"Are You Sure?": Lapses in Self-Reported Activities Among Healthy Older Adults Reporting Online

Using Continuous Passive Assessment Technology to Describe Health and Behavior Patterns Preceding and Following a Cancer Diagnosis in Older Adults: Proof-of-Concept Case Series Study

BACKGROUND

Describing changes in health and behavior that precede and follow a sentinel health event, such as a cancer diagnosis, is challenging because of the lack of longitudinal, objective measurements that are collected frequently enough to capture varying trajectories of change leading up to and following the event. A continuous passive assessment system that continuously monitors older adults' physical activity, weight, medication-taking behavior, pain, health events, and mood could enable the identification of more specific health and behavior patterns leading up to a cancer diagnosis and whether and how patterns change thereafter.

OBJECTIVE

In this study, we conducted a proof-of-concept retrospective analysis, in which we identified new cancer diagnoses in older adults and compared trajectories of change in health and behaviors before and after cancer diagnosis.

METHODS

Participants were 10 older adults (mean age 71.8, SD 4.9 years; 3/10, 30% female) with various self-reported cancer types from a larger prospective cohort study of older adults. A technology-agnostic assessment platform using multiple devices provided continuous data on daily physical activity via wearable sensors (actigraphy); weight via a Wi-Fi-enabled digital scale; daily medication-taking behavior using electronic Bluetooth-enabled pillboxes; and weekly pain, health events, and mood with online, self-report surveys.

RESULTS

Longitudinal linear mixed-effects models revealed significant differences in the pre- and postcancer trajectories of step counts (P<.001), step count variability (P=.004), weight (P<.001), pain severity (P<.001), hospitalization or emergency room visits (P=.03), days away from home overnight (P=.01), and the number of pillbox door openings (P<.001). Over the year preceding a cancer diagnosis, there were gradual reductions in step counts and weight and gradual increases in pain severity, step count variability, hospitalization or emergency room visits, and days away from home overnight compared with 1 year after the cancer diagnosis. Across the year after the cancer diagnosis, there was a gradual increase in the number of pillbox door openings compared with 1 year before the cancer diagnosis. There was no significant trajectory change from the pre- to post-cancer diagnosis period in terms of low mood (P=.60) and loneliness (P=.22).

CONCLUSIONS

A home-based, technology-agnostic, and multidomain assessment platform could provide a unique approach to monitoring different types of behavior and health markers in parallel before and after a life-changing health event. Continuous passive monitoring that is ecologically valid, less prone to bias, and limits participant burden could greatly enhance research that aims to improve early detection efforts, clinical care, and outcomes for people with cancer.

Sensor-Based Assessment of Social Isolation and Loneliness in Older Adults: A Survey

Social isolation (SI) and loneliness are 'invisible enemies'. They affect older people's health and quality of life and have significant impact on aged care resources. While in-person screening tools for SI and loneliness exist, staff shortages and psycho-social challenges fed by stereotypes are significant barriers to their implementation in routine care. Autonomous sensor-based approaches can be used to overcome these challenges by enabling unobtrusive and privacy-preserving assessments of SI and loneliness. This paper presents a comprehensive overview of sensor-based tools to assess social isolation and loneliness through a structured critical review of the relevant literature. The aim of this survey is to identify, categorise, and synthesise studies in which sensing technologies have been used to measure activity and behavioural markers of SI and loneliness in older adults. This survey identified a number of feasibility studies using ambient sensors for measuring SI and loneliness activity markers. Time spent out of home and time spent in different parts of the home were found to show strong associations with SI and loneliness scores derived from standard instruments. This survey found a lack of long-term, in-depth studies in this area with older populations. Specifically, research gaps on the use of wearable and smart phone sensors in this population were identified, including the need for co-design that is important for effective adoption and practical implementation of sensor-based SI and loneliness assessment in older adults.

Unobtrusive Sensing Technology Detects Ecologically Valid Spatiotemporal Patterns of Daily Routines Distinctive to Persons With Mild Cognitive Impairment

BACKGROUND

The ability to capture people's movement throughout their home is a powerful approach to inform spatiotemporal patterns of routines associated with cognitive impairment. The study estimated indoor room activities over 24 hours and investigated relationships between diurnal activity patterns and mild cognitive impairment (MCI).

