scholarly articles stress

An official website of the United States government

The .gov means it’s official. Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

The site is secure. The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

• Publications
• Account settings
• Advanced Search
• Journal List
• HHS Author Manuscripts

STRESS AND HEALTH: Psychological, Behavioral, and Biological Determinants

Stressors have a major influence upon mood, our sense of well-being, behavior, and health. Acute stress responses in young, healthy individuals may be adaptive and typically do not impose a health burden. However, if the threat is unremitting, particularly in older or unhealthy individuals, the long-term effects of stressors can damage health. The relationship between psychosocial stressors and disease is affected by the nature, number, and persistence of the stressors as well as by the individual’s biological vulnerability (i.e., genetics, constitutional factors), psychosocial resources, and learned patterns of coping. Psychosocial interventions have proven useful for treating stress-related disorders and may influence the course of chronic diseases.

INTRODUCTION

Claude Bernard (1865/1961) noted that the maintenance of life is critically dependent on keeping our internal milieu constant in the face of a changing environment. Cannon (1929) called this “homeostasis.” Selye (1956) used the term “stress” to represent the effects of anything that seriously threatens homeostasis. The actual or perceived threat to an organism is referred to as the “stressor” and the response to the stressor is called the “stress response.” Although stress responses evolved as adaptive processes, Selye observed that severe, prolonged stress responses might lead to tissue damage and disease.

Based on the appraisal of perceived threat, humans and other animals invoke coping responses ( Lazarus & Folkman 1984 ). Our central nervous system (CNS) tends to produce integrated coping responses rather than single, isolated response changes ( Hilton 1975 ). Thus, when immediate fight-or-flight appears feasible, mammals tend to show increased autonomic and hormonal activities that maximize the possibilities for muscular exertion ( Cannon 1929 , Hess 1957 ). In contrast, during aversive situations in which an active coping response is not available, mammals may engage in a vigilance response that involves sympathetic nervous system (SNS) arousal accompanied by an active inhibition of movement and shunting of blood away from the periphery ( Adams et al. 1968 ). The extent to which various situations elicit different patterns of biologic response is called “situational stereotypy” ( Lacey 1967 ).

Although various situations tend to elicit different patterns of stress responses, there are also individual differences in stress responses to the same situation. This tendency to exhibit a particular pattern of stress responses across a variety of stressors is referred to as “response stereotypy” ( Lacey & Lacey 1958 ). Across a variety of situations, some individuals tend to show stress responses associated with active coping, whereas others tend to show stress responses more associated with aversive vigilance ( Kasprowicz et al. 1990 , Llabre et al. 1998 ).

Although genetic inheritance undoubtedly plays a role in determining individual differences in response stereotypy, neonatal experiences in rats have been shown to produce long-term effects in cognitive-emotional responses ( Levine 1957 ). For example, Meaney et al. (1993) showed that rats raised by nurturing mothers have increased levels of central serotonin activity compared with rats raised by less nurturing mothers. The increased serotonin activity leads to increased expression of a central glucocorticoid receptor gene. This, in turn, leads to higher numbers of glucocorticoid receptors in the limbic system and improved glucocorticoid feedback into the CNS throughout the rat’s life. Interestingly, female rats who receive a high level of nurturing in turn become highly nurturing mothers whose offspring also have high levels of glucocorticoid receptors. This example of behaviorally induced gene expression shows how highly nurtured rats develop into low-anxiety adults, who in turn become nurturing mothers with reduced stress responses.

In contrast to highly nurtured rats, pups separated from their mothers for several hours per day during early life have a highly active hypothalamic-pituitary adrenocortical axis and elevated SNS arousal ( Ladd et al. 2000 ). These deprived rats tend to show larger and more frequent stress responses to the environment than do less deprived animals.

Because evolution has provided mammals with reasonably effective homeostatic mechanisms (e.g., baroreceptor reflex) for dealing with short-term stressors, acute stress responses in young, healthy individuals typically do not impose a health burden. However, if the threat is persistent, particularly in older or unhealthy individuals, the long-term effects of the response to stress may damage health ( Schneiderman 1983 ). Adverse effects of chronic stressors are particularly common in humans, possibly because their high capacity for symbolic thought may elicit persistent stress responses to a broad range of adverse living and working conditions. The relationship between psychosocial stressors and chronic disease is complex. It is affected, for example, by the nature, number, and persistence of the stressors as well as by the individual’s biological vulnerability (i.e., genetics, constitutional factors) and learned patterns of coping. In this review, we focus on some of the psychological, behavioral, and biological effects of specific stressors, the mediating psychophysiological pathways, and the variables known to mediate these relationships. We conclude with a consideration of treatment implications.

PSYCHOLOGICAL ASPECTS OF STRESS

Stressors during childhood and adolescence and their psychological sequelae.

The most widely studied stressors in children and adolescents are exposure to violence, abuse (sexual, physical, emotional, or neglect), and divorce/marital conflict (see Cicchetti 2005 ). McMahon et al. (2003) also provide an excellent review of the psychological consequences of such stressors. Psychological effects of maltreatment/abuse include the dysregulation of affect, provocative behaviors, the avoidance of intimacy, and disturbances in attachment ( Haviland et al. 1995 , Lowenthal 1998 ). Survivors of childhood sexual abuse have higher levels of both general distress and major psychological disturbances including personality disorders ( Polusny & Follett 1995 ). Childhood abuse is also associated with negative views toward learning and poor school performance ( Lowenthal 1998 ). Children of divorced parents have more reported antisocial behavior, anxiety, and depression than their peers ( Short 2002 ). Adult offspring of divorced parents report more current life stress, family conflict, and lack of friend support compared with those whose parents did not divorce ( Short 2002 ). Exposure to nonresponsive environments has also been described as a stressor leading to learned helplessness ( Peterson & Seligman 1984 ).

Studies have also addressed the psychological consequences of exposure to war and terrorism during childhood ( Shaw 2003 ). A majority of children exposed to war experience significant psychological morbidity, including both post-traumatic stress disorder (PTSD) and depressive symptoms. For example, Nader et al. (1993) found that 70% of Kuwaiti children reported mild to severe PTSD symptoms after the Gulf War. Some effects are long lasting: Macksound & Aber (1996) found that 43% of Lebanese children continued to manifest post-traumatic stress symptoms 10 years after exposure to war-related trauma.

Exposure to intense and chronic stressors during the developmental years has long-lasting neurobiological effects and puts one at increased risk for anxiety and mood disorders, aggressive dyscontrol problems, hypo-immune dysfunction, medical morbidity, structural changes in the CNS, and early death ( Shaw 2003 ).

Stressors During Adulthood and Their Psychological Sequelae

Life stress, anxiety, and depression.

It is well known that first depressive episodes often develop following the occurrence of a major negative life event ( Paykel 2001 ). Furthermore, there is evidence that stressful life events are causal for the onset of depression (see Hammen 2005 , Kendler et al. 1999 ). A study of 13,006 patients in Denmark, with first psychiatric admissions diagnosed with depression, found more recent divorces, unemployment, and suicides by relatives compared with age- and gender-matched controls ( Kessing et al. 2003 ). The diagnosis of a major medical illness often has been considered a severe life stressor and often is accompanied by high rates of depression ( Cassem 1995 ). For example, a meta-analysis found that 24% of cancer patients are diagnosed with major depression ( McDaniel et al. 1995 ).

Stressful life events often precede anxiety disorders as well ( Faravelli & Pallanti 1989 , Finlay-Jones & Brown 1981 ). Interestingly, long-term follow-up studies have shown that anxiety occurs more commonly before depression ( Angst &Vollrath 1991 , Breslau et al. 1995 ). In fact, in prospective studies, patients with anxiety are most likely to develop major depression after stressful life events occur ( Brown et al. 1986 ).

DISORDERS RELATED TO TRAUMA

Lifetime exposure to traumatic events in the general population is high, with estimates ranging from 40% to 70% ( Norris 1992 ). Of note, an estimated 13% of adult women in the United States have been exposed to sexual assault ( Kilpatrick et al. 1992 ). The Diagnostic and Statistical Manual (DSM-IV-TR; American Psychiatric Association 2000 ) includes two primary diagnoses related to trauma: Acute Stress Disorder (ASD) and PTSD. Both these disorders have as prominent features a traumatic event involving actual or threatened death or serious injury and symptom clusters including re-experiencing of the traumatic event (e.g., intrusive thoughts), avoidance of reminders/numbing, and hyperarousal (e.g., difficulty falling or staying asleep). The time frame for ASD is shorter (lasting two days to four weeks), with diagnosis limited to within one month of the incident. ASD was introduced in 1994 to describe initial trauma reactions, but it has come under criticism ( Harvey & Bryant 2002 ) for weak empirical and theoretical support. Most people who have symptoms of PTSD shortly after a traumatic event recover and do not develop PTSD. In a comprehensive review, Green (1994) estimates that approximately 25% of those exposed to traumatic events develop PTSD. Surveys of the general population indicate that PTSD affects 1 in 12 adults at some time in their life ( Kessler et al. 1995 ). Trauma and disasters are related not only to PTSD, but also to concurrent depression, other anxiety disorders, cognitive impairment, and substance abuse ( David et al. 1996 , Schnurr et al. 2002 , Shalev 2001 ).

