Remote patient monitoring acceptance trends among older adults residing in a frontier state

Determinants of the intention to use mHealth in the future: Evidence from an intervention study of patients with chronic diseases in Slovenia

BACKGROUND

Mobile health (mHealth) implementation is crucial for developing sustainable healthcare systems, but it faces the challenge of user acceptance. Extending traditional acceptance models allows for the cognitive, emotional and social aspects of engaging with mHealth to be captured, creating a more comprehensive understanding of users' intentions to use it in the future. User-centred intervention studies based on users' real experiences with mHealth are essential for accurate assessments and for improving upon studies that rely merely on anticipated mHealth use.

METHODS

An intervention study was conducted with 103 patients with at least one chronic condition (type 2 diabetes and/or arterial hypertension) who had used an mHealth service for three months. They were recruited through purposive sampling at a community health centre in Slovenia. Path analysis was applied to the survey data collected after a three-month testing period to validate an explanatory model with eight hypotheses.

RESULTS

The intensity of mHealth use affected usability, which in turn affected acceptability, the psychosocial impacts of engagement with mHealth and intention for future use. The results showed that the intensity of mHealth use did not affect mHealth acceptability. Likewise, acceptability did not affect the psychosocial impacts of engagement with mHealth or the intention for its future use. Notably, perceptions of the psychosocial impacts of mHealth had no significant effect on the intention for future use.

CONCLUSION

Usability and intensity of use play a central role in the post-intervention usage of mHealth, offering valuable insights for policymakers and healthcare providers involved in the delivery of mHealth-based treatment to patients with chronic diseases.

A systematic review of the impacts of remote patient monitoring (RPM) interventions on safety, adherence, quality-of-life and cost-related outcomes

Due to rapid technological advancements, remote patient monitoring (RPM) technology has gained traction in recent years. While the effects of specific RPM interventions are known, few published reviews examine RPM in the context of care transitions from an inpatient hospital setting to a home environment. In this systematic review, we addressed this gap by examining the impacts of RPM interventions on patient safety, adherence, clinical and quality of life outcomes and cost-related outcomes during care transition from inpatient care to a home setting. We searched five academic databases (PubMed, CINAHL, PsycINFO, Embase and SCOPUS), screened 2606 articles, and included 29 studies from 16 countries. These studies examined seven types of RPM interventions (communication tools, computer-based systems, smartphone applications, web portals, augmented clinical devices with monitoring capabilities, wearables and standard clinical tools for intermittent monitoring). RPM interventions demonstrated positive outcomes in patient safety and adherence. RPM interventions also improved patients' mobility and functional statuses, but the impact on other clinical and quality-of-life measures, such as physical and mental health symptoms, remains inconclusive. In terms of cost-related outcomes, there was a clear downward trend in the risks of hospital admission/readmission, length of stay, number of outpatient visits and non-hospitalisation costs. Future research should explore whether incorporating intervention components with a strong human element alongside the deployment of technology enhances the effectiveness of RPM. The review highlights the need for more economic evaluations and implementation studies that shed light on the facilitators and barriers to adopting RPM interventions in different care settings.

Family caregiver readiness to adopt smart home technology to monitor care-Dependent older adults: A qualitative exploratory study

AIMS

The aim of this study was to explore factors that influence family caregiver readiness to adopt health smart home technology for their care-dependent older adult family member. Health smart homes are designed to remotely monitor the health and wellness of community-dwelling older adults supporting independent living for as long as possible. Accordingly, if the health smart home is deployed into the home of a care-depended older adult, it can potentially support family caregivers by facilitating workforce participation and give piece of mind to the family caregiver who may not live close to the older adult. However, wider adoption of health smart home technologies into the homes of community-older adults is low, and little is known about the factors that influence the readiness of family caregivers to adopt smart home technologies for their care-dependent older adults.

DESIGN

A qualitative Descriptive study design was utilized.

METHODS

Qualitative data were collected between 2019 and 2020 via semi-structured interviews. Thematic analysis of interviews was completed, and data were organized into themes.

RESULTS

Study findings show that caregiver readiness (N = 10) to adopt smart home technology to monitor older adult family members were influenced by five primary themes including a 'big brother effect', 'framing for acceptance', 'data privacy', 'burden' and 'cost.'

CONCLUSION

Family caregivers were open to adopting smart home technology to support the independent living of their older adult family members. However, the readiness of family caregivers was inextricably linked to the older adults' readiness for smart home adoption. The family caregiver's primary concern was on how they could frame the idea of the smart home to overcome what they viewed as hesitancy to adopt in the older adult. The findings suggest that family caregivers endeavour to balance the hesitancy in their older adult family members with the potential benefits of smart home technology.

IMPACT

Family caregivers could benefit if their care-dependent older adults adopt smart home technology. Recognizing the role of caregivers and their perspectives on using smart home technologies with their care-dependents is critical to the meaningful design, use and adoption.

A study on community older people's willingness to use smart home-an extended technology acceptance model with intergenerational relationships

Introduction

Despite the potential of smart home technology to promote sustainable lifestyles, the adoption rate among older adults remains relatively low. This study aims to investigate the influence of intergenerational relationships on the acceptance of smart home services among seniors.

Methods

A survey was conducted among 298 older adults in China, and data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). Ten predictor variables were examined to assess their impact on the willingness to use smart home services.

