Social network determinants of depression

Social network composition of vascular patients and its associations with health behavior and clinical risk factors

BACKGROUND

This study aimed to explore linkages of patients' social network composition with health behaviors and clinical risk factors.

METHODS/DESIGN

This observational study was embedded in a project aimed at improving cardiovascular risk management (CRVM) in primary care. 657 vascular patients (227 with cardiovascular disease, 380 at high vascular risk), mean age 72.4 (SD 9.4) years, were recruited as were individuals patients considered important for dealing with their disease, so called alters (n = 487). Network composition was measured with structured patient questionnaires. Both patients and alters completed questionnaires to measure health behavior (habits for physical activity, diet, and smoking). Clinical risk factors (systolic blood pressure, LDL cholesterol level, and body mass index) were extracted from patients' medical records. Six logistic regression analyses, using generalized estimating equations, were used to test three hypothesized effects of network composition (having alters with healthful behaviors, without depression, and with specialized knowledge) on six outcomes, adjusted for demographic, personal and psychological characteristics.

RESULTS

Having alters with overall healthful behavior was related to healthful patient diet (OR 2.14, 95%CI: 1.52-3.02). Having non-smoking alters in networks was related to reduced odds for patient smoking (OR 0.17, 95%CI: 0.05-0.60). No effects of presence of non-depressed alters were found. Presence of alters with specialized knowledge on CVRM was inversely related to healthful diet habits of patients (OR 0.47, 95%CI 0.24-0.89). No significant associations between social network composition and clinical risk factors were found.

DISCUSSION

Diet and smoking, but not physical exercise and clinical risk factors, were associated with social network composition of patients with vascular conditions. In this study of vascular patients, controlling for both personal and psychological factors, fewer network influences were found compared to previous research. Further research is needed to examine network structure characteristics as well as the role of psychological factors to enhance understanding health behavior of patients involved in CVRM.

Physiological attunement in mother–infant dyads at clinical high risk: The influence of maternal depression and positive parenting

A growing number of research studies have examined the intradyadic coregulation (or attunement) of hypothalamus–pituitary–adrenal axis functioning in mothers and their children. However, it is unclear how early this coregulation may be present in dyads at clinical high risk and whether certain factors, such as maternal depression or positive parenting, are associated with the strength of this coregulation. The present study examined cortisol attunement within mother–infant dyads in a high-risk sample of 233 mothers who received treatment for psychiatric illness during pregnancy and whose infants were 6 months old at the study visit. Results showed that maternal and infant cortisol covaried across four time points that included a stressor paradigm and a mother–infant interaction task. Greater maternal positive affect, but not depression, predicted stronger cortisol attunement. In addition, infants’ cortisol level following separation from the mother predicted mothers’ cortisol level at the next time point. Mothers’ cortisol level following the separation and the laboratory stress paradigm predicted infants’ cortisol levels at each successive time point, over and above infants’ own cortisol at the previous time point. These findings suggest that maternal and infant cortisol levels influence one another in a bidirectional fashion that may be temporally and context dependent.

Happy classes make happy students: Classmates' well-being predicts individual student well-being

Student well-being has mostly been studied as an individual phenomenon with little research investigating how the well-being of one's classmates could influence a student's well-being. The aim of the current study was to examine how the aggregate well-being of students who comprise a class could predict students' subsequent well-being (Time 2 well-being) after controlling for the effects of prior well-being (Time 1 well-being) as well as key demographic variables such as gender and age. Two studies among Filipino secondary school students were conducted. In Study 1, 788 students from 21 classes participated; in Study 2, 404 students from 10 classes participated. For Study 1, questionnaires assessing students' life satisfaction, positive affect and negative affect were administered twice seven months apart. For Study 2, the well-being questionnaires were administered twice, three months apart. Hierarchical linear modeling was used with level 1 (Time 1 individual well-being, gender, and age) and level 2 (class well-being) predictors. Results across the two studies provided converging lines of evidence: students who were in classes with higher levels of life satisfaction and positive affect were also more likely to have higher life satisfaction and positive affect at Time 2. The study indicated that the well-being of a student partly depends on the well-being of their classmates providing evidence for the social contagion of well-being in the classroom context.

Social interventions: An effective approach to reduce adult depression?

BACKGROUND

Social interventions that aim to facilitate bonds and interaction among individuals could reduce depression at a population level; yet, the scope and effectiveness of these interventions remain unclear. This systematic review classifies and reports on social interventions that have been implemented to target depression in adults.

METHODS

Search terms related to 'intervention', 'depression', and 'social' were entered into databases, including: The Cochrane Database of Systematic Reviews, MEDLINE, Embase, PsycInfo, CINAHL, and TRoPHI. Inclusion criteria included: (1) depression was an intervention outcome, (2) depression was not attributable to concomitant illnesses or circumstances (e.g., chronic illness or exposure to natural disasters), (3) the intervention facilitated social interaction, (4) the intervention targeted adults (18-64), (5) the sample was community-based, (6) the study was available in English, and (7) within-group or between-group comparison group information was available.

RESULTS

Of the 24 studies meeting the inclusion criteria, 17 reported reductions in depressive symptoms. Social interventions often incorporated multiple strategies to improve depressive symptoms, including: peer support (n=17), skill building (n=11), group-based activities (n =11), psycho-education (n =9), psychotherapy (n =5), exercise (n =5), and links to community resources (n=3).

LIMITATIONS

Findings of this review may not be generalizable to specific population subgroups with depression, including those who have chronic illnesses or postpartum depression.

CONCLUSIONS

Various types of social interventions can be effective in reducing adult depression. Social interventions can be tailored to diverse groups, are feasible in resource-scarce communities, and have the potential to reduce population-level depression due to their group formats.

Perceiving emotion in non-social targets: The effect of trait empathy on emotional contagion through art

This research examines the role of trait empathy in emotional contagion through non-social targets—art objects. Studies 1a and 1b showed that high- (compared to low-) empathy individuals are more likely to infer an artist’s emotions based on the emotional valence of the artwork and, as a result, are more likely to experience the respective emotions themselves. Studies 2a and 2b experimentally manipulated artists’ emotions via revealing details about their personal life. Study 3 experimentally induced positive vs. negative emotions in individuals who then wrote literary texts. These texts were shown to another sample of participants. High- (compared to low-) empathy participants were more like to accurately identify and take on the emotions ostensibly (Studies 2a and 2b) or actually (Study 3) experienced by the “artists”. High-empathy individuals’ enhanced sensitivity to others’ emotions is not restricted to social targets, such as faces, but extends to products of the human mind, such as objects of art.