Other consequences of stress that could provide linkages to health have been identified, such as increases in smoking, substance use, accidents, sleep problems, and eating disorders. Populations that live in more stressful environments (communities with higher divorce rates, business failures, natural disasters, etc.) smoke more heavily and experience higher mortality from lung cancer and chronic obstructive pulmonary disorder ( Colby et al. 1994 ). A longitudinal study following seamen in a naval training center found that more cigarette smoking occurred on high-stress days ( Conway et al. 1981 ). Life events stress and chronically stressful conditions have also been linked to higher consumption of alcohol ( Linsky et al. 1985 ). In addition, the possibility that alcohol may be used as self-medication for stress-related disorders such as anxiety has been proposed. For example, a prospective community study of 3021 adolescents and young adults ( Zimmerman et al. 2003 ) found that those with certain anxiety disorders (social phobia and panic attacks) were more likely to develop substance abuse or dependence prospectively over four years of follow-up. Life in stressful environments has also been linked to fatal accidents ( Linsky & Strauss 1986 ) and to the onset of bulimia ( Welch et al. 1997 ). Another variable related to stress that could provide a link to health is the increased sleep problems that have been reported after sychological trauma ( Harvey et al. 2003 ). New onset of sleep problems mediated the relationship between post-traumatic stress symptoms and decreased natural killer (NK) cell cytotoxicity in Hurricane Andrew victims ( Ironson et al. 1997 ).

Variations in Stress Responses

Certain characteristics of a situation are associated with greater stress responses. These include the intensity or severity of the stressor and controllability of the stressor, as well as features that determine the nature of the cognitive responses or appraisals. Life event dimensions of loss, humiliation, and danger are related to the development of major depression and generalized anxiety ( Kendler et al. 2003 ). Factors associated with the development of symptoms of PTSD and mental health disorders include injury, damage to property, loss of resources, bereavement, and perceived life threat ( Freedy et al. 1992 , Ironson et al. 1997 , McNally 2003 ). Recovery from a stressor can also be affected by secondary traumatization ( Pfefferbaum et al. 2003 ). Other studies have found that multiple facets of stress that may work synergistically are more potent than a single facet; for example, in the area of work stress, time pressure in combination with threat ( Stanton et al. 2001 ), or high demand in combination with low control ( Karasek & Theorell 1990 ).

Stress-related outcomes also vary according to personal and environmental factors. Personal risk factors for the development of depression, anxiety, or PTSD after a serious life event, disaster, or trauma include prior psychiatric history, neuroticism, female gender, and other sociodemographic variables ( Green 1996 , McNally 2003 , Patton et al. 2003 ). There is also some evidence that the relationship between personality and environmental adversity may be bidirectional ( Kendler et al. 2003 ). Levels of neuroticism, emotionality, and reactivity correlate with poor interpersonal relationships as well as “event proneness.” Protective factors that have been identified include, but are not limited to, coping, resources (e.g., social support, self-esteem, optimism), and finding meaning. For example, those with social support fare better after a natural disaster ( Madakaisira & O’Brien 1987 ) or after myocardial infarction ( Frasure-Smith et al. 2000 ). Pruessner et al. (1999) found that people with higher self-esteem performed better and had lower cortisol responses to acute stressors (difficult math problems). Attaching meaning to the event is another protective factor against the development of PTSD, even when horrific torture has occurred. Left-wing political activists who were tortured by Turkey’s military regime had lower rates of PTSD than did nonactivists who were arrested and tortured by the police ( Basoğlu et al. 1994 ).

Finally, human beings are resilient and in general are able to cope with adverse situations. A recent illustration is provided by a study of a nationally representative sample of Israelis after 19 months of ongoing exposure to the Palestinian intifada. Despite considerable distress, most Israelis reported adapting to the situation without substantial mental health symptoms or impairment ( Bleich et al. 2003 ).

BIOLOGICAL RESPONSES TO STRESSORS

Acute stress responses.

Following the perception of an acute stressful event, there is a cascade of changes in the nervous, cardiovascular, endocrine, and immune systems. These changes constitute the stress response and are generally adaptive, at least in the short term ( Selye 1956 ). Two features in particular make the stress response adaptive. First, stress hormones are released to make energy stores available for the body’s immediate use. Second, a new pattern of energy distribution emerges. Energy is diverted to the tissues that become more active during stress, primarily the skeletal muscles and the brain. Cells of the immune system are also activated and migrate to “battle stations” ( Dhabar & McEwen 1997 ). Less critical activities are suspended, such as digestion and the production of growth and gonadal hormones. Simply put, during times of acute crisis, eating, growth, and sexual activity may be a detriment to physical integrity and even survival.

Stress hormones are produced by the SNS and hypothalamic-pituitary adrenocortical axis. The SNS stimulates the adrenal medulla to produce catecholamines (e.g., epinephrine). In parallel, the paraventricular nucleus of the hypothalamus produces corticotropin releasing factor, which in turn stimulates the pituitary to produce adrenocorticotropin. Adrenocorticotropin then stimulates the adrenal cortex to secrete cortisol. Together, catecholamines and cortisol increase available sources of energy by promoting lipolysis and the conversion of glycogen into glucose (i.e., blood sugar). Lipolysis is the process of breaking down fats into usable sources of energy (i.e., fatty acids and glycerol; Brindley & Rollan 1989 ).

Energy is then distributed to the organs that need it most by increasing blood pressure levels and contracting certain blood vessels while dilating others. Blood pressure is increased with one of two hemodynamic mechanisms ( Llabre et al.1998 , Schneiderman & McCabe 1989 ). The myocardial mechanism increases blood pressure through enhanced cardiac output; that is, increases in heart rate and stroke volume (i.e., the amount of blood pumped with each heart beat). The vascular mechanism constricts the vasculature, thereby increasing blood pressure much like constricting a hose increases water pressure. Specific stressors tend to elicit either myocardial or vascular responses, providing evidence of situational stereotypy ( Saab et al. 1992 , 1993 ). Laboratory stressors that call for active coping strategies, such as giving a speech or performing mental arithmetic, require the participant to do something and are associated with myocardial responses. In contrast, laboratory stressors that call for more vigilant coping strategies in the absence of movement, such as viewing a distressing video or keeping one’s foot in a bucket of ice water, are associated with vascular responses. From an evolutionary perspective, cardiac responses are believed to facilitate active coping by shunting blood to skeletal muscles, consistent with the fight-or-flight response. In situations where decisive action would not be appropriate, but instead skeletal muscle inhibition and vigilance are called for, a vascular hemodynamic response is adaptive. The vascular response shunts blood away from the periphery to the internal organs, thereby minimizing potential bleeding in the case of physical assault.

Finally, in addition to the increased availability and redistribution of energy, the acute stress response includes activation of the immune system. Cells of the innate immune system (e.g., macrophages and natural killer cells), the first line of defense, depart from lymphatic tissue and spleen and enter the bloodstream, temporarily raising the number of immune cells in circulation (i.e., leukocytosis). From there, the immune cells migrate into tissues that are most likely to suffer damage during physical confrontation (e.g., the skin). Once at “battle stations,” these cells are in position to contain microbes that may enter the body through wounds and thereby facilitate healing ( Dhabar & McEwen 1997 ).

Chronic Stress Responses

The acute stress response can become maladaptive if it is repeatedly or continuously activated ( Selye 1956 ). For example, chronic SNS stimulation of the cardiovascular system due to stress leads to sustained increases in blood pressure and vascular hypertrophy ( Henry et al. 1975 ). That is, the muscles that constrict the vasculature thicken, producing elevated resting blood pressure and response stereotypy, or a tendency to respond to all types of stressors with a vascular response. Chronically elevated blood pressure forces the heart to work harder, which leads to hypertrophy of the left ventricle ( Brownley et al. 2000 ). Over time, the chronically elevated and rapidly shifting levels of blood pressure can lead to damaged arteries and plaque formation.