Results

Intergenerational relationships significantly influenced the utilization of smart home services among older adults. Specifically, intergenerational instrumental support had a direct positive effect on the behavioral intention to use smart homes. Additionally, intergenerational emotional and financial support affected life satisfaction, which subsequently influenced the behavioral intention to use smart homes.

Discussion

The assistance and guidance provided by younger generations play a crucial role in shaping the willingness of older adults to adopt smart home technology. Intergenerational support can contribute positively to enabling aging individuals to age in place through the utilization of technology.

Exploring Older Adults' Willingness to Install Home Surveil-Lance Systems in Taiwan: Factors and Privacy Concerns

Taiwan has a rapidly increasing aging population with a considerably high life expectancy rate, which poses challenges for healthcare and medical systems. This study examines three key factors: safety concerns, family expectations, and privacy concerns, and their influence on surveillance system installation decisions. A cross-sectional study was conducted involving a group of physically active older adults in Taiwan, using a questionnaire to collect data on the reasons for in-stalling a surveillance system and preferences for three image privacy protection techniques: blurring the face and transformation to a 2D or 3D character. The study concluded that while safety concerns and family expectations facilitate the adoption of surveillance systems, privacy concerns serve as a significant barrier. Furthermore, older adults showed a clear preference for avatar-based privacy protection methods over simpler techniques, such as blurring. The outcomes of this research will be instrumental in shaping the development of privacy-conscious home surveillance technologies, adeptly balancing safety and privacy. This understanding can pave the way for technology design that skillfully balances privacy concerns with remote monitoring quality, thereby enhancing the well-being and safety of this demographic. These results could possibly be extended to other demographics as well.

The technological intervention in e-health management: evidence from Thailand

Purpose

The e-health services came up as an effective tool to mitigate effects of COVID-19 and following social distance norms. This study highlighted an issue of contentious usage intentions of e-health services among Thai older citizens. This study aims to examine the relationship of social influence (SI), information quality (IQ) and the digital literacy (DL) to contentious usage intentions.

Design/methodology/approach

This study follows quantitative techniques, and the sample size is 140 to analyze, that is collected from the older Thai citizens. The convenient sampling technique was used to collect the data and the items were measured by using a five-point Likert scale.

Findings

The findings of this study are having mixed results. The effect of DL and satisfaction (SAT) on continuous usage intention (CUI) is significant. The effect of IQ and SI on CUI is non-significant. The effect of IQ and SI on SAT is significant. Further, the mediating effect of SAT between IQ and CUI is non-significant. However, the mediating effect of SAT between SI and CUI is significant.

Originality/value

This study contributes to knowledge by empirical testing of DL and usage of the medicine. Furthermore, to the best of the authors’ knowledge, this study is one of the rare studies that incorporate technological intervention for drug usage intentions.

Exploring Challenges and Strategies in Partnering With Community-Based Organizations to Advance Intervention Development and Implementation With Older Adults

Minoritized older adults face multiple health inequities and disparities, but are less likely to benefit from evidence-based health care interventions. With the increasing diversity of the U.S. aging population, there is a great promise for gerontology researchers to partner with racial/ethnic minority organizations and underrepresented communities to develop and implement evidence-based health interventions. Community-Based Participatory Research and Implementation Science offer guidance and strategies for researchers to develop and sustain community partnerships. However, researchers partnering with community organizations continue to face challenges in these collaborations, study outcomes, and sustainability. This may be especially true for those junior in their career trajectory or new to community-engaged research. The purpose of this forum article is to detail critical challenges that can affect gerontology researcher-community partnerships and relationships from the perspective of researchers. Seven challenges (pre- or mid-intervention design, implementation, and postimplementation phases) described within the Equity-focused Implementation Research for health programs framework are identified and discussed. Potential solutions are also presented. Planning for potential obstacles of the researcher-community partnerships can inform innovative solutions that will facilitate successful partnerships, thereby promoting the advancement of collaborative research between academic institutions and community organizations to improve older adult health outcomes.

Understanding Students’ Acceptance and Usage Behaviors of Online Learning in Mandatory Contexts: A Three-Wave Longitudinal Study during the COVID-19 Pandemic

Online learning has been mandatorily adopted in many countries due to the closure of educational institutions caused by the COVID-19 pandemic. However, antecedents of the acceptance and continuance of online learning in such a situation and their changing role over time have not been well understood. This study proposed and empirically tested a longitudinal acceptance model of online learning by integrating the technology acceptance model (TAM) with the task–technology fit (TTF). Data were collected using a three-wave longitudinal survey from 251 Chinese college students after the outbreak of the COVID-19 pandemic. The results showed that most hypothesized relationships in the proposed model were supported and remained across the three-time stages, while the effects of perceived ease of use on perceived usefulness and behavioral intention changed over time. In addition, students’ perceptions at previous stages had little impact on perceptions at subsequent stages, except for perceived usefulness and behavioral intention. Our study demonstrates that the integrated model of TAM and TTF could be an effective tool to understand students’ acceptance of online learning across different time stages in a mandatory setting and that longitudinal design could be applicable to examine the changing mechanism of the acceptance and continuance use of online learning over time.

Creation of an Evidence-Based Implementation Framework for Digital Health Technology in the Intensive Care Unit: Qualitative Study

Background

Digital health technologies such as continuous remote monitoring and artificial intelligence–driven clinical decision support systems could improve clinical outcomes in intensive care medicine. However, comprehensive evidence and guidelines for the successful implementation of digital health technologies into specific clinical settings such as the intensive care unit (ICU) are scarce. We evaluated the implementation of a remote patient monitoring platform and derived a framework proposal for the implementation of digital health technology in an ICU.

