Conference PaperPDF Available

Relationship between social interaction and mental health

December 2011

DOI:10.1109/SII.2011.6147454

Conference: System Integration (SII), 2011 IEEE/SICE International Symposium on

Authors:

Eisuke Ono

Tokyo Institute of Technology

Takayuki Nozawa

University of Toyama

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In order to explore the relationship between human social interaction and mental health, we investigated the correlations between the amount of face-to-face contact time and quantified mental health. Social interaction data were obtained by wearable sensing system for two organizations in Japan. In this study, we regarded face-to-face contact between individuals as social interaction. The mental health of individuals was measured by psychological questionnaire. We found that the social behavioral property of individuals tended to reflect quantified stress in both organizations. The results suggest the possibility that people who experience large amounts of social interaction tend to have less stress.

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Relationship between Social Interaction and Mental Health

Eisuke Ono, Takayuki Nozawa, Taiki Ogata, Masanari Motohashi, Naoki Higo, Tetsuro Kobayashi,

Kunihiro Ishikawa, Koji Ara, Kazuo Yano, and Yoshihiro Miyake

Abstract— In order to explore the relationship between hu-

man social interaction and mental health, we investigated the

correlations between the amount of face-to-face contact time

and quantiﬁed mental health. Social interaction data were

obtained by wearable sensing system for two organizations

in Japan. In this study, we regarded face-to-face contact

between individuals as social interaction. The mental health

of individuals was measured by psychological questionnaire.

We found that the social behavioral property of individuals

tended to reﬂect quantiﬁed stress in both organizations. The

results suggest the possibility that people who experience large

amounts of social interaction tend to have less stress.

I. INTRODUCTION

Data on human social behavior are now readily avail-

able. Human behavior has been investigated statistically

and dynamically, enabled by developments in sensing and

information technologies [1]. Interevent time distributions of

human activities such as communication, trade transactions,

and library loans have been found to follow power-law [2],

[3]. Although the statistical structure of human behavior has

been partially revealed, the psychological or social meaning

of the structure is not clear yet.

In social psychology, some previous studies have inves-

tigated the relation between social relationship and psy-

chological state. It has been suggested that ofﬁce layout

arrangement encourages employee satisfaction and improves

work satisfaction [4]. Social capital and mental illness were

also found to relate to each other [5]. Social interaction

and psychological state were indicated to be important for

maintaining quality of life. However, previous studies had

technical limitations to measure observable social interaction

accurately [5].

Manuscript received October 11, 2011.

E. Ono, M. Motohashi, N. Higo and Y. Miyake are with the Department

of Computational Intelligence and Systems Science, Tokyo Institute of

Technology, Yokohama, Japan.

(e-mail: ono@myk.dis.titech.ac.jp, motohashi@myk.dis.titech.ac.jp,

higo@myk.dis.titech.ac.jp, miyake@dis.titech.ac.jp)

T. Nozawa is with the Institute of Development, Aging and Cancer,

Tohoku University, Sendai, Japan. (e-mail: nozawa@idac.tohoku.ac.jp)

T. Ogata is with the Intelligent Modeling Laboratory, the University of

Tokyo, Tokyo, Japan and with the Department of Computational Intelligence

and Systems Science, Interdisciplinary Graduate School of Science and En-

gineering, Tokyo Institute of Technology. (e-mail: ogata@iml.u-tokyo.ac.jp)

T. Kobayashi is with the National Institute of Informatics, Tokyo, Japan.

(e-mail: k-tetsu@nii.ac.jp)

K. Ishikawa is with the Department of Human System Science, Graduate

School of Decision Science and Technology, Tokyo Institute of Technology,

Tokyo, Japan. (e-mail: ishikawa@hum.titech.ac.jp )

K. Ara and K. Yano are with the Central Research Labora-

tory, Hitachi, Ltd., Tokyo, Japan. (e-mail: koji.ara.he@hitachi.com,

kazuo.yano.bb@hitachi.com)

Nakamura et al. found that the resting duration distribution

of human physical activity obeyed power-law. [6], [7]. They

also found that the scaling exponent of resting duration

distribution of depressed patients was statistically lower than

that of healthy people. These ﬁndings suggest that depressed

patients tend to remain in their resting state more than healthy

people.