The elevated basal levels of stress hormones associated with chronic stress also suppress immunity by directly affecting cytokine profiles. Cytokines are communicatory molecules produced primarily by immune cells (see Roitt et al. 1998 ). There are three classes of cytokines. Proinflammatory cytokines mediate acute inflammatory reactions. Th1 cytokines mediate cellular immunity by stimulating natural killer cells and cytotoxic T cells, immune cells that target intracellular pathogens (e.g., viruses). Finally, Th2 cytokines mediate humoral immunity by stimulating B cells to produce antibody, which “tags” extracellular pathogens (e.g., bacteria) for removal. In a meta-analysis of over 30 years of research, Segerstrom & Miller (2004) found that intermediate stressors, such as academic examinations, could promote a Th2 shift (i.e., an increase in Th2 cytokines relative to Th1 cytokines). A Th2 shift has the effect of suppressing cellular immunity in favor of humoral immunity. In response to more chronic stressors (e.g., long-term caregiving for a dementia patient), Segerstrom & Miller found that proinflammatory, Th1, and Th2 cytokines become dysregulated and lead both to suppressed humoral and cellular immunity. Intermediate and chronic stressors are associated with slower wound healing and recovery from surgery, poorer antibody responses to vaccination, and antiviral deficits that are believed to contribute to increased vulnerability to viral infections (e.g., reductions in natural killer cell cytotoxicity; see Kiecolt-Glaser et al. 2002 ).

Chronic stress is particularly problematic for elderly people in light of immunosenescence, the gradual loss of immune function associated with aging. Older adults are less able to produce antibody responses to vaccinations or combat viral infections ( Ferguson et al. 1995 ), and there is also evidence of a Th2 shift ( Glaser et al. 2001 ). Although research has yet to link poor vaccination responses to early mortality, influenza and other infectious illnesses are a major cause of mortality in the elderly, even among those who have received vaccinations (e.g., Voordouw et al. 2003 ).

PSYCHOSOCIAL STRESSORS AND HEALTH

Cardiovascular disease.

Both epidemiological and controlled studies have demonstrated relationships between psychosocial stressors and disease. The underlying mediators, however, are unclear in most cases, although possible mechanisms have been explored in some experimental studies. An occupational gradient in coronary heart disease (CHD) risk has been documented in which men with relatively low socioeconomic status have the poorest health outcomes ( Marmot 2003 ). Much of the risk gradient in CHD can be eliminated, however, by taking into account lack of perceived job control, which is a potent stressor ( Marmot et al. 1997 ). Other factors include risky behaviors such as smoking, alcohol use, and sedentary lifestyle ( Lantz et al. 1998 ), which may be facilitated by stress. Among men ( Schnall et al. 1994 ) and women ( Eaker 1998 ), work stress has been reported to be a predictor of incident CHD and hypertension ( Ironson 1992 ). However, in women with existing CHD, marital stress is a better predictor of poor prognosis than is work stress ( Orth-Gomer et al. 2000 ).

Although the observational studies cited thus far reveal provocative associations between psychosocial stressors and disease, they are limited in what they can tell us about the exact contribution of these stressors or about how stress mediates disease processes. Animal models provide an important tool for helping to understand the specific influences of stressors on disease processes. This is especially true of atherosclerotic CHD, which takes multiple decades to develop in humans and is influenced by a great many constitutional, demographic, and environmental factors. It would also be unethical to induce disease in humans by experimental means.

Perhaps the best-known animal model relating stress to atherosclerosis was developed by Kaplan et al. (1982) . Their study was carried out on male cynomolgus monkeys, who normally live in social groups. The investigators stressed half the animals by reorganizing five-member social groups at one- to three-month intervals on a schedule that ensured that each monkey would be housed with several new animals during each reorganization. The other half of the animals lived in stable social groups. All animals were maintained on a moderately atherogenic diet for 22 months. Animals were also assessed for their social status (i.e., relative dominance) within each group. The major findings were that ( a ) socially dominant animals living in unstable groups had significantly more atherosclerosis than did less dominant animals living in unstable groups; and ( b ) socially dominant male animals living in unstable groups had significantly more atherosclerosis than did socially dominant animals living in stable groups. Other important findings based upon this model have been that heart-rate reactivity to the threat of capture predicts severity of atherosclerosis ( Manuck et al. 1983 ) and that administration of the SNS-blocking agent propranolol decreases the progression of atherosclerosis ( Kaplan et al. 1987 ). In contrast to the findings in males, subordinate premenstrual females develop greater atherosclerosis than do dominant females ( Kaplan et al. 1984 ) because they are relatively estrogen deficient, tending to miss ovulatory cycles ( Adams et al. 1985 ).

Whereas the studies in cynomolgus monkeys indicate that emotionally stressful behavior can accelerate the progression of atherosclerosis, McCabe et al. (2002) have provided evidence that affiliative social behavior can slow the progression of atherosclerosis in the Watanabe heritable hyperlipidemic rabbit. This rabbit model has a genetic defect in lipoprotein clearance such that it exhibits hypercholesterolemia and severe atherosclerosis. The rabbits were assigned to one of three social or behavioral groups: ( a ) an unstable group in which unfamiliar rabbits were paired daily, with the pairing switched each week; ( b ) a stable group, in which littermates were paired daily for the entire study; and ( c ) an individually caged group. The stable group exhibited more affiliative behavior and less agonistic behavior than the unstable group and significantly less atherosclerosis than each of the other two groups. The study emphasizes the importance of behavioral factors in atherogenesis, even in a model of disease with extremely strong genetic determinants.

Upper Respiratory Diseases

The hypothesis that stress predicts susceptibility to the common cold received support from observational studies ( Graham et al. 1986 , Meyer & Haggerty 1962 ). One problem with such studies is that they do not control for exposure. Stressed people, for instance, might seek more outside contact and thus be exposed to more viruses. Therefore, in a more controlled study, people were exposed to a rhinovirus and then quarantined to control for exposure to other viruses ( Cohen et al. 1991 ). Those individuals with the most stressful life events and highest levels of perceived stress and negative affect had the greatest probability of developing cold symptoms. In a subsequent study of volunteers inoculated with a cold virus, it was found that people enduring chronic, stressful life events (i.e., events lasting a month or longer including unemployment, chronic underemployment, or continued interpersonal difficulties) had a high likelihood of catching cold, whereas people subjected to stressful events lasting less than a month did not ( Cohen et al. 1998 ).

Human Immunodeficiency Virus

The impact of life stressors has also been studied within the context of human immunodeficiency virus (HIV) spectrum disease. Leserman et al. (2000) followed men with HIV for up to 7.5 years and found that faster progression to AIDS was associated with higher cumulative stressful life events, use of denial as a coping mechanism, lower satisfaction with social support, and elevated serum cortisol.

Inflammation, the Immune System, and Physical Health

Despite the stress-mediated immunosuppressive effects reviewed above, stress has also been associated with exacerbations of autoimmune disease ( Harbuz et al. 2003 ) and other conditions in which excessive inflammation is a central feature, such as CHD ( Appels et al. 2000 ). Evidence suggests that a chronically activated, dysregulated acute stress response is responsible for these associations. Recall that the acute stress response includes the activation and migration of cells of the innate immune system. This effect is mediated by proinflammatory cytokines. During periods of chronic stress, in the otherwise healthy individual, cortisol eventually suppresses proinflammatory cytokine production. But in individuals with autoimmune disease or CHD, prolonged stress can cause proinflammatory cytokine production to remain chronically activated, leading to an exacerbation of pathophysiology and symptomatology.

Miller et al. (2002) proposed the glucocorticoid-resistance model to account for this deficit in proinflammatory cytokine regulation. They argue that immune cells become “resistant” to the effects of cortisol (i.e., a type of glucocorticoid), primarily through a reduction, or downregulation, in the number of expressed cortisol receptors. With cortisol unable to suppress inflammation, stress continues to promote proinflammatory cytokine production indefinitely. Although there is only preliminary empirical support for this model, it could have implications for diseases of inflammation. For example, in rheumatoid arthritis, excessive inflammation is responsible for joint damage, swelling, pain, and reduced mobility. Stress is associated with more swelling and reduced mobility in rheumatoid arthritis patients ( Affleck et al. 1997 ). Similarly, in multiple sclerosis (MS), an overactive immune system targets and destroys the myelin surrounding nerves, contributing to a host of symptoms that include paralysis and blindness. Again, stress is associated with an exacerbation of disease ( Mohr et al. 2004 ). Even in CHD, inflammation plays a role. The immune system responds to vascular injury just as it would any other wound: Immune cells migrate to and infiltrate the arterial wall, setting off a cascade of biochemical processes that can ultimately lead to a thrombosis (i.e., clot; Ross 1999 ). Elevated levels of inflammatory markers, such as C-reactive protein (CRP), are predictive of heart attacks, even when controlling for other traditional risk factors (e.g., cholesterol, blood pressure, and smoking; Morrow & Ridker 2000 ). Interestingly, a history of major depressive episodes has been associated with elevated levels of CRP in men ( Danner et al. 2003 ).