Objective

This study aims to investigate barriers and facilitators to the implementation of a remote patient monitoring technology and to develop a proposal for an implementation framework for digital health technology in the ICU.

Methods

This study was conducted from May 2018 to March 2020 during the implementation of a tablet computer–based remote patient monitoring system. The system was installed in the ICU of a large German university hospital as a supplementary monitoring device. Following a hybrid qualitative approach with inductive and deductive elements, we used the Consolidated Framework for Implementation Research and the Expert Recommendations for Implementing Change to analyze the transcripts of 7 semistructured interviews with clinical ICU stakeholders and descriptive questionnaire data. The results of the qualitative analysis, together with the findings from informal meetings, field observations, and previous explorations, provided the basis for the derivation of the proposed framework.

Results

This study revealed an insufficient implementation process due to lack of staff engagement and few perceived benefits from the novel solution. Further implementation barriers were the high staff presence and monitoring coverage in the ICU. The implementation framework includes strategies to be applied before and during implementation, targeting the implementation setting by involving all ICU stakeholders, assessing the intervention’s adaptability, facilitating the implementation process, and maintaining a vital feedback culture. Setting up a unit responsible for implementation, considering the guidance of an implementation advisor, and building on existing institutional capacities could improve the institutional context of implementation projects in the ICU.

Conclusions

Implementation of digital health in the ICU should involve a thorough preimplementation assessment of the ICU’s need for innovation and its readiness to change, as well as an ongoing evaluation of the implementation conditions. Involvement of all stakeholders, transparent communication, and continuous feedback in an equal atmosphere are essential, but leadership roles must be clearly defined and competently filled. Our proposed framework may guide health care providers with concrete, evidence-based, and step-by-step recommendations for implementation practice, facilitating the introduction of digital health in intensive care.

Trial Registration

ClinicalTrials.gov NCT03514173; https://clinicaltrials.gov/ct2/show/NCT03514173

A longitudinal examination of tablet self-management technology acceptance by patients with chronic diseases: Integrating perceived hand function, perceived visual function, and perceived home space adequacy with the TAM and TPB

BACKGROUND

Health information technologies (HITs) are increasingly being used to support the self-management of chronic diseases. However, patients' initial or continued acceptance of such technologies is not always achieved.

OBJECTIVE

The aim of this study was to develop a theory-driven HIT acceptance model to examine factors affecting acceptance of HIT (measured by behavioral intention; BI) for disease self-management among patients with chronic diseases, in which we also focused on three additional, previously unexplored factors related to perceived hand function (PHF), perceived visual function (PVF), and perceived space adequacy (PSA) and a longitudinal scrutinization of changes in the effects of these factors on acceptance over time.

METHODS

The theoretical basis of our acceptance model was drawn from the technology acceptance model and the theory of planned behavior. The model was further extended by including patients' PHF, PVF (related to patients with chronic diseases who are mostly elderly), and PSA (related to the patients' home environment). The model was tested in the context of type 2 diabetes and hypertension self-management via a touchscreen tablet-based system over a 24-week period. A questionnaire was administered at four time points (baseline and 8, 16, and 24 weeks after implementation) to collect data from 151 patients with coexisting type 2 diabetes and hypertension. We tested the model at each time point using partial least squares structural equation modeling.

RESULTS

Perceived usefulness of the self-management system influenced BI directly at 8 and 24 weeks and indirectly at 8, 16, and 24 weeks. Perceived ease of use indirectly affected BI at 8, 16, and 24 weeks. Attitude directly affected BI at 8, 16, and 24 weeks. Perceived behavioral control directly influenced BI at baseline and 8 and 16 weeks. Subjective norms indirectly influenced BI at 8, 16, and 24 weeks. PHF and PVF indirectly influenced BI over the entire study period. PSA influenced BI directly at 16 weeks and indirectly at 8, 16, and 24 weeks.

CONCLUSION

The effects of the proposed factors in our model on patient-focused HIT acceptance changed over a longer time period, emphasizing the importance of further investigation of the longitudinal mechanisms influencing technology acceptance behavior. It is recommended that healthcare practitioners consider such changes when implementing comparable technologies. Moreover, beyond technology attributes, the characteristics, needs, and limitations of older adults and elderly patient users and their home environments should also be considered in the design and implementation of patient-focused HIT systems for chronic disease self-management at home.

Older Adults' and Clinicians' Perspectives on a Smart Health Platform for the Aging Population: Design and Evaluation Study

Background

Over recent years, interest in the development of smart health technologies aimed at supporting independent living for older populations has increased. The integration of innovative technologies, such as the Internet of Things, wearable technologies, artificial intelligence, and ambient-assisted living applications, represents a valuable solution for this scope. Designing such an integrated system requires addressing several aspects (eg, equipment selection, data management, analytics, costs, and users’ needs) and involving different areas of expertise (eg, medical science, service design, biomedical and computer engineering).

Objective

The objective of this study is 2-fold; we aimed to design the functionalities of a smart health platform addressing 5 chronic conditions prevalent in the older population (ie, hearing loss, cardiovascular diseases, cognitive impairments, mental health problems, and balance disorders) by considering both older adults’ and clinicians’ perspectives and to evaluate the identified smart health platform functionalities with a small group of older adults.

