Assessing older adults' perceptions of sensor data and designing visual displays for ambient environments. An exploratory study

Development of a Smart Home Interface With Older Adults: Multi-Method Co-Design Study

BACKGROUND

Smart home technologies have the potential to support aging in place; however, older people's perceptions of the value of smart homes may be influenced by their access to the information gathered by the technology. This information is needed to support their informed decision-making. Limited research has been conducted on how best to design visualizations of smart home data in keeping with the needs and wishes of older people.

OBJECTIVE

We aimed to investigate the design options that impact the usefulness of smart home systems, older people's information needs, their perceptions of data visualization, and the ways they would like information displayed to them.

METHODS

We used a qualitative approach to empower the participants as co-designers. Data collection comprised a sequence of methods such as interviews, observation, focus groups, scenario design, probes, and design workshops. Each phase informed the next. Overall, 13 older adults (n=8, 62% female and n=5, 38% male; aged 65-89 years) consented to participate. A thematic approach was used to analyze the data set, and participants were actively involved in designing the in-home interface, which enabled them to better conceptualize their needs.

RESULTS

The information collected was clustered into 5 themes: enabling home, health, and self-monitoring; enabling opportunities for social inclusion and engagement; enhancing cognitive abilities; customizability of the display; and promoting inclusion in recreation and leisure activities. These themes informed 5 design sessions in which participants co-designed visual metaphors for the themes based on their own experiences in an age-inclusive manner. Together, the participants produced a user-friendly prototype, which they chose to call My Buddy. They found it useful to receive social and cognitive triggers, as well as recommendations for special diets or activities based on their mood, health, and social status.

CONCLUSIONS

Smart home data visualization is much more than a nice-to-have option. Visualization is a must-have feature because it deepens the understanding of the information collected and means that technology provides information of value and relevance to older people. This may improve the acceptability and perceived utility of in-home technology. By understanding what older people want to know from smart home technology and considering how to visualize data in ways that work for them, we can provide an appropriate in-home interface. Such an interface would suggest ways or opportunities to connect and socialize; stimulate contact with close friends or family members; maintain awareness of health and well-being; provide support in decision-making, cognitive tasks, and daily life activities; and monitor health status. Older adults are the best co-designers for the development of visual metaphors that resonate with their own experiences. Our findings promote the development of technologies that foreground and reflect the information needs of older people and engage them as designers of the display.

Evaluating the acceptance of ambient assisted living technology (AALT) in rehabilitation: A scoping review

OBJECTIVES

Ambient assisted living technologies (AALTs) are being used to help community-dwelling older adults (OAs) age in place. Although many AALT are available, their acceptance (perceived usefulness, ease of use, intention to use and actual usage) is needed to improve their design and impact. This study aims to 1) identify AALTs that underwent an acceptance evaluation in rehabilitation contexts, 2) identify methodological tools and approaches to measure acceptance in ambient assisted living (AAL) in rehabilitation research, and 3) summarize AALT acceptance results in existing rehabilitation literature with a focus on peer-reviewed scientific articles.

METHODS

A scoping review was conducted in the following databases: Medline, Embase, Cinahl, and PsycInfo, following the Arksey and O'Malley framework (2009). Four acceptance attributes were extracted: 'user acceptance', 'perceived usefulness', 'ease of use', and 'intention to use'. Data regarding AALT, participants, acceptance evaluation methods and results were extracted.

RESULTS

A total of 21 articles were included among 634 studies retrieved from the literature. We identified 51 AALTs dedicated to various rehabilitation contexts, most of which focused on monitoring OAs' activities and environmental changes. Acceptance of AALT was evaluated using interviews, questionnaires, focus groups, informal feedback, observation, card sort tasks, and surveys. Although OAs intend to use - or can perceive the usefulness of - AALTs, they are hesitant to accept the technology and have concerns about its adoption.

DISCUSSION AND CONCLUSIONS

The assessment of AALT acceptance in contexts of rehabilitation requires more comprehensive and standardized methodologies. The use of mixed-methods research is encouraged to cover the needs of particular studies. The timing of acceptance assessment should be considered throughout technology development phases to maximize AALT implementation.