Inflammation, Cytokine Production, and Mental Health

In addition to its effects on physical health, prolonged proinflammatory cytokine production may also adversely affect mental health in vulnerable individuals. During times of illness (e.g., the flu), proinflammatory cytokines feed back to the CNS and produce symptoms of fatigue, malaise, diminished appetite, and listlessness, which are symptoms usually associated with depression. It was once thought that these symptoms were directly caused by infectious pathogens, but more recently, it has become clear that proinflammatory cytokines are both sufficient and necessary (i.e., even absent infection or fever) to generate sickness behavior ( Dantzer 2001 , Larson & Dunn 2001 ).

Sickness behavior has been suggested to be a highly organized strategy that mammals use to combat infection ( Dantzer 2001 ). Symptoms of illness, as previously thought, are not inconsequential or even maladaptive. On the contrary, sickness behavior is thought to promote resistance and facilitate recovery. For example, an overall decrease in activity allows the sick individual to preserve energy resources that can be redirected toward enhancing immune activity. Similarly, limiting exploration, mating, and foraging further preserves energy resources and reduces the likelihood of risky encounters (e.g., fighting over a mate). Furthermore, decreasing food intake also decreases the level of iron in the blood, thereby decreasing bacterial replication. Thus, for a limited period, sickness behavior may be looked upon as an adaptive response to the stress of illness.

Much like other aspects of the acute stress response, however, sickness behavior can become maladaptive when repeatedly or continuously activated. Many features of the sickness behavior response overlap with major depression. Indeed, compared with healthy controls, elevated rates of depression are reported in patients with inflammatory diseases such as MS ( Mohr et al. 2004 ) or CHD ( Carney et al. 1987 ). Granted, MS patients face a number of stressors and reports of depression are not surprising. However, when compared with individuals facing similar disability who do not have MS (e.g., car accident victims), MS patients still report higher levels of depression ( Ron & Logsdail 1989 ). In both MS ( Fassbender et al. 1998 ) and CHD ( Danner et al. 2003 ), indicators of inflammation have been found to be correlated with depressive symptomatology. Thus, there is evidence to suggest that stress contributes to both physical and mental disease through the mediating effects of proinflammatory cytokines.

HOST VULNERABILITY-STRESSOR INTERACTIONS AND DISEASE

The changes in biological set points that occur across the life span as a function of chronic stressors are referred to as allostasis, and the biological cost of these adjustments is known as allostatic load ( McEwen 1998 ). McEwen has also suggested that cumulative increases in allostatic load are related to chronic illness. These are intriguing hypotheses that emphasize the role that stressors may play in disease. The challenge, however, is to show the exact interactions that occur among stressors, pathogens, host vulnerability (both constitutional and genetic), and such poor health behaviors as smoking, alcohol abuse, and excessive caloric consumption. Evidence of a lifetime trajectory of comorbidities does not necessarily imply that allostatic load is involved since immunosenescence, genetic predisposition, pathogen exposure, and poor health behaviors may act as culprits.

It is not clear, for example, that changes in set point for variables such as blood pressure are related to cumulative stressors per se, at least in healthy young individuals. Thus, for example, British soldiers subjected to battlefield conditions for more than a year in World War II showed chronic elevations in blood pressure, which returned to normal after a couple of months away from the front ( Graham 1945 ). In contrast, individuals with chronic illnesses such as chronic fatigue syndrome may show a high rate of relapse after a relatively acute stressor such as a hurricane ( Lutgendorf et al. 1995 ). Nevertheless, by emphasizing the role that chronic stressors may play in multiple disease outcomes, McEwen has helped to emphasize an important area of study.

TREATMENT FOR STRESS-RELATED DISORDERS

For PTSD, useful treatments include cognitive-behavioral therapy (CBT), along with exposure and the more controversial Eye Movement Desensitization and Reprocessing ( Foa & Meadows 1997 , Ironson et al. 2002 , Shapiro 1995 ). Psychopharmacological approaches have also been suggested ( Berlant 2001 ). In addition, writing about trauma has been helpful both for affective recovery and for potential health benefit ( Pennebaker 1997 ). For outpatients with major depression, Beck’s CBT ( Beck 1976 ) and interpersonal therapy ( Klerman et al. 1984 ) are as effective as psychopharmacotherapy ( Clinical Practice Guidelines 1993 ). However, the presence of sleep problems or hypercortisolemia is associated with poorer response to psychotherapy ( Thase 2000 ). The combination of psychotherapy and pharmacotherapy seems to offer a substantial advantage over psychotherapy alone for the subset of patients who are more severely depressed or have recurrent depression ( Thase et al. 1997 ). For the treatment of anxiety, it depends partly on the specific disorder [e.g., generalized anxiety disorder (GAD), panic disorder, social phobia], although CBT including relaxation training has demonstrated efficacy in several subtypes of anxiety ( Borkovec & Ruscio 2001 ). Antidepressants such as selective serotonin reuptake inhibitors also show efficacy in anxiety ( Ballenger et al. 2001 ), especially when GAD is comorbid with major depression, which is the case in 39% of subjects with current GAD ( Judd et al. 1998 ).

BEHAVIORAL INTERVENTIONS IN CHRONIC DISEASE

Patients dealing with chronic, life-threatening diseases must often confront daily stressors that can threaten to undermine even the most resilient coping strategies and overwhelm the most abundant interpersonal resources. Psychosocial interventions, such as cognitive-behavioral stress management (CBSM), have a positive effect on the quality of life of patients with chronic disease ( Schneiderman et al. 2001 ). Such interventions decrease perceived stress and negative mood (e.g., depression), improve perceived social support, facilitate problem-focused coping, and change cognitive appraisals, as well as decrease SNS arousal and the release of cortisol from the adrenal cortex. Psychosocial interventions also appear to help chronic pain patients reduce their distress and perceived pain as well as increase their physical activity and ability to return to work ( Morley et al. 1999 ). These psychosocial interventions can also decrease patients’ overuse of medications and utilization of the health care system. There is also some evidence that psychosocial interventions may have a favorable influence on disease progression ( Schneiderman et al. 2001 ).

Morbidity, Mortality, and Markers of Disease Progression

Psychosocial intervention trials conducted upon patients following acute myocardial infarction (MI) have reported both positive and null results. Two meta-analyses have reported a reduction in both mortality and morbidity of approximately 20% to 40% ( Dusseldorp et al. 1999 , Linden et al. 1996 ). Most of these studies were carried out in men. The major study reporting positive results was the Recurrent Coronary Prevention Project (RCPP), which employed group-based CBT, and decreased hostility and depressed affect ( Mendes de Leon et al. 1991 ), as well as the composite medical end point of cardiac death and nonfatal MI ( Friedman et al. 1986 ).

In contrast, the major study reporting null results for medical end points was the Enhancing Recovery in Coronary Heart Disease (ENRICHD) clinical trial ( Writing Committee for ENRICHD Investigators 2003 ), which found that the intervention modestly decreased depression and increased perceived social support, but did not affect the composite medical end point of death and nonfatal MI. However, a secondary analysis, which examined the effects of the psychosocial intervention within gender by ethnicity subgroups, found significant decreases approaching 40% in both cardiac death and nonfatal MI for white men but not for other subgroups such as minority women ( Schneiderman et al. 2004 ). Although there were important differences between the RCPP and ENRICHD in terms of the objectives of psychosocial intervention and the duration and timing of treatment, it should also be noted that more than 90% of the patients in the RCPP were white men. Thus, because primarily white men, but not other subgroups, may have benefited from the ENRICHD intervention, future studies need to attend to variables that may have prevented morbidity and mortality benefits among gender and ethnic subgroups other than white men.

Psychosocial intervention trials conducted upon patients with cancer have reported both positive and null results with regard to survival ( Classen 1998 ). A number of factors that generally characterized intervention trials that observed significant positive effects on survival were relatively absent in trials that failed to show improved survival. These included: ( a ) having only patients with the same type and severity of cancer within each group, ( b ) creation of a supportive environment, ( c ) having an educational component, and ( d ) provision of stress-management and coping-skills training. In one study that reported positive results, Fawzy et al. (1993) found that patients with early stage melanoma assigned to a six-week cognitive-behavioral stress management (CBSM) group showed significantly longer survival and longer time to recurrence over a six-year follow-up period compared with those receiving surgery and standard care alone. The intervention also significantly reduced distress, enhanced active coping, and increased NK cell cytotoxicity compared with controls.