Methods

Overall, 24 older adults (aged >65 years) and 118 clinicians were interviewed through focus group activities and web-based questionnaires to elicit the smart health platform requirements. Considering the elicited requirements, the main functionalities of smart health platform were designed. Then, a focus group involving 6 older adults was conducted to evaluate the proposed solution in terms of usefulness, credibility, desirability, and learnability.

Results

Eight main functionalities were identified and assessed—cognitive training and hearing training (usefulness: 6/6, 100%; credibility: 6/6, 100%; desirability: 6/6, 100%; learnability: 6/6, 100%), monitoring of physiological parameters (usefulness: 6/6, 100%; credibility: 6/6, 100%; desirability: 6/6, 100%; learnability: 5/6, 83%), physical training (usefulness: 6/6, 100%; credibility: 6/6, 100%; desirability: 5/6, 83%; learnability: 2/6, 33%), psychoeducational intervention (usefulness: 6/6, 100%; credibility: 6/6, 100%; desirability: 4/6, 67%; learnability: 2/6, 33%), mood monitoring (usefulness: 4/6, 67%; credibility: 4/6, 67%; desirability: 3/6, 50%; learnability: 5/6, 50%), diet plan (usefulness: 5/6, 83%; credibility: 4/6, 67%; desirability: 1/6, 17%; learnability: 2/6, 33%), and environment monitoring and adjustment (usefulness: 1/6, 17%; credibility: 1/6, 17%; desirability: 0/6, 0%; learnability: 0/6, 0%). Most of them were highly appreciated by older participants, with the only exception being environment monitoring and adjustment. The results showed that the proposed functionalities met the needs and expectations of users (eg, improved self-management of patients’ disease and enhanced patient safety). However, some aspects need to be addressed (eg, technical and privacy issues).

Conclusions

The presented smart health platform functionalities seem to be able to meet older adults’ needs and desires to enhance their self-awareness and self-management of their medical condition, encourage healthy and independent living, and provide evidence-based support for clinicians’ decision-making. Further research with a larger and more heterogeneous pool of stakeholders in terms of demographics and clinical conditions is needed to assess system acceptability and overall user experience in free-living conditions.

Seniors' adoption of digital devices and virtual event platforms in Singapore during Covid-19

In Singapore, with the nationwide implementation of Covid-19 physical restrictions and safe management measures (SMMs) in place because of the pandemic, the seniors' regular routines and daily social activities have been disrupted. Prior research on seniors' adoption of digital technologies has primarily focused on health-related purposes such as nutrition and exercise and managing old-age related diseases. However, there is limited research done to understand how seniors use digital technologies for other purposes, such as social networks or leisure activities, that can help seniors socialise and reduce loneliness despite ongoing SMMs and restrictions on social distancing and physical interactions because of the Covid-19 pandemic. In particular, the use of virtual event platforms can make it easier for seniors to communicate and socialise with their peers, thus keeping social isolation and loneliness at bay. In this paper, we discuss seniors' relationship with technology, guided by the social exchange theory. We also share the methodological framework that guided this small-scale study on the use of virtual event platforms, along with the research instruments and measurements required for data collection. The research findings of this study, conducted with 144 respondents aged 60 years old and above, are discussed and further analysed with their theoretical contributions and implications for practice.

Mixed methods protocol to examine the acceptability and clinical characteristics of a remote monitoring programme for delivery of COVID-19 care, among healthcare staff and patients

INTRODUCTION

The use of remote monitoring technology to manage the care of patients with COVID-19 has been implemented to help reduce the burden placed on healthcare systems during the pandemic and protect the well-being of both staff and patients. Remote monitoring allows patients to record their signs and symptoms remotely (eg, while self-isolating at home) rather than requiring hospitalisation. Healthcare staff can, therefore, continually monitor their symptoms and be notified when the patient is showing signs of clinical deterioration. However, given the recency of the COVID-19 outbreak, there is a lack of research regarding the acceptance of remote monitoring interventions to manage COVID-19. This study will aim to evaluate the use of remote monitoring for managing COVID-19 cases from the perspective of both the patient and healthcare staff.

METHODS AND ANALYSIS

Discharged patients from a large urban teaching hospital in Ireland, who have undergone remote monitoring for COVID-19, will be recruited to take part in a cross-sectional study consisting of a quantitative survey and a qualitative interview. A mixed methods design will be used to understand the experiences of remote monitoring from the perspective of the patient. Healthcare staff who have been involved in the provision of remote monitoring of patients with COVID-19 will be recruited to take part in a qualitative interview to understand their experiences with the process. Structural equation modelling will be used to examine the acceptance of the remote monitoring technology. Latent class analysis will be used to identify COVID-19 symptom profiles. Interview data will be examined using thematic analysis.

ETHICS AND DISSEMINATION

Ethical approval has been granted by the ethical review boards at University College Dublin and the National Research Ethics Committee for COVID-19-related Research. Findings will be disseminated via publications in scientific journals, policy briefs, short reports and social media.

Patient Perspectives on Innovative Telemonitoring Enhanced Care Program for Chronic Heart Failure (ITEC-CHF): Usability Study

Background

Telemonitoring enables care providers to remotely support outpatients in self-managing chronic heart failure (CHF), but little is known about the usability and patients’ willingness to engage with this technology.