Detecting Anxiety States when Caring for People with Dementia

Background: Caregiving is a complex, stressful activity, which frequently leads to anxiety and the development of depressive disorders. Recent advances in wearable sensing allows to monitor relevant physiological data of the caregiver for detecting anxiety spans and for enacting coping strategies to reduce their anxiety when needed.

Objectives: This work proposes a method to infer anxiety states of caregivers when caring for people with dementia, by using physiological data.

Methods: A model using Markov chains for detecting internal anxiety states is proposed. The model is tested with a physiological dataset gathered from a naturalistic enactment experiment with 10 participants. A visual analysis for observing anxiety states is employed. The Markov chain model is evaluated by using Inter-beat Interval (IBI) data to detect 4 internal states: “Relaxed”, “Arousing”, “Anxiety”, and “Relaxing”.

Results: From the visual inspection of interbeat interval data, self-report and observation labels a total of 823 state segments were identified which contained the following states: 137 “relaxed”, 91 “arousing”, 410 “anxious”, and 185 “relaxing”. By using the average IBI value of 60 seconds segments as classification feature, the model was evaluated with a “leave one-out” cross validation with an average accuracy of 73.03%.

Conclusions: We proposed a Markov chain model for internal anxiety state detection of caregivers that care for people with dementia. The model was evaluated in a naturalistic enactment experiment with 10 participants. The resulting accuracy is comparable to previous results on stress classification.

Clinical Informatics Researcher's Desiderata for the Data Content of the Next Generation Electronic Health Record

OBJECTIVE

Clinical informatics researchers depend on the availability of high-quality data from the electronic health record (EHR) to design and implement new methods and systems for clinical practice and research. However, these data are frequently unavailable or present in a format that requires substantial revision. This article reports the results of a review of informatics literature published from 2010 to 2016 that addresses these issues by identifying categories of data content that might be included or revised in the EHR.

MATERIALS AND METHODS

We used an iterative review process on 1,215 biomedical informatics research articles. We placed them into generic categories, reviewed and refined the categories, and then assigned additional articles, for a total of three iterations.

RESULTS

Our process identified eight categories of data content issues: Adverse Events, Clinician Cognitive Processes, Data Standards Creation and Data Communication, Genomics, Medication List Data Capture, Patient Preferences, Patient-reported Data, and Phenotyping.

DISCUSSION

These categories summarize discussions in biomedical informatics literature that concern data content issues restricting clinical informatics research. These barriers to research result from data that are either absent from the EHR or are inadequate (e.g., in narrative text form) for the downstream applications of the data. In light of these categories, we discuss changes to EHR data storage that should be considered in the redesign of EHRs, to promote continued innovation in clinical informatics.

CONCLUSION

Based on published literature of clinical informaticians' reuse of EHR data, we characterize eight types of data content that, if included in the next generation of EHRs, would find immediate application in advanced informatics tools and techniques.

Creating Affording Situations: Coaching through Animate Objects

We explore the ways in which animate objects can be used to cue actions as part of coaching in Activities of Daily Living (ADL). In this case, changing the appearance or behavior of a physical object is intended to cue actions which are appropriate for a given context. The context is defined by the intention of the users, the state of the objects and the tasks for which these objects can be used. We present initial design prototypes and simple user trials which explore the impact of different cues on activity. It is shown that raising the handle of a jug, for example, not only cues the act of picking up the jug but also encourages use of the hand adjacent to the handle; that combinations of lights (on the objects) and auditory cues influence activity through reducing uncertainty; and that cueing can challenge pre-learned action sequences. We interpret these results in terms of the idea that the animate objects can be used to create affording situations, and discuss implications of this work to support relearning of ADL following brain damage or injury, such as might arise following a stroke.

Supporting Patient-Provider Collaboration to Identify Individual Triggers using Food and Symptom Journals

Patient-generated data can allow patients and providers to collaboratively develop accurate diagnoses and actionable treatment plans. Unfortunately, patients and providers often lack effective support to make use of such data. We examine patient-provider collaboration to interpret patient-generated data. We focus on irritable bowel syndrome (IBS), a chronic illness in which particular foods can exacerbate symptoms. IBS management often requires patient-provider collaboration using a patient's food and symptom journal to identify the patient's triggers. We contribute interactive visualizations to support exploration of such journals, as well as an examination of patient-provider collaboration in interpreting the journals. Drawing upon individual and collaborative interviews with patients and providers, we find that collaborative review helps improve data comprehension and build mutual trust. We also find a desire to use tools like our interactive visualizations within and beyond clinic appointments. We discuss these findings and present guidance for the design of future tools.