Nozawa et al. investigated the relationship between the

physical activity of individuals and their social interaction

[8]. In their study, social interaction was deﬁned as the

amount of face-to-face contact time. Their results suggest the

possibility that social context of individuals can be evaluated

from their physical activity patterns. In other words, the

effect of social relationship on individual physical activity

state was indicated.

The statistical structure of human social behavior possibly

reﬂects our qualitative states such as mental health and

sociality. The effect of social interaction on mental health

of individuals is not clear quantitatively yet. What does

interacting with others mean for our psychological states?

In this research, we focus on the relationship between

observable social interaction and mental health. We used

two sets of data measured in Japanese organizations. Our

data are unique in that they are records of face-to-face

interaction, measured by using a wearable sensing system.

Simultaneously, we conducted a questionnaire to measure

individual mental health. We propose a hypothesis that the

amount of social interaction and mental health are related

to each other. The purpose of this research is to verify the

hypothesis by investigating the correlation between social

interaction and mental health.

II. METHODS

A. Data

We analyzed two sets of face-to-face interaction data. The

social interaction data were provided by the Central Research

Laboratory, Hitachi, Ltd., Japan. The sets of data include two

organizations in Japan. The ﬁrst is a consulting ﬁrm (Org.

A). In Org. A, 136 participants were objects of analysis.

The data were measured from January 1, to February 22,

2011. The second is a nursing home (Org. B). In Org.

B, 50 participants were objects of analysis. The data were

measured from March 1, to March 31, 2011. People in Org.

B were separated into two different groups: staff and elderly

users. The data were collected anonymously and analyzed.

The summary of organization is shown in Table I.

- 246 - SI International 2011

Fig. 1. Device used in the measurement of social interaction. The

device contains an infrared sensor and detects face-to-face contact between

participants only if they are within 2 (m) and facing each other.

TABLE I

ORGANIZATION SUMMARY.THE NUMBER IN PARENTHESES IS THE

NUMBER OF ELDERLY USERS IN ORG.B.

Number of Number of Observation Category of

participants valid answers period organization

Org. A 136 57 2011/1/5- Consulting

2011/2/22 ﬁrm

Org. B 50(36) 49(35) 2011/3/1- Nursing home

2011/3/31 for the elderly

B. Social interaction

1) Measurement method: In order to measure social inter-

action as conversation events, we used the Business Micro-

scope, which is a wearable sensing system developed by the

Central Research Laboratory, Hitachi, Ltd [9]. The Business

Microscope contains an infrared sensor, and its shape is

similar to a name tag as shown in Fig. 1. Each participant

wore the name tag around the neck and placed at the chest.

The infrared sensor can detect face-to-face contact between

participants if they are within 2 (m) of one another. The

infrared sensor only senses the other within a 120∘circular

area in front of the name tag, and the system records face-

to-face contact events cumulatively when two individuals

are facing each other. We regard the amount of face-to-

face contact as a feature of observable social interaction. It

should be noted that the sensor records the face-to-face state

as one minute even if a momentary contact was detected

between participants. In other words, the time resolution of

the system is equal to 1 (min). Face-to-face interaction logs

were gathered through the whole measurement period. Then,

the amount of face-to-face contact time between every pair of

participants was obtained for the whole measurement period

in each organization.

2) Analysis method: Nozawa et al. investigated social

interaction in an ofﬁce setting [8]. They analyzed social in-

teraction using the social network analysis method. Inspired

by their previous study, we regard the amount of social

interaction between participants as connection weight in the

Fig. 2. Example of the calculation of social interaction characteristics

social network. For instance, if the total face-to-face contact

time between 𝑖and 𝑗is 100 (min), the connection weight

between 𝑖and 𝑗is 100, denoted as 𝑓𝑖𝑗 in (1). However,

it was problematic to use face-to-face contact time as a

weighted edge because the sensor-wearing time depended

on the participants. To overcome individual differences, a

normalized matrix 𝐺was adopted as an adjacency matrix

for analysis.