Objective

This study aims to evaluate feedback from patients with CHF following participation in the Innovative Telemonitoring Enhanced Care program for CHF (ITEC-CHF) study.

Methods

The telemonitoring intervention consisted of three components: remote weight monitoring, structured telephone support, and nurse-led collaborative care. Participants were provided with electronic weighing scales (W550; ForaCare), and a computer tablet (Galaxy Tab A; Samsung). They were asked to weigh themselves on the provided scales daily. Telemonitoring was integrated with a personal assistance call service and a nurse care service according to their workflows in usual care. Feedback on the usability of ITEC-CHF was collected via survey from study participants following 6 months of receiving telemonitoring care for their body weight. Survey responses were provided on a 5-point Likert scale and through open-ended questions to determine participants’ perceived benefits and barriers to using ITEC-CHF.

Results

A total of 67 participants (49/67, 73% male), with a mean age of 69.8 (SD 12.4) years completed the survey. The majority of participants agreed or strongly agreed that the ITEC-CHF program was easy to use (61/67, 91%), easy to navigate (51/65, 78%), useful (59/65, 91%), and made them feel more confident in managing their weight (57/67, 85%). Themes related to participants’ perceptions of telemonitoring included increased support for early intervention of clinical deterioration, improved compliance to daily weighing, a sense of reassurance, and improved self-care and accountability, among others.

Conclusions

ITEC-CHF was rated highly on usability and was well accepted by users as part of their routine self-management activities. Participants were willing to use telemonitoring because they perceived a broad spectrum of benefits for CHF management.

Trial Registration

Australian New Zealand Clinical Trial Registry ID ACTRN 12614000916640; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=366691.

Human Factors and Requirements of People with Cognitive Impairment, Their Caregivers, and Healthcare Professionals for mHealth Apps Including Reminders, Games, and Geolocation Tracking: A Survey-Questionnaire Study

Background:

Mobile Health (mHealth) apps can delay the cognitive decline of people with dementia (PwD), by providing both objective assessment and cognitive enhancement.

Objective:

This patient involvement survey aims to explore human factors, needs and requirements of PwD, their caregivers, and Healthcare Professionals (HCPs) with respect to supportive and interactive mHealth apps, such as brain games, medication reminders, and geolocation trackers through a constructive questionnaire.

Methods:

Following the principles of user-centered design to involve end-users in design we constructed a questionnaire, containing both open-ended and closed-ended questions as well as multiple choice and Likert scale, in order to investigate the specific requirements and preferences for mHealth apps. We recruited 48 participants including people with cognitive impairment (n = 15), caregivers (n = 16), and HCPs (n = 17) and administered the questionnaire.

Results:

All participants are likely to use mHealth apps, with the primary desired features being the improvement of memory and cognition, assistance on medication treatment, and perceived ease to use. HCPs, caregivers, and PwD consider brain games as an important technology-based, non-pharmaceutical intervention. Both caregivers and patients are willing to use a medication reminder app frequently. Finally, caregivers are worried about the patient wandering. Therefore, global positioning system tracking would be particularly important to them. On the other hand, patients are concerned about their privacy, but are still willing to use a geolocation app for cases of emergency.

Conclusion:

This research contributes to mHealth app design and potential adoption. All three groups agree that mHealth services could facilitate care and ameliorate behavioral and cognitive disturbances of patients.

Wearable Devices for Assessing Function in Alzheimer's Disease: A European Public Involvement Activity About the Features and Preferences of Patients and Caregivers

Background: Alzheimer's Disease (AD) impairs the ability to carry out daily activities, reduces independence and quality of life and increases caregiver burden. Our understanding of functional decline has traditionally relied on reports by family and caregivers, which are subjective and vulnerable to recall bias. The Internet of Things (IoT) and wearable sensor technologies promise to provide objective, affordable, and reliable means for monitoring and understanding function. However, human factors for its acceptance are relatively unexplored.

Objective: The Public Involvement (PI) activity presented in this paper aims to capture the preferences, priorities and concerns of people with AD and their caregivers for using monitoring wearables. Their feedback will drive device selection for clinical research, starting with the study of the RADAR-AD project.

Method: The PI activity involved the Patient Advisory Board (PAB) of the RADAR-AD project, comprised of people with dementia across Europe and their caregivers (11 and 10, respectively). A set of four devices that optimally represent various combinations of aspects and features from the variety of currently available wearables (e.g., weight, size, comfort, battery life, screen types, water-resistance, and metrics) was presented and experienced hands-on. Afterwards, sets of cards were used to rate and rank devices and features and freely discuss preferences.

Results: Overall, the PAB was willing to accept and incorporate devices into their daily lives. For the presented devices, the aspects most important to them included comfort, convenience and affordability. For devices in general, the features they prioritized were appearance/style, battery life and water resistance, followed by price, having an emergency button and a screen with metrics. The metrics valuable to them included activity levels and heart rate, followed by respiration rate, sleep quality and distance. Some concerns were the potential complexity, forgetting to charge the device, the potential stigma and data privacy.

Conclusions: The PI activity explored the preferences, priorities and concerns of the PAB, a group of people with dementia and caregivers across Europe, regarding devices for monitoring function and decline, after a hands-on experience and explanation. They highlighted some expected aspects, metrics and features (e.g., comfort and convenience), but also some less expected (e.g., screen with metrics).

Are we ready for artificial intelligence health monitoring in elder care?