Researching Mental Health Disorders in the Era of Social Media: Systematic Review

Background

Mental illness is quickly becoming one of the most prevalent public health problems worldwide. Social network platforms, where users can express their emotions, feelings, and thoughts, are a valuable source of data for researching mental health, and techniques based on machine learning are increasingly used for this purpose.

Objective

The objective of this review was to explore the scope and limits of cutting-edge techniques that researchers are using for predictive analytics in mental health and to review associated issues, such as ethical concerns, in this area of research.

Methods

We performed a systematic literature review in March 2017, using keywords to search articles on data mining of social network data in the context of common mental health disorders, published between 2010 and March 8, 2017 in medical and computer science journals.

Results

The initial search returned a total of 5386 articles. Following a careful analysis of the titles, abstracts, and main texts, we selected 48 articles for review. We coded the articles according to key characteristics, techniques used for data collection, data preprocessing, feature extraction, feature selection, model construction, and model verification. The most common analytical method was text analysis, with several studies using different flavors of image analysis and social interaction graph analysis.

Conclusions

Despite an increasing number of studies investigating mental health issues using social network data, some common problems persist. Assembling large, high-quality datasets of social media users with mental disorder is problematic, not only due to biases associated with the collection methods, but also with regard to managing consent and selecting appropriate analytics techniques.

Hunter-Gatherer Social Networks and Reproductive Success

Individuals' centrality in their social network (who they and their social ties are connected to) has been associated with fertility, longevity, disease and information transmission in a range of taxa. Here, we present the first exploration in humans of the relationship between reproductive success and different measures of network centrality of 39 Agta and 38 BaYaka mothers. We collected three-meter contact ('proximity') networks and reproductive histories to test the prediction that individual centrality is positively associated with reproductive fitness (number of living offspring). Rather than direct social ties influencing reproductive success, mothers with greater indirect centrality (i.e. centrality determined by second and third degree ties) produced significantly more living offspring. However, indirect centrality is also correlated with sickness in the Agta, suggesting a trade-off. In complex social species, the optimisation of individuals' network position has important ramifications for fitness, potentially due to easy access to different parts of the network, facilitating cooperation and social influence in unpredictable ecologies.

Loneliness and depression in the elderly: the role of social network

PURPOSE

Loneliness and depression are associated, in particular in older adults. Less is known about the role of social networks in this relationship. The present study analyzes the influence of social networks in the relationship between loneliness and depression in the older adult population in Spain.

METHODS

A population-representative sample of 3535 adults aged 50 years and over from Spain was analyzed. Loneliness was assessed by means of the three-item UCLA Loneliness Scale. Social network characteristics were measured using the Berkman-Syme Social Network Index. Major depression in the previous 12 months was assessed with the Composite International Diagnostic Interview (CIDI). Logistic regression models were used to analyze the survey data.

RESULTS

Feelings of loneliness were more prevalent in women, those who were younger (50-65), single, separated, divorced or widowed, living in a rural setting, with a lower frequency of social interactions and smaller social network, and with major depression. Among people feeling lonely, those with depression were more frequently married and had a small social network. Among those not feeling lonely, depression was associated with being previously married. In depressed people, feelings of loneliness were associated with having a small social network; while among those without depression, feelings of loneliness were associated with being married.

CONCLUSION

The type and size of social networks have a role in the relationship between loneliness and depression. Increasing social interaction may be more beneficial than strategies based on improving maladaptive social cognition in loneliness to reduce the prevalence of depression among Spanish older adults.

Longitudinal Changes in Psychological States in Online Health Community Members: Understanding the Long-Term Effects of Participating in an Online Depression Community

BACKGROUND

Major depression is a serious challenge at both the individual and population levels. Although online health communities have shown the potential to reduce the symptoms of depression, emotional contagion theory suggests that negative emotion can spread within a community, and prolonged interactions with other depressed individuals has potential to worsen the symptoms of depression.

OBJECTIVE

The goals of our study were to investigate longitudinal changes in psychological states that are manifested through linguistic changes in depression community members who are interacting with other depressed individuals.

METHODS

We examined emotion-related language usages using the Linguistic Inquiry and Word Count (LIWC) program for each member of a depression community from Reddit. To measure the changes, we applied linear least-squares regression to the LIWC scores against the interaction sequence for each member. We measured the differences in linguistic changes against three online health communities focusing on positive emotion, diabetes, and irritable bowel syndrome.

RESULTS

On average, members of an online depression community showed improvement in 9 of 10 prespecified linguistic dimensions: "positive emotion," "negative emotion," "anxiety," "anger," "sadness," "first person singular," "negation," "swear words," and "death." Moreover, these members improved either significantly or at least as much as members of other online health communities.

CONCLUSIONS

We provide new insights into the impact of prolonged participation in an online depression community and highlight the positive emotion change in members. The findings of this study should be interpreted with caution, because participating in an online depression community is not the sole factor for improvement or worsening of depressive symptoms. Still, the consistent statistical results including comparative analyses with different communities could indicate that the emotion-related language usage of depression community members are improving either significantly or at least as much as members of other online communities. On the basis of these findings, we contribute practical suggestions for designing online depression communities to enhance psychosocial benefit gains for members. We consider these results to be an important step toward a better understanding of the impact of prolonged participation in an online depression community, in addition to providing insights into the long-term psychosocial well-being of members.

The protective properties of Act-Belong-Commit indicators against incident depression, anxiety, and cognitive impairment among older Irish adults: Findings from a prospective community-based study

The Act-Belong-Commit campaign is the world's first comprehensive, population-wide, community-based program designed to promote mental health. The campaign targets individuals to engage in mentally healthy activities, while at the same time, encouraging community organizations that offer such activities, to increase participation in their activities. Using nationally-representative data from Ireland, the aim of this study was to prospectively assess the association between indicators of the Act-Belong-Commit behavioral domains and incident depression, anxiety, and cognitive impairment. Data from two consecutive waves of the Irish Longitudinal Study on Ageing (TILDA) were analyzed. The analytical sample consisted of 6098 adults aged ≥50years. Validated scales for depression, anxiety, and cognitive impairment were used. The number of social/recreational activities engaged in was used as an indicator of Act, social network integration as an indicator of Belong, and frequency of participation in these social/recreational activities as an indicator of Commit. Multivariable logistic regression analyses were conducted to assess associations between baseline indicators of Act-Belong-Commit and incident depression, anxiety, and cognitive impairment at two-year follow-up. The adjusted model showed that each increase in the number of social/recreational activities (Act) inversely predicted the onset of depression, anxiety, and cognitive impairment. The same was the case for social network integration (Belong); that is, being well integrated into social networks was a significant protective factor against all mental health outcomes. Finally, frequency of participation in social/recreational activities (Commit) significantly and inversely predicted the onset of depression and anxiety, while the protective effect against cognitive impairment was only marginally significant. Act-Belong-Commit indicators are shown to be protective against mental disorders and cognitive impairment among older Irish adults. This provides further evidence for the campaign's potential efficacy and has potentially wide-ranging implications for preventing the deterioration of mental health and cognitive decline in the aging community.