Although published studies have not yet shown that psychosocial interventions can decrease disease progression in HIV/AIDS, several studies have significantly influenced factors that have been associated with HIV/AIDS disease progression ( Schneiderman & Antoni 2003 ). These variables associated with disease progression include distress, depressed affect, denial coping, low perceived social support, and elevated serum cortisol ( Ickovics et al. 2001 , Leserman et al. 2000 ). Antoni et al. have used group-based CBSM (i.e., CBT plus relaxation training) to decrease the stress-related effects of HIV+ serostatus notification. Those in the intervention condition showed lower distress, anxiety, and depressed mood than did those in the control condition as well as lower antibody titers of herpesviruses and higher levels of T-helper (CD4) cells, NK cells, and lymphocyte proliferation ( Antoni et al. 1991 , Esterling et al. 1992 ). In subsequent studies conducted upon symptomatic HIV+ men who were not attempting to determine their HIV serostatus, CBSM decreased distress, dysphoria, anxiety, herpesvirus antibody titers, cortisol, and epinephrine ( Antoni et al. 2000a , b ; Lutgendorf et al. 1997 ). Improvement in perceived social support and adaptive coping skills mediated the decreases in distress ( Lutgendorf et al. 1998 ). In summary, it appears that CBSM can positively influence stress-related variables that have been associated with HIV/AIDS progression. Only a randomized clinical trial, however, could document that CBSM can specifically decrease HIV/AIDS disease progression.

Stress is a central concept for understanding both life and evolution. All creatures face threats to homeostasis, which must be met with adaptive responses. Our future as individuals and as a species depends on our ability to adapt to potent stressors. At a societal level, we face a lack of institutional resources (e.g., inadequate health insurance), pestilence (e.g., HIV/AIDS), war, and international terrorism that has reached our shores. At an individual level, we live with the insecurities of our daily existence including job stress, marital stress, and unsafe schools and neighborhoods. These are not an entirely new condition as, in the last century alone, the world suffered from instances of mass starvation, genocide, revolutions, civil wars, major infectious disease epidemics, two world wars, and a pernicious cold war that threatened the world order. Although we have chosen not to focus on these global threats in this paper, they do provide the backdrop for our consideration of the relationship between stress and health.

A widely used definition of stressful situations is one in which the demands of the situation threaten to exceed the resources of the individual ( Lazarus & Folkman 1984 ). It is clear that all of us are exposed to stressful situations at the societal, community, and interpersonal level. How we meet these challenges will tell us about the health of our society and ourselves. Acute stress responses in young, healthy individuals may be adaptive and typically do not impose a health burden. Indeed, individuals who are optimistic and have good coping responses may benefit from such experiences and do well dealing with chronic stressors ( Garmezy 1991 , Glanz & Johnson 1999 ). In contrast, if stressors are too strong and too persistent in individuals who are biologically vulnerable because of age, genetic, or constitutional factors, stressors may lead to disease. This is particularly the case if the person has few psychosocial resources and poor coping skills. In this chapter, we have documented associations between stressors and disease and have described how endocrine-immune interactions appear to mediate the relationship. We have also described how psychosocial stressors influence mental health and how psychosocial treatments may ameliorate both mental and physical disorders. There is much we do not yet know about the relationship between stress and health, but scientific findings being made in the areas of cognitive-emotional psychology, molecular biology, neuroscience, clinical psychology, and medicine will undoubtedly lead to improved health outcomes.

ACKNOWLEDGMENTS

Preparation of this manuscript was supported by NIH grants P01-MH49548, P01- HL04726, T32-HL36588, R01-MH66697, and R01-AT02035. We thank Elizabeth Balbin, Adam Carrico, and Orit Weitzman for library research.