𝐺=[𝑔𝑖𝑗]=[(𝑓𝑖𝑗

𝑢𝑖)] (1)

This matrix 𝐺was obtained by dividing each row of

𝐹=[𝑓𝑖𝑗 ]with 𝑢𝑖, where 𝑓𝑖𝑗 represents the total face-to-

face contact time between participants 𝑖and 𝑗through the

whole measurement period and 𝑢𝑖represents the total sensor-

wearing time of participant 𝑖.

We calculated in-degree centrality 𝐶𝑖𝑛 and out-degree

centrality 𝐶𝑜𝑢𝑡 to characterize the quality of each participant

in the social network based on the method of [8]. In-degree

centrality 𝐶𝑖𝑛 was calculated using (2).

𝐶𝑖𝑛(𝑖;𝐺)=∑

𝑗

𝑔𝑗𝑖 =∑

𝑗

𝑓𝑗𝑖

𝑢𝑗

(2)

𝐶𝑖𝑛 quantiﬁes the individual property that a person has been

required to contact from other people. Out-degree centrality

𝐶𝑜𝑢𝑡 was calculated using (3).

𝐶𝑜𝑢𝑡(𝑖;𝐺)=∑

𝑗

𝑔𝑖𝑗 =1

𝑢𝑖∑

𝑗

𝑓𝑖𝑗 (3)

𝐶𝑜𝑢𝑡 quantiﬁes the individual property that the person has

dedicated to social relationship. An example of calculation

of 𝐶𝑖𝑛 and 𝐶𝑜𝑢𝑡 is shown in Fig. 2. These two centralities

were the characteristics for social interaction analysis.

C. Mental health

1) Participants and measurement periods: A question-

naire to measure mental health was conducted in each

organization. In Org. A, 57 responses were obtained from

- 247 - SI International 2011

TABLE II

EXAMPLES AND SUBSCALE FOR QOL AND SCL

Psychological Scale Subscale An Example of Statements

Stress Check List (SCL) Psychological Stress Obsession Obsessed with things

Inattention Worried about carelessness

Social Stress Interpersonal Avoidance Feeling worried about meeting someone

Interpersonal Nervousness Feeling nervous to meet someone

Physical Stress Tired Feeling Feeling tired

Sleep Disorder Trouble falling asleep

Quality of Life (QOL) Life Satisfaction Satisﬁed with your life

Motivational Life Having dream for your future

0.1 0.2 0.3 0.4 0.5

Cin

SCL

R = −0.270

(p < .05)

(a) 𝐶𝑖𝑛 and SCL (N= 57, ofﬁce workers in Org. A)

0.5 1.0 1.5 2.0

Cout

SCL

R = −0.377

(p < .05)

(b) 𝐶𝑜𝑢𝑡 and SCL (N=35, elderly users in Org. B)

Fig. 3. Scatter diagrams showing the relationship between observable social interaction and degree of stress

136 participants. The answers were measured from February

7 to February 14, 2011. In Org. B, 49 responses were

obtained from 50 participants. The responses were measured

from March 4 to March 15, 2011. In Org. B, 35 answers

were from elderly users, 14 were from staff.

2) Measurement method: In this research, the Mental

Health Pattern (MHP) scale developed by Hashimoto et al.

was adopted for the contents of questionnaire. Validity and

reliability of the MHP scale have already been proven in

their research [10], [11]. The MHP scale contains degree of

stress and degree of life satisfaction. The Stress Checklist

(SCL) scale and Quality of Life (QOL) scale were used to

measure. The SCL scale has six subscales. QOL scale has

two subscales. Examples of statements are shown in Table

II. Each subscale had ﬁve questions. The total number of

the questions was 40. During the procedure, the participant

selected from four options: strongly agree,agree,disagree

and strongly disagree. The answers were scored from four

points (strongly agree) to one point (strongly disagree).

