The emerging field of emotion regulation studies how individuals influence which emotions they have, when they have them, and how they experience and express them. This review takes an evolutionary perspective and characterizes emotion in terms of response tendencies. Emotion regulation is denned and distinguished from coping, mood regulation, defense, and affect regulation. In the increasingly specialized discipline of psychology, the field of emotion regulation cuts across traditional boundaries and provides common ground. According to a process model of emotion regulation, emotion may be regulated at five points in the emotion generative process: (a) selection of the situation, (b) modification of the situation, (c) deployment of attention, (d) change of cognitions, and (e) modulation of responses. The field of emotion regulation promises new insights into age-old questions about how people manage their emotions.

http://www.elaborer.org/cours/A13/lectures/Gross1998.pdf

The emerging field of emotion regulation: An integrative review.

Over 60 years ago, Selye1 recognized the paradox that the physiologic systems activated by stress can not only protect and restore but also damage the body. What links these seemingly contradictory roles? How does stress influence the pathogenesis of disease, and what accounts for the variation in vulnerability to stress-related diseases among people with similar life experiences? How can stress-induced damage be quantified? These and many other questions still challenge investigators. This article reviews the long-term effect of the physiologic response to stress, which I refer to as allostatic load.2 Allostasis — the ability to achieve stability through change3 — . . .

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Protective and Damaging Effects of Stress Mediators

Background 
The quality and quantity of individuals' social relationships has been linked not only to mental health but also to both morbidity and mortality.
Objectives 
This meta-analytic review was conducted to determine the extent to which social relationships influence risk for mortality, which aspects of social relationships are most highly predictive, and which factors may moderate the risk.
Data Extraction 
Data were extracted on several participant characteristics, including cause of mortality, initial health status, and pre-existing health conditions, as well as on study characteristics, including length of follow-up and type of assessment of social relationships.
Results 
Across 148 studies (308,849 participants), the random effects weighted average effect size was OR = 1.50 (95% CI 1.42 to 1.59), indicating a 50% increased likelihood of survival for participants with stronger social relationships. This finding remained consistent across age, sex, initial health status, cause of death, and follow-up period. Significant differences were found across the type of social measurement evaluated (p<0.001); the association was strongest for complex measures of social integration (OR = 1.91; 95% CI 1.63 to 2.23) and lowest for binary indicators of residential status (living alone versus with others) (OR = 1.19; 95% CI 0.99 to 1.44).
Conclusions 
The influence of social relationships on risk for mortality is comparable with well-established risk factors for mortality.

Please see later in the article for the Editors' Summary

/pdf/social-relationships-and-mortality-risk-a-meta-analytic-2ghmxi4ksm.pdf

Social Relationships and Mortality Risk: A Meta-analytic Review

The author discusses 3 variables that assess different aspects of social relationships—social support, social integration, and negative interaction. The author argues that all 3 are associated with health outcomes, that these variables each influence health through different mechanisms, and that associations between these variables and health are not spurious findings attributable to our personalities. This argument suggests a broader view of how to intervene in social networks to improve health. This includes facilitating both social integration and social support by creating and nurturing both close (strong) and peripheral (weak) ties within natural social networks and reducing opportunities for negative social interaction. Finally, the author emphasizes the necessity to understand more about who benefits most and least from socialconnectedness interventions.

/pdf/social-relationships-and-health-3l9d7bp4y3.pdf

Social relationships and health.

Using a process model of emotion, a distinction between antecedent-focused and response-focused emotion regulation is proposed. To test this distinction, 120 participants were shown a disgusting film while their experiential, behavioral, and physiological responses were recorded. Participants were told to either (a) think about the film in such a way that they would feel nothing (reappraisal, a form of antecedent-focused emotion regulation), (b) behave in such a way that someone watching them would not know they were feeling anything (suppression, a form of response-focused emotion regulation), or (c) watch the film (a control condition). Compared with the control condition, both reappraisal and suppression were effective in reducing emotion-expressive behavior. However, reappraisal decreased disgust experience, whereas suppression increased sympathetic activation. These results suggest that these 2 emotion regulatory processes may have different adaptive consequences.

/pdf/antecedent-and-response-focused-emotion-regulation-divergent-vs5od848ei.pdf

Antecedent- and response-focused emotion regulation: Divergent consequences for experience, expression, and physiology.

Effect of psychosocial treatment on survival of patients with metastatic breast cancer

The effects of family environment on the psychological adjustment of 54 women with metastatic carcinoma of the breast were studied over a one-year period. Family environment was assessed using the Family Environment Scale (FES) and a descriptive checklist, and adjustment was measured using the Profile of Mood States (POMS). Patients described their families as supportive and relatively free of conflict, and their spouses or other family members agreed moderately with them. Patient mood disturbance during the year was made the dependent variable in a stepwise multiple regression analysis, with FES subscale scores at the beginning of the year and other control variables as predictors. Better adjustment was found to be predicted by more expressiveness and less conflict and moral-religious orientation in the family. These findings are presented as evidence that the family is a crucial factor in patient adjustment, and that 'conspiracies of silence' in the family may be harmful. A clinical illustration is pres...

Ellen Gottheil

Papers

Effect of psychosocial treatment on survival of patients with metastatic breast cancer

Family Environment as a Predictor of Adjustment to Metastatic Breast Carcinoma

Psychological support for cancer patients