LITERATURE CITED

• Adams DB, Bacelli G, Mancia G, Zanchetti A. Cardiovascular changes during naturally elicited fighting behavior in the cat. Am. J. Physiol. 1968; 216 :1226–1235. [ PubMed ] [ Google Scholar ]
• Adams MR, Kaplan JR, Koritnik DR. Psychosocial influences on ovarian, endocrine and ovulatory function in Macaca fascicularis . Physiol. Behav. 1985; 35 :935–940. [ PubMed ] [ Google Scholar ]
• Affleck G, Urrows S, Tennen H, Higgins P, Pav D, Aloisi R. A dual pathway model of daily stressor effects on rheumatoid arthritis. Ann. Behav. Med. 1997; 19 :161–170. [ PubMed ] [ Google Scholar ]
• American Psychiatric Association. Diagnostic and Statistical Manual of Mental Disorders IV-TR. 4th ed. Washington, DC: Am. Psychiatr. Assoc.; 2000. [ Google Scholar ]
• Angst J, Vollrath M. The natural history of anxiety disorders. Acta Psychiatr. Scand. 1991; 84 :446–452. [ PubMed ] [ Google Scholar ]
• Antoni MH, Baggett L, Ironson G, LaPerriere A, Klimas N, et al. Cognitive behavioral stress management intervention buffers distress responses and elevates immunologic markers following notification of HIV-1 seropositivity. J. Consult. Clin. Psychol. 1991; 59 :906–915. [ PubMed ] [ Google Scholar ]
• Antoni MH, Cruess DG, Cruess S, Lutgendorf S, Kumar M, et al. Cognitive behavioral stress management intervention effects on anxiety, 24-hour urinary catecholamine output, and T-cytotoxic/suppressor cells over time among symptomatic HIV-infected gay men. J. Consult. Clin. Psychol. 2000a; 68 :31–45. [ PubMed ] [ Google Scholar ]
• Antoni MH, Cruess S, Cruess DG, Kumar M, Lutgendorf S, et al. Cognitive-behavioral stress management reduces distress and 24-hour urinary free cortisol output among symptomatic HIV-infected gay men. Ann. Behav. Med. 2000b; 22 :29–37. [ PubMed ] [ Google Scholar ]
• Appels A, Bar FW, Bar J, Bruggeman C, de Bates M. Inflammation, depressive symptomatology, and coronary artery disease. Psychosom. Med. 2000; 62 :601–605. [ PubMed ] [ Google Scholar ]
• Ballenger JC, Davidson JRT, Lecrubier Y, Nutt DJ, Borkovec TD, et al. Consensus statement on generalized anxiety disorder from the international consensus group on depression and anxiety. J. Clin. Psychiatry. 2001; 62 :53–58. [ PubMed ] [ Google Scholar ]
• Başoğlu M, Parker M, Parker Ö, Özmen E, Marks I, et al. Psychological effects of torture: a comparison of tortured with non-tortured political activists in Turkey. Am. J. Psychiatry. 1994; 151 :76–81. [ PubMed ] [ Google Scholar ]
• Baum A. Stress, intrusive imagery, and chronic distress. Health Psychol. 1990; 9 :653–675. [ PubMed ] [ Google Scholar ]
• Beck AT. Cognitive Therapy and the Emotional Disorders. New York: Int. Univ. Press; 1976. [ Google Scholar ]
• Berlant JL. Topiramate in posttraumatic stress disorder: preliminary clinical observations. J. Clin. Psychiatry. 2001; 62 :60–63. [ PubMed ] [ Google Scholar ]
• Bernard C. An Introduction to the Study of Experimental Medicine. Transl. HC Greene. New York: Collier; 18651961. [ Google Scholar ]
• Bleich A, Gelkopf M, Solomon Z. Exposure to terrorism, stress-related mental health symptoms, and coping behaviors among a nationally representative sample in Israel. JAMA. 2003; 290 :612–620. [ PubMed ] [ Google Scholar ]
• Borkovec TD, Ruscio AM. Psychotherapy for generalized anxiety disorder. J. Clin. Psychiatry. 2001; 61 :37–42. [ PubMed ] [ Google Scholar ]
• Breslau N, Davis GC, Andreski P, Peterson E. Sex differences in depression: a role for preexisting anxiety. Psychiatr. Res. 1995; 58 :1–12. [ PubMed ] [ Google Scholar ]
• Brindley D, Rollan Y. Possible connections between stress, diabetes, obesity, hypertension, and altered lipoprotein metabolism that may result in atherosclerosis. Clin. Sci. 1989; 77 :453–461. [ PubMed ] [ Google Scholar ]
• Brown GW, Bifulco A, Harris T, Bridge L. Life stress, chronic subclinical symptoms and vulnerability to clinical depression. J. Affect. Disord. 1986; 11 :1–19. [ PubMed ] [ Google Scholar ]
• Brownley KA, Hurwitz BE, Schneiderman N. Cardiovascular psychophysiology. In: Cacioppo JT, Tassinary LG, Berntson GG, editors. Handbook of Psychophysiology. 2nd ed. New York: Cambridge Univ.; 2000. pp. 224–264. [ Google Scholar ]
• Cannon WB. Bodily Changes in Pain, Hunger, Fear and Rage. 2nd ed. New York: Appleton; 1929. [ Google Scholar ]
• Carney RM, Rich MW, Tevelde A, Saini J, Clark K, Jaffe AS. Major depressive disorder in coronary artery disease. Am. J. Cardiol. 1987; 60 :1273–1275. [ PubMed ] [ Google Scholar ]
• Cassem EH. Depressive disorders in the medically ill: an overview. Psychosomatics. 1995; 36 :S2–S10. [ PubMed ] [ Google Scholar ]
• Cicchetti D. Child maltreatment. Annu. Rev. Clin. Psychol. 2005; 1 :409–438. [ PubMed ] [ Google Scholar ]
• Classen C, Sephton SE, Diamond S, Spiegel D. Studies of life-extending psychosocial interventions. In: Holland J, editor. Textbook of Psycho-Oncology. New York: Oxford Univ. Press; 1998. pp. 730–742. [ Google Scholar ]
• Clinical Practice Guidelines. No. 5. Depression in Primary Care. Vol. 2: Treatment of Major Depression. Rockville, MD: US Dept. Health Hum. Serv., Agency Health Care Policy Res.; 1993. AHCPR Publ. 93-0551.
• Cohen S, Frank E, Doyle WJ, Skoner DP, Rabin BS, Gwaltney JM., Jr Types of stressors that increase susceptibility to the common cold in healthy adults. Health Psychol. 1998; 17 :214–223. [ PubMed ] [ Google Scholar ]
• Cohen S, Tyrrell DA, Smith AP. Psychological stress and susceptibility to the common cold. N. Engl. J. Med. 1991; 325 :606–612. [ PubMed ] [ Google Scholar ]
• Colby JP, Linsky AS, Straus MA. Social stress and state-to-state differences in smoking-related mortality in the United States. Soc. Sci. Med. 1994; 38 :373–381. [ PubMed ] [ Google Scholar ]
• Conway TL, Vickers RR, Ward HW, Rahe RH. Occupational stress and variation in cigarette, coffee and alcohol consumption. J. Health Soc. Behav. 1981; 22 :156–165. [ PubMed ] [ Google Scholar ]
• Danner M, Kasl SV, Abramson JL, Vaccarion V. Association between depression and elevated C-reactive protein. Psychosom. Med. 2003; 65 :347–356. [ PubMed ] [ Google Scholar ]
• Dantzer R. Cytokine-induced sickness behavior: Where do we stand? Brain Behav. Immun. 2001; 15 :7–24. [ PubMed ] [ Google Scholar ]
• David D, Mellman TA, Mendoza LM, Kulick-Bell R, Ironson G, Schneiderman N. Psychiatric morbidity following Hurricane Andrew. Int. Soc. Trauma. Stress Stud. 1996; 9 :607–612. [ PubMed ] [ Google Scholar ]
• Dhabar FS, McEwen BS. Acute stress enhances while chronic stress suppresses cell-mediated immunity in vivo: a potential role for leukocyte trafficking. Brain Behav. Immun. 1997; 11 :286–306. [ PubMed ] [ Google Scholar ]
• Dusseldorp E, van Elderen T, Maes S, Meulman J, Kraaij V. A meta-analysis of psychoeducational programs for coronary heart disease patients. Health Psychol. 1999; 18 :506–519. [ PubMed ] [ Google Scholar ]
• Eaker ED. Psychosocial risk factors for coronary heart disease in women. Cardiovasc. Clin. 1998; 16 :103–111. [ PubMed ] [ Google Scholar ]
• Esterling BA, Antoni MH, Schneiderman N, Carver CS, LaPerriere A, et al. Psychosocial modulation of antibody to Epstein-Barr viral capsid antigen and herpes virus type-6 HIV-1 infected and at-risk gay men. Psychosom. Med. 1992; 54 :354–371. [ PubMed ] [ Google Scholar ]
• Faravelli C, Pallanti S. Recent life events and panic disorder. Am. J. Psychiatry. 1989; 146 :622–626. [ PubMed ] [ Google Scholar ]
• Fassbender K, Schmidt R, Mossner R, Kischka U, Kuhnen J, et al. Mood disorders and dysfunction of the hypothalamic-pituitary-adrenal axis in multiple sclerosis: associations with cerebral inflammation. Arch. Neurol. 1998; 55 :66–72. [ PubMed ] [ Google Scholar ]
• Fawzy FI, Fawzy NW, Hyun CS, Elashoff R, Guthrie D, et al. Malignant melanoma. Effects of an early structured psychiatric intervention, coping and affective state on recurrence and survival 6 years later. Arch. Gen. Psychol. 1993; 50 :681–689. [ PubMed ] [ Google Scholar ]
• Ferguson RG, Wikby A, Maxson P, Olsson J, Johansson B. Immune parameters in a longitudinal study of a very old population of Swedish people: a comparison between survivors and nonsurvivors. J. Gerontol. 1995; 50 :B378–B382. [ PubMed ] [ Google Scholar ]
• Finlay-Jones R, Brown GW. Types of stressful life events and the onset of anxiety and depressive disorders. Psychol. Med. 1981; 11 :803–815. [ PubMed ] [ Google Scholar ]
• Foa EB, Meadows EA. Psychosocial treatments for posttraumatic stress disorder: critical review. Annu. Rev. Psychol. 1997; 48 :449–480. [ PubMed ] [ Google Scholar ]