Reversed question items were calculated by reversing the

points.

III. RESULTS

We found a statistically signiﬁcant correlation between

amount of social interaction and individual mental health.

Pearson’s correlation coefﬁcients are presented in Table III.

Notably, a signiﬁcant negative correlation between 𝐶𝑖𝑛 and

SCL was observed in Org. A (p<.05). In addition, a

signiﬁcant negative correlation between 𝐶𝑜𝑢𝑡 and SCL was

observed in the cluster of elderly users in Org. B (p<.05).

Slight positive correlations between social interaction and

QOL were observed for both organizations.

Two diagrams and each correlation coefﬁcient R are

presented for precise observation of the correlations. Scatter

diagrams describing the relation between social interaction

and degree of stress are shown in Fig. 3. First, the result

of Org. A is presented. The x-axis is 𝐶𝑖𝑛 and the y-axis is

SCL, as shown in Fig. 3(a). A negative correlation tendency

is observed. Second, the result of the cluster of elderly users

in Org. B is presented. The x-axis is 𝐶𝑜𝑢𝑡 and the y-axis is

SCL, as shown in Fig. 3(b). A negative correlation tendency

is observed. Regression lines were drawn in each ﬁgure to

aid understanding.

- 248 - SI International 2011

TABLE III

CORRELATION COEFFICIENTS BETWEEN SOCIAL INTERACTION AND

MENTAL HEALTH

Organization Mental Scale Cin Cout

Org A SCL *-0.270 -0.069

QOL 0.060 0.067

Org B(staff) SCL -0.089 0.184

QOL 0.291 0.108

Org B(elderly users) SCL -0.058 *-0.377

QOL 0.124 0.129

∗:p<.05

IV. DISCUSSION

The results shows that the amount of social interaction is

correlated to individual mental health. In particular, we found

that the degree of stress (SCL) possibly reﬂects participants’

behavioral property. These results support the hypothesis that

there is a correlation between social interaction and mental

health.

However, the degree of the correlation coefﬁcient depends

on the organization or cluster as shown in Table III. The

correlation coefﬁcient of the elderly users cluster in Org. B

was larger than that of the staff cluster. In addition, the calcu-

lated centrality values of Org. B were higher than the those

of Org. A. We assume that centrality value differences were

caused by the organization’s characteristics and shortness of

the measurement period.

The results indicate that social supports were possibly

exchanged through face-to-face social interaction. Social

support means supports as help, advice that is exchanged

through social relationships. Social support has been consid-

ered to be a buffer for stress generated in social life [12].

Allen et al. also reported that an open-space layout in an

ofﬁce setting encouraged communication and improved ease

of communication [4]. The results in this research support

the previous studies in social psychology.

Findings in this research are new because we investigated

the relationship between social relation and psychological

state quantitatively. The results suggest that not only physical

activity, but also individual mental health possibly reﬂects the

amount of social interaction. Nozawa et al. found signiﬁcant

positive correlations between the degree of physical resting

state and network centralities, suggesting the effect of social

relationship on individual physical activity [8]. Our results

added psychological meaning on their previous study.

In this research, we did not consider individual attribute

such as sex, age, and position. The experiment design also

should be modiﬁed. There is still a possibility that the results

occurred because of other causes such as home problems.

Deeper investigations must be done in the future work.

V. CONCLUSION

In order to explore the relationship between observable

social interaction and psychological state, we have conducted

a correlation analysis of the amount of face-to-face contact

time and quantiﬁed mental health. Signiﬁcant negative corre-

lations between the amount of social interaction and mental

health were observed. These results suggest that people who

interact with others relatively tended to have less stress.

There has not been a study of how the amount of observ-

able social interaction is mutually related to psychological

states. We have ﬁrst partially clariﬁed the relationship.

VI. ACKNOWLEDGMENTS

This work was supported by the Homo Contribuence

Research and Development Institute.