Background

The world is experiencing a dramatic increase in the aging population, challenging the sustainability of traditional care models that have relied on in-person monitoring. This debate article discusses whether artificial intelligence health monitoring may be suitable enhancement or replacement for elder care.

Main text

Internationally, as life expectancy continues to rise, many countries are facing a severe shortage of direct care workers. The health workforce is aging, and replacement remains a challenge. Artificial intelligence health monitoring technologies may play a novel and significant role in filling the human resource gaps in caring for older adults by complementing current care provision, reducing the burden on family caregivers, and improving the quality of care. Nonetheless, opportunities brought on by these emerging technologies raise ethical questions that must be addressed to ensure that these automated systems can truly enhance care and health outcomes for older adults. This debate article explores some ethical dimensions of using automated health monitoring technologies. It argues that, in order for these health monitoring technologies to fulfill the wishes of older adults to age in place and also to empower them and improve their quality of life, we need deep knowledge of how stakeholders may balance their considerations of relational care, safety, and privacy.

Conclusion

It is only when we design artificial intelligence health monitoring technologies with intersecting clinical and ethical factors in mind that the resulting systems will enhance productive relational care, facilitate independent living, promote older adults’ health outcomes, and minimize waste.

Bridging the Digital Divide for Older Adults via Observational Training: Effects of Model Identity from a Generational Perspective

The proliferation of technology offers potential solutions for enhancing the well-being of older adults. However, older adults often have low digital literacy and are disengaged from the digital world. With age-appropriate training, older adults are expected to acquire a wide range of technological skills and bridge the digital divide. Through the lens of social cognitive theory, this study aims to investigate the effectiveness of observational training through behavior modeling in enhancing technology acceptance in older adults. The moderating effects of model identity on training outcomes from a generational perspective are examined. An empirical training experiment was completed with 59 community-dwelling older adults. Training outcomes were measured using cognitive knowledge, affective variables, and meta-cognition. The results ascertain the effectiveness of observational training in improving their technological knowledge, self-efficacy, outcome expectations, and sense of social connectedness when using technologies. From a generational perspective, the older adult behavior model is more effective than the young or child behavior models in increasing self-efficacy and willingness to use technology. The model identity further enhances the positive outcomes of training. The results of this study contribute to designing educational interventions to bridge the digital divide.

Smart Environments and Social Robots for Age-Friendly Integrated Care Services

The world is facing major societal challenges because of an aging population that is putting increasing pressure on the sustainability of care. While demand for care and social services is steadily increasing, the supply is constrained by the decreasing workforce. The development of smart, physical, social and age-friendly environments is identified by World Health Organization (WHO) as a key intervention point for enabling older adults, enabling them to remain as much possible in their residences, delay institutionalization, and ultimately, improve quality of life. In this study, we survey smart environments, machine learning and robot assistive technologies that can offer support for the independent living of older adults and provide age-friendly care services. We describe two examples of integrated care services that are using assistive technologies in innovative ways to assess and deliver of timely interventions for polypharmacy management and for social and cognitive activity support in older adults. We describe the architectural views of these services, focusing on details about technology usage, end-user interaction flows and data models that are developed or enhanced to achieve the envisioned objective of healthier, safer, more independent and socially connected older people.

A re-organizing biosurveillance framework based on fog and mobile edge computing

Biological threats are becoming a serious security issue for many countries across the world. Effective biosurveillance systems can primarily support appropriate responses to biological threats and consequently save human lives. Nevertheless, biosurveillance systems are costly to implement and hard to operate. Furthermore, they rely on static infrastructures that might not cope with the evolving dynamics of the monitored environment. In this paper, we present a reorganizing biosurveillance framework for the detection and localization of biological threats with fog and mobile edge computing support. In the proposed framework, a hierarchy of fog nodes are responsible for aggregating monitoring data within their regions and detecting potential threats. Although fog nodes are deployed on a fixed base station infrastructure, the framework provides an innovative technique for reorganizing the monitored environment structure to adapt to the evolving environmental conditions and to overcome the limitations of the static base station infrastructure. Evaluation results illustrate the ability of the framework to localize biological threats and detect infected areas. Moreover, the results show the effectiveness of the reorganization mechanisms in adjusting the environment structure to cope with the highly dynamic environment.

Identifying risk and protective factors related to depressive symptoms among Northern Plains American Indian women cancer survivors

Cancer is the leading cause of death among American Indian and Alaska Native (AIAN) women, and depressive symptoms have been linked to higher mortality, but research on depressive symptoms among AIAN cancer patients has been scant. The purpose of this exploratory study was, using the Framework of Historical Oppression, Resilience, and Transcendence, to examine risk and protective factors related to depressive symptoms in American Indian (AI) women cancer survivors. We examined the relationships of adverse childhood experiences (ACE), perceived health status, resilience, and social support with depressive symptoms in Northern Plains AI women cancer survivors. We used a cross-sectional design with purposive sampling of 73 female cancer survivors (aged 18 years or older) between June 2014 and February 2015. Hierarchical multiple regression was used to test three sets of variables in relation to depressive symptoms: (1) sociodemographics, (2) risk factors (ACE and perceived health), and (3) protective factors (psychological resilience and social support). Approximately 47 percent of participants had probable depressive symptoms. Depressive symptoms were inversely associated with perceived health, psychological resilience, and social support. These results support bolstering existing social support among AI cancer patients and survivors as well as prevention and intervention efforts that strengthen resilience.