METHODS

One hundred and sixty-one older adults (26 with MCI) living alone (age = 78.9 ± 9.2) were included from 2 study cohorts-the Oregon Center for Aging & Technology and the Minority Aging Research Study. Indoor room activities were measured by the number of trips made to rooms (bathroom, bedroom, kitchen, living room). Trips made to rooms (transitions) were detected using passive infrared motion sensors fixed on the walls for a month. Latent trajectory models were used to identify distinct diurnal patterns of room activities and characteristics associated with each trajectory.

RESULTS

Latent trajectory models identified 2 diurnal patterns of bathroom usage (high and low usage). Participants with MCI were more likely to be in the high bathroom usage group that exhibited more trips to the bathroom than the low-usage group (odds ratio [OR] = 4.1, 95% CI [1.3-13.5], p = .02). For kitchen activity, 2 diurnal patterns were identified (high and low activity). Participants with MCI were more likely to be in the high kitchen activity group that exhibited more transitions to the kitchen throughout the day and night than the low kitchen activity group (OR = 3.2, 95% CI [1.1-9.1], p = .03).

CONCLUSIONS

The linkage between bathroom and kitchen activities with MCI may be the result of biological, health, and environmental factors in play. In-home, real-time unobtrusive-sensing offers a novel way of delineating cognitive health with chronologically-ordered movement across indoor locations.

Association between low level of physical activity and mobility limitation in older adults: evidence from the SABE study

Several studies are limited by verifying the level of physical activity with questionnaires and not through objective measurement in older adults. This article aims to analyze the association between a low level of physical activity with accelerometry) and mobility limitation in older adults. A population-based cross-sectional study conducted with 543 older adults. Multiple regression analysis was performed using hierarchical analysis, grouping the variables into two blocks ordered according to the precedence with which they acted on the outcomes. Among the evaluated older adults, 13.7% presented mobility limitations and among these 60.39% were in the low level of physical activity group. Older adults with a low level of physical activity (OR = 3.49 [2.0 - 6.13]), aged 75 and over (OR = 1.97 [1.03 - 3.72]), living without a partner (OR = 2.01 [1.09 - 3.68]), having difficulty performing basic (OR = 2.49 [1.45 - 4.28]) and instrumental (OR = 2.28) [1.18 - 4.36]) activities of daily life, and multimorbidity (OR = 2.06 [1.04 - 4.08]) were independently associated with mobility limitation. A low level of physical activity increases the chance of mobility limitation in older adults, regardless of sociodemographic and clinical variables.

The Remote Assessment and Dynamic Response Program: Development of an In-Home Dementia-Related Care Needs Assessment to Improve Well-Being

Background and Objectives

The Remote Assessment and Dynamic Response (READyR) Program was developed in order to address the current lack of early-stage dementia care planning programs that assess the care needs of persons with dementia. The goal was to create a program informed by care values and ongoing ecologically valid data. The objectives of this study are to describe the development and design process of the READyR Program, and to evaluate the utility of the READyR Program for identifying dementia-related care needs.

Research Design and Methods

A prototype of the web-based READyR Program tool was first created using digital activity data that were collected by previous studies using a platform of multimodal sensors installed in the homes of older adult couples with and without dementia. Digital activity data were then mapped onto potential care values (e.g., safety & autonomy) to create a values-based needs assessment that is tailored to the individual care dyad. Next, evaluation of the READyR Program by 11 professional dementia care coordinators and case managers (across 3 semistructured focus groups) was used to explore the utility of READyR for assessing dementia-related needs. Qualitative description using conventional content analysis was used to iteratively code focus group data and to describe prevalent themes.

Results

Prevalent focus groups themes included barriers to (e.g., family relationship strain) and facilitators of (e.g., tailored assessments) the optimal process for assessing dementia-related care needs by care coordinators, as well as advantages to (e.g., providing new objective insights into function, and routines) and disadvantages of (e.g., bringing up new questions about care) incorporating the remote monitoring data into a values-based needs assessment.

Discussion and Implications

READyR has the potential to help family members, as well as care coordinators and providers, gain insight into the values-based care needs of persons with early-stage dementia. Clinical Trials Registration Number: NCT04542109.

Effects of Activity Tracker Use With Health Professional Support or Telephone Counseling on Maintenance of Physical Activity and Health Outcomes in Older Adults: Randomized Controlled Trial

BACKGROUND

Despite a range of efforts to increase physical activity participation in Australia, inactivity levels in older adults have remained high over recent decades, contributing to increased rates of chronic health conditions. Lifestyle interventions, including telephone counseling (TC), improve physical activity participation and associated health outcomes over the short term; however, ongoing feedback and support is required to maintain these changes. Newer technologies such as wearable activity trackers (ATs) may offer an alternative method for providing ongoing support.