• Frasure-Smith N, Lespérance F, Gravel G, Masson A, Juneau M, et al. Social support, depression, and mortality during the first year after myocardial infarction. Circulation. 2000; 101 :1919–1924. [ PubMed ] [ Google Scholar ]
• Freedy JR, Shaw DL, Jarrell MP, Masters CR. Towards an understanding of the psychological impact of natural disasters: an application of the conservation of resources stress model. J. Trauma. Stress. 1992; 5 :441–454. [ Google Scholar ]
• Friedman M, Thoresen CE, Gill JJ, Ulmer D, Powell LH, et al. Alteration of type A behavior and its effects on cardiac recurrences in post myocardial patients: summary results of the Recurrent Coronary Prevention Project. Am. Heart J. 1986; 112 :653–665. [ PubMed ] [ Google Scholar ]
• Garmezy N. Resiliency and vulnerability to adverse developmental outcomes associated with poverty. Am. Behav. Sci. 1991; 34 :416–430. [ Google Scholar ]
• Glanz MD, Johnson JL. Resilience and Development: Positive Life Adaptations. New York: Kluwer Acad./Plenum; 1999. [ Google Scholar ]
• Glaser R, MacCallum RC, Laskowski BF, Malarkey WB, Sheridan JF, Kiecolt-Glaser JK. Evidence for a shift in the Th-1 to Th-2 cytokine response associated with chronic stress and aging. J. Gerontol. 2001; 56 :M477–M482. [ PubMed ] [ Google Scholar ]
• Graham JDP. High blood pressure after battle. Lancet. 1945; 248 :239–240. [ Google Scholar ]
• Graham NMH, Douglas RB, Ryan P. Stress and acute respiratory infection. Am. J. Epidemiol. 1986; 124 :389–401. [ PubMed ] [ Google Scholar ]
• Green BL. Psychosocial research in traumatic stress: an update. J. Trauma. Stress. 1994; 7 :341–362. [ PubMed ] [ Google Scholar ]
• Green BL. Traumatic stress and disaster: mental health effects and factors influencing adaptation. In: Mak FL, Nadelson C, editors. International Review of Psychiatry. Washington, DC: Am. Psychiatr. Press; 1996. pp. 177–211. [ Google Scholar ]
• Hammen C. Stress and depression. Annu. Rev. Clin. Psychol. 2005; 1 :293–319. [ PubMed ] [ Google Scholar ]
• Harbuz MS, Chover-Gonzalez AJ, Jessop DS. Hypothalamo-pituitary-adrenal axis and chronic immune activation. Ann. NY Acad. Sci. 2003; 992 :99–106. [ PubMed ] [ Google Scholar ]
• Harvey AG, Bryant RA. Acute stress disorder: a synthesis and critique. Psychol. Bull. 2002; 128 :886–902. [ PubMed ] [ Google Scholar ]
• Harvey AG, Jones C, Schmidt DA. Sleep and posttraumatic stress disorder: a review. Clin. Psychol. Rev. 2003; 23 :377–407. [ PubMed ] [ Google Scholar ]
• Haviland MG, Sonne JL, Woods LR. Beyond posttraumatic stress disorder: object relations and reality testing disturbances in physically and sexually abused adolescents. J. Am. Acad. Child Adolesc. Psychiatry. 1995; 34 :1054–1059. [ PubMed ] [ Google Scholar ]
• Henry JP, Stephens PM, Santisteban GA. A model of psychosocial hypertension showing reversibility and progression of cardiovascular complications. Circ. Res. 1975; 36 :156–164. [ PubMed ] [ Google Scholar ]
• Hess WR. Functional Organization of the Diencephalons. New York: Grune & Stratton; 1957. [ Google Scholar ]
• Hilton SM. Ways of viewing the central nervous control of the circulation—old and new. Brain Res. 1975; 87 :213–228. [ PubMed ] [ Google Scholar ]
• Ickovics JR, Hamburger ME, Vlahov D, Schoenbaum EE, Schumm P, Boland RJ. Mortality, CD4 cell count decline, and depressive symptoms among HIV-seropositive women. JAMA. 2001; 285 :1466–1474. [ PubMed ] [ Google Scholar ]
• Ironson GH. Job stress and health. In: Cranny CJ, Smith PC, Stone EF, editors. Job Satisfaction: How People Feel About Their Jobs and How It Affects Their Performance. New York: Lexington; 1992. pp. 219–239. [ Google Scholar ]
• Ironson GH, Freund B, Strauss JL, Williams J. Comparison of two treatments for traumatic stress: a community-based study of EMDR and prolonged exposure. J. Clin. Psychol. 2002; 58 :113–128. [ PubMed ] [ Google Scholar ]
• Ironson GH, Wynings C, Schneiderman N, Baum A, Rodriguez M, et al. Posttraumatic stress symptoms, intrusive thoughts, loss, and immune function after Hurricane Andrew. Psychosom. Med. 1997; 59 :128–141. [ PubMed ] [ Google Scholar ]
• Judd LL, Kessler RC, Paulus MP, Zeller PV, Whittchen HU, Kunovac JL. Comorbidity as a fundamental feature of generalized anxiety disorders: results from the National Comorbidity Survey (NCS) Acta Psychiatr. Scand. Suppl. 1998; 393 :6–11. [ PubMed ] [ Google Scholar ]
• Kaplan JR, Adams MR, Clarkson TB, Koritnik DR. Psychosocial influences on female “protection” among cynomolgues macaques. Atherosclerosis. 1984; 53 :283–295. [ PubMed ] [ Google Scholar ]
• Kaplan JR, Manuck SB, Adams MR, Weingard KW, Clarkson TB. Inhibition of coronary atherosclerosis by propranolol in behaviorally predisposed monkeys fed an atherogenic diet. Circulation. 1987; 76 :1364–1372. [ PubMed ] [ Google Scholar ]
• Kaplan JR, Manuck SB, Clarkson TB, Lusso FM, Taub DM. Social status, environment and atherosclerosis in cynomolgus monkeys. Arteriosclerosis. 1982; 2 :359–368. [ PubMed ] [ Google Scholar ]
• Karasek RA, Theorell TG. Healthy Work. New York: Basic Books; 1990. [ Google Scholar ]
• Kasprowicz AL, Manuck SB, Malkoff SB, Krantz DS. Individual differences in behaviorally evoked cardiovascular response: temporal stability and hemodynamic patterning. Psychophysiology. 1990; 27 :605–619. [ PubMed ] [ Google Scholar ]
• Kendler KS, Gardner CO, Prescott CA. Personality and the experience of environmental adversity. Psychol. Med. 2003; 33 :1193–1202. [ PubMed ] [ Google Scholar ]
• Kendler KS, Hettema JM, Butera F, Gardner CO, Prescott CA. Life event dimensions of loss, humiliation, entrapment and danger in the prediction of onsets of major depression and generalized anxiety. Arch. Gen. Psychiatry. 2003; 60 :789–796. [ PubMed ] [ Google Scholar ]
• Kendler KS, Karkowski LM, Prescott CA. Causal relationship between stressful life events and the onset of major depression. Am. J. Psychiatry. 1999; 156 :837–841. [ PubMed ] [ Google Scholar ]
• Kessing LV, Agerbro E, Mortensen PB. Does the impact of major stressful life events on the risk of developing depression change throughout life? Psychol. Med. 2003; 33 :1177–1184. [ PubMed ] [ Google Scholar ]
• Kessler RC, Sonnega A, Bromet E, Hughes M, Nelson CB. Posttraumatic stress disorder in the National Comorbidity Survey. Arch. Gen. Psychiatry. 1995; 52 :1048–1060. [ PubMed ] [ Google Scholar ]
• Kiecolt-Glaser JK, McGuire L, Robles TF, Glaser R. Psychoneuroimmunology: psychological influences on immune function and health. J. Consult. Clin. Psychol. 2002; 70 :537–547. [ PubMed ] [ Google Scholar ]
• Kilpatrick DG, Edmunds CN, Seymour AK. Rape in America: A Report to the Nation. Arlington, VA: Natl. Victims Cent.; 1992. [ Google Scholar ]
• Klerman GL, Weissman MM, Rounsaville BJ, Chevron ES. Interpersonal Psycho-Therapy of Depression. New York: Basic Books; 1984. [ Google Scholar ]
• Lacey JI. Somatic response patterning and stress: some revisions of activation theory. In: Appleyo MH, Trumble R, editors. Psychological Stress. New York: Appleton-Century-Crofts; 1967. p. 14. [ Google Scholar ]
• Lacey JL, Lacey BC. Verification and extension of the principle of autonomic response stereotyping. Am. J. Psychol. 1958; 71 :50–73. [ PubMed ] [ Google Scholar ]
• Ladd CO, Huot RL, Thrivikraman P, Nemeroff CB, Meaney MJ, Plotsky PM. Long-term behavioral and neuroendocrine adaptations to adverse early experience. Prog. Brain Res. 2000; 122 :79–101. [ PubMed ] [ Google Scholar ]
• Lantz PM, House JS, Lepkowski JM, Williams DR, Mero RP, Chen J. Socioeconomic factors, health behaviors, and mortality: results from nationally representative prospective study of US adults. JAMA. 1998; 279 :1703–1708. [ PubMed ] [ Google Scholar ]
• Larson SJ, Dunn AJ. Behavioral effects of cytokines. Brain Behav. Immun. 2001; 15 :371–387. [ PubMed ] [ Google Scholar ]
• Lazarus RS, Folkman S. Stress, Appraisal and Coping. New York: Springer; 1984. [ Google Scholar ]
• Leserman J, Pettito JM, Golden RN, Gaynes BN, Gu H, Perkins DO. The impact of stressful life events, depression, social support, coping and cortisol on progression to AIDS. Am. J. Psychiatry. 2000; 57 :1221–1228. [ PubMed ] [ Google Scholar ]
• Levine S. Infantile experience and resistance to physiological stress. Science. 1957; 126 :405–406. [ PubMed ] [ Google Scholar ]
• Linden W, Stossel C, Maurice J. Psychosocial interventions for patients with coronary artery disease. Arch. Intern. Med. 1996; 156 :745–752. [ PubMed ] [ Google Scholar ]