Epigenetic Mechanisms of Integrative Medicine

Since time immemorial humans have utilized natural products and therapies for their healing properties. Even now, in the age of genomics and on the cusp of regenerative medicine, the use of complementary and alternative medicine (CAM) approaches represents a popular branch of health care. Furthermore, there is a trend towards a unified medical philosophy referred to as Integrative Medicine (IM) that represents the convergence of CAM and conventional medicine. The IM model not only considers the holistic perspective of the physiological components of the individual, but also includes psychological and mind-body aspects. Justification for and validation of such a whole-systems approach is in part dependent upon identification of the functional pathways governing healing, and new data is revealing relationships between therapies and biochemical effects that have long defied explanation. We review this data and propose a unifying theme: IM's ability to affect healing is due at least in part to epigenetic mechanisms. This hypothesis is based on a mounting body of evidence that demonstrates a correlation between the physical and mental effects of IM and modulation of gene expression and epigenetic state. Emphasis on mapping, deciphering, and optimizing these effects will facilitate therapeutic delivery and create further benefits.

Depression, Smoking, and Ego-Centric Social Network Characteristics in Ohio Appalachian Women

Depression is a serious, costly, and debilitating disorder that is understudied in rural women. Studies show that depression is associated with low social integration and support, but few studies investigate the relationship between depression and social network characteristics. This study examined the associations among women from three Ohio Appalachian counties enrolled in a health study, which aimed to collect information for a future social network smoking cessation intervention. An address-based sampling method was used to randomly select and recruit 404 women. A cross-sectional survey and interview were used to collect information about demographic, psychosocial, behavioral factors, and ego-centric social network characteristics, which are variables derived from an individual (ego) and her first degree contacts (alters). The CES-D scale assessed depressive symptoms. A multivariable logistic regression analysis described the association between these factors and participants with depression (defined as CES-D≥16). Higher network density, or greater number of relationships among alters divided by the total amount of alters, reduced the risk for depression (OR = 0.84, 95% confidence interval [CI] 0.73-0.95). Additionally, women with a high percentage of smoking alters were at greater risk for depression (OR = 1.19, 95% CI 1.02-1.39). Other factors associated with risk for depression included perceived stress score (OR = 1.34, 95% CI 1.24-1.45), loneliness score (OR = 1.37, 95% CI 1.05-1.80), and days with poor physical health (OR = 1.06, 95% CI 1.02-1.11). Findings suggest that psychosocial factors and social networks should be considered when addressing depression in clinical practice.

Social disadvantage and borderline personality disorder: A study of social networks

Examining differences in social integration, social support, and relationship characteristics in social networks may be critical for understanding the character and costs of the social difficulties experienced of borderline personality disorder (BPD). We conducted an ego-based (self-reported, individual) social network analysis of 142 participants recruited from clinical and community sources. Each participant listed the 30 most significant people (called alters) in their social network, then rated each alter in terms of amount of contact, social support, attachment strength and negative interactions. In addition, measures of social integration were determined using participant's report of the connection between people in their networks. BPD was associated with poorer social support, more frequent negative interactions, and less social integration. Examination of alter-by-BPD interactions indicated that whereas participants with low BPD symptoms had close relationships with people with high centrality within their networks, participants with high BPD symptoms had their closest relationships with people less central to their networks. The results suggest that individuals with BPD are at a social disadvantage: Those with whom they are most closely linked (including romantic partners) are less socially connected (i.e., less central) within their social network. (PsycINFO Database Record

Social Networking Sites, Depression, and Anxiety: A Systematic Review

BACKGROUND

Social networking sites (SNSs) have become a pervasive part of modern culture, which may also affect mental health.

OBJECTIVE

The aim of this systematic review was to identify and summarize research examining depression and anxiety in the context of SNSs. It also aimed to identify studies that complement the assessment of mental illness with measures of well-being and examine moderators and mediators that add to the complexity of this environment.

METHODS

A multidatabase search was performed. Papers published between January 2005 and June 2016 relevant to mental illness (depression and anxiety only) were extracted and reviewed.

RESULTS

Positive interactions, social support, and social connectedness on SNSs were consistently related to lower levels of depression and anxiety, whereas negative interaction and social comparisons on SNSs were related to higher levels of depression and anxiety. SNS use related to less loneliness and greater self-esteem and life satisfaction. Findings were mixed for frequency of SNS use and number of SNS friends. Different patterns in the way individuals with depression and individuals with social anxiety engage with SNSs are beginning to emerge.

CONCLUSIONS

The systematic review revealed many mixed findings between depression, anxiety, and SNS use. Methodology has predominantly focused on self-report cross-sectional approaches; future research will benefit from leveraging real-time SNS data over time. The evidence suggests that SNS use correlates with mental illness and well-being; however, whether this effect is beneficial or detrimental depends at least partly on the quality of social factors in the SNS environment. Understanding these relationships will lead to better utilization of SNSs in their potential to positively influence mental health.

Mostly Heterosexual and Lesbian/Gay Young Adults: Differences in Mental Health and Substance Use and the Role of Minority Stress

Individuals mostly attracted to other-sex but also to same-sex partners are a distinct and common sexual orientation group with possibly increased levels of health problems. The current study examined whether mostly heterosexual individuals differed in mental health and substance use from lesbian/gay individuals and whether sexual minority risk and protective factors offer an explanation in a sample of 528 Dutch young adults (16 to 25 years old, M = 21.2 years). Mostly heterosexual participants reported higher levels of psychological distress, suicidality, drug use, and smoking than lesbian/gay participants and equal levels of binge drinking. They also reported higher levels of internalized negativity to same-sex attractions, less openness to family members and others, less community involvement, and lower numbers of lesbian/gay/bisexual friends. However, bootstrapped mediation analysis showed that the differences in minority stress risk and protective factors did not mediate most of the differences in mental health and substance use with one exception: higher levels of psychological distress were mediated by the higher levels of internalized negativity to same-sex attractions. The limited explanatory power of the minority stress factors combined with the elevated level of problems of mostly heterosexual individuals call for future studies examining other risk and protective factors.