REFERENCES

[1] C. Cattuto, W. Van den Broeck, A. Barrat, V. Colizza, J.-F. Pinton,

and A. Vespignani, “Dynamics of Person-to-Person Interactions from

Distributed RFID Sensor Networks,” PLoS ONE, 5, e11596, 2010.

[2] A. L. Barabasi, “The Origin of Bursts and Heavy Tails in Human

Dynamics,” Nature (London), vol. 435, pp. 207-211, 2005.

[3] D. Rybski, S.V. Buldyrev, S. Havlin, F. Liljeros, and H. A. Makse,

“Scaling Laws of Human Activity Patterns on the Dynamics of

Information Diffusion,” Proceedings of National Academy of Science

U.S.A., vol. 106, 12640, 2009.

[4] T. J. Allen, P. G. Gerstberger, “A Field Experiment to Improve

Communications in a Product Engineering Department: the Non-

territorial Ofﬁce,” The Journal of the Human Factors and Ergonomics

Society, Vol. 15, Number 5, pp. 487-498, 1973.

[5] M. J. D. Silva, K. McKenzie, T. Harpham, S. R. A. Huttly, “Social

capital and mental illness: a systematic review,” Journal of Epidemiol

Community Health , vol. 59, pp. 619-627, 2005.

[6] T. Nakamura, K. Kiyono, K. Yoshiuchi, R. Nakahara, Z. R. Struzik, Y.

Yamamoto, “Universal scaling law in human behavioral organization,”

Physical Review, Letter, vol. 99, 138103-1-4, 2007.

[7] T. Nakamura, K. Kiyono, K. Yoshiuchi, R. Nakahara, Z. R. Struzik,

Y. Yamamoto, “Of mice and men-universality and break down of

behavioral organization,” PLoS One, vol. 3, e2050-1-8, 2008.

[8] T. Nozawa, N. Higo, T. Ogata, K. Ara, K. Yano, Y. Miyake, “Rela-

tionship between characteristics of individual physical activity pattern

and social interaction,” 11th SICE System Integration Division Annual

Conference, 2G2-3, 2010.

[9] R. Otsuka, K. Yano, N. Sato, “An organization topographic map for

visualizing business hierarchical relationships,” IEEE Paciﬁc Visual-

ization Symposium 2009 (PaciﬁcVis ’09), April 20-23, Beijing, China,

pp. 25-32, 2009.

[10] K. Hashimoto, M. Tokunaga, “Development of a diagnostic inventory

for Mental Health Pattern (MHP): reliability and validity of the MHP

Scale,” Japan Health Society, vol. 21, pp. 53-62, 1999.

[11] K. Hashimoto, M. Tokunaga, S. Takayanagi, “A study on character-

istics of Mental Health Pattern,” Journal of Health Science, Kyushu

University, vol. 16, pp. 49-56, 1994.

[12] T. C. Antonucci, J. E. Lansford, K. J. Ajrouch, Social support,

Encyclopedia of stress, San Diego, CA: Academic Press, pp. 479-482,

2000.

- 249 - SI International 2011

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Sep 2020

Duy Tran Hoang Le

Recent changes in Vietnam’s higher education system and challenges at university put Vietnamese students’ mental health at risk. In the psychological literature, social integration and relationship expectancies (attachment styles) are predictive of mental health among Western university students. However, these patterns are unclear for an Asian population, like the Vietnamese, who are thought to have a ‘collective’ or ‘interdependent’ view of the self (interdependent self-construal). The present study aimed to investigate the impact of social integration and attachment insecurities (anxiety and avoidance) on the psychological symptoms of Australian and Vietnamese undergraduates and how their self-construal profiles explain potential differences in results across cultures. Participants were 542 first- and second-year university students (245 Australian and 297 Vietnamese) who completed self-report measures administered online. Data showed cross-cultural measurement invariance only for the mental health concept and poor psychometric properties for the self-construal scale, leading to separate analyses for each cultural group and the exclusion of the self-construal factor from the statistical analyses. Overall, the results emphasised the role of attachment anxiety and the cognitive aspect of social integration in student’s mental health. Specifically, attachment insecurities were predictive of social integration among students, although this effect was less consistent for attachment avoidance. Attachment anxiety influenced student’s mental health both directly and indirectly through social integration. The impact of attachment avoidance on mental health was indirect and only significant for the Vietnamese data. The cognitive aspect of social integration directly predicted psychological symptoms and played the main role in mediating the attachment – mental health link. These roles appeared weaker and less consistent for the behavioural side of social integration. The discussion addresses differences in the mental health profile and the conception of attachment across cultures, possible explanations for variables’ interactions especially in the Vietnamese data, and implications of the current study on mental health services, university policies, and future research.