Development of the Older Adult Prescription Drug Assessment Questionnaire for Case Workers

Instruments assessing geriatric case managers’ perceptions of prescription abuse are limited. Based on a review of current literature and pilot testing feedback, 22 items were initially assembled to form an older adult Prescription Drug Assessment Questionnaire (PDAQ). Case managers ( N = 161) at an older adult agency located in a Midwestern state were surveyed using the instrument. Data were subjected to exploratory factor analysis using principal axis factoring (PAF) and Promax rotation, and Horn’s parallel analysis determined the number of extracted factors. PAF generated a final 11-item three-factor model accounting for 51% of total variance explained: Standard Assessment (Factor 1; four items; ∞ = .83), Assessment Belief (Factor 2; three items; ∞ = .74), and Problem Scope (Factor 3; four items; ∞ = .62). The older adult PDAQ is a brief, data-driven instrument with acceptable psychometric properties for assessing perceptions of prescription drug abuse and misuse assessment and counseling.

Can Digital Technology Enhance Social Connectedness Among Older Adults? A Feasibility Study

This study examined the feasibility of a novel communication technology to enhance social connectedness among older adults in residential care. Research suggests that technology can create opportunities for social connectedness, helping alleviate social isolation and loneliness. Studies on implementation and feasibility of such technological interventions, particularly among frail and institutionalized older adults, are scant. Data were gathered in a 3-month deployment with 12 older adults, including semistructured interviews with participants and relatives/friends, psychometric scales, field observations, and usability tests. Data were analyzed with qualitative profiling, thematic analysis, and Friedman tests. The technology was a feasible communication tool, although requiring an adaptation period. Use increased perceived social interaction with ties, but increased social connectedness (meaningful social interaction) was only reported by participants with geographically distant relatives. Sense of well-being and confidence with technology was enhanced, but negative effects were also observed. Findings are useful for researchers and practitioners interested in technological interventions.

Wearable IoT sensor based healthcare system for identifying and controlling chikungunya virus

Chikungunya is a vector borne disease that spreads quickly in geographically affected areas. Its outbreak results in acute illness that may lead to chronic phase. Chikungunya virus (CHV) diagnosis solutions are not easily accessible and affordable in developing countries. Also old approaches are very slow in identifying and controlling the spread of CHV outbreak. The sudden development and advancement of wearable internet of things (IoT) sensors, fog computing, mobile technology, cloud computing and better internet coverage have enhanced the quality of remote healthcare services. IoT assisted fog health monitoring system can be used to identify possibly infected users from CHV in an early phase of their illness so that the outbreak of CHV can be controlled. Fog computing provides many benefits such as low latency, minimum response time, high mobility, enhanced service quality, location awareness and notification service itself at the edge of the network. In this paper, IoT and fog based healthcare system is proposed to identify and control the outbreak of CHV. Fuzzy-C means (FCM) is used to diagnose the possibly infected users and immediately generate diagnostic and emergency alerts to users from fog layer. Furthermore on cloud server, social network analysis (SNA) is used to represent the state of CHV outbreak. Outbreak role index is calculated from SNA graph which represents the probability of any user to receive or spread the infection. It also generates warning alerts to government and healthcare agencies to control the outbreak of CHV in risk prone or infected regions. The experimental results highlight the advantages of using both fog computing and cloud computing services together for achieving network bandwidth efficiency, high quality of service and minimum response time in generation of real time notification as compared to a cloud only model.

Predicting personal self-care in informal caregivers

Caregiver research often focuses on negative health outcomes, yet little is known about the self-care practices of caregivers. The present study investigates self-care practices among family caregivers and the relationships between personal self-care, perceived stress, and other health variables. Data were collected from informal caregivers through self-administered Internet and paper surveys that included the Medical Outcomes Study Short Form 36-item Health Survey, Perceived Stress Scale, and Self-Care Practices Scale. Personal self-care was most strongly associated with emotional well-being, pain, perceived stress, and general health. The relevance of study findings to strengthening family caregiver programs and future research is discussed.

Temporal Informative Analysis in Smart-ICU Monitoring: M-HealthCare Perspective

The rapid introduction of Internet of Things (IoT) Technology has boosted the service deliverance aspects of health sector in terms of m-health, and remote patient monitoring. IoT Technology is not only capable of sensing the acute details of sensitive events from wider perspectives, but it also provides a means to deliver services in time sensitive and efficient manner. Henceforth, IoT Technology has been efficiently adopted in different fields of the healthcare domain. In this paper, a framework for IoT based patient monitoring in Intensive Care Unit (ICU) is presented to enhance the deliverance of curative services. Though ICUs remained a center of attraction for high quality care among researchers, still number of studies have depicted the vulnerability to a patient's life during ICU stay. The work presented in this study addresses such concerns in terms of efficient monitoring of various events (and anomalies) with temporal associations, followed by time sensitive alert generation procedure. In order to validate the system, it was deployed in 3 ICU room facilities for 30 days in which nearly 81 patients were monitored during their ICU stay. The results obtained after implementation depicts that IoT equipped ICUs are more efficient in monitoring sensitive events as compared to manual monitoring and traditional Tele-ICU monitoring. Moreover, the adopted methodology for alert generation with information presentation further enhances the utility of the system.