OBJECTIVE

This study aims to investigate whether newer technologies such as wearable ATs assist in providing ongoing support to maintain physical activity levels and health outcomes.

METHODS

Older adults aged >60 years who had just completed a 12-week face-to-face individualized community exercise program in Tasmania, Australia, participated in the study. They were randomized to receive AT, TC, or usual care (UC). All groups received a home exercise program and an optional referral to a community-based exercise program. The AT group also received an AT and text message feedback from an accredited exercise physiologist (AEP). The TC group received phone calls from an AEP throughout the 12-month intervention. The primary outcome was daily steps measured by an ActivPAL (TM) accelerometer at baseline and at 3, 6, and 12 months. Secondary outcome measures included body composition, blood pressure, 10-time sit-to-stand (TTSTS) test, timed up and go test, and cardiorespiratory fitness. This trial was approved by the Tasmanian Health and Medical Human Research Ethics Committee (H0014713).

RESULTS

A total of 117 participants were randomized to the study (AT, n=37; TC, n=38; UC, n=42). At baseline, the participants (75/117, 64.1% female; mean age 72.4 years, SD 6.4) completed an average of 6136 steps (SD 2985) per day. Although there were no significant differences between groups, the TC and AT groups maintained daily step counts (mean difference [MD] -79 steps, 95% CI -823 to 663 steps; P=.81; and MD -588 steps, 95% CI -1359 to 182 steps; P=.09), and UC showed a reduction in daily steps (MD 981 steps, 95% CI -1668 to -294 steps; P=.003) during the 12-month period. Diastolic blood pressure was significantly higher after AT than after UC (MD 5.62 mm Hg, 95% CI 1.30 to 9.94 mm Hg; P=.01), and TTSTS was significantly slower on TC compared with UC (MD 2.36 seconds, 95% CI -0.14 to 4.87 seconds; P=.03).

CONCLUSIONS

The use of an AT with AEP support or TC is effective at maintaining daily step count in older adults over a 12-month period, suggesting that wearable ATs are as effective as TC. Further research to investigate which option is more cost-effective would be beneficial.

TRIAL REGISTRATION

Australian New Zealand Clinical Trial Registry ACTRN12615001104549; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=369118.

An Ecologically Valid, Longitudinal, and Unbiased Assessment of Treatment Efficacy in Alzheimer Disease (the EVALUATE-AD Trial): Proof-of-Concept Study

Background

The current clinical trial assessment methodology relies on a combination of self-report measures, cognitive and physical function tests, and biomarkers. This methodology is limited by recall bias and recency effects in self-reporting and by assessments that are brief, episodic, and clinic based. Continuous monitoring of ecologically valid measures of cognition and daily functioning in the community may provide a more sensitive method to detect subtle, progressive changes in patients with cognitive impairment and dementia.

Objective

This study aimed to present an alternative trial approach using a home-based sensing and computing system to detect changes related to common treatments employed in Alzheimer disease (AD). This paper introduces an ongoing study that aims to determine the feasibility of capturing sensor-based data at home and to compare the sensor-based outcomes with conventional outcomes. We describe the methodology used in the assessment protocol and present preliminary results of feasibility measures and examples of data related to medication-taking behavior, activity levels, and sleep.

Methods

The EVALUATE-AD (Ecologically Valid, Ambient, Longitudinal and Unbiased Assessment of Treatment Efficacy in Alzheimer’s Disease) trial is a longitudinal naturalistic observational cohort study recruiting 30 patients and 30 spouse coresident care partners. Participants are monitored continuously using a home-based sensing and computing system for up to 24 months. Outcome measures of the automated system are compared with conventional clinical outcome measures in AD. Acceptance of the home system and protocol are assessed by rates of dropout and protocol adherence. After completion of the study monitoring period, a composite model using multiple functional outcome measures will be created that represents a behavioral-activity signature of initiating or discontinuing AD-related medications, such as cholinesterase inhibitors, memantine, or antidepressants.

Results

The home-based sensing and computing system has been well accepted by individuals with cognitive impairment and their care partners. Participants showed good adherence to the completion of a weekly web-based health survey. Daily activity, medication adherence, and total time in bed could be derived from algorithms using data from the sensing and computing system. The mean monitoring time for current participants was 14.6 months. Medication adherence, as measured with an electronic pillbox, was 77% for participants taking AD-related medications.