Social Interaction on Patients with Schizophrenia in Psychiatric Hospital

Article

Full-text available

Jan 2020

Cecilia Indri Kurniasari

Social interaction is one of important indicator in the recovery process of mental patients, especially in patients with schizophrenia. Active social interactions can help patients with schizophrenia to socialize, while less active social interactions can cause social isolation to the risk of suicide. The purpose of this study was to determine the social interaction of patients with schizophrenia in psychiatric hospital. The number of participant in this study were 52 patients. Sampling with a purposive sampling technique. Data were collected using Social Interaction Questionnaire and Behavior Observation Sheet consisting of 18 statements. The analysis of this study was using univariate analysis with table of frequency distribution. The results showed that social interactions in schizophrenia patients were 45 patients with less active interacting categories, 5 patients with moderately active interacting categories, and 2 patients with active interacting categories. The results of the study can be used as a reference in determining appropriate nursing therapy in increasing social interaction in schizophrenia patients in mental hospitalsKeywords: social interaction; social psychological factors; schizophrenia;

PENGARUH TERAPI REMINISCENCE TERHADAP HARAPAN HIDUP LANSIA

Article

Full-text available

Dec 2021

Penelitian ini yaitu sesuai dengan hasil survei pendahuluan yang dilakukan oleh penulis pada tanggal 5 juli 2021 terhadap 30 lansia di Panti Werdha Welas Asih Singaparna Kabupaten Tasikmalaya menyebutkan bahwa harapan hidup lansia di Panti Werdha Welas Asih Singaparna Kabupaten Tasikmalaya ada pada kategori harapan hidup rendah sebelum diberikan intervensi terapi reminiscence yaitu sebanyak 14 orang (47%) dan setelah diberikan intervensi terapi reminiscence ada pada kategori harapan hidup sedang yaitu sebanyak 26 orang (87%) yang menunjukan adanya peningkatan. Penelitian ini bertujuan untuk mengetahui harapan hidup lansia di Panti Werdha Welas Asih Singaparna Kabupaten Tasikmalaya sebelum dan setelah diberikan intervensi terapi reminiscence. Metode yang digunakan adalah Quasi Experimental dengan jumlah populasi sebanyak 30 lansia di Panti Werdha Welas Asih Singaparna Kabupaten Tasikmalaya. Data hasil penelitian dianalisa menggunakan uiji Paired T. Hasil penelitian menunjukan bahwa hasil uji statistic didapatkan sig (2-tailed) sebesar 0,000 (a < 0,05). Hal ini menunjukan bahwa Ho ditolak yang artinya ada pengaruh yang signifikan antara terapi reminiscence terhadap harapan hidup lansia di Panti Werdha Welas Asih Singaparna Kabupaten Tasikmalaya, dan disarankan untuk lansia yang memiliki harapan hidup rendah, diharapkan lebih berusaha untuk meningkatkan harapan hidupnya. Pembahasan terkait pengaruh terapi reminiscence terhadap harapan hidup lansia dijadikan tambahan kepustakaan di bidang ilmu keperawatan, agar dapat memperluas pengetahuan mahasiswa dalam mempelajarinya.

