Phone behaviour and its relationship to loneliness in older adults

Petersen, Jóhanna; Thielke, Stephen; Austin, Daniel; Kaye, Jeffrey

doi:10.1080/13607863.2015.1060947

Cited by 38 publications

(62 citation statements)

References 44 publications

(38 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Participants in high-score group receive less incoming calls at any time. Petersen et al (2015) also found that loneliness is tightly associated with incoming but not outgoing calls. Besides, lonely individuals tend to use healthy apps more frequently, which can provide them online and ubiquitous access to health care services, and this finding confirms that lonely people prefer to use health care system ( Geller et al, 1999 ).…”

Section: Discussionmentioning

confidence: 87%

How smartphone usage correlates with social anxiety and loneliness

Gao

Zhu

et al. 2016

PeerJ

View full text Add to dashboard Cite

Introduction: Early detection of social anxiety and loneliness might be useful to prevent substantial impairment in personal relationships. Understanding the way people use smartphones can be beneficial for implementing an early detection of social anxiety and loneliness. This paper examines different types of smartphone usage and their relationships with people with different individual levels of social anxiety or loneliness.Methods: A total of 127 Android smartphone volunteers participated in this study, all of which have agreed to install an application (MobileSens) on their smartphones, which can record user’s smartphone usage behaviors and upload the data into the server. They were instructed to complete an online survey, including the Interaction Anxiousness Scale (IAS) and the University of California Los Angeles Loneliness Scale (UCLA-LS). We then separated participants into three groups (high, middle and low) based on their scores of IAS and UCLA-LS, respectively. Finally, we acquired digital records of smartphone usage from MobileSens and examined the differences in 105 types of smartphone usage behaviors between high-score and low-score group of IAS/UCLA-LS.Results: Individuals with different scores on social anxiety or loneliness might use smartphones in different ways. For social anxiety, compared with users in low-score group, users in high-score group had less number of phone calls (incoming and outgoing) (Mann-Whitney U = 282.50∼409.00, p < 0.05), sent and received less number of text messages in the afternoon (Mann-Whitney U = 391.50∼411.50, p < 0.05), used health & fitness apps more frequently (Mann-Whitney U = 493.00, p < 0.05) and used camera apps less frequently (Mann-Whitney U = 472.00, p < 0.05). For loneliness, users in low-score group, users in high-score group had less number of phone calls (incoming and outgoing) (Mann-Whitney U = 305.00∼407.50, p < 0.05) and used following apps more frequently: health & fitness (Mann-Whitney U = 510.00, p < 0.05), system (Mann-Whitney U = 314.00, p < 0.01), phone beautify (Mann-Whitney U = 385.00, p < 0.05), web browser (Mann-Whitney U = 416.00, p < 0.05) and social media (RenRen) (Mann-Whitney >U = 388.50, p < 0.01).Discussion: The results show that individuals with social anxiety or loneliness receive less incoming calls and use healthy applications more frequently, but they do not show differences in outgoing-call-related features. Individuals with higher levels of social anxiety also receive less SMSs and use camera apps less frequently, while lonely individuals tend to use system, beautify, browser and social media (RenRen) apps more frequently.Conclusion: This paper finds that there exists certain correlation among smartphone usage and social anxiety and loneliness. The result may be useful to improve social interaction for those who lack social interaction in daily lives and may be insightful for recognizing individual levels of social anxiety and loneliness through smartphone usage behaviors.

show abstract

Section: Discussionmentioning

confidence: 87%

How smartphone usage correlates with social anxiety and loneliness

Gao

Zhu

et al. 2016

PeerJ

View full text Add to dashboard Cite

show abstract

“…We were also not able to differentiate between incoming calls and outgoing calls in this study as not all the phone companies we collected logs from stored this information. This was unfortunate as previous work has demonstrated that loneliness is more closely linked to the number of incoming calls than outgoing calls [39]. Future studies on loneliness in older adults should include incoming and outgoing calls separately.…”

Section: Discussionmentioning

confidence: 98%

A Smart-Home System to Unobtrusively and Continuously Assess Loneliness in Older Adults

Austin

Dodge

Riley

et al. 2016

IEEE J. Transl. Eng. Health Med.

