Association between social asymmetry and depression in older adults: A phone Call Detail Records analysis

Abstract

Analyzing social interactions on a passive and non-invasive way through the use of phone call detail records (CDRs) is now recognized as a promising approach in health monitoring. However, deeper investigations are required to confirm its relevance in social interaction modeling. Particularly, no clear consensus exists in the use of the direction parameter characterizing the directed nature of interactions in CDRs. In the present work, we specifically investigate, in a 26-older-adults population over 12 months, whether and how this parameter could be used in CDRs analysis. We then evaluate its added-value for depression assessment regarding the Geriatric Depression Scale score assessed within our population during the study. The results show the existence of three clusters of phone call activity named (1) proactive, (2) interactive, and (3) reactive. Then, we introduce the notion of asymmetry that synthesizes these activities. We find significant correlations between asymmetry and the depressive state assessed in the older individual. Particularly, (1) reactive users are more depressed than the others, and (2) not depressed older adults tend to be proactive. Taken together, the present findings suggest the phone’s potential to be used as a social sensor containing relevant health-related insights when the direction parameter is considered.

Exploitation of Outgoing and Incoming Telephone Calls in the Context of Circadian Rhythms of Social Activity Among Elderly People: Observational Descriptive Study

“…Finally, a technical limitation is present in the size of the time interval used in our data analysis for investigating the persistence and synchronization of circadian rhythms over time. Although no clear consensus exists in the literature about the size of the time interval when analyzing temporal telephone data, previous studies [ 41 ] have reported that aggregating data over long time intervals (eg, several months) limits the effect of short-term variations in call patterns, thereby enhancing the robustness of the persistence analysis. Consequently, by splitting our 12-month data set into three equal 4-month intervals as performed in previous work [ 32 ], the results for persistence and synchronization are valid only for a 4-month interval.…”

“…This study involved a secondary analysis of previously published and unpublished data set analyses [ 41 - 43 ]. Our data set included 12 months of outgoing call detail records for 26 volunteers (20 women and 6 men; median age 84 years, range 71-91 years).…”

Gaining Insights Into the Estimation of the Circadian Rhythms of Social Activity in Older Adults From Their Telephone Call Activity With Statistical Learning: Observational Study (Preprint)

“…Data collection, volunteer recruitment, and data preprocessing followed the general principles set in previous investigations of this secondary analysis [39][40][41][42][43] and remain unchanged for consistency.…”

Exploitation of Outgoing and Incoming Telephone Calls in the Context of Circadian Rhythms of Social Activity Among Elderly People: Observational Descriptive Study (Preprint)

“…This study involved a secondary analysis of previously published and unpublished data set analyses [41][42][43]. Our data set included 12 months of outgoing call detail records for 26 volunteers (20 women and 6 men; median age 84 years, range 71-91 years).…”