Conclusions

Continuous, home-based assessment provides a novel approach to test the impact of new or existing dementia treatments generating objective, clinically meaningful measures related to cognition and everyday functioning. Combining this approach with the current clinical trial methodology may ultimately reduce trial durations, sample size needs, and reliance on a clinic-based assessment.

International Registered Report Identifier (IRRID)

DERR1-10.2196/17603

The Five W's of Falls: Weekly Online Health Survey of Community-Dwelling Older Adults: Analysis of 4 Years Prospective Follow-up

BACKGROUND

An in-depth examination of prospectively collected falls details may facilitate more effective falls prevention. Who was involved? What happened? Where did the fall take place? When did it happen? Why did it occur? This study aimed to provide previously unavailable details about the circumstances surrounding fall events and their consequences.

METHOD

A retrospective analysis of falls prospectively self-reported by older adults via an online weekly health form over 4 years.

RESULTS

We collected 371 falls during the 4 year time period from 120 clinically characterized fallers (74% women, mean age 83.3 years). Most of the 371 falls occurred indoors (62%) and in well-lit areas (81%). Bedrooms were the most common places for in-home falls. Commonly observed precipitating factors included loss of balance, slipping or tripping. Almost one-third (31%) of falls were defined as injurious whereas 22% resulted in a change in the walking ability of which 26% led to the use of a cane or walker. Among falls that did not give rise to any formal health care intervention, 8% resulted in a modification of walking ability.

CONCLUSIONS

A relatively high rate of fall-related injuries compared to the existing literature was observed. Online weekly surveys and the richness of details provided through these data capture method allowed us to identify falls that did not result in health care utilization but did result in decreased mobility. This finding suggests why some falls classified in the literature as noninjurious may nevertheless increase the risk of loss of autonomy and undesired outcomes.

Age-friendly cities and communities: a review and future directions

The unprecedented increase in the ageing population, coupled with urbanisation, has led to a vast number of research publications on age-friendly cities and communities (AFCC). However, the existing reviews on AFCC studies are not sufficiently up-to-date for AFCC researchers. This paper presents a thorough analysis of the annual publication trend, the contributions of authors and institutions from different countries, and the trending research themes in the AFCC research corpus through a systematic review of 98 publications. A contribution assessment formula and thematic analysis were used for the review. The results indicated a growing AFCC research interest in recent times. Researchers and institutions from the United States of America, Canada, United Kingdom and Hong Kong made the highest contribution to the AFCC research corpus. The thematic analysis classified the AFCC research corpus into four main themes: conceptualisation; implementation and development; assessment; and challenges and opportunities. The themes indicate the current and future research patterns and issues to be considered in the development of AFCC and for interested researchers to make proposals for future research. Future directions are proposed, including suggestions on adopting new assessment methods and instruments, collaboration and cross-nation comparative research, considering older adults as place-makers and conducting a prior participatory analysis to maximise the participation of older adults.

Real-Time Detection of Behavioral Anomalies of Older People Using Artificial Intelligence (The 3-PEGASE Study): Protocol for a Real-Life Prospective Trial

BACKGROUND

Most frail older persons are living at home, and we face difficulties in achieving seamless monitoring to detect adverse health changes. Even more important, this lack of follow-up could have a negative impact on the living choices made by older individuals and their care partners. People could give up their homes for the more reassuring environment of a medicalized living facility. We have developed a low-cost unobtrusive sensor-based solution to trigger automatic alerts in case of an acute event or subtle changes over time. It could facilitate older adults' follow-up in their own homes, and thus support independent living.

OBJECTIVE

The primary objective of this prospective open-label study is to evaluate the relevance of the automatic alerts generated by our artificial intelligence-driven monitoring solution as judged by the recipients: older adults, caregivers, and professional support workers. The secondary objective is to evaluate its ability to detect subtle functional and cognitive decline and major medical events.

METHODS

The primary outcome will be evaluated for each successive 2-month follow-up period to estimate the progression of our learning algorithm performance over time. In total, 25 frail or disabled participants, aged 75 years and above and living alone in their own homes, will be enrolled for a 6-month follow-up period.

RESULTS

The first phase with 5 participants for a 4-month feasibility period has been completed and the expected completion date for the second phase of the study (20 participants for 6 months) is July 2020.