Leveraging geotagged Twitter data to examine neighborhood happiness, diet, and physical activity

OBJECTIVES

Using publicly available, geotagged Twitter data, we created neighborhood indicators for happiness, food and physical activity for three large counties: Salt Lake, San Francisco and New York.

METHODS

We utilize 2.8 million tweets collected between February-August 2015 in our analysis. Geo-coordinates of where tweets were sent allow us to spatially join them to 2010 census tract locations. We implemented quality control checks and tested associations between Twitter-derived variables and sociodemographic characteristics.

RESULTS

For a random subset of tweets, manually labeled tweets and algorithm labeled tweets had excellent levels of agreement: 73% for happiness; 83% for food, and 85% for physical activity. Happy tweets, healthy food references, and physical activity references were less frequent in census tracts with greater economic disadvantage and higher proportions of racial/ethnic minorities and youths.

CONCLUSIONS

Social media can be leveraged to provide greater understanding of the well-being and health behaviors of communities-information that has been previously difficult and expensive to obtain consistently across geographies. More open access neighborhood data can enable better design of programs and policies addressing social determinants of health.

Is Social Network Diversity Associated with Tooth Loss among Older Japanese Adults?

BACKGROUND

We sought to examine social network diversity as a potential determinant of oral health, considering size and contact frequency of the social network and oral health behaviors.

METHODS

Our cross-sectional study was based on data from the 2010 Japan Gerontological Evaluation Study. Data from 19,756 community-dwelling individuals aged 65 years or older were analyzed. We inquired about diversity of friendships based on seven types of friends. Ordered logistic regression models were developed to determine the association between the diversity of social networks and number of teeth (categorized as ≥20, 10-19, 1-9, and 0).

RESULTS

Of the participants, 54.1% were women (mean age, 73.9 years; standard deviation, 6.2). The proportion of respondents with ≥20 teeth was 34.1%. After adjusting for age, sex, socioeconomic status (income, education, and occupation), marital status, health status (diabetes and mental health), and size and contact frequency of the social network, an increase in the diversity of social networks was significantly associated with having more teeth (odds ratio = 1.08; 95% confidence interval, 1.04-1.11). Even adjusted for oral health behaviors (smoking, curative/preventive dental care access, use of dental floss/fluoride toothpaste), significant association was still observed (odds ratio = 1.05 (95% confidence interval, 1.02-1.08)).

CONCLUSION

Social connectedness among people from diverse backgrounds may increase information channels and promote the diffusion of oral health behaviors and prevent tooth loss.

Modelling the Evolution of Social Structure

Although simple social structures are more common in animal societies, some taxa (mainly mammals) have complex, multi-level social systems, in which the levels reflect differential association. We develop a simulation model to explore the conditions under which multi-level social systems of this kind evolve. Our model focuses on the evolutionary trade-offs between foraging and social interaction, and explores the impact of alternative strategies for distributing social interaction, with fitness criteria for wellbeing, alliance formation, risk, stress and access to food resources that reward social strategies differentially. The results suggest that multi-level social structures characterised by a few strong relationships, more medium ties and large numbers of weak ties emerge only in a small part of the overall fitness landscape, namely where there are significant fitness benefits from wellbeing and alliance formation and there are high levels of social interaction. In contrast, 'favour-the-few' strategies are more competitive under a wide range of fitness conditions, including those producing homogeneous, single-level societies of the kind found in many birds and mammals. The simulations suggest that the development of complex, multi-level social structures of the kind found in many primates (including humans) depends on a capacity for high investment in social time, preferential social interaction strategies, high mortality risk and/or differential reproduction. These conditions are characteristic of only a few mammalian taxa.

Minor mental disorders in Taiwanese healthcare workers and the associations with psychosocial work conditions

BACKGROUND/PURPOSE

Healthcare workers face multiple psychosocial work hazards intrinsic to their work, including heavy workloads and shift work. However, how contemporary adverse psychosocial work conditions, such as workplace justice and insecurity, may contribute to increased mental health risks has rarely been studied. This study aimed to search for modifiable psychosocial work factors associated with mental health disorders in Taiwanese healthcare workers.

METHODS

A total of 349 healthcare workers were identified from 19,641 employees who participated in a national survey of Taiwan. Minor mental disorder was assessed using the five-item brief symptom rating scale. We compared psychosocial work characteristics and the prevalence of minor mental disorder in healthcare workers with that in a sociodemographically matched sample, and examined the associations of psychosocial work conditions with mental health status.

RESULTS

Healthcare workers were found to have a higher prevalence of minor mental disorder than general workers, and they were more likely to have longer working hours, heavier psychological job demands, higher job control, more workplace violence, and a higher prevalence of shift work. Among healthcare workers, experiences of workplace violence, lower workplace justice, heavier psychological job demands, and job insecurity were associated with a higher risk for minor mental disorder, even after controlling for working hours and shift work.

CONCLUSION

Despite the fact that healthcare workers work longer hours and shift work, there were several modifiable psychosocial work conditions that should be targeted to improve their mental health.

Technology and Reflection: Mood and Memory Mechanisms for Well-Being

Background

We report a psychologically motivated intervention to explore Technology Mediated Reflection (TMR), the process of systematically reviewing rich digital records of past personal experiences. Although TMR benefits well-being, and is increasingly being deployed, we know little about how one’s mood when using TMR influences these benefits. We use theories of memory and emotion-regulation to motivate hypotheses about the relationship between reflection, mood, and well-being when using technology. We test these hypotheses in a large-scale month long real world deployment using a web-based application, MoodAdaptor. MoodAdaptor prompted participants to reflect on positive or negative memories depending on current mood.

Methods

We evaluated how mood and memory interact during written reflection and measured effects on well-being. We analyzed qualitative and quantitative data from 128 participants who generated 11157 mood evaluations, 5051 logfiles, 256 surveys, and 20 interviews.

Results

TMR regulated emotion; when participants reflected on memories with valences opposite to their current mood, their mood became more neutral. However this did not impact overall well-being. Our findings also clarify underlying TMR mechanisms. Moods and memories competed with each other; when positive moods prevailed over negative memories, people demonstrated classic mechanisms shown in prior work to influence well-being. When negative moods prevailed over positive memories, memories became negatively tainted.

Conclusions

Our results have implications for new well-being interventions and technologies that capitalize on the interconnectedness of memory and emotion.

