic.MethodsData were obtained from a cross-sectional survey of 4,800 individuals drawn from 16 cities in China in 2021. Tobit regression models were used to assess the impacts of an array of determinants on an individual's willingness to share information with governments when adopting health technologies.ResultsIndividuals who perceived a higher level of helpfulness, risk, expectations from others, weariness toward privacy issues, and were sensitive to positive outcomes were more willing to share information with governments when adopting health technologies during the COVID-19 pandemic. Across all the subgroups, self-efficacy only reduced the willingness to share information with governments for individuals who spent more than seven hours per day online. The negative impacts of being sensitive to negative outcomes on the willingness to share information were only found among females and the less educated group.ConclusionsThis study revealed the seemingly paradoxical behavior of individuals who perceived high risks of sharing information and a sense of fatigue toward privacy issues yet continued to be willing to share their information with their governments when adopting health technologies during the COVID-19 pandemic. This work highlighted significant differential motivations for sharing information with governments when using health technologies during a pandemic. Tailored policies that resonate with population sub-groups were suggested to be proposed to facilitate crisis management in future situations.
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Project description:OBJECTIVES:To assess whether hospital participation in alternative payment models (APMs) is associated with greater engagement in health information exchange (HIE) along 4 dimensions: volume of patients for whom information is exchanged, diversity of information types, breadth of partner types, and depth of technical approach. STUDY DESIGN:Pooled, cross-sectional analysis of data on US hospitals from 2014 to 2015. METHODS:APM participation came from Leavitt Partners data, Medicare public use files, and the American Hospital Association (AHA) Annual Survey. We used Medicare data to measure HIE volume for 798 hospitals attesting to stage 2 Meaningful Use and the AHA Information Technology Supplement to measure HIE diversity, breadth, and depth for 1730 hospitals. We used mixed-effects regression to estimate the association between participation in APMs and each dimension of HIE. RESULTS:Compared with nonparticipating hospitals, full-year APM participation was associated with lower HIE volume (data were sent for 11 percentage points fewer discharges; P = .003), greater HIE diversity (of 4 data types, 0.3 more were transmitted; P <.001), greater HIE breadth (of 3 partner types, data were sent to 0.3 more; P <.001), and greater HIE depth (the odds of using a push and pull approach were 1.68 times greater; P = .004). CONCLUSIONS:Our finding that APM participation was associated with greater HIE diversity, breadth, and depth suggests that value-based payment may be spurring improvements in HIE infrastructure. However, our finding that APM participation is associated with lower HIE volume suggests that there may be an incentive to focus HIE investments on a limited number of partners.
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Project description:ObjectiveGeriatric syndromes such as functional disability and lack of social support are often not encoded in electronic health records (EHRs), thus obscuring the identification of vulnerable older adults in need of additional medical and social services. In this study, we automatically identify vulnerable older adult patients with geriatric syndrome based on clinical notes extracted from an EHR system, and demonstrate how contextual information can improve the process.Materials and methodsWe propose a novel end-to-end neural architecture to identify sentences that contain geriatric syndromes. Our model learns a representation of the sentence and augments it with contextual information: surrounding sentences, the entire clinical document, and the diagnosis codes associated with the document. We trained our system on annotated notes from 85 patients, tuned the model on another 50 patients, and evaluated its performance on the rest, 50 patients.ResultsContextual information improved classification, with the most effective context coming from the surrounding sentences. At sentence level, our best performing model achieved a micro-F1 of 0.605, significantly outperforming context-free baselines. At patient level, our best model achieved a micro-F1 of 0.843.DiscussionOur solution can be used to expand the identification of vulnerable older adults with geriatric syndromes. Since functional and social factors are often not captured by diagnosis codes in EHRs, the automatic identification of the geriatric syndrome can reduce disparities by ensuring consistent care across the older adult population.ConclusionEHR free-text can be used to identify vulnerable older adults with a range of geriatric syndromes.
| S-EPMC7647225 | biostudies-literature
Project description:BackgroundOlder adults face growing health care needs and could potentially benefit from personal health information management (PHIM) and PHIM technology. To ensure effective PHIM and to provide supportive tools, it is crucial to investigate the needs, challenges, processes, and tools used by this subpopulation. The literature on PHIM by older adults, however, remains scattered and has not provided a clear picture of what we know about the elements that play a role in older adults' PHIM.ObjectiveThe goal of our review was to provide a comprehensive overview of extant knowledge on PHIM by older adults, establish the status quo of research on this topic, and identify research gaps.MethodsWe carried out a scoping review of the literature from 1998 to 2020, which followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) framework. First, we executed a broad and structured search. We then carried out a qualitative analysis of papers pertinent to the topic taking into consideration the five elements of the patient work system as follows: (1) personal-level factors, (2) PHIM tasks, (3) tools used, (4) physical settings of PHIM activities, and (5) socio-organizational aspects.ResultsThe review included 22 studies. Consolidated empirical evidence was related to all elements of the patient work system. Multiple personal factors affected PHIM. Various types of personal health information were managed (clinical, patient-generated, and general) and tools were used (electronic, paper-based, and others). Older adults' PHIM was intertwined with their surroundings, and various individuals participated. The largest body of evidence concerned personal factors, while findings regarding the physical environment of PHIM were scarce. Most research has thus far examined older adults as a single group, and scant attention has been paid to age subgroups.ConclusionsOpportunities for further PHIM studies remain across all elements of the patient work system in terms of empirical, design science, or review work.
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Project description:At an academic health science center, librarians partnered with a community research engagement program to offer a suite of consumer health information services. The services included training staff in the use of online consumer health resources, purchasing a print collection of monographs, and creating a guide to both the online and print resources for staff use. Focus groups were conducted to assess information needs, and the workshop attendees' online health information competency was assessed presession and postsession. This article details planning and intervention efforts, and proposes future activities to meet the information needs of HealthStreet and its clients.
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Project description:ObjectiveThe purpose of this study was to compare two pedagogical methods, active learning and passive instruction, to determine which is more useful in helping students to achieve the learning outcomes in a one-hour research skills instructional session.MethodsTwo groups of high school students attended an instructional session to learn about consumer health resources and strategies to enhance their searching skills. The first group received passive instruction, and the second engaged in active learning. We assessed both groups' learning using 2 methods with differing complexity. A total of 59 students attended the instructional sessions (passive instruction, n=28; active learning, n=31).ResultsWe found that the active learning group scored more favorably in four assessment categories.ConclusionsActive learning may help students engage with and develop a meaningful understanding of several resources in a single session. Moreover, when using a complex teaching strategy, librarians should be mindful to gauge learning using an equally complex assessment method.
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Project description:Testing theories about human senescence and longevity demands accurate information on older-adult mortality; this is rare in low- to middle-income countries where raw data may be distorted by defective completeness and systematic age misreporting. For this reason, such populations are frequently excluded from empirical tests of mortality and longevity theories, thus limiting their reach, as they reflect only a small and selected human mortality experience. In this paper we formulate an integrated method to compute estimates of older-adult mortality when vital registration and population counts are defective due to inaccurate coverage and/or systematic age misreporting. The procedure is validated with a simulation study that identifies a strategy to compute adjustments, which, under some assumptions, performs quite well. While the paper focuses on Latin American and Caribbean countries, the method is quite general and, with additional information and some model reformulation, could be applied to other populations with similar problems.
| S-EPMC9026698 | biostudies-literature