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JMIR Aging
Digital health technologies, apps, and informatics for patient education, medicine and nursing, preventative interventions, and clinical care / home care for elderly populations
(Toronto, Aug 31st, 2019) We are pleased to report that JMIR Aging (JA) has been accepted for indexing in PubMed Central and PubMed. The staff at PubMed Central is currently finalizing the setup and we expect all articles published since Vol 1 / Iss 1 to be in PubMed Central and PubMed within the next couple of weeks. The acceptance is the result of a rigorous scientific and technical evaluation by the US National Library's (NLM’s) Library Operations Division, which decided that the scientific and editorial character and quality of a JMIR Aging merits its inclusion in PMC. In making this decision NLM has considered the suitability of the journal for the NLM collection as well as the opinions of expert consultants.
JMIR Aging (JA, Founding Editor-in-chief: Jing Wang, Professor and Vice Dean for Research, Hugh Roy Cullen Professor, UT Health San Antonio School of Nursing, San Antonio, TX, USA) is an open access journal, focusing on technologies, medical devices, apps, engineering, informatics applications and patient education for medicine and nursing, education, preventative interventions and clinical care / home care for elderly populations. In addition, aging-focused big data analytics using data from electronic health record systems, health insurance databases, federal reimbursement databases (e.g. U.S. Medicare and Medicaid), and other large databases are also welcome.
This journal is read by clinicians, nurses/allied health professionals, informal caregivers and patients alike and have (as all JMIR journals) a focus on readable and applied science reporting the design and evaluation of health innovations and emerging technologies. We publish original research, viewpoints, and reviews (both literature reviews and medical device/technology/app reviews).
Articles are carefully copyedited and XML-tagged, ready for submission in PubMed Central. The journal is indexed in PMC and PubMed. Upon acceptance, an article processing fee will apply.
Background: Mobile health (mHealth) apps are dramatically changing how patients and providers manage and monitor chronic health conditions, especially in the area of self-monitoring. African Americans have higher mortality rates from heart failure than other racial groups in the United States. Therefore, self-management of heart failure may improve health outcomes for African American patients.
Objective: The aim of the present study was to determine the feasibility of using an mHealth app, and explore the outcomes of quality of life, including self-care maintenance, management, and confidence, among African American patients managing their condition after discharge with a diagnosis of heart failure.
Methods: Prior to development of the app, we conducted qualitative interviews with 7 African American patients diagnosed with heart failure, 3 African American patients diagnosed with cardiovascular disease, and 6 health care providers (cardiologists, nurse practitioners, and a geriatrician) who worked with heart failure patients. In addition, we asked 6 hospital chaplains to provide positive spiritual messages for the patients, since spirituality is an important coping method for many African Americans. These formative data were then used for creating a prototype of the app, named Healthy Heart. Specifically, the Healthy Heart app incorporated the following evidence-based features to promote self-management: one-way messages, journaling (ie, weight and symptoms), graphical display of data, and customized feedback (ie, clinical decision support) based on daily or weekly weight. The educational messages about heart failure self-management were derived from the teaching materials provided to the patients diagnosed with heart failure, and included information on diet, sleep, stress, and medication adherence. The information was condensed and simplified to be appropriate for text messages and to meet health literacy standards. Other messages were derived from interviews conducted during the formative stage of app development, including interviews with African American chaplains. Usability testing was conducted over a series of meetings between nurses, social workers, and computer engineers. A pilot one-group pretest-posttest design was employed with participants using the mHealth app for 4 weeks. Descriptive statistics were computed for each of the demographic variables, overall and subscales for Health Related Quality of Life Scale 14 (HQOL14) and subscales for the Self-Care of Heart Failure Index (SCHFI) Version 6 using frequencies for categorical measures and means with standard deviations for continuous measures. Baseline and postintervention comparisons were computed using the Fisher exact test for overall health and paired t tests for HQOL14 and SCHFI questionnaire subscales.
Results: A total of 12 African American participants (7 men, 5 women; aged 51-69 years) diagnosed with heart failure were recruited for the study. There was no significant increase in quality of life (P=.15), but clinically relevant changes in self-care maintenance, management, and confidence were observed.
Conclusions: An mHealth app to assist with the self-management of heart failure is feasible in patients with low literacy, low health literacy, and limited smartphone experience. Based on the clinically relevant changes observed in this feasibility study of the Healthy Heart app, further research should explore effectiveness in this vulnerable population.