Dynamics of Person-to-Person Interactions from Distributed RFID Sensor Networks

Article

Full-text available

Jul 2010
PLOS ONE

Digital networks, mobile devices, and the possibility of mining the ever-increasing amount of digital traces that we leave behind in our daily activities are changing the way we can approach the study of human and social interactions. Large-scale datasets, however, are mostly available for collective and statistical behaviors, at coarse granularities, while high-resolution data on person-to-person interactions are generally limited to relatively small groups of individuals. Here we present a scalable experimental framework for gathering real-time data resolving face-to-face social interactions with tunable spatial and temporal granularities. We use active Radio Frequency Identification (RFID) devices that assess mutual proximity in a distributed fashion by exchanging low-power radio packets. We analyze the dynamics of person-to-person interaction networks obtained in three high-resolution experiments carried out at different orders of magnitude in community size. The data sets exhibit common statistical properties and lack of a characteristic time scale from 20 seconds to several hours. The association between the number of connections and their duration shows an interesting super-linear behavior, which indicates the possibility of defining super-connectors both in the number and intensity of connections. Taking advantage of scalability and resolution, this experimental framework allows the monitoring of social interactions, uncovering similarities in the way individuals interact in different contexts, and identifying patterns of super-connector behavior in the community. These results could impact our understanding of all phenomena driven by face-to-face interactions, such as the spreading of transmissible infectious diseases and information.

The Origins of Bursts and Heavy Tails in Human Dynamics

Article

Full-text available

Jun 2005
NATURE

Albert-Laszlo Barabasi

The dynamics of many social, technological and economic phenomena are driven by individual human actions, turning the quantitative understanding of human behaviour into a central question of modern science. Current models of human dynamics, used from risk assessment to communications, assume that human actions are randomly distributed in time and thus well approximated by Poisson processes. In contrast, there is increasing evidence that the timing of many human activities, ranging from communication to entertainment and work patterns, follow non-Poisson statistics, characterized by bursts of rapidly occurring events separated by long periods of inactivity. Here I show that the bursty nature of human behaviour is a consequence of a decision-based queuing process: when individuals execute tasks based on some perceived priority, the timing of the tasks will be heavy tailed, with most tasks being rapidly executed, whereas a few experience very long waiting times. In contrast, random or priority blind execution is well approximated by uniform inter-event statistics. These finding have important implications, ranging from resource management to service allocation, in both communications and retail.

Social Capital and Mental Illness: A Systematic Review

Article

Full-text available

Sep 2005

The concept of social capital has influenced mental health policies of nations and international organisations despite its limited evidence base. This papers aims to systematically review quantitative studies examining the association between social capital and mental illness. Twenty electronic databases and the reference sections of papers were searched to identify published studies. Authors of papers were contacted for unpublished work. Anonymised papers were reviewed by the authors of this paper. Papers with a validated mental illness outcome and an exposure variable agreed as measuring social capital were included. No limitations were put on date or language of publication. Twenty one studies met the inclusion criteria for the review. Fourteen measured social capital at the individual level and seven at an ecological level. The former offered evidence for an inverse relation between cognitive social capital and common mental disorders. There was moderate evidence for an inverse relation between cognitive social capital and child mental illness, and combined measures of social capital and common mental disorders. The seven ecological studies were diverse in methodology, populations investigated, and mental illness outcomes, making them difficult to summarise. Individual and ecological social capital may measure different aspects of the social environment. Current evidence is inadequate to inform the development of specific social capital interventions to combat mental illness.

Universal Scaling Law in Human Behavioral Organization

Article

Full-text available

Oct 2007

We describe the nature of human behavioral organization, specifically how resting and active periods are interwoven throughout daily life. Active period durations with physical activity count successively above a predefined threshold, when rescaled with individual means, follow a universal stretched exponential (gamma-type) cumulative distribution with characteristic time, both in healthy individuals and in patients with major depressive disorder. On the other hand, resting period durations below the threshold for both groups obey a scale-free power-law cumulative distribution over two decades, with significantly lower scaling exponents in the patients. We thus find universal distribution laws governing human behavioral organization, with a parameter altered in depression.