Understanding Older Adult Use of Data Visualizations as a Resource for Maintaining Health and Wellness

To better understand how older adults use health visualizations and the potential barriers that impact utility, we conducted semistructured interviews with 21 older adults. Within these sessions, we presented participants with two interactive visualizations for exploration. Through an affinity mapping exercise, we extracted five key themes associated with how older adults utilize health visualizations and provide corresponding recommendations as points of consideration for designers developing older adult focused health visualizations. By examining how older adults perceive the utility of health visualizations, we lay the groundwork for design choices that impact eventual use and adoption of systems that generate data for such visualizations.

A Comparison of Health Visualization Evaluation Techniques with Older Adults

Aging-associated changes in visual acuity, cognition, and motor control in addition to attitudinal and affective perceptions of technology impact the design of information systems for older adults. Although design guidelines and cognitive theories on information visualization exist, they are often understudied for use with older adults. In an effort to evaluate interactive health visualizations with older adults, the authors applied and compared a benchmark evaluation, an insight-based evaluation, and a subjective usability questionnaire. They were unable to identify statistically significant differences between visualizations using the benchmark evaluation, but found moderate differences with the perceived usability scale and more granular differences through the insight evaluation.

Smart homes and home health monitoring technologies for older adults: A systematic review

BACKGROUND

Around the world, populations are aging and there is a growing concern about ways that older adults can maintain their health and well-being while living in their homes.

OBJECTIVES

The aim of this paper was to conduct a systematic literature review to determine: (1) the levels of technology readiness among older adults and, (2) evidence for smart homes and home-based health-monitoring technologies that support aging in place for older adults who have complex needs.

RESULTS

We identified and analyzed 48 of 1863 relevant papers. Our analyses found that: (1) technology-readiness level for smart homes and home health monitoring technologies is low; (2) the highest level of evidence is 1b (i.e., one randomized controlled trial with a PEDro score ≥6); smart homes and home health monitoring technologies are used to monitor activities of daily living, cognitive decline and mental health, and heart conditions in older adults with complex needs; (3) there is no evidence that smart homes and home health monitoring technologies help address disability prediction and health-related quality of life, or fall prevention; and (4) there is conflicting evidence that smart homes and home health monitoring technologies help address chronic obstructive pulmonary disease.

CONCLUSIONS

The level of technology readiness for smart homes and home health monitoring technologies is still low. The highest level of evidence found was in a study that supported home health technologies for use in monitoring activities of daily living, cognitive decline, mental health, and heart conditions in older adults with complex needs.

Current Telerehabilitation Research With Older Adults at Home: An Integrative Review

Increased demand for in-home rehabilitation services for older adults may be met through telerehabilitation information and communication technologies. The current article reports the results of an integrative literature review summarizing current in-home telerehabilitation research with older adults. Nine studies from 2006-2015 are included. Six studies employed a remote therapist using real-time video. Three studies used text- or web-based messaging and electronic surveys. Six studies relied on dial-up Internet service and the remaining three studies used broad-band Internet connections. Future research should address (a) in-home and wearable sensing technologies to monitor health and (b) mobile devices, such as tablet computers, to collect patient self-reports. Interoperable platforms are needed to integrate disparate devices and support continuity of care across post-acute care settings. [Journal of Gerontological Nursing, 42(10), 15-20.].

Improving Bridging from Informatics Theory to Practice

BACKGROUND

In 1962, Methods of Information in Medicine (MIM) began to publish papers on the methodology and scientific fundamentals of managing data, information, and knowledge in biomedicine and health care. Meeting an increasing demand for research about practical implementation of health information systems, the journal Applied Clinical Informatics (ACI) was launched in 2009. Both journals are official journals of the International Medical Informatics Association (IMIA).

