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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 a new sister journal of JMIR (the leading open-access journal in health informatics (Impact Factor 2017: 4.671), 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.
As open access journal we are 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).
During a limited period of time, there are no fees to publish in this journal. Articles are carfully copyedited and XML-tagged, ready for submission in PubMed Central.
Be a founding author of this new journal and submit your paper today!
Right click to copy or hit: ctrl+c (cmd+c on mac)
Background: Novel and sustainable approaches to scale Home-Based Primary Care (HBPC) programs are needed to meet the medical needs of a growing number of homebound older adults in the US. Telehealth m...
Background: Novel and sustainable approaches to scale Home-Based Primary Care (HBPC) programs are needed to meet the medical needs of a growing number of homebound older adults in the US. Telehealth may be a viable option for scaling HBPC programs. Objective: The purpose of this qualitative study was to gain insight into the perspectives of HBPC staff regarding adopting telehealth technology to scale the program. Methods: We collected qualitative data from HBPC staff (physicians, nurses, nurse practitioners, care managers, social workers, and medical coordinators) at a practice in the New York Metropolitan area through 16 semi-structured interviews and 3 focus groups. Data were analyzed thematically using the template analysis approach with Self-Determination Theory concepts (relatedness, competence, and autonomy) as an analytical lens. Results: Four broad themes (work climate, technology impact on staff autonomy, technology impact on competence in providing care, and technology impact on the patient-caregiver-provider relationship) and multiple second-level themes emerged from the analysis. Within the theme of work climate, staff acknowledged the need to scale the program without diminishing effective patient-centered care. Within the theme of technology impact on staff autonomy, participants perceived alerts generated from patients and caregivers using telehealth as a potentially increasing burden and necessitating a rapid response from an already busy staff while increasing ambiguity. Regarding technology impact on competence in providing care, participants noted that it could increase efficiency and enable more informed care provision. Regarding technology impact on the patient-provider relationship, participants noted the opportunity to make caregivers part of the team through telehealth. Staff members, however, were concerned that patients or caregivers might unnecessarily over utilize the technology, and that some visits are more appropriate in-person rather than via telehealth. Conclusions: These findings suggest the importance of taking into account the perspectives of medical professionals regarding telehealth adoption. A proactive approach exploring the benefits and concerns professionals perceive in the adoption of health technology within the HBPC program is likely to facilitate the integration of telehealth innovations. Clinical Trial: Not applicable
Background: Changes noted within the ageing population are physical, cognitive as well as emotional. Social isolation and loneliness are also serious problems that the ageing population may encounter....
Background: Changes noted within the ageing population are physical, cognitive as well as emotional. Social isolation and loneliness are also serious problems that the ageing population may encounter. As technology and applications become more accessible, many basic services, such as though offered by social services, wellbeing organisations and healthcare institutions have invested in the development of supportive devices, services and online interaction. Despite the perceived benefits that these offer, many ageing individuals choose not to engage, or engage in a limited manner. In order to explore this phenomena we developed a theory to describe the condition for engagement. Objective: The main objective of this study was to understand the perceptions of an ageing South African population regarding online services and technologies that could support ageing-in-place. Although the concept of ageing-in-place speaks to a great number of everyday activities, this paper explores aspects of health and wellbeing as being central to ageing in place. Methods: The study used a grounded theory methodology, relying on an iterative and simultaneous process of data collection, coding, category development and data comparisons. Data was collected through qualitative methods, including interviews (13 participants, between the ages of 64 and 85), two participatory workshops (15 participants) and observations. The study focused on Charmaz’s approach to grounded theory, which puts forward the premise that theory or knowledge cannot take shape in a purely objective manner. Instead, theory is constructed through the interaction of the researcher and research participant. Results: Coding and data analysis was supported with Atlas.ti. The study resulted in a substantive theory exploring the process of interaction and engaging factors, through user insights and experiences. The emerging design theory, AUDDE (Ageing User Decision Driven Engagement), explored the elements that support engagement with technology and supportive applications, which could offer access to required health and wellness services. Conclusions: In AUDDE the perceived value of the interaction is a crucial catalyst for engagement. Ageing users continuously make meaning of their experiences, which affects their current and future actions.
Background: More than 15 million Americans provide unpaid care for persons with Alzheimer’s disease or other related dementias (ADRD). While there is good evidence to suggest that caregivers benefit...