Background: Previous studies have reported older adults’ perceptions of using health monitors; however, no studies have examined the actual use of multiple health monitors for lifestyle changes over time among older adults with type 2 diabetes (T2D).
Objective: The primary aim of this study was to examine the actual use of multiple health monitors for lifestyle changes over 3 months among older adults with T2D. The secondary aim was to explore changes in caloric intake and physical activity (PA) over 3 months.
Methods: This was a single-group study lasting 3 months. The study sample included participants who were aged ≥65 years with a diagnosis of T2D. Participants were recruited through fliers posted at the Joslin Diabetes Center in Boston. Participants attended five 60-min, biweekly group sessions, which focused on self-monitoring, goal setting, self-regulation to achieve healthy eating and PA habits, and the development of problem-solving skills. Participants were provided with the Lose It! app to record daily food intake and devices such as a Fitbit Alta for monitoring PA, a Bluetooth-enabled blood glucose meter, and a Bluetooth-enabled digital scale. Descriptive statistics were used for analysis.
Results: Of the enrolled participants (N=9), the sample was white (8/9, 89%) and female (4/9, 44%), with a mean age of 76.4 years (SD 6.0; range 69-89 years), 15.7 years (SD 2.0) of education, 33.3 kg/m2 (SD 3.1) BMI, and 7.4% (SD 0.8) hemoglobin A1c. Over the 84 days of self-monitoring, the mean percentage of days using the Lose It!, Fitbit Alta, blood glucose meter, and scale were 82.7 (SD 17.6), 85.2 (SD 19.7), 65.3 (SD 30.1), and 53.0 (SD 34.5), respectively. From baseline to completion of the study, the mean daily calorie intake was 1459 (SD 661) at week 1, 1245 (SD 554) at week 11, and 1333 (SD 546) at week 12, whereas the mean daily step counts were 5618 (SD 3654) at week 1, 5792 (SD 3814) at week 11, and 4552 (SD 3616) at week 12. The mean percentage of weight loss from baseline was 4.92% (SD 0.25). The dose of oral hypoglycemic agents or insulin was reduced in 55.6% (5/9) of the participants.
Conclusions: The results from the pilot study are encouraging and suggest the need for a larger study to confirm the outcomes. In addition, a study design that includes a control group with educational sessions but without the integration of technology would offer additional insight to understand the value of mobile health in behavior changes and the health outcomes observed during this pilot study.
Background: Fall-risk assessment is complex. Based on current scientific evidence, a multifactorial approach, including the analysis of physical performance, gait parameters, and both extrinsic and intrinsic risk factors, is highly recommended. A smartphone-based app was designed to assess the individual risk of falling with a score that combines multiple fall-risk factors into one comprehensive metric using the previously listed determinants.
Objective: This study provides a descriptive evaluation of the designed fall-risk score as well as an analysis of the app’s discriminative ability based on real-world data.
Methods: Anonymous data from 242 seniors was analyzed retrospectively. Data was collected between June 2018 and May 2019 using the fall-risk assessment app. First, we provided a descriptive statistical analysis of the underlying dataset. Subsequently, multiple learning models (Logistic Regression, Gaussian Naive Bayes, Gradient Boosting, Support Vector Classification, and Random Forest Regression) were trained on the dataset to obtain optimal decision boundaries. The receiver operating curve with its corresponding area under the curve (AUC) and sensitivity were the primary performance metrics utilized to assess the fall-risk score's ability to discriminate fallers from nonfallers. For the sake of completeness, specificity, precision, and overall accuracy were also provided for each model.
Results: Out of 242 participants with a mean age of 84.6 years old (SD 6.7), 139 (57.4%) reported no previous falls (nonfaller), while 103 (42.5%) reported a previous fall (faller). The average fall risk was 29.5 points (SD 12.4). The performance metrics for the Logistic Regression Model were AUC=0.9, sensitivity=100%, specificity=52%, and accuracy=73%. The performance metrics for the Gaussian Naive Bayes Model were AUC=0.9, sensitivity=100%, specificity=52%, and accuracy=73%. The performance metrics for the Gradient Boosting Model were AUC=0.85, sensitivity=88%, specificity=62%, and accuracy=73%. The performance metrics for the Support Vector Classification Model were AUC=0.84, sensitivity=88%, specificity=67%, and accuracy=76%. The performance metrics for the Random Forest Model were AUC=0.84, sensitivity=88%, specificity=57%, and accuracy=70%.