OBJECTIVES

Based on prior analyses, we aimed to describe major topics published in MIM during 2014 and to explore whether theory of MIM influenced practice of ACI. Our objectives were further to describe lessons learned and to discuss possible editorial policies to improve bridging from theory to practice.

METHODS

We conducted a retrospective, observational study reviewing MIM articles published during 2014 (N=61) and analyzing reference lists of ACI articles from 2014 (N=70). Lessons learned and opinions about MIM editorial policies were developed in consensus by the two authors. These have been influenced by discussions with the journal's associate editors and editorial board members.

RESULTS

The publication topics of MIM in 2014 were broad, covering biomedical and health informatics, medical biometry and epidemiology. Important topics discussed were biosignal interpretation, boosting methodologies, citation analysis, health-enabling and ambient assistive technologies, health record banking, safety, and standards. Nine ACI practice articles from 2014 cited eighteen MIM theory papers from any year. These nine ACI articles covered mainly the areas of clinical documentation and medication-related decision support. The methodological basis they cited from was almost exclusively related to evaluation. We could show some direct links where theory impacted practice. These links are however few in relation to the total amount of papers published.

CONCLUSIONS

Editorial policies such as publishing systematic methodological reviews and clarification of possible practical impact of theory-focused articles may improve bridging.

Using data from ambient assisted living and smart homes in electronic health records

INTRODUCTION

This editorial is part of the Focus Theme of Methods of Information in Medicine on "Using Data from Ambient Assisted Living and Smart Homes in Electronic Health Records".

BACKGROUND

To increase efficiency in the health care of the future, data from innovative technology like it is used for ambient assisted living (AAL) or smart homes should be available for individual health decisions. Integrating and aggregating data from different medical devices and health records enables a comprehensive view on health data.

OBJECTIVES

The objective of this paper is to present examples of the state of the art in research on information management that leads to a sustainable use and long-term storage of health data provided by innovative assistive technologies in daily living.

RESULTS

Current research deals with the perceived usefulness of sensor data, the participatory design of visual displays for presenting monitoring data, and communication architectures for integrating sensor data from home health care environments with health care providers either via a regional health record bank or via a telemedical center.

CONCLUSIONS

Integrating data from AAL systems and smart homes with data from electronic patient or health records is still in an early stage. Several projects are in an advanced conceptual phase, some of them exploring feasibility with the help of prototypes. General comprehensive solutions are hardly available and should become a major issue of medical informatics research in the near future.

Using personas to tailor educational messages to the preferences of coronary heart disease patients

PURPOSE

Although tailoring health education messages to individual characteristics of patients has shown promising results, most patient education materials still take a one-size-fits-all approach. The aim of this study was to develop a method for tailoring health education messages to patients' preferences for various message features, using the concept of personas. This is a preliminary study focused on education for coronary heart disease (CHD) patients.

METHODS

This study used a three-step approach. First, we created personas by (i) performing k-means cluster analysis on data from an online survey that assessed the preferences of 213 CHD patients for various message features and, (ii) creating a vivid description of the preferences per patient cluster in an iterative process with the research team. Second, we developed adaptation rules to tailor existing educational messages to the resulting personas. Third, we conducted a pilot validation by adapting nine existing educational messages to each of the personas. These messages and the resulting personas were then presented to a separate group of 38 CHD patients who visited the cardiology outpatient clinic. They were first asked to choose their most preferred, second most preferred, and least preferred persona. Subsequently, they were asked to rate three of the adapted messages; one for every of the persona choices.

RESULTS

We created five personas that pertained to five patient clusters. Personas varied mainly on preferences for medical or lay language, current or future temporal perspective, and including or excluding explicit health risks. Fifty-five different adaptation rules were developed, primarily describing adaptations to the message's perspective, level of detail, sentence structure, and terminology. Most participants in the validation study could identify with one of the five personas, although some of them found it hard to choose. On average, 68.5% of all participants rated the messages that matched their most preferred persona more positively than, or in the same way as, the messages that matched their least preferred persona.

CONCLUSIONS

The persona-based method developed in this study can be used to create a manageable set of patient-centered tailored messages, while additionally using the developed personas to assess patients' preferences.