Johanna Petersen1, Stephen Thielke2, Daniel Austin3, Jeffrey Kaye3. 1. a Department of Biomedical Engineering , Oregon Health & Science University , Portland , OR , USA. 2. b Department of Psychiatry and Behavioural Sciences , University of Washington , Seattle , WA , USA. 3. c Department of Neurology and the Oregon Center for Aging and Technology , Oregon Health & Science University , Portland , OR , USA.
Abstract
OBJECTIVES: Loneliness and social isolation are two important health outcomes among older adults. Current assessment of these outcomes relies on self-report which is susceptible to bias. This paper reports on the relationship between loneliness and objective measures of isolation using a phone monitoring device. METHOD: Phone monitors were installed in the homes of 26 independent elderly individuals from the ORCATECH Life Laboratory cohort (age 86 ± 4.5, 88% female) and used to monitor the daily phone usage for an average of 174 days. Loneliness was assessed using the 20-item University of California Los Angeles (UCLA) Loneliness scale. A mixed effects negative binomial regression was used to model the relationship between loneliness and social isolation, as assessed using the total number of calls, controlling for cognitive function, pain, age, gender, and weekday. A secondary analysis examined the differential effect of loneliness on incoming and outgoing calls. RESULTS: The average UCLA Loneliness score was 35.3 ± 7.6, and the median daily number of calls was 4. Loneliness was negatively associated with telephone use (IRR = 0.99, p < 0.05). Daily phone use was also associated with gender (IRR = 2.03, p < 0.001) and cognitive status (IRR = 1.51, p < 0.001). The secondary analysis revealed that loneliness was significantly related to incoming (IRR = 0.98, p < 0.01) but not outgoing calls. CONCLUSIONS: These results demonstrate the close relationship between loneliness and social isolation, showing that phone behaviour is associated with emotional state and cognitive function. Because phone behaviour can be monitored unobtrusively, it may be possible to sense loneliness levels in older adults using objective assessments of key aspects of behaviour.
OBJECTIVES: Loneliness and social isolation are two important health outcomes among older adults. Current assessment of these outcomes relies on self-report which is susceptible to bias. This paper reports on the relationship between loneliness and objective measures of isolation using a phone monitoring device. METHOD: Phone monitors were installed in the homes of 26 independent elderly individuals from the ORCATECH Life Laboratory cohort (age 86 ± 4.5, 88% female) and used to monitor the daily phone usage for an average of 174 days. Loneliness was assessed using the 20-item University of California Los Angeles (UCLA) Loneliness scale. A mixed effects negative binomial regression was used to model the relationship between loneliness and social isolation, as assessed using the total number of calls, controlling for cognitive function, pain, age, gender, and weekday. A secondary analysis examined the differential effect of loneliness on incoming and outgoing calls. RESULTS: The average UCLA Loneliness score was 35.3 ± 7.6, and the median daily number of calls was 4. Loneliness was negatively associated with telephone use (IRR = 0.99, p < 0.05). Daily phone use was also associated with gender (IRR = 2.03, p < 0.001) and cognitive status (IRR = 1.51, p < 0.001). The secondary analysis revealed that loneliness was significantly related to incoming (IRR = 0.98, p < 0.01) but not outgoing calls. CONCLUSIONS: These results demonstrate the close relationship between loneliness and social isolation, showing that phone behaviour is associated with emotional state and cognitive function. Because phone behaviour can be monitored unobtrusively, it may be possible to sense loneliness levels in older adults using objective assessments of key aspects of behaviour.
Authors: Johanna Austin; Hiroko H Dodge; Thomas Riley; Peter G Jacobs; Stephen Thielke; Jeffrey Kaye Journal: IEEE J Transl Eng Health Med Date: 2016-06-10 Impact factor: 3.316
Authors: Johanna Petersen; Jeffrey Kaye; Peter G Jacobs; Ana Quinones; Hiroko Dodge; Alice Arnold; Stephen Thielke Journal: J Aging Health Date: 2015-10-21