CONCLUSIONS

The originality of our real-life project lies in the choice of the primary outcome and in our user-centered evaluation. We will evaluate the relevance of the alerts and the algorithm performance over time according to the end users. The first-line recipients of the information are the older adults and their care partners rather than health care professionals. Despite the fast pace of electronic health devices development, few studies have addressed the specific everyday needs of older adults and their families.

TRIAL REGISTRATION

ClinicalTrials.gov NCT03484156; https://clinicaltrials.gov/ct2/show/NCT03484156.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

PRR1-10.2196/14245.

Validity of pervasive computing based continuous physical activity assessment in community-dwelling old and oldest-old

In older adults, physical activity is crucial for healthy aging and associated with numerous health indicators and outcomes. Regular assessments of physical activity can help detect early health-related changes and manage physical activity targeted interventions. The quantification of physical activity, however, is difficult as commonly used self-reported measures are biased and rather unprecise point in time measurements. Modern alternatives are commonly based on wearable technologies which are accurate but suffer from usability and compliance issues. In this study, we assessed the potential of an unobtrusive ambient-sensor based system for continuous, long-term physical activity quantification. Towards this goal, we analysed one year of longitudinal sensor- and medical-records stemming from thirteen community-dwelling old and oldest old subjects. Based on the sensor data the daily number of room-transitions as well as the raw sensor activity were calculated. We did find the number of room-transitions, and to some degree also the raw sensor activity, to capture numerous known associations of physical activity with cognitive, well-being and motor health indicators and outcomes. The results of this study indicate that such low-cost unobtrusive ambient-sensor systems can provide an adequate approximation of older adults’ overall physical activity, sufficient to capture relevant associations with health indicators and outcomes.

EVALUATE-AD and Tele-STAR: Novel Methodologies for Assessment of Caregiver Burden in a Telehealth Caregiver Intervention - A Case Study

AIMS

We explored the relationship between objective and subjective measures of burden prior to and after a telehealth-based caregiver intervention. One caregiver participated in two studies, one to assess the feasibility of objective, home-based monitoring (EVALUATE-AD), the second to assess the feasibility of a caregiver education telehealth-based intervention, Tele-STAR.

METHODS

Subjective measures of burden and depression in Tele-STAR and objective measures related to daily activities of the caregiver in EVALUATE-AD were compared to examine trends between the different outcome measures.

RESULTS

While the caregiver reported an increase in distressing behaviors by her partner, burden levels did not significantly change during or after the Tele-STAR intervention, while objective measures of activity and sleep showed a slight decline.

CONCLUSION

Unobtrusive home-based monitoring may provide a novel, objective method to assess the effectiveness of caregiver intervention programs.

Why Older Adults and Their Children Disagree About In-Home Surveillance Technology, Sensors, and Tracking

Background and Objectives

Despite the surveilling nature of technologies that allow caregivers to remotely monitor location, movements, or activities, the potential differences in comfort with remote monitoring between caregivers and care recipients have not been examined in depth. On the dyad and aggregate level, we compare preferences of older adult women and their adult children for three remote monitoring technologies. Their assessments of each technology’s impact on privacy, safety, independence, freedom, relationship with family member, social life, and identity are also compared.

Research Design and Methods

This dyadic study used cognitive-based interview probing and value-centered design methods. Twenty-eight individual, in-depth, structured interviews were conducted with 18 women who are Meals on Wheels clients and 10 of their adult children.

Results

Meals on Wheels participants reported multiple chronic conditions and an average of 1.7 ADL and 3.3 IADL difficulties; two thirds were enrolled in Medicaid. Adult children preferred each technology more than their mothers did and underestimated both their mothers’ ability to comprehend the functions of the technologies and the importance of engaging them fully in decision making. Most were confident that they could persuade their mothers to adopt. For both groups, privacy was the most-cited concern, and participants perceived significant overlap between values of privacy, independence, identity, and freedom.

Discussion and Implications

Studying privacy in isolation overlooks privacy’s instrumental role in enabling other values. Shared decision-making tools are needed to promote remote monitoring use consistent with older adults’ values and to prevent conflict and caregiver overreach.

Six-Month Effectiveness of Remote Activity Monitoring for Persons Living With Dementia and Their Family Caregivers: An Experimental Mixed Methods Study

Background and Objectives

This study aimed to evaluate if and how remote activity monitoring (RAM) improves caregiver outcomes for family members providing care for persons living with Alzheimer's disease or a related dementia (ADRD).