Conclusions: Descriptive statistics for the dataset were provided as comparison and reference values. The fall-risk score exhibited a high discriminative ability to distinguish fallers from nonfallers, irrespective of the learning model evaluated. The models had an average AUC of 0.86, an average sensitivity of 93%, and an average specificity of 58%. Average overall accuracy was 73%. Thus, the fall-risk app has the potential to support caretakers in easily conducting a valid fall-risk assessment. The fall-risk score’s prospective accuracy will be further validated in a prospective trial.
: Presently, 6.5 million Americans are living with heart failure (HF). These patients are expected to follow a complex self-management regimen at home. Several demographic and psychosocial factors limit patients with HF in following the prescribed self-management recommendations at home. Poor self-care is associated with increased hospital readmissions. Under the Affordable Care Act, there are financial implications related to hospital readmissions for hospitals and programs such as the Program of All-Inclusive Care for the Elderly (PACE) in Pinellas County, Florida. Previous studies and systematic reviews demonstrated improvement in self-management and quality of life (QoL) in patients with HF with structured telephone support (STS) and SMS text messaging.
: This study aimed to evaluate the effects of STS and SMS on self-care, knowledge, medication adherence, and QoL of patients with HF.
: A prospective quality improvement project using a pre-post design was implemented. Data were collected at baseline, 30 days, and 3 months from 51 patients with HF who were enrolled in PACE in Pinellas County, Florida. All participants received STS and SMS for 30 days. The feasibility and sustained benefit of using STS and SMS was assessed at a 3-month follow-up.
: A paired t test was used to compare the mean difference in HF outcomes at the baseline and 30-day follow-up, which demonstrated improved HF self-care maintenance (t49=0.66; P=.01), HF knowledge (t49=0.71; P=.01), medication adherence (t49=0.92; P=.01), and physical and mental health measured using Short-Form-12 (SF-12; t49=0.81; P=.01). The results also demonstrated the sustained benefit with improved HF self-care maintenance, self-care management, self-care confidence, knowledge, medication adherence, and physical and mental health (SF-12) at 3 months with P<.05 for all outcomes. Living status and social support had a strong correlation with HF outcomes. Younger participants (aged less than 65 years) performed extremely well compared with older adults.
: STS and SMS were feasible to use among PACE participants with sustained benefits at 3 months. Implementing STS and SMS may serve as viable options to improve HF outcomes. Improving outcomes with HF affects hospital systems and the agencies that monitor and provide care for outpatients and those in independent or assisted-living facilities. Investigating viable options and support for implementation will improve outcomes.
Background: Alzheimer disease and related dementias (AD/RD) are progressive neurocognitive disorders that currently affect approximately 50 million people worldwide. Mobile phone apps have been well-integrated into daily lives and can be used to deliver and promote health care. There is an increase in the use of technology to provide care and support to AD/RD patients and their families.
Objective: This study aimed to review apps designed for AD/RD patients and analyze the benefits of, and challenges to, such technological solutions.
Methods: A systematic approach was applied to review the availability, content, features, and quality of mobile phone apps to support self-care among AD/RD patients.
Results: The initial search for this review was conducted in January 2019, and the screening and analysis of the included apps were completed in May 2019. A total of 14 apps were included from an initial search of 245 apps. The top 3 features were alert (9/14, 64%), self-care tips (6/14, 42%), and social networking capacity (5/14, 35%). On average, the readability of the apps was a tenth-grade reading level (SD 3.06). The overall quality was 3.71 out of 5 (SD 1.37).
Conclusions: Our findings suggest that currently available apps for AD/RD patients may not meet complex needs and may be challenging to use, given the possible impaired communication ability associated with AD/RD. Therefore, high-quality apps need to be developed and rigorously evaluated for feasibility and efficacy.
Background: Intelligent assistants (IAs), also known as intelligent agents, use artificial intelligence to help users achieve a goal or complete a task. IAs represent a potential solution for providing older adults with individualized assistance at home, for example, to reduce social isolation, serve as memory aids, or help with disease management. However, to design IAs for health that are beneficial and accepted by older adults, it is important to understand their beliefs about IAs, how they would like to interact with IAs for consumer health, and how they desire to integrate IAs into their homes.