Social functioning in major depressive disorder

Depression is associated with social risk factors, social impairments and poor social functioning. This paper gives an overview of these social aspects using the NIMH Research and Domain Criteria 'Systems for Social Processes' as a framework. In particular, it describes the bio-psycho-social interplay regarding impaired affiliation and attachment (social anhedonia, hyper-sensitivity to social rejection, competition avoidance, increased altruistic punishment), impaired social communication (impaired emotion recognition, diminished cooperativeness), impaired social perception (reduced empathy, theory-of-mind deficits) and their impact on social networks and the use of social media. It describes these dysfunctional social processes at the behavioural, neuroanatomical, neurochemical and genetic levels, and with respect to animal models of social stress. We discuss the diagnostic specificity of these social deficit constructs for depression and in relation to depression severity. Since social factors are importantly involved in the pathogenesis and the consequences of depression, such research will likely contribute to better diagnostic assessments and concepts, treatments and preventative strategies both at the diagnostic and transdiagnostic level.

Does long-term experience of nonstandard employment increase the incidence of depression in the elderly?

Objectives:

Our prospective study aimed to elucidate the effect of long-term experience of nonstandard employment status on the incidence of depression in elderly population using the Korean Longitudinal Study of Ageing (KLoSA) study.

Methods:

This study used the first- to fourth-wave cohorts of KLoSA. After the exclusion of the unemployed and participants who experienced a change in employment status during the follow-up periods, we analyzed a total of 1,817 participants. Employment contracts were assessed by self-reported questions:standard or nonstandard employment. The short form of the Center for Epidemiologic Studies Depression Scale (CES-D) served as the outcome measure. Hazard ratios (HRs) with 95% confidence intervals (CIs) were calculated using Cox proportional hazards models to evaluate the association between standard/nonstandard employees and development of depression.

Results:

The mean age of the participants was 53.90 (±7.21) years. We observed that nonstandard employment significantly increased the risk of depression. Compared with standard employees, nonstandard employees had a 1.5-fold elevated risk for depression after adjusting for age, gender, CES-D score at baseline, household income, occupation category, current marital status, number of living siblings, perceived health status, and chronic diseases [HR=1.461, 95% CI= (1.184, 1.805) ]. Moreover, regardless of other individual characteristics, the elevated risk of depression was observed among all kinds of nonstandard workers, such as temporary and day workers, full-time and part-time workers, and directly employed and dispatched labor.

Conclusions:

The 6-year follow-up study revealed that long-term experience of nonstandard employment status increased the risk of depression in elderly population in Korea.

Biological mechanisms underlying evolutionary origins of psychotic and mood disorders

Psychotic and mood disorders are brain dysfunctions that are caused by gene environment interactions. Although these disorders are disadvantageous and involve behavioral phenotypes that decrease the reproductive success of afflicted individuals in the modern human society, the prevalence of these disorders have remained constant in the population. Here, we propose several biological mechanisms by which the genes associated with psychotic and mood disorders could be selected for in specific environmental conditions that provide evolutionary bases for explanations of when, why, and where these disorders emerged and have been maintained in humans. We discuss the evolutionary origins of psychotic and mood disorders with specific focuses on the roles of dopamine and serotonin in the conditions of social competitiveness/hierarchy and maternal care and other potential mechanisms, such as social network homophily and symbiosis.

Risky Integration

Abstract. Background: Although the protective value of social connectedness is emphasized in suicide prevention programming, little is known about the relationship between connectedness in high-risk runaway and homeless youth (RHY) networks and suicidal ideation. Aims: The study examined how social connectedness, in the form of social network position and network exposures, was associated with suicidal ideation among RHY. Method: Using population-level social network data from 384 RHY, each youth’s network position and exposure to potentially suicidogenic peer attributes were calculated. Logistic regression analyses were used to examine associations between network position (core vs. periphery), peer exposures (e.g., depressed or suicidal peers), and suicidal ideation. Results: In univariable analyses, being in the core of the network and being connected to greater proportions of depressed and suicidal peers increased the likelihood of suicidal ideation. In the final multivariable model, higher exposure to depressed peers remained associated with suicidal ideation, and a marginal effect for network position was observed. Conclusion: The risk of suicidal ideation was linked to depression among peers and to a lesser extent being more integrated into the RHY network. Identifying and treating depression in naturally occurring friendship groups, particularly in the core of the network, represents a promising network-level intervention.

Model-based testing for space-time interaction using point processes: An application to psychiatric hospital admissions in an urban area

Spatio-temporal interaction is inherent to cases of infectious diseases and occurrences of earthquakes, whereas the spread of other events, such as cancer or crime, is less evident. Statistical significance tests of space-time clustering usually assess the correlation between the spatial and temporal (transformed) distances of the events. Although appealing through simplicity, these classical tests do not adjust for the underlying population nor can they account for a distance decay of interaction. We propose to use the framework of an endemic-epidemic point process model to jointly estimate a background event rate explained by seasonal and areal characteristics, as well as a superposed epidemic component representing the hypothesis of interest. We illustrate this new model-based test for space-time interaction by analysing psychiatric inpatient admissions in Zurich, Switzerland (2007-2012). Several socio-economic factors were found to be associated with the admission rate, but there was no evidence of general clustering of the cases.

Effects of voluntary/involuntary retirement on their own and spouses' depressive symptoms

OBJECTIVES

The aim of our study was to elucidate the effect of voluntary/involuntary retirement on individuals' and spouses' depressive symptoms using the Korean Longitudinal Study of Aging (KLoSA).

METHODS

This study used a sample derived from the first- to fourth-wave cohort datasets of KLoSA, which was conducted in 2006, 2008, 2010, and 2012. After applying inclusion and exclusion criteria, we analyzed a total of 6706 subjects. Information about employment status, the short-form Center for Epidemiological Studies-Depression scale, and covariates (age, property, household income, perceived health status and medical disability) were obtained. Cox proportional hazards models were used to evaluate the effects of voluntary/involuntary retirement on individuals' and spouses' depressive symptoms.

RESULTS

The voluntary/involuntary retirement groups showed significantly more depressive symptoms than the working group in wave 1-4, and the same results were revealed in the spouse's retirement and job loss measures. The hazard ratios of depressive symptoms of the voluntary/involuntary retirement groups were 1.26-1.31 during the 6year follow-up period. The wives' risk of depressive symptoms was also significantly increased if their husbands voluntarily retired (HR=1.35, 95% CI=1.10-1.65).

CONCLUSION

During the 6year follow-up study, Voluntary/involuntary retirement increased the risk of depressive symptoms in a Korean elderly population. Furthermore, husbands' voluntary retirement increased wives' risk of depressive symptoms.