Background: More than 15 million Americans provide unpaid care for persons with Alzheimer’s disease or other related dementias (ADRD). While there is good evidence to suggest that caregivers benefit from psychosocial interventions, these have primarily been delivered via face-to-face individual or group-formats. Alternatively, offering eHealth interventions may assist them in providing quality care while remaining in good health. Research to date has generated little knowledge about what app features support ADRD caregivers behaviour change and how developers might optimize features over the long term. Objective: There is an evident knowledge gap in the current landscape of commercially available apps, their integration of behavioural techniques, content focus, and compliance with usability recommendations. This paper systematically reviews and inventories the apps caregivers might typically be exposed to and determines the supports integrated into the apps and their functionality for older adults. Methods: The search strategy was designed to mimic typical online health information-seeking behaviour for adults. Apps were included based on their explicit focus on ADRD caregiver knowledge and skill improvement. Two coders with expertise in behavioural interventions and eHealth pilot tested the data extraction. One coder retained app characteristics and design features. Techniques used to promote change were determined and two questions from the Mobile App Rating Scale were used to assess app credibility and evidence-base. Content topics were evaluated using a thematic framing technique and each app was assessed using a usability heuristic checklist. Results: The search results generated 18 unique apps that met inclusion criteria. Some apps were unavailable and only 8 unique apps were reviewed. Seven apps (88%) did not state which scientific orientation was followed to develop their content. None of the apps made clinical claims of improving caregivers’ and care recipients’ overall health. All apps relied on textual information to disseminate their contents. None of the apps were trialed and evidence-based. Apps included on average 7 out of 10 behavioural change techniques, 5 out of 10 C.A.R.E. features, and 10 out of 18 features on the usability heuristics checklist. Conclusions: Our findings suggest that caregivers are likely to discover apps that are not actually accessible and have low-no evidence base. Apps were found to be largely static, text-based informational resources and few supported behaviours needed to maintain caregivers’ health. While apps may be providing high-volume of information, caregivers must still navigate what resources they need with limited guidance. Finally, the commercial marketplace is addressing some of the major usability elements, but there are many design elements that are not addressed.
Background: Health information, patient education, and self-management (HIA) tools are increasingly being made available to adults with chronic health conditions through eHealth and mHealth modalities...
Background: Health information, patient education, and self-management (HIA) tools are increasingly being made available to adults with chronic health conditions through eHealth and mHealth modalities. However, there is limited information about patient preferences for using specific types of ehealth and mHealth resources and how this differs by age and education. Objective: The objective of this study was to examine how current use of digital information technologies (DITs) and preferred methods for obtaining HIA varies by age and education among middle-aged and older adults with chronic health conditions. Methods: The study used cross-sectional survey data for 9,005 Kaiser Permanente Northern California members aged 45-85 who responded to a mailed/online health survey conducted 2014-2015 and indicated having ≥1 chronic health condition. Bivariate analyses and logistic regression models with weighted data were used to estimate and compare prevalence of DIT use, past-year use of online HIA resources, and preferences for using ehealth, mHealth, and traditional HIA modalities for adults aged 45-65, 66-75, and 76-85. Results: The percentages of adults who used DITs (computers, smartphones, internet, email, apps), had obtained HIA from an online resource in the past year, and who were interested in using eHealth and mHealth modalities for obtaining HIA declined with age group. Within age group, prevalence of DIT use and interest in ehealth and mHealth modalities was lower among adults who had not attended any college compared to college graduates. Differences between the oldest and younger groups and those with lower versus higher education in preferences for eHIA modalities were substantially diminished when we restricted analyses to internet users. Conclusions: Healthcare providers and other organizations serving middle-aged and older adults with chronic health conditions should not assume that patients will want to engage with ehealth and mHealth resources. This is especially true among those who are older and less educated. Since these groups are also less likely to be using digital devices and the internet, increasing their engagement with online HIA and health apps may require both instrumental (e.g., providing DIT devices, internet, and skills training) and social support. As part of patient-centered care, it is important for providers to ascertain their patients’ use of digital technologies and preferences for obtaining health information and patient education rather than routinely referring them to online resources. It is also important for healthcare providers and consumer health organizations to user-test their online resources to make sure they are easy for older and less educated adults to use and to make sure that it remains easy for adults with chronic conditions to obtain health information and patient education using off-line resources.
Background: Little is known about whether off-the-shelf wearable sensor data can contribute to fall risk classification or complement clinical assessment tools like the Resident Assessment Instrument-...