Objective: We explore older adults’ mental models and beliefs about IAs, the tasks they want IAs to support, and how they would like to interact with IAs for consumer health. For the purpose of this study, we focus on IAs in the context of consumer health information management and search.
Methods: We present findings from an exploratory, qualitative study that investigated older adults’ perspectives of IAs that aid with consumer health information search and management tasks. Eighteen older adults participated in a multiphase, participatory design workshop in which we engaged them in discussion, brainstorming, and design activities that helped us identify their current challenges managing and finding health information at home. We also explored their beliefs and ideas for an IA to assist them with consumer health tasks. We used participatory design activities to identify areas in which they felt IAs might be useful, but also to uncover the reasoning behind the ideas they presented. Discussions were audio-recorded and later transcribed. We compiled design artifacts collected during the study to supplement researcher transcripts and notes. Thematic analysis was used to analyze data.
Results: We found that participants saw IAs as potentially useful for providing recommendations, facilitating collaboration between themselves and other caregivers, and for alerts of serious illness. However, they also desired familiar and natural interactions with IAs (eg, using voice) that could, if need be, provide fluid and unconstrained interactions, reason about their symptoms, and provide information or advice. Other participants discussed the need for flexible IAs that could be used by those with low technical resources or skills.
Conclusions: From our findings, we present a discussion of three key components of participants’ mental models, including the people, behaviors, and interactions they described that were important for IAs for consumer health information management and seeking. We then discuss the role of access, transparency, caregivers, and autonomy in design for addressing participants’ concerns about privacy and trust as well as its role in assisting others that may interact with an IA on the older adults’ behalf.
Background: The increase in life expectancy and recent advancements in technology and medical science have changed the way we deliver health services to the aging societies. Evidence suggests that home telemonitoring can significantly decrease the number of readmissions, and continuous monitoring of older adults’ daily activities and health-related issues might prevent medical emergencies.
Objective: The primary objective of this review was to identify advances in assistive technology devices for seniors and aging-in-place technology and to determine the level of evidence for research on remote patient monitoring, smart homes, telecare, and artificially intelligent monitoring systems.
Methods: A literature review was conducted using Cumulative Index to Nursing and Allied Health Literature Plus, MEDLINE, EMBASE, Institute of Electrical and Electronics Engineers Xplore, ProQuest Central, Scopus, and Science Direct. Publications related to older people’s care, independent living, and novel assistive technologies were included in the study.
Results: A total of 91 publications met the inclusion criteria. In total, four themes emerged from the data: technology acceptance and readiness, novel patient monitoring and smart home technologies, intelligent algorithm and software engineering, and robotics technologies. The results revealed that most studies had poor reference standards without an explicit critical appraisal.
Conclusions: The use of ubiquitous in-home monitoring and smart technologies for aged people’s care will increase their independence and the health care services available to them as well as improve frail elderly people’s health care outcomes. This review identified four different themes that require different conceptual approaches to solution development. Although the engineering teams were focused on prototype and algorithm development, the medical science teams were concentrated on outcome research. We also identified the need to develop custom technology solutions for different aging societies. The convergence of medicine and informatics could lead to the development of new interdisciplinary research models and new assistive products for the care of older adults.
Background:
The use of online health communities such as the diabetes online community (DOC) is growing. Individuals who engage in the DOC are able to interact with peers who have the same medical condition. It is not known if older adults are perceiving the DOC differently compared with younger adults.
Methods:
This study represents a subset of participants from a larger study of DOC users. Baby boomers and younger adults with diabetes were recruited from the DOC to participate in a cross-sectional survey. Demographics, electronic health use (reasons to join the DOC, DOC intensity, DOC engagement, internet social capital, and help or harm from the DOC), source credibility, health-related quality of life, and diabetes self-care data were collected. We examined the differences between baby boomer and younger adult responses.