Exploring Entrainment Patterns of Human Emotion in Social Media

Emotion entrainment, which is generally defined as the synchronous convergence of human emotions, performs many important social functions. However, what the specific mechanisms of emotion entrainment are beyond in-person interactions, and how human emotions evolve under different entrainment patterns in large-scale social communities, are still unknown. In this paper, we aim to examine the massive emotion entrainment patterns and understand the underlying mechanisms in the context of social media. As modeling emotion dynamics on a large scale is often challenging, we elaborate a pragmatic framework to characterize and quantify the entrainment phenomenon. By applying this framework on the datasets from two large-scale social media platforms, we find that the emotions of online users entrain through social networks. We further uncover that online users often form their relations via dual entrainment, while maintain it through single entrainment. Remarkably, the emotions of online users are more convergent in nonreciprocal entrainment. Building on these findings, we develop an entrainment augmented model for emotion prediction. Experimental results suggest that entrainment patterns inform emotion proximity in dyads, and encoding their associations promotes emotion prediction. This work can further help us to understand the underlying dynamic process of large-scale online interactions and make more reasonable decisions regarding emergency situations, epidemic diseases, and political campaigns in cyberspace.

Social attachments and traumatic stress

The extent to which we engage with our social world has been central to our survival as a species and, accordingly, is relevant to how we cope with trauma and adversity. This review summarises current knowledge about the importance of social connections from an evolutionary perspective, as well as integrating this with a discussion of prevailing attachment theories. Experimental research supporting the potential benefit of attachments for managing adversity are presented, along with a review of how these benefits are moderated by individual differences in attachment style. The potential impact of trauma on attachment systems, and the manner in which this can compound trauma stress is discussed. Finally, a broader overview of social network analysis is introduced and it is proposed that a more sociocentric framework of trauma response would promote a fuller understanding of how social processes moderate trauma response.

Prevalence of depressive symptoms and suicidal thoughts among elderly persons in rural Bangladesh

BACKGROUND

Depression, if broadly defined, is the commonest late-life mental disorder. We examined the distribution of depressive symptoms and suicidal thoughts, across age, sex, literacy, and marital status, among elderly individuals residing in rural Bangladesh and participating in a population-based study on health and aging.

METHODS

Prevalence figures of depressive symptoms were assessed with SRQ20 (n = 625), and possible social network and economic associations were examined. Morbidity accounts of depressive symptoms and suicidal thoughts were examined for a subsample that also underwent complete medical examination (n = 471).

RESULTS

We selected for analyses the items that corresponded to DSM-IV criteria and constructed a dichotomous variable. The prevalence was 45%, and most pronounced among the oldest women (70%). The overall prevalence of suicidal thoughts was 23%. Being a woman, illiterate or single were all risk factors for depressive symptoms and suicidal thoughts. These associations remained unaccounted for by the social network and economic variables. Co-residing with a child and having a high quality of contact were protective of both depressive symptoms and suicidal thoughts. The main findings were replicated in the subsample, where it was found that morbidities were also associated with the outcomes, independently of the four main predictors.

CONCLUSIONS

Prevalence figures for depressive symptoms among elderly in rural Bangladesh are high. Demographic, social network, and morbidity factors are independently associated with both depressive symptoms and suicidal thoughts. This is the first study to report prevalence figures for depressive symptoms in this population.

Mapping dynamic social networks in real life using participants' own smartphones

Interpersonal relationships are vital for our daily functioning and wellbeing. Social networks may form the primary means by which environmental influences determine individual traits. Several studies have shown the influence of social networks on decision-making, behaviors and wellbeing. Smartphones have great potential for measuring social networks in a real world setting. Here we tested the feasibility of using people's own smartphones as a data collection platform for face-to-face interactions. We developed an application for iOS and Android to collect Bluetooth data and acquired one week of data from 14 participants in our organization. The Bluetooth scanning statistics were used to quantify the time-resolved connection strength between participants and define the weights of a dynamic social network. We used network metrics to quantify changes in network topology over time and non-negative matrix factorization to identify cliques or subgroups that reoccurred during the week. The scanning rate varied considerably between smartphones running Android and iOS and egocentric networks metrics were correlated with the scanning rate. The time courses of two identified subgroups matched with two meetings that took place that week. These findings demonstrate the feasibility of using participants' own smartphones to map social network, whilst identifying current limitations of using generic smartphones. The bias introduced by variations in scanning rate and missing data is an important limitation that needs to be addressed in future studies.

The impact of lifetime suicidality on academic performance in college freshmen

BACKGROUND

While suicidal thoughts and behaviors (STB) among college students are common, the associations between STB and academic performance are not well understood.

METHODS

As part of the World Mental Health Surveys International College Student project, web-based self-reported STB of KU Leuven (Leuven, Belgium) incoming freshmen (N=4921; response rate=65.4%) was collected, as well as academic year percentage (AYP), and the departments to which students belong. Single- and multilevel multivariate analyses were conducted, adjusted for gender, age, parental educational level, and comorbid lifetime emotional problems.

RESULTS

Lifetime suicide plan and attempt upon college entrance were associated with significant decreases in AYP (3.6% and 7.9%, respectively). A significant interaction was found with average departmental AYP, with STB more strongly associated with reduced AYP in departments with lower than higher average AYP.

LIMITATIONS

Limited sample size precluded further investigation of interactions between department-level and student-level variables. No information was available on freshman secondary school academic performance.

CONCLUSIONS

Lifetime STB has a strong negative association with academic performance in college. Our study suggests a potential role for the college environment as target for treatment and prevention interventions.

The Association Between Physical Activity, Mental Status, and Social and Family Support with Five Major Non-Communicable Chronic Diseases Among Elderly People: A Cross-Sectional Study of a Rural Population in Southern China

Background: Non-communicable chronic diseases (NCDs) have become the top threat in China. This study aimed to estimate the prevalence of major NCDs among the elderly population in rural areas in southern China and explore its associated social determinants. Methods: A multistage cluster random sampling methodology was adopted to select a total of 9245 rural elderly people from 3860 rural households in Guangdong Province. Interviews and physical examinations were performed to collect patient information. Descriptive and logistic regression analyses were conducted to explore factors associated with the presence of major NCDs. Results: Over one-third (38.5%) of the study population suffered from five major NCDs. The grade of activities of daily living (ADL), mental status, and social relationship of elderly people without NCDs were better than those with NCDs. The major factors associated with the presence of NCDs among the elderly people included age (70–79 years group and 80–89 years group), education level (senior high/technical secondary school and junior college and above), mental status (concentration, enrichment and happy life and memory), relationship with neighbours, activities of daily living (ADL) (being able to climb three floors and bend over), physical activity, marital status (bereft), and living conditions (with offspring and family members). Conclusions: The study identified several social determinants associated with the presence of major NCDs. A higher level of family support and physical exercise might contribute to improved physical condition, mental status, and ADL among the elderly people in rural areas in southern China.