Background: Little is known about whether off-the-shelf wearable sensor data can contribute to fall risk classification or complement clinical assessment tools like the Resident Assessment Instrument-Home Care (RAI-HC). Objective: This study aimed to: 1) investigate the similarities and differences in physical activity, heart rate, and night sleep in a sample of community-dwelling older adults with varying fall histories, using a smart wrist-worn device; and 2) create and evaluate fall risk classification models based on: i) wearable data, ii) the RAI-HC, and iii) the combination of wearable and RAI-HC data. Methods: A prospective, observational study was conducted among three faller groups (G0, G1, G2+) based on the number of previous falls (0, 1, ≥2 falls) in a sample of older community-dwelling adults. The wearable and RAI-HC assessment data were analyzed and utilized to create fall risk classification models, with three supervised machine learning algorithms: logistic regression, decision tree, and random forest (RF). Results: Of 40 participants aged 65-93, 16 (40%) had no previous falls, while 8 (20%) and 16 (40%) had experienced one and multiple (≥2) falls, respectively. Level of physical activity as measured by average daily steps was significantly different between groups (p = .036). In the three faller group classification, RF achieved the best accuracy of 70.0% using both wearable and RAI-HC data. In discriminating between G0 and G1+G2+, RF achieved the best area under the receiver operating characteristic curve of 0.816 based on wearable data only. Discrimination between G0+G1 and G2+ did not result in better classification performance than that between G0 and G1+G2+. Conclusions: Both wearable data and the RAI-HC assessment can contribute to fall risk classification. Future studies in fall risk assessment should consider using wearable technologies to supplement resident assessment instruments.
Background: Background: Hyperkyphosis is common among older adults, and is associated with multiple adverse health outcomes. A kyphosis-specific exercise and posture training program improves hyperkyp...
Background: Background: Hyperkyphosis is common among older adults, and is associated with multiple adverse health outcomes. A kyphosis-specific exercise and posture training program improves hyperkyphosis, but in-person programs are expensive to implement and maintain over longer-periods of time. It is unknown if a technology-based posture training program disseminated through a smartphone is a feasible or acceptable alternative to in-person training among older adults with hyperkyphosis. Objective: Objective: The primary purpose of this study was to assess the feasibility of subject recruitment, retention and adherence, and the acceptability of a technology-based exercise and postural training program disseminated as video clip links and text messaging prompts via a smartphone. The secondary purpose was to explore the potential efficacy of this program on kyphosis, physical function and health-related quality of life in older adults with hyperkyphosis Methods: Methods: This was a 6-week pre-post design pilot trial. We recruited community-dwelling adults ≥65 years with hyperkyphosis ≥40 degrees and access to a smartphone. The intervention had two parts: 1) exercise and posture training via video clips sent to participants daily via text messaging which included 6 weekly video clip links to be viewed on the participant’s smartphone and 2) text messaging prompts to practice good posture. We determined subject recruitment, adherence, retention and acceptability of the intervention. Outcomes included change in kyphometer-measured kyphosis, occiput to wall (OTW), Short Physical Performance Battery (SPPB), Scoliosis Research Society SRS-30, Center for Epidemiological Studies Depression (CESD) and Physical Activity Scale for the Elderly (PASE). Results: Results: 64 potential participants were recruited, 17 participants were enrolled and 12 completed post-intervention testing at 6-weeks. Average age was 71.6 (SD=4.8) years and 53% were female. Median adherence to daily video viewing was 100%, (range 14 to 100) and to practicing good posture three times or more per day was 71%, (range 0 to 100). Qualitative evaluation of acceptability of the intervention revealed the smartphone screen was too small for participants to view the videos well and daily prompts to practice posture were too frequent. Kyphosis, OTW and physical activity significantly improved after the 6-week intervention. Kyphosis decreased by -8.4 (95% CI: -11.8, -5.0) degrees (p<0.001), OTW decreased -1.9 (95% CI: -3.3, -0.7) cm (p=0.007), and physical activity measured by PASE increased 29 (95% CI: 3, 54) points (p=0.03). The health-related quality of life SRS-30 score increased 0.11 (SD=0.19) points, but it was not statistically significant, p=0.09. Conclusions: Conclusions: Technology-based exercise and posture training using video clip viewing and text messaging reminders is feasible and acceptable in a small cohort of older adults with hyperkyphosis. Technology-based exercise and posture training warrants further study as a potential self-management program for age-related hyperkyphosis that may be more easily disseminated than in-person training.