Results:
The participants included baby boomers (N=76) and younger adult counterparts (N=102). Participants scored their diabetes health care team (mean 33.5 [SD 8]) significantly higher than the DOC (mean 32 [SD 6.4]) with regard to competence (P<.05) and trustworthiness (diabetes health care team mean 36.3 [SD 7.1]; DOC mean 33.6 [SD 6.2]; P<.001). High bonding and bridging social capital correlated with high DOC intensity (r=.629; P<.001 and r=.676; P<.001, respectively) and high DOC engagement (r=.474; P<.01 and r=.507; P≤.01, respectively). The greater majority (69.8%) reported the DOC as being helpful, and 1.8% reported that the DOC had caused minor harm. Baby boomers perceived DOC credibility, social capital, help, and harm similarly to their younger adult counterparts.
Conclusions:
Baby boomers are using and perceiving the DOC similarly to younger adults. DOC users find the DOC to be credible; however, they scored their health care team higher with regard to competence and trustworthiness. The DOC is beneficial with low risk and may augment current diabetes care.
Background: The importance of supporting caregivers is recognized in home care for older persons, and facilitating their help-seeking process is a way to meet that need. The use of electronic health (eHealth) is a potentially promising solution to facilitate caregivers’ help-seeking process. Objective: The aim of this research was to develop, in partnership with community organizations, health and social service professionals and caregivers, an eHealth tool promoting the earlier identification of needs of older persons and an optimal use of available resources. Methods: To design the tool, 8 co-design sessions (CoDs) were conducted and 3 advisory committees were created (in 11 regions) in Quebec between May 2017 and May 2018. A variety of methods were used, including the sorting method, the use of personas, eHealth tool analysis, brainstorming, sketching, prototyping, and pretesting. Results: A total of 74 co-designers (women n=64 and men n=10) were recruited to participate in the CoDs or the advisory committees. This number allowed for the identification of needs to which the tool must respond and for the identification of its requirements (functionalities and content), as well as for the development of the information architecture. Throughout the study, adjustments were made to the planning of CoD, notably because certain steps required more sessions than expected. Among others, this was true for the identification of functionalities. Conclusions: This study led to the development of an eHealth tool for caregivers of functionally dependent older persons to help them identify their needs and the resources available to meet them. International Registered Report Identifier (IRRID): RR2-10.2196/11634
Background: Informal carers play an increasingly vital role in supporting the older population and the sustainability of health care systems. Care Companion is a theory-based and coproduced Web-based intervention to help support informal carers’ resilience. It aims to provide personalized access to information and resources that are responsive to individuals’ caring needs and responsibilities and thereby reduce the burdens associated with caregiving roles. Following the development of a prototype, it was necessary to undertake user acceptability testing to assess its suitability for wider implementation. Objective: This study aimed to undertake user acceptance testing to investigate the perceived usefulness and ease of use of Care Companion. The key objectives were to (1) explore how potential and actual users perceived its usefulness, (2) explore the barriers and facilitators to its uptake and use and (3) gather suggestions to inform plans for an area-wide implementation. Methods: We conducted user acceptance testing underpinned by principles of rapid appraisal using a qualitative descriptive approach. Focus groups, observations, and semistructured interviews were used in two phases of data collection. Participants were adult carers who were recruited through local support groups. Within the first phase, think-aloud interviews and observations were undertaken while the carers familiarized themselves with and navigated through the platform. In the second phase, focus group discussions were undertaken. Interested participants were then invited to trial Care Companion for up to 4 weeks and were followed up through semistructured telephone interviews exploring their experiences of using the platform. Thematic analysis was applied to the data, and a coding framework was developed iteratively with each phase of the study, informing subsequent phases of data collection and analysis. Results: Overall, Care Companion was perceived to be a useful tool to support caregiving activities. The key themes were related to its appearance and ease of use, the profile setup and log-in process, concerns related to the safety and confidentiality of personal information, potential barriers to use and uptake and suggestions for overcoming them, and suggestions for improving Care Companion. More specifically, these related to the need for personalized resources aimed specifically at the carers (instead of care recipients), the benefits of incorporating a Web-based journal, the importance of providing transparency about security and data usage, minimizing barriers to initial registration, offering demonstrations to support uptake by people with low technological literacy, and the need to develop a culturally sensitive approach. Conclusions: The findings identified ways of improving the ease of use and usefulness of Care Companion and demonstrated the importance of undertaking detailed user acceptance testing when developing an intervention for a diverse population, such as informal carers of older people. These findings have informed the further refinement of Care Companion and the strategy for its full implementation.