Self Cite

View full text Add to dashboard Cite

Loneliness is a common condition in older adults and is associated with increased morbidity and mortality, decreased sleep quality, and increased risk of cognitive decline. Assessing loneliness in older adults is challenging due to the negative desirability biases associated with being lonely. Thus, it is necessary to develop more objective techniques to assess loneliness in older adults. In this paper, we describe a system to measure loneliness by assessing in-home behavior using wireless motion and contact sensors, phone monitors, and computer software as well as algorithms developed to assess key behaviors of interest. We then present results showing the accuracy of the system in detecting loneliness in a longitudinal study of 16 older adults who agreed to have the sensor platform installed in their own homes for up to 8 months. We show that loneliness is significantly associated with both time out-of-home (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} }{}$ {\beta } = -0.88$ \end{document} and \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} }{}$p<0.01$ \end{document}) and number of computer sessions (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} }{}$ {\beta } = 0.78$ \end{document} and \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} }{}$p<0.05$ \end{document}). \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} }{}$R^{2}$ \end{document} for the model was 0.35. We also show the model’s ability to predict out-of-sample loneliness, demonstrating that the correlation between true loneliness and predicted out-of-sample loneliness is 0.48. When compared with the University of California at Los Angeles loneliness score, the normalized mean absolute error of the predicted loneliness scores was 0.81 and the normalized root mean squared error was 0.91. These results represent first steps toward an unobtrusive, objective method for the prediction of loneliness among older adults, and mark the first time multiple objective behavioral measures that have been related to this key health outcome.

show abstract

“…Because loneliness may change in response to many life events and is closely related to social isolation, it may be more timely and informative to identify lonely individuals by tracking changes in the social network or other daily behaviors using unobtrusive monitoring techniques (Kaye et al, 2010; Petersen, Austin, Kaye, Pavel, & Hayes, 2014). For example, tracking call history would enable assessment of social network size and frequency of contact—the two major components of social isolation scales (Petersen, Thielke, Austin, & Kaye, 2015). Other behaviors that may relate to loneliness that can be tracked unobtrusively include time spent outside the home (Petersen et al, 2014; Petersen, Austin, Mattek, & Kaye, 2015), computer use (Amichai-Hamburger & Ben-Artzi, 2003), and sleep quality (Hawkley et al, 2010).…”

Section: Discussionmentioning

confidence: 99%

Longitudinal Relationship Between Loneliness and Social Isolation in Older Adults

et al. 2015

Self Cite

View full text Add to dashboard Cite

Objective To understand the longitudinal relationship between loneliness and isolation. Method Participants included 5,870 adults 65 years and older (M = 72.89 ± 5.59 years) from the first 5 years of the Cardiovascular Health Study. Loneliness was assessed using a dichotomized loneliness question. Social isolation was assessed using six items from the Lubben Social Network Scale. Yearly life events were included to assess abrupt social network changes. Mixed effects logistic regression was employed to analyze the relationship between isolation and loneliness. Results Higher levels of social isolation were associated with higher odds of loneliness, as was an increase (from median) in level of social isolation. Life events such as a friend dying were also associated with increased odds of loneliness. Discussion These results suggest that average level of isolation and increases in the level of isolation are closely tied to loneliness, which has implications for future assessment or monitoring of loneliness in older adult populations.

show abstract

Phone behaviour and its relationship to loneliness in older adults

Cited by 38 publications

References 44 publications

How smartphone usage correlates with social anxiety and loneliness

How smartphone usage correlates with social anxiety and loneliness

A Smart-Home System to Unobtrusively and Continuously Assess Loneliness in Older Adults

Longitudinal Relationship Between Loneliness and Social Isolation in Older Adults

Contact Info

Product

Resources

About