A Smart-Home System to Unobtrusively and Continuously Assess Loneliness in Older Adults

Loneliness is a common condition in older adults and is associated with increased morbidity and mortality, decreased sleep quality, and increased risk of cognitive decline. Assessing loneliness in older adults is challenging due to the negative desirability biases associated with being lonely. Thus, it is necessary to develop more objective techniques to assess loneliness in older adults. In this paper, we describe a system to measure loneliness by assessing in-home behavior using wireless motion and contact sensors, phone monitors, and computer software as well as algorithms developed to assess key behaviors of interest. We then present results showing the accuracy of the system in detecting loneliness in a longitudinal study of 16 older adults who agreed to have the sensor platform installed in their own homes for up to 8 months. We show that loneliness is significantly associated with both time out-of-home (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} }{}$ {\beta } = -0.88$ \end{document} and \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} }{}$p<0.01$ \end{document}) and number of computer sessions (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} }{}$ {\beta } = 0.78$ \end{document} and \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} }{}$p<0.05$ \end{document}). \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} }{}$R^{2}$ \end{document} for the model was 0.35. We also show the model’s ability to predict out-of-sample loneliness, demonstrating that the correlation between true loneliness and predicted out-of-sample loneliness is 0.48. When compared with the University of California at Los Angeles loneliness score, the normalized mean absolute error of the predicted loneliness scores was 0.81 and the normalized root mean squared error was 0.91. These results represent first steps toward an unobtrusive, objective method for the prediction of loneliness among older adults, and mark the first time multiple objective behavioral measures that have been related to this key health outcome.

Feasibility and Acceptability of Smartphone Assessment in Older Adults with Cognitive and Emotional Difficulties

OBJECTIVES

Ecological momentary assessment (EMA) has several advantages in clinical research yet little is known about the feasibility of collecting EMA data with mobile technologies in older adults, particularly those with emotional or cognitive difficulties. The aim of this feasibility study was to assess perceived acceptability, adherence rates, and reasons for non-adherence to smartphone-based EMA.

METHOD

At two sites, participants (n=103) aged 65 years or older with a DSM-IV-defined anxiety or depressive disorder and cognitive concerns responded three times daily to smartphone-based EMA questions assessing clinical outcomes for two 10-day periods. Quantitative and qualitative measures assessed acceptability, adherence, and reasons for non-adherence following both 10-day EMA periods.

RESULTS

Participants were moderately satisfied with and comfortable using smartphone-based EMA. Overall, 76% of participants completed surveys on ≥10 of the 20 assessment days, and 70% of participants completed at least 30% of the total surveys. Reasons for non-adherence included technical (malfunction), logistical (competing demands), physiological (hearing difficulties), and cognitive (forgetting) issues.

DISCUSSION

Smartphone-based EMA is feasible in older adults with cognitive and emotional difficulties. EMA tools should be responsive to the needs and preferences of participants to ensure adequate acceptability and adherence in this population. Our findings can inform the design, development, and implementation of mobile technologies in older adults in research and clinical contexts.

Remote Health Monitoring for Older Adults and Those with Heart Failure: Adherence and System Usability

BACKGROUND

Remote health monitoring technology has been suggested as part of an early intervention and prevention care model. Older adults with a chronic health condition have been shown to benefit from remote monitoring but often have challenges with complex technology. The current study reports on the usability of and adherence with an integrated, real-time monitoring system over an extended period of time by older adults with and without a chronic health condition.

MATERIALS AND METHODS

Older adults 55 years of age and over with and without heart failure participated in a study in which a telehealth system was used for 6 months each. The system consisted of a wireless wristwatch-based monitoring device that continuously collected temperature and motion data. Other health information was collected daily using a weight scale, blood pressure cuff, and tablet that participants used for health surveys. Data were automatically analyzed and summarized by the system and presented to study nurses.

RESULTS

Forty-one older adults participated. Seventy-one percent of surveys, 75% of blood pressure readings, and 81% of daily weight measurements were taken. Participants wore the watch monitor 77% of the overall 24/7 time requested. The weight scale had the highest usability rating in both groups. The groups did not otherwise differ on device usage.

CONCLUSIONS

The findings indicate that a health monitoring system designed for older adults can and will be used for an extended period of time and may help older adults with chronic conditions reside longer in their own homes in partnership with the healthcare system.

Evolution of technology perceptions over time

Purpose

– As the information society further develops, electronic services are created and physical distribution networks become sparse, it is important to analyse the determinants that inhibit or facilitate the ability to use these services. By focusing on the perceived behavioural control of computers, the purpose of this paper is to analyse how perceived physical restrictions, computer anxiety and ease of use influence the perceptions of control.

Design/methodology/approach

– The authors examined older consumers (aged 60-79) in two cross-sectional studies conducted through mail surveys in 2004 and 2012. Randomized samples (n=1,000 in 2004 and n=3,000 in 2012) were drawn from the Finnish Population Register. The empirical research utilized structural equation modelling through multi-group analysis to explore the differences in the interrelationships between physical restrictions, computer anxiety, perceived ease of use and perceived behavioural control.

Findings

– The results indicate that perceived behavioural control is directly influenced by ease of use and indirectly influenced by physical restrictions and computer anxiety. The eight-year time gap moderated only the relationship between physical restrictions and ease of use. Development seems to have been favourable, and device-related restrictions do not decrease ease of use as much as previously reported.

Originality/value

– The present study starts a new discussion on how time moderates the relationship of technology perceptions in behavioural models that have been used to predict behavioural intent.