The iTreAD project: a study protocol for a randomised controlled clinical trial of online treatment and social networking for binge drinking and depression in young people

Background

Depression and binge drinking behaviours are common clinical problems, which cause substantial functional, economic and health impacts. These conditions peak in young adulthood, and commonly co-occur. Comorbid depression and binge drinking are undertreated in young people, who are reluctant to seek help via traditional pathways to care. The iTreAD project (internet Treatment for Alcohol and Depression) aims to provide and evaluate internet-delivered monitoring and treatment programs for young people with depression and binge drinking concerns.

Methods

Three hundred sixty nine participants will be recruited to the trial, and will be aged 18–30 years will be eligible for the study if they report current symptoms of depression (score 5 or more on the depression subscale of the Depression Anxiety Stress Scale) and concurrent binge drinking practices (5 or more standard drinks at least twice in the prior month). Following screening and online baseline assessment, participants are randomised to: (a) online monthly self-assessments, (b) online monthly self-assessments + 12-months of access to a 4 week online automated cognitive behaviour therapy program for binge drinking and depression (DEAL); or (c) online monthly assessment + DEAL + 12-months of access to a social networking site (Breathing Space). Independent, blind follow-up assessments occur at 26, 39, 52 and 64-weeks post-baseline.

Discussion

The iTreAD project is the first randomised controlled trial combining online cognitive behaviour therapy, social networking and online monitoring for young people reporting concerns with depression and binge drinking. These treatments represent low-cost, wide-reach youth-appropriate treatment, which will have significantly public health implications for service design, delivery and health policy for this important age group.

Trial registration

Australian and New Zealand Clinical Trials Registry ACTRN12614000310662. Date registered 24 March 2014.

Social network analysis identified central outcomes for core outcome sets using systematic reviews of HIV/AIDS

OBJECTIVES

Methods to develop core outcome sets, the minimum outcomes that should be measured in research in a topic area, vary. We applied social network analysis methods to understand outcome co-occurrence patterns in human immunodeficiency virus (HIV)/AIDS systematic reviews and identify outcomes central to the network of outcomes in HIV/AIDS.

STUDY DESIGN AND SETTING

We examined all Cochrane reviews of HIV/AIDS as of June 2013. We defined a tie as two outcomes (nodes) co-occurring in ≥2 reviews. To identify central outcomes, we used normalized node betweenness centrality (nNBC) (the extent to which connections between other outcomes in a network rely on that outcome as an intermediary). We conducted a subgroup analysis by HIV/AIDS intervention type (i.e., clinical management, biomedical prevention, behavioral prevention, and health services).

RESULTS

The 140 included reviews examined 1,140 outcomes, 294 of which were unique. The most central outcome overall was all-cause mortality (nNBC = 23.9). The most central and most frequent outcomes differed overall and within subgroups. For example, "adverse events (specified)" was among the most central but not among the most frequent outcomes, overall.

CONCLUSION

Social network analysis methods are a novel application to identify central outcomes, which provides additional information potentially useful for developing core outcome sets.

Realizing the potential of mobile mental health: new methods for new data in psychiatry

Smartphones are now ubiquitous and can be harnessed to offer psychiatry a wealth of real-time data regarding patient behavior, self-reported symptoms, and even physiology. The data collected from smartphones meet the three criteria of big data: velocity, volume, and variety. Although these data have tremendous potential, transforming them into clinically valid and useful information requires using new tools and methods as a part of assessment in psychiatry. In this paper, we introduce and explore numerous analytical methods and tools from the computational and statistical sciences that appear readily applicable to psychiatric data collected using smartphones. By matching smartphone data with appropriate statistical methods, psychiatry can better realize the potential of mobile mental health and empower both patients and providers with novel clinical tools.

The association of relationship quality and social networks with depression, anxiety, and suicidal ideation among older married adults: Findings from a cross-sectional analysis of the Irish Longitudinal Study on Ageing (TILDA)

BACKGROUND

Important associations have been found between social relationships and various mental health outcomes. However, limited data exists for these associations among older adults especially in terms of relationship quality in partnerships. This study aimed to examine the associations of positive and negative partner interactions and social networks with depression, anxiety and suicidal ideation.

METHODS

Nationally-representative, cross-sectional data of the Irish Longitudinal Study on Ageing (TILDA) was analyzed. The analytical sample consisted of 4988 community dwelling adults aged >50 years in spouse/partner relationships. Information on sociodemographics and social relationships were assessed using standard questions. Validated scales for depression and anxiety, and a single-item question for suicidal ideation were used to assess mental health outcomes. Multivariable logistic regression was used to assess the association between social relationships and depression, anxiety, and suicidal ideation.

RESULTS

After adjusting for confounders, negative partner interactions were significantly associated with increased likelihood of depression, anxiety, and suicidal ideation, while positive partner interactions were significantly and inversely related to anxiety and suicidal ideation. Higher levels of social integration were significantly associated with lower odds for depression.

LIMITATIONS

Given the cross-sectional nature of the research, no firm conclusions can be made in terms of directions of causality.

CONCLUSION

By assessing the available social network of older adults, as well as the areas in their social relationships that need to be addressed, it may be possible for practitioners and policy makers to maximize the benefits of network integration and minimize the potentially harmful aspects of social relationships, thereby improving overall mental health and emotional well-being.

Affect and well-being similarity among older Indian spouses

OBJECTIVES

Previous work suggests that husbands and wives are likely to share affective states so that depression or happiness in one spouse is predictive of depression or happiness in the other. Studies that have examined spousal affect similarity, however, have been concentrated in the Western world where the meaning of marriage may be different than it is in other cultural contexts. Marriage in India, unlike that in the United States, is focused on the extended family so that love and intimacy between spouses are downplayed. This study examined affect and well-being similarity between 603 older married couples in India using pilot data from the Longitudinal Aging Study of India.

METHOD

We ran linear regression models to assess the relationship between the well-being states of husbands and wives using dyadic observations for four different measures: depressive symptoms, dissatisfaction with daily life, social isolation, and overall life satisfaction.

RESULTS

Across all four measures, the well-being scores of one spouse were positively and significantly associated with the well-being scores of the other. These associations did not vary by marital satisfaction, but were slightly stronger for respondents reporting poor health.

CONCLUSION

Our increased understanding of social connectedness has prompted a shift from the consideration of single individuals to a broader understanding of individuals in the context of their social environments. The results of this study suggest that interventions designed to foster well-being among older adults in India might benefit from a focus on couples as a unit rather than individuals.