Research Design and Methods

We conducted an embedded experimental mixed methods study of 132 persons living with ADRD and their family caregivers (n = 64 randomly assigned to RAM treatment condition). In addition to baseline and 6-month quantitative survey data on context of care, primary objective stressors, resources, self-efficacy/competence, and distress collected from caregivers, 6-month RAM review checklists contained open-ended, qualitative information on perceived acceptability of the technology.

Results

The RAM system did not exert statistically significant effects on caregiving outcomes over a 6-month period. However, qualitative analyses identified several potential moderators of RAM technology effectiveness that were subsequently tested in post-hoc repeated measures analyses of variance. Caregivers who utilized RAM technology and cared for relatives with: (a) less severe cognitive impairment; and (b) difficulty navigating around the home were more likely to indicate statistically significant increases in competence and self-efficacy, respectively.

Discussion and Implications

We found that the early months spent calibrating and modifying RAM are potentially challenging for families, which may prevent this technology from improving caregiving outcomes during initial months of use. Remote activity monitoring may work optimally for caregivers of persons living with ADRD in specific situations (e.g., earlier stages of dementia; wandering risk), which suggests the need for appropriate needs assessments that can better target such innovations.

Methodology for Establishing a Community-Wide Life Laboratory for Capturing Unobtrusive and Continuous Remote Activity and Health Data

An end-to-end suite of technologies has been established for the unobtrusive and continuous monitoring of health and activity changes occurring in the daily life of older adults over extended periods of time. The technology is aggregated into a system that incorporates the principles of being minimally obtrusive, while generating secure, privacy protected, continuous objective data in real-world (home-based) settings for months to years. The system includes passive infrared presence sensors placed throughout the home, door contact sensors installed on exterior doors, connected physiological monitoring devices (such as scales), medication boxes, and wearable actigraphs. Driving sensors are also installed in participants' cars and computer (PC, tablet or smartphone) use is tracked. Data is annotated via frequent online self-report options that provide vital information with regard to the data that is difficult to infer via sensors such as internal states (e.g., pain, mood, loneliness), as well as data referent to activity pattern interpretation (e.g., visitors, rearranged furniture). Algorithms have been developed using the data obtained to identify functional domains key to health or disease activity monitoring, including mobility (e.g., room transitions, steps, gait speed), physiologic function (e.g., weight, body mass index, pulse), sleep behaviors (e.g., sleep time, trips to the bathroom at night), medication adherence (e.g., missed doses), social engagement (e.g., time spent out of home, time couples spend together), and cognitive function (e.g., time on computer, mouse movements, characteristics of online form completion, driving ability). Change detection of these functions provides a sensitive marker for the application in health surveillance of acute illnesses (e.g., viral epidemic) to the early detection of prodromal dementia syndromes. The system is particularly suitable for monitoring the efficacy of clinical interventions in natural history studies of geriatric syndromes and in clinical trials.

Persuasive technology to support active and healthy ageing: An exploration of past, present, and future

The age of the population worldwide is rapidly increasing, bringing social and economic challenges. Persuasive technology can alleviate the burden on traditional healthcare services when used to support healthy behaviors, for instance in the prevention and treatment of chronic diseases. Additionally, healthy behaviors are key factors for active and healthy ageing by delaying or even reversing functional decline. In this manuscript, we present a multi-perspective analysis of technologies that can be used in the support of active and healthy ageing in the daily life. First, we take the perspective of physical and mental health, by focusing on the promotion of physical activity and emotional wellbeing. From a temporal perspective, we look at how technology evolved from past, present and future. The overview of the literature is structured in four main sections: (1) measurement of current behavior (monitoring), (2) analysis of the data gathered to derive meaningful information (analyzing & reasoning), (3) support the individual in the adoption or maintenance of a behavior (coaching), and (4) tools or interfaces that provide the information to the individual to stimulate the desired behavior (applications). Finally, we provide recommendations for the design, development and implementation of future technological innovations to support Active and Healthy Ageing in daily life.

