These results demonstrate for the first time the feasibility of engaging seniors in a large-scale deployment of in-home activity assessment technology and the successful collection of these activity metrics. We plan to use this platform to determine if continuous unobtrusive monitoring may detect incident cognitive decline.

Research Methods and Procedures:Participants, 2862 eligible overweight and obese (BMI ϭ 27 to 40 kg/m 2 ) members from four regions of Kaiser Permanente's integrated health care delivery system, were randomized to receive either a tailored expert system or information-only Web-based weight management materials. Weight change and program satisfaction were assessed by self-report through an Internet-based survey at 3-and 6-month follow-up periods. Results: Significantly greater weight loss at follow-up was found among participants assigned to the tailored expert system than among those assigned to the information-only condition. Subjects in the tailored expert system lost a mean of 3 Ϯ 0.3% of their baseline weight, whereas subjects in the information-only condition lost a mean of 1.2 Ϯ 0.4% (p Ͻ 0.0004). Participants were also more likely to report that the tailored expert system was personally relevant, helpful, and easy to understand. Notably, 36% of enrollees were African-American, with enrollment rates higher than the general proportion of African Americans in any of the study regions. Discussion: The results of this large, randomized control trial show the potential benefit of the Web-based tailored expert system for weight management compared with a Web-based information-only weight management program.

Objective: To evaluate the impact of exam‐room computers on communication between clinicians and patients. Design and Methods: Longitudinal, qualitative study using videotapes of regularly scheduled visits from 3 points in time: 1 month before, 1 month after, and 7 months after introduction of computers into the exam room. Setting: Primary care medical clinic in a large integrated delivery system. Participants: Nine clinicians (6 physicians, 2 physician assistants, and 1 nurse practitioner) and 54 patients. Results: The introduction of computers into the exam room affected the visual, verbal, and postural connection between clinicians and patients. There were variations across the visits in the magnitude and direction of the computer's effect. We identified 4 domains in which exam‐room computing affected clinician–patient communication: visit organization, verbal and nonverbal behavior, computer navigation and mastery, and spatial organization of the exam room. We observed a range of facilitating and inhibiting effects on clinician–patient communication in all 4 domains. For 2 domains, visit organization and verbal and nonverbal behavior, facilitating and inhibiting behaviors observed prior to the introduction of the computer appeared to be amplified when exam‐room computing occurred. Likewise, exam‐room computing involving navigation and mastery skills and spatial organization of the exam‐room created communication challenges and opportunities. In all 4 domains, there was little change observed in exam‐room computing behaviors from the point of introduction to 7‐month follow‐up. Conclusions: Effective use of computers in the outpatient exam room may be dependent upon clinicians' baseline skills that are carried forward and are amplified, positively or negatively, in their effects on clinician–patient communication. Computer use behaviors do not appear to change much over the first 7 months. Administrators and educators interested in improving exam‐room computer use by clinicians need to better understand clinician skills and previous work habits associated with electronic medical records. More study of the effects of new technologies on the clinical relationship is also needed.

The Microsoft Kinect camera is becoming increasingly popular in many areas aside from entertainment, including human activity monitoring and rehabilitation. Many people, however, fail to consider the reliability and accuracy of the Kinect human pose estimation when they depend on it as a measuring system. In this paper we compare the Kinect pose estimation (skeletonization) with more established techniques for pose estimation from motion capture data, examining the accuracy of joint localization and robustness of pose estimation with respect to the orientation and occlusions. We have evaluated six physical exercises aimed at coaching of elderly population. Experimental results present pose estimation accuracy rates and corresponding error bounds for the Kinect system.

Background Mild disturbances of higher order activities of daily living are present in people diagnosed with mild cognitive impairment (MCI). These deficits may be difficult to detect among those still living independently. Unobtrusive continuous assessment of a complex activity such as home computer use may detect mild functional changes and identify MCI. We sought to determine whether long-term changes in remotely monitored computer use differ in persons with MCI in comparison to cognitively intact volunteers. Methods Participants enrolled in a longitudinal cohort study of unobtrusive in-home technologies to detect cognitive and motor decline in independently living seniors were assessed for computer usage (number of days with use, mean daily usage and coefficient of variation of use) measured by remotely monitoring computer session start and end times. Results Over 230,000 computer sessions from 113 computer users (mean age, 85; 38 with MCI) were acquired during a mean of 36 months. In mixed effects models there was no difference in computer usage at baseline between MCI and intact participants controlling for age, sex, education, race and computer experience. However, over time, between MCI and intact participants, there was a significant decrease in number of days with use (p=0.01), mean daily usage (~1% greater decrease/month; p=0.009) and an increase in day-to-day use variability (p=0.002). Conclusions Computer use change can be unobtrusively monitored and indicate individuals with MCI. With 79% of those 55–64 years old now online, this may be an ecologically valid and efficient approach to track subtle clinically meaningful change with aging.

To be suitable for informing digital behavior change interventions, theories and models of behavior change need to capture individual variation and changes over time. The aim of this paper is to provide recommendations for development of models and theories that are informed by, and can inform, digital behavior change interventions based on discussions by international experts, including behavioral, computer, and health scientists and engineers. The proposed framework stipulates the use of a state-space representation to define when, where, for whom, and in what state for that person, an intervention will produce a targeted effect. The “state” is that of the individual based on multiple variables that define the “space” when a mechanism of action may produce the effect. A state-space representation can be used to help guide theorizing and identify crossdisciplinary methodologic strategies for improving measurement, experimental design, and analysis that can feasibly match the complexity of real-world behavior change via digital behavior change interventions.

The examination room computers appeared to have positive effects on physician-patient interactions related to medical communication without significant negative effects on other areas such as time available for patient concerns. Further study is needed to better understand HIT use during outpatient visits.

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