Table IV.

Descriptions and result summaries for effective (first tier) and promising studies

EVIDENCE TYPE	STUDY DESCRIPTION	RESULTS
Effective (1st) Kelly (2005)[43]	6 year community-level implementation of an integrated activity/environment monitoring system with medication reminders (historical controlled trial)	“Mainstreamed” a successful smart home system to anyone over 60 as a preventive measure. Increased quality of life for OAs*, reduced hospital admissions, reduced length of stay in hospitals and reduced length of stay in nursing homes due to preventive measures. (1.4 per 1000 West Lothian OAs in hospital beds vs 2.74 per 1000 in Scotland overall, 30 days mean duration stay vs. 112 days in Scotland overall)
Effective (1st) Tomita et al. (2007)[48]	2 year randomized controlled trial to evaluate the effectiveness of commercial smart home technology with sensing and automation capabilities to support independent aging in older adults	Intervention group had a significant higher cognitive level after controlling for age and initial cognitive level. 80.4% of the intervention group lived at home versus 65.7% of control group at study end. 82.4% reported the computer “very important”/14.7% “somewhat important” at study end. All intervention group participants accepted a computer, sensor software, a lighting system, chimes for security and medication reminders; Types of problem were related to person, computer, ×10 products and the home.
Effective (1st) Brownsell et al. (2008)[49]	12 month non-randomized controlled trial to evaluate the effectiveness of a sensing system for activity and environmental monitoring	Intervention group participants maintained times outside the home at 5 per week and increased time outside from 3.6 to 4 hours while control reduced times outside from 5 to 4.4 and decreased from 2.6 to 2.4 hours per week. Intervention group experienced a 1% increase in feeling safe during the day and a 5% increase at night while the control group experienced a 1% decrease during the day and 3% decrease at night. Intervention experienced 10% decrease in fear of crime while the control experienced a 6% decrease.
Promising Sixsmith (2000)[39]	3 month field study of a sensing system for activity monitoring	OAs indicated a high level of satisfaction with the system, 1/3 felt more independent and nearly 1/2 said it helped them stay living at home. All but one FM** was satisfied with the system. There were a high number of false alerts and some OAs misunderstood the capabilities of the technology.
Promising Alwan et al. (2006)[44]	4 month pilot study to evaluate the pyschosocial impact of an activity monitoring system adapted to an independent retirement community	Technology did not decrease participant QOL (OAs, FMs) or increase informal caregiver strain. Mean number of hours of care rose from 5.16 to 8.10, suggesting that wellness reports prompted greater involvement by FMs in OAs lives. 2 case studies indicate that lowered activity levels and increased restlessness could have prompted preventive measures prior to hospitalization.
Promising Rantz et al. (2008)[53]	Using retrospective data analysis, demonstrated the ability to detect health status decline using a sensing system from an ongoing longitudinal study of 2+ years.	Changes in heart rate and restlessness in one case were indicators of decline in health status. Increase and decrease in restlessness during and following cardiac rehabilitation could have indicated increased/decreased pain in another case.
Promising Glascock et al. (2007)[46]	Longitudinal study of a sensing system for activity monitoring at 8 installations (1 site for 6 months)	3 cases regarding detected falls, decreases in eating and increases in lavatory use prompted participant contact and preventive measures resulting in positive results.
Promising Mahoney et al. (2009)[54]	Pilot study implemented over 18 months (average 4 months/participant) to test a sensing system adapted to an independent retirement community setting and evaluate stakeholder perceptions	OAs and FMs felt the system addressed their needs and was not intrusive. Unexpectedly, for OAs there was a categorical drop from “strong agree” to “somewhat agree regarding feelings of security”. FMs reported slight increase in concern but decrease in time need to check on relatives. FMs suggested the ability to see the reason for “no activity” alerts. 5 of 10 FMs were willing to pay 60 USD/month. Water sensor alerts endorsed by staff.
Promising Rantz et al. (2009)[57]	Using retrospective data analysis, demonstrated the ability to detect health status decline using a sensing system from an ongoing longitudinal study of 3+ years.	In one case, an increase in bed restlessness prior to a fall could have been used to prompt assessment for an OA resident who was not feeling well. In another case, decreased activity and increased restlessness in a resident who experienced cognitive decline could have been used to raise levels of watchfulness.
Promising Skubic et al. (2009)[58]	Reported lessons learned from a 3+ year ongoing longitudinal study of a sensing system in a “living laboratory”.	Typical patterns of activity for an individual were monitored for changes. Detection of increased pulse pressure was consistent with cerebral cardiovascular incident in one case. Decreases in activity were consistent with depression in another. Changes in restlessness and bed tachypnea (breathing rate > 30bpm) were detected prior to a heart attack in another case. Changes in restlessness/tachnypea were detected before a surgery and returned to normal afterwards.
Promising Kim et al. (2010)[60]	Evaluated participant perceptions of sensor technology installed for 10 years in 4 different apartment buildings for older adults.	Participants felt comforted by sensor technology but did not think it changed the patterns of their lives. Residents often overestimated the capabilities of the technology.
Promising Kaye et al. (2011)[63]	Demonstrated feasibility of a large scale, longitudinal activity sensing project for older adults in their homes with average enrollment time of 33 months	Times/day walked past in-home sensor: 22, Mean walking speed: 61.0 cm/s, Fast walking: 96.0 cm/s, Slow walking: 36.2 cm/s, Average times out of home: 2/day for a mean of 208 minutes, Average computer use time when used: 76 minutes/day, Average days computer/use: 43% of days. 83% reported physical health problems using the online form. Over half reported at least one fall and 35% at least one trip to the hospital/ER. Oldest old were more likely to report a fall or cardiac issue versus young old.
Promising van Hoof et al. (2011)[65]	Investigated the use of ambient technologies by older adults enrolled for 8–23 months and the ability of technology to support aging in place	Participants had a greater sense of security after technology installation. One participant developed a fear of the equipment and had it removed after a year. Two participants were dissatisfied with false alerts but kept the technology for the increased feeling of safety. Some participants felt the technology was too loud.

^*OA = Older adult

^**FM = Family Member