Digital technologies as biomarkers, clinical outcomes assessment, and recruitment tools in Alzheimer's disease clinical trials

Digital technology is transforming the development of drugs for Alzheimer's disease and was the topic of the Alzheimer's Association's Research Roundtable on its May 23–24, 2017 meeting. Research indicates that wearable devices and unobtrusive passive sensors that enable the collection of frequent or continuous, objective, and multidimensional data during daily activities may capture subtle changes in cognition and functional capacity long before the onset of dementia. The potential to exploit these technologies to improve clinical trials as both recruitment and retention tools as well as for potential end points was discussed. The implications for the collection and use of large amounts of data, lessons learned from other related disease areas, ethical concerns raised by these new technologies, and regulatory issues were also covered in the meeting. Finally, the challenges and opportunities of these new technologies for future use were discussed.

"It's Like a Cyber-Security Blanket": The Utility of Remote Activity Monitoring in Family Dementia Care

Technologies have emerged that aim to help older persons with Alzheimer's disease and related dementias (ADRDs) remain at home while also supporting their caregiving family members. However, the usefulness of these innovations, particularly in home-based care contexts, remains underexplored. The current study evaluated the acceptability and utility of an in-home remote activity monitoring (RAM) system for 30 family caregivers of persons with ADRD via quantitative survey data collected over a 6-month period and qualitative survey and interview data collected for up to 18 months. A parallel convergent mixed methods design was employed. The integrated qualitative and quantitative data suggested that RAM technology offered ongoing monitoring and provided caregivers with a sense of security. Considerable customization was needed so that RAM was most appropriate for persons with ADRD. The findings have important clinical implications when considering how RAM can supplement, or potentially substitute for, ADRD family care.

An exploratory study on the impact of daily activities on the pleasure and physical activity of older adults

Background

Pleasure is one determinant of intrinsic motivation and yet a dimension often forgotten when promoting physical activity among the older population. In this study we investigate the relation between daily activities and physical activity, experience of pleasure, and the interaction between pleasure and physical activity in the daily lives of community-dwelling older adults.

Methods

Participants carried a hip-worn accelerometer during 30 consecutive days resulting in a total of 320 days of data collection. Current activity, location, companion and experience of pleasure during each activity were assessed through experience sampling on a smartphone every 1–2 h. Between- and within-individual differences were analysed with multi-level models and 10xN = 1 regression analysis.

Results

Outdoor activities were associated with higher physical activity than indoor activities (p < 0.001). Performing leisure activities, outdoors and not alone significantly predicted pleasure in daily life (all p’s < 0.05). Being more active while performing leisure activities resulted in higher experiences of pleasure (p < 0.001). However, when performing basic activities of daily living (e.g. commuting or households) this relation was inverted. Results provide meaningful indication for individual variance. The 30 days of data collected from each participant allow for identification of individual differences.

Conclusions

Daily activities and their contexts do influence the experience of pleasure and physical activity of older adults in daily life of older adults, although similar research with larger population is recommended. Results are in accordance with the literature, indicating that the method adopted (accelerometry combined with experience sampling) provides reliable representation of daily life. Identification of individual differences can eventually be automatically performed through data mining techniques. Further research could look at innovative approaches to promote Active Ageing using mobile technology in the daily life, by promoting physical activity through recommendation of pleasurable activities, and thus likely to increase the intrinsic motivation to become physically active.

Pervasive Computing Technologies to Continuously Assess Alzheimer's Disease Progression and Intervention Efficacy

Traditionally, assessment of functional and cognitive status of individuals with dementia occurs in brief clinic visits during which time clinicians extract a snapshot of recent changes in individuals’ health. Conventionally, this is done using various clinical assessment tools applied at the point of care and relies on patients’ and caregivers’ ability to accurately recall daily activity and trends in personal health. These practices suffer from the infrequency and generally short durations of visits. Since 2004, researchers at the Oregon Center for Aging and Technology (ORCATECH) at the Oregon Health and Science University have been working on developing technologies to transform this model. ORCATECH researchers have developed a system of continuous in-home monitoring using pervasive computing technologies that make it possible to more accurately track activities and behaviors and measure relevant intra-individual changes. We have installed a system of strategically placed sensors in over 480 homes and have been collecting data for up to 8 years. Using this continuous in-home monitoring system, ORCATECH researchers have collected data on multiple behaviors such as gait and mobility, sleep and activity patterns, medication adherence, and computer use. Patterns of intra-individual variation detected in each of these areas are used to predict outcomes such as low mood, loneliness, and cognitive function. These methods have the potential to improve the quality of patient health data and in turn patient care especially related to cognitive decline. Furthermore, the continuous real-world nature of the data may improve the efficiency and ecological validity of clinical intervention studies.