Of Mice and Men — Universality and Breakdown of Behavioral Organization

Article

Full-text available

Feb 2008
PLOS ONE

Mental or cognitive brain functions, and the effect on them of abnormal psychiatric diseases, are difficult to approach through molecular biological techniques due to the lack of appropriate assay systems with objective measures. We therefore study laws of behavioral organization, specifically how resting and active periods are interwoven throughout daily life, using objective criteria, and first discover that identical laws hold both for healthy humans subject to the full complexity of daily life, and wild-type mice subject to maximum environmental constraints. We find that active period durations with physical activity counts successively above a predefined threshold, when rescaled with individual means, follow a universal stretched exponential (gamma-type) cumulative distribution, while resting period durations below the threshold obey a universal power-law cumulative distribution with identical parameter values for both of the mammalian species. Further, by analyzing the behavioral organization of mice with a circadian clock gene (Period2) eliminated, and humans suffering from major depressive disorders, we find significantly lower parameter values (power-law scaling exponents) for the resting period durations in both these cases. Such a universality and breakdown of the behavioral organization of mice and humans, revealed through objective measures, is expected to facilitate the understanding of the molecular basis of the pathophysiology of neurobehavioral diseases, including depression, and lay the foundations for formulating a range of neuropsychiatric behavioral disorder models.

A Field Experiment to Improve Communications in a Product Engineering Department: The Nonterritorial Office1

Article

Oct 1973

A year-long investigation was undertaken to determine the impact, of a radical new scheme of office layout on work-related behavior, communication, and performance. The office layout under investigation is best described as “nonterritorial”. It is an open floor plan arrangement, but goes far beyond the traditional open-space office, removing not only office walls, but most permanent stations as well. Employees (product engineers) work at large round tables, which are distributed through the office area, and may locate themselves anywhere that they wish on any given day, or at different times during a day. The experiment was successful to the extent that employees preferred the new arrangement over the traditional one- and two-person offices they had previously occupied and that communication within the department increased significantly. It was unsuccessful in that no measurable increase in departmental performance was registered over the period of the study.

An organization topographic map for visualizing business hierarchical relationships

Conference Paper

May 2009

Visualization of the actual conditions of an organization is a very challenging issue. We propose a new system called a Business Microscope that senses the activities of people in an organization and provides visual feedback to users. We use name-tag shaped sensor nodes to measure face-to-face interaction between employees. The massive amount of data collected by the sensor-network terminal are signal-processed by the server and displayed as an organization's topographic map that displays the frequencies of organizational activities. To depict the organization's topographic map, our system creates a novel relation tree using the interaction data from all pairs of members. In this kind of map, some groups in the organization hierarchically form islands. Members in those islands who have relationships with many others form mountains that are plotted with contours. We can comprehend the actual conditions of organizations from our topographic map. We tested our technique in several experiments to evaluate this system.

Social support, Encyclopedia of stress

Jan 2000
479-482

T C Antonucci
J E Lansford
K J Ajrouch

T. C. Antonucci, J. E. Lansford, K. J. Ajrouch, Social support, Encyclopedia of stress, San Diego, CA: Academic Press, pp. 479-482, 2000.

Relationship between characteristics of individual physical activity pattern and social interaction

Jan 2010
2-2

T Nozawa
N Higo
T Ogata
K Ara
K Yano
Y Miyake

T. Nozawa, N. Higo, T. Ogata, K. Ara, K. Yano, Y. Miyake, "Relationship between characteristics of individual physical activity pattern and social interaction," 11th SICE System Integration Division Annual Conference, 2G2-3, 2010.

Scaling Laws of Human Activity Patterns on the Dynamics of Information Diffusion

Jan 2009
12640

D Rybski
S V Buldyrev
S Havlin
F Liljeros
H A Makse

D. Rybski, S.V. Buldyrev, S. Havlin, F. Liljeros, and H. A. Makse, "Scaling Laws of Human Activity Patterns on the Dynamics of Information Diffusion," Proceedings of National Academy of Science U.S.A., vol. 106, 12640, 2009.

Relationship between social interaction and mental health

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