Sleep, mood and sociability in a healthy population
Abstract
Sleep and mood problems have a considerable public health impact with serious societal and significant financial effects. In this work, we study the relationship between these factors in the everyday life of healthy young adults. More importantly, we look at these factors from a social perspective, studying the impact that couples have on each other and the role that face-to-face interactions play. We find that there is a significant bi-directional relationship between mood and sleep. More interestingly, we find that the spouse's sleep and mood may have an effect on the subject's mood and sleep. Further, we find that subjects whose sleep is significantly correlated with mood tend to be more sociable. Finally, we observe that less sociable subjects show poor mood more often than their more sociable contemporaries. These novel insights, especially those involving sociability, measured from quantified face-to-face interaction data gathered through smartphones, open up several avenues to enhance public health research through the use of latest wireless sensing technologies.
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Previous studies [15-18] have been performed on relatively small (approximately 100 participants) homogeneous (eg, university students) cohorts of participants over relatively short periods (8-10 weeks), which may limit their generalizability.
“Previous studies [15-18] have been performed on relatively small (approximately 100 participants) homogeneous (eg, university students) cohorts of participants over relatively short periods (8-10 weeks), which may limit their generalizability.”
From Predicting depressive symptom severity through individuals’ nearby Bluetooth device count data collected by mobile phones: preliminary longitudinal study (2021) · cites this paper as [16]
Moturu et al found that individuals with lower sociability (estimated by the NBDC) tend to report lower mood more often.
“Moturu et al found that individuals with lower sociability (estimated by the NBDC) tend to report lower mood more often [16].”
From Predicting depressive symptom severity through individuals’ nearby Bluetooth device count data collected by mobile phones: preliminary longitudinal study (2021) · cites this paper as [16]
Bluetooth features used in previous studies [15-18] have been limited to basic statistical features (eg, sum, mean, and standard deviation), which are unable to characterize some nonlinear aspects (such as complexity, regularity, and periodicity) of the Bluetooth data.
“Besides, Bluetooth features used in these studies [15-18] have been limited to basic statistical features (eg, sum, mean, and standard deviation), which are unable to characterize some nonlinear aspects (such as complexity, regularity, and periodicity) of the Bluetooth data.”
From Predicting depressive symptom severity through individuals’ nearby Bluetooth device count data collected by mobile phones: preliminary longitudinal study (2021) · cites this paper as [16]
The above three studies were all performed on the "Friends and Family" data set, including 8 weeks of mobile phone data from 117 participants living in a major US university's married graduate student residency.
“The above three studies were all performed on the “Friends and Family” data set, including 8 weeks of mobile phone data from 117 participants living in a major US university’s married graduate student residency.”
From Predicting depressive symptom severity through individuals’ nearby Bluetooth device count data collected by mobile phones: preliminary longitudinal study (2021) · cites this paper as [16]
Our study was performed on a larger (N=316) multicenter data set with a longer follow-up (median 4 months) than previous Bluetooth-related studies.
“Compared with previous Bluetooth-related studies [15-18], our study was performed on a larger (N=316) multicenter data set with a longer follow-up (median 4 months).”
From Predicting depressive symptom severity through individuals’ nearby Bluetooth device count data collected by mobile phones: preliminary longitudinal study (2021) · cites this paper as [16]
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- Authors
- Moturu, S. T., Khayal, I., Aharony, N., Pan, W., & Pentland, A.
- Affiliations
- MIT Media Lab (US)
- Masdar Institute of Science and Technology (AE)
- Venue
- 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society
- Publisher
- IEEE
- Published
- 2011-08
- Volume
- 2011
- Pages
- 5267-5270
- ISSN
- 2375-7477 (ISSN-L)
- OpenAlex
- W2056110495
- Cited by
- 35
- References
- 25
- Citations by year
- 2026: 1 · 2024: 1 · 2023: 2 · 2022: 3 · 2021: 4 · 2020: 2 · 2019: 3 · 2018: 2 · 2017: 3 · 2016: 3 · 2015: 4 · 2014: 2 · 2013: 2 · 2012: 1
- FWCI
- 3.56
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Sleep and related disorders
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Sleep and Work-Related Fatigue
- Life Sciences › Neuroscience › Endocrine and Autonomic Systems › Circadian rhythm and melatonin
- Keywords
- sleep, mood, sociability, couples, spousal influence, face-to-face interaction, smartphone sensing, wireless sensing, healthy young adults, bidirectional relationship
- MeSH terms
- Adult, Emotions, Female, Humans, Male, Massachusetts, Motor Activity, Reference Values, Sleep, Social Behavior, Polysomnography, Monitoring, Ambulatory, Young Adult
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