Overcoming Barriers to Early Detection with Pervasive Computing

Embedded assessment leverages the capabilities of pervasive computing to advance early detection of health conditions. In this approach, technologies embedded in the home setting are used to establish personalized baselines against which later indices of health status can be compared. Our ethnographic and concept feedback studies suggest that adoption of such health technologies among end users will be increased if monitoring is woven into preventive and compensatory health applications, such that the integrated system provides value beyond assessment. We review health technology advances in the three areas of monitoring, compensation, and prevention. We then define embedded assessment in terms of these three components. The validation of pervasive computing systems for early detection involves unique challenges due to conflicts between the exploratory nature of these systems and the validation criteria of medical research audiences. We discuss an approach for demonstrating value that incorporates ethnographic observation and new ubiquitous computing tools for behavioral observation in naturalistic settings such as the home.

Leveraging synergies in these three areas holds promise for advancing detection of disease states. We believe this highly integrated approach will greatly increase adoption of home health technologies among end users and ease the transition of embedded health assessment prototypes from computing laboratories into medical research and practice. We derive our observations from a series of exploratory and qualitative studies on ubiquitous computing for health and well being. These studies, highlighted barriers to early detection in the clinical setting, concerns about home assessment technologies among end users, and values of target user groups related to prevention and detection. Observations from the studies are used to identify challenges that must be overcome  by  pervasive computing developers if ubiquitous computing systems are to gain wide acceptance for early detection of health  conditions.

The motivation driving research on pervasive home monitoring is that clinical diagnostic practices frequently fail to detect health problems in their early stages. Often, clinical testing is first conducted after the onset of a health problem when there is no data about an individual’s previous level of functioning. Subsequent clinical assessments are conducted periodically, often with no data other than self-report about functioning in between clinical visits. Self-report data on mundane or repetitive health-related behaviors has been repeatedly demonstrated as unreliable. Clinical diagnostics are also limited in ecological validity, not accounting for  functioning in the home and other daily environments. Another barrier to early detection is that age based norms used to detect  impairment may fail to capture significant decline among people whose premorbid functioning was far above average. Cultural differences have also been repeatedly shown to influence performance on standardized tests. Although early detection can cut costs in the long term, most practitioners are more accustomed to dealing with severe, late stage health issues than subclinical patterns that may or may not be markers for more serious problems. In our participatory design interviews, clinicians voiced concerns about false positives causing unwarranted patient concerns and additional demands on their time. Compounding the clinical barriers to early detection listed above are psychological and behavioral patterns among individuals contending with the possibility of illness. Our interviews highlighted denial, perceptual biases regarding variability of health states, over-confidence in recall and insight, preference for preventive and compensatory directives over pure assessment results, and a disinclination towards time consuming self-monitoring as barriers to early detection. Our ethnographic studies of households coping with cognitive decline revealed a  tension between a desire for forecasting of what illness might lie ahead and a counter current of denial. Almost all caregivers and patients wished that they had received an earlier diagnosis to guide treatment and lifestyle choices, but they also acknowledged that they had overlooked blatant warning signs until the occurrence of a catastrophic incident (e.g. a car accident). This lag between  awareness and actual decline caused them to miss out on the critical window for initiation of treatments and planning that could have had a major impact on independence and quality of life. Ethnography and concept feedback participants attributed this denial in part to a fear of being diagnosed with a disease for which there is no cure. They also worried about the effect of this data on  insurers and other outside parties. Participants in the three cohorts included in our studies (boomers, healthy older adults, and older adults coping with illness themselves or in a spouse) were much more interested in, and less conflicted about, preventive and compensatory directives than pure assessment.

Perceptual biases also appear to impede traditional assessment and self monitoring. Ethnography participants reported consistently overestimating functioning before a catastrophic event and appeared, during the interview, to consistently underestimate functioning following detection of cognitive impairment Additionally, we observed probable over-confidence among healthy adults in their ability to recall behaviors and analyze their relationship to both environmental factors and well being. This confidence in recall and insight seemed exaggerated given findings that recall of frequent events is generally poor. As a result of these health perceptions, many of those interviewed felt that the time and discipline required for journaling (e.g. of eating, sleeping, mood, etc.) outweighed the benefits. Additionally, they expressed wariness of confronting or being reprimanded about what is already obvious
to them. They would prefer to lead investigations and develop strategies for improving their lives. Pervasive computing systems may enable this type of integrated, contextualized inquiry if they can also overcome the clinical and individual barriers that might otherwise impede adoption of the new technologies.

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