Peer influence processes for youth delinquency and depression

This study explores the multiple factors that account for peer influence processes of adolescent delinquency and depression using data from Waves I and II of the National Longitudinal Study of Adolescent to Adult Health (Add Health). Random-effects longitudinal negative binomial models were used to predict depression and delinquency, controlling for social connection variables to account for selection bias. Findings suggest peer depression and delinquency are both predictive of youth delinquency, while peer influences of depression are much more modest. Youth who are more connected to parents and communities and who are more popular within their networks are more susceptible to peer influence, while self-regulating youth are less susceptible. We find support for theories of popularity-socialization as well as weak-ties in explaining social network factors that amplify or constrain peer influence. We argue that practitioners working with youth should consider network-informed interventions to improve program efficacy and avoid iatrogenic effects.

Connectedness and suicidal ideation among adolescents involved with child welfare: a national survey

Using data from the National Survey of Child and Adolescent Well-Being, this study examined the relationship between connectedness in major social domains (i.e., caregiver, peers, deviant peers, and school) and suicidal ideation among adolescents (11-17 years old) investigated by child welfare agencies (N=995). Weighted logistic regression models were used to evaluate the relationships between connectedness variables and suicidal ideation, after adjusting for covariates. Youths with a stronger connection to caregivers were much less likely to report suicidal ideation, whereas youths with stronger deviant peer relationships were significantly more likely to report suicidal ideation. Significant associations found between primary caregiver and deviant peer connectedness and suicidal ideation highlight the need for attentive consideration of these relationships when working with this highly vulnerable population. Identifying domain-specific connectedness factors related to suicidal ideation presents an opportunity for the development of targeted early intervention for child welfare-involved youths.

The association between social relationships and depression: a systematic review

BACKGROUND

Depression is one of the most prevalent mental disorders globally and has implications for various aspects of everyday-life. To date, studies assessing the association between social relationships and depression have provided conflicting results. The aim of this paper was to review the evidence on associations between social relationships and depression in the general population.

METHODS

Studies investigating the association of social support, social networks, or social connectedness with depression were retrieved and summarized (searches using Pubmed, ScienceDirect, PsycNet were conducted in May 2014).

RESULTS

Fifty-one studies were included in this review. The strongest and most consistent findings were significant protective effects of perceived emotional support, perceived instrumental support, and large, diverse social networks. Little evidence was found on whether social connectedness is related to depression, as was also the case for negative interactions.

LIMITATIONS

Due to the strict inclusion criteria relating to study quality and the availability of papers in the domain of interest, the review did not capture 'gray literature' and qualitative studies.

CONCLUSION

Future research is warranted to account for potential bias introduced by the use of subjective measures as compared to objective measures of received support and actual networks. Due to the heterogeneity between available studies on the measure of social relationships, the inclusion of comparable measures across studies would allow for more valid comparisons. In addition, well-designed prospective studies will provide more insight into causality. Future research should address how social support and networks interact and together affect risks for depression. Social connectedness and negative interactions appear to be underutilized as measures in population-based studies.

The use of technology in Suicide Prevention

Suicide is one of the leading causes of death globally, and is notably a significant cause of death amongst young people. A suicide outcome is a complex combination of personal, social, and health factors, and therefore suicide prevention is a challenge, requiring a systems approach incorporating public health strategies, screening at-risk individuals, targeted interventions, and follow-up for suicide survivors and those bereaved by suicide. Engineering practice has been implicated in the hindrance of the adoption of suicide prevention strategies, such as installing safety barriers at the Golden Gate Bridge, however technological developments offer new opportunities in suicide prevention, and the potential to reduce the number of deaths by suicide. We present an overview of current technological developments which are facilitating research in the field of suicide prevention, including multiple modes of screening such as network analysis of mobile-phone collected connectivity data, automatic detection of suicidality from social media content, and crisis detection from acoustic variability in speech patterns. The current field of mhealth apps for suicide prevention is assessed, and an innovative app for an Indigenous population is presented. From this overview, future challenges - technical and ethical - are discussed.

Depressive Symptoms: The Interaction between Rumination and Self-Reported Insomnia

Objective. Prior research has found consistent support that rumination and insomnia are important risk factors for depressive symptoms. The aim of the present cross-sectional study is to examine the interaction between these two previously well-established risk factors (i.e., rumination and insomnia) in the explanation of depressive symptoms. Design. A total of 417 participants (277 women) with a mean age of 39 (SD = 17.59; range 18-85) completed a cross-sectional survey. Main Outcome Measures. Participants filled out the Response Rumination Scale, the Athens Insomnia Scale, and the short version of the Center for Epidemiologic Studies Depression Scale. Results. It was predicted and found that self-reported insomnia moderated the relationship between rumination and depressive symptoms. We found that particularly participants who reported higher levels of rumination as well as insomnia had the highest depressive symptoms. Conclusion. This study is the first to suggest that particularly individuals exhibiting both self-reported insomnia and higher levels of rumination also report higher levels of depressive symptoms. Health professionals screening for mental problems should be aware of this specific combination of insomnia and rumination. Explanations for this moderation effect were discussed in light of study's limitations.

Bidirectional Influence: A Longitudinal Analysis of Size of Drug Network and Depression Among Inner-City Residents in Baltimore, Maryland

BACKGROUND

The prevalence of depression among drug users is high. It has been recognized that drug use behaviors can be influenced and spread through social networks.

OBJECTIVES

We investigated the directional relationship between social network factors and depressive symptoms among a sample of inner-city residents in Baltimore, MD.

METHODS

We performed a longitudinal study of four-wave data collected from a network-based HIV/STI prevention intervention for women and network members, consisting of both men and women. Our primary outcome and exposure were depression using CESD scale and social network characteristics, respectively. Linear-mixed model with clustering adjustment was used to account for both repeated measurement and network design.

RESULTS

Of the 746 participants, those who had high levels of depression tended to be female, less educated, homeless, smokers, and did not have a main partner. In the univariate longitudinal model, larger size of drug network was significantly associated with depression (OR = 1.38, p < .001). This relationship held after controlling for age, gender, homeless in the past 6 months, college education, having a main partner, cigarette smoking, perceived health, and social support network (aOR = 1.19, p = .001). In the univariate mixed model using depression to predict size of drug network, the data suggested that depression was associated with larger size of drug network (coef. = 1.23, p < .001) and the same relation held in multivariate model (adjusted coef. = 1.08, p = .001).

CONCLUSIONS

The results suggest that larger size of drug network is a risk factor for depression, and vice versa. Further intervention strategies to reduce depression should address social networks factors.