• Linsky AS, Strauss M. Social Stress in the United States: Links to Regional Patterns in Crime and Illness. Dover, MA: Auburn House; 1986. [ Google Scholar ]
• Linsky AS, Strauss MA, Colby JP. Stressful events, stressful conditions, and alcohol problems in the United States: a partial test of the Bales theory of alcoholism. J. Stud. Alcohol. 1985; 46 :72–80. [ PubMed ] [ Google Scholar ]
• Llabre MM, Klein BR, Saab PG, McCalla JB, Schneiderman N. Classification of individual differences in cardiovascular responsivity. The contribution of reactor type controlling for race and gender. Int. J. Behav. Med. 1998; 5 :213–229. [ PubMed ] [ Google Scholar ]
• Lowenthal B. The effects of early childhood abuse and the development of resiliency. Early Child Dev. Care. 1998; 142 :43–52. [ Google Scholar ]
• Lutgendorf S, Antoni MH, Ironson G, Fletcher MA, Penedo F, Van Riel F. Physical symptoms of chronic fatigue syndrome are exacerbated by the stress of Hurricane Andrew. Psychiatr. Med. 1995; 57 :310–325. [ PubMed ] [ Google Scholar ]
• Lutgendorf S, Antoni MH, Ironson G, Klimas N, Fletcher MA, Schneiderman N. Cognitive processing style, mood, and immune function following HIV seropositivity notification. Cogn. Ther. Res. 1997; 21 :157–184. [ Google Scholar ]
• Lutgendorf S, Antoni MH, Ironson G, Starr K, Costello N, et al. Changes in cognitive coping skills and social support mediate distress outcomes in symptomatic HIV-seropositive gay men during a cognitive behavioral stress management intervention. Psychosom. Med. 1998; 60 :204–214. [ PubMed ] [ Google Scholar ]
• Macksound M, Aber J. The war experience and psychosocial development of children in Lebanon. Child Dev. 1996; 67 :70–88. [ PubMed ] [ Google Scholar ]
• Madakasira S, O’Brien KF. Acute post-traumatic stress disorder in victims of a natural disaster. J. Nerv. Ment. Dis. 1987; 175 :286–290. [ PubMed ] [ Google Scholar ]
• Manuck SB, Kamarack TW, Kasprowica AS, Waldstein SR. Stability and patterning of behaviorally evoked cardiovascular reactivity. In: Blascovich J, Katkin ES, editors. Cardiovascular Reactivity to Psychological Stress and Disease. Washington, DC: Am. Psychol. Assoc.; 1993. pp. 111–134. [ Google Scholar ]
• Manuck SB, Kaplan JR, Clarkson TB. Behaviorally induced heart rate reactivity and atherosclerosis in cynomolgus monkeys. Psychosom. Med. 1983; 45 :95–108. [ PubMed ] [ Google Scholar ]
• Marmot M. Social resources and health. In: Kessel F, Rosenfield PL, Anderson NB, editors. Expanding the Boundaries of Health and Social Science. New York: Oxford Univ. Press; 2003. pp. 259–285. [ Google Scholar ]
• Marmot MG, Bosma H, Hemingway H, Brunner EJ, Stansfeld S. Contribution of job control and other risk factors to social variations in coronary heart disease incidence. Lancet. 1997; 350 :235–239. [ PubMed ] [ Google Scholar ]
• McCabe PM, Gonzalez JA, Zaias J, Szeto A, Kumar M, et al. Social environment influences the progression of atherosclerosis in the Watanabe heritable hyperlipidemic rabbit. Circulation. 2002; 105 :354–359. [ PubMed ] [ Google Scholar ]
• McDaniel JS, Musselman DL, Porter MR, Reed DA, Nemeroff CB. Depression in patients with cancer. diagnosis biology and treatment. Arch. Gen. Psychiatry. 1995; 2 :89–99. [ PubMed ] [ Google Scholar ]
• McEwen BS. Protective and damaging effects of stress mediators. N. Engl. J. Med. 1998; 338 :171–179. [ PubMed ] [ Google Scholar ]
• McEwen BS, Steller E. Stress and the individual: mechanisms leading to disease. Arch. Intern. Med. 1993; 153 :2093–2101. [ PubMed ] [ Google Scholar ]
• McMahon SD, Grant KE, Compas BE, Thurm AE, Ey S. Stress and psychopathology in children and adolescents: Is there evidence of specificity? J. Child Psychol. Psychiatry. 2003; 44 :107–133. [ PubMed ] [ Google Scholar ]
• McNally RJ. Psychological mechanisms in acute response to trauma. Biol. Psychiatry. 2003; 53 :779–788. [ PubMed ] [ Google Scholar ]
• Meaney MJ, Bhatnagan S, Dioria J, Larogue S, Francis D, et al. Molecular basis for the development of individual differences in the hypothalamic-pituitary-adrenal stress response. Cell. Mol. Neurobiol. 1993; 13 :321–347. [ PubMed ] [ Google Scholar ]
• Mendes de Leon CF, Powell LH, Kaplan BH. Change in coronary-prone behaviors in the recurrent coronary prevention project. Psychosom. Med. 1991; 53 :407–419. [ PubMed ] [ Google Scholar ]
• Meyer RJ, Haggerty RJ. Streptococcal infection in families. Pediatrics. 1962; 29 :539–549. [ PubMed ] [ Google Scholar ]
• Miller GE, Cohen S, Ritchey AK. Chronic psychological stress and regulation of pro-inflammatory cytokines: a glucocorticoid-resistance model. Health Psychol. 2002; 21 :531–541. [ PubMed ] [ Google Scholar ]
• Mohr DC, Classen C, Barrera M. The relationship between social support, depression and treatment for depression in people with multiple sclerosis. Psychol. Med. 2004; 34 :533–541. [ PubMed ] [ Google Scholar ]
• Mohr DC, Hart SL, Julian L, Cox D, Pelletier D. Association between stressful life events and exacerbation in multiple sclerosis: a meta-analysis. Br. Med. J. 2004; 328 :731. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Morley S, Eccleston C, Williams A. Systematic review and meta-analysis of randomized controlled trials of cognitive behavior therapy and behavior therapy for chronic pain in adults, excluding headache. Pain. 1999; 80 :1–13. [ PubMed ] [ Google Scholar ]
• Morrow DA, Ridker PM. C-reactive protein, inflammation, and coronary disease. Med. Clin. North Am. 2000; 81 :149–161. [ PubMed ] [ Google Scholar ]
• Nader KO, Pynoos RS, Fairbanks LA, al Ajeel M, al-Asfour A. A preliminary study of PTSD and grief among the children of Kuwait following the Gulf crisis. Br. J. Clin. Psychol. 1993; 32 :407–416. [ PubMed ] [ Google Scholar ]
• Norris FH. Epidemiology of trauma: frequency and impact of different potentially traumatic events on different demographic groups. J. Consult. Clin. Psychol. 1992; 60 :409–418. [ PubMed ] [ Google Scholar ]
• O’Donnell ML, Creamer M, Bryant RA, Schnyder U, Shalev A. Posttraumatic disorders following injury: an empirical and methodological review. Clin. Psychol. Rev. 2003; 23 :587–603. [ PubMed ] [ Google Scholar ]
• Orth-Gomér K, Wamala SP, Horsten M, Schenk-Gustafsson K, Schneiderman N, Mittleman MA. Marital stress worsens prognosis in women with coronary heart disease. JAMA. 2000; 284 :3008–3014. [ PubMed ] [ Google Scholar ]
• Patton GC, Coffey C, Posterino M, Carlin JB, Bowes G. Life events and early onset depression: cause or consequence? Psychol. Med. 2003; 33 :1203–1210. [ PubMed ] [ Google Scholar ]
• Paykel ES. Stress and affective disorders in humans. Semin. Clin. Neuropsychiatry. 2001; 6 :4–11. [ PubMed ] [ Google Scholar ]
• Pennebaker JW. Writing about emotional experiences as a therapeutic process. Psychol. Sci. 1997; 8 :162–164. [ Google Scholar ]
• Peterson C, Seligman MEP. Causal explanations as a risk factor for depression: theory and evidence. Psychol. Rev. 1984; 91 :347–374. [ PubMed ] [ Google Scholar ]
• Pfefferbaum B, Sconzo GM, Flynn BW, Kearns LJ, Doughty DE, et al. Case finding and mental health services for children in the aftermath of the Oklahoma City bombing. J. Behav. Health Serv. Res. 2003; 30 :215–227. [ PubMed ] [ Google Scholar ]
• Polusny MA, Follette VM. Long-term correlates of childhood sexual abuse: theory and review of the empirical literature. Appl. Prev. Psychol. 1995; 4 :143–166. [ Google Scholar ]
• Pruessner JC, Hellhammer DH, Kirschbaum C. Low self-esteem, induced failure and the adrenocortical stress response. Personal. Individ. Differ. 1999; 27 :477–489. [ Google Scholar ]
• Roitt I, Brostoff J, Male D. Immunology. 5th ed. London: Mosby Int.; 1998. p. 125. [ Google Scholar ]
• Ron M, Logsdail S. Psychiatric morbidity in multiple sclerosis: a clinical and MRI study. Psychol. Med. 1989; 19 :887–895. [ PubMed ] [ Google Scholar ]
• Ross R. Atherosclerosis—an inflammatory disease. N. Engl. J. Med. 1999; 340 :115–126. [ PubMed ] [ Google Scholar ]
• Saab PG, Llabre MM, Hurwitz BE, Frame CA, Reineke LJ, et al. Myocardial and peripheral vascular responses to behavioral changes and their stability in black and white Americans. Psychophysiology. 1992; 29 :384–397. [ PubMed ] [ Google Scholar ]
• Saab PG, Llabre MM, Hurwitz BE, Schneiderman N, Wohlgemuth W, et al. The cold pressor test: vascular and myocardial response patterns and their stability. Psychophysiology. 1993; 30 :366–373. [ PubMed ] [ Google Scholar ]
• Schnall PL, Landsbergis PA, Baker D. Job strain and cardiovascular disease. Annu. Rev. Public Health. 1994; 15 :381–411. [ PubMed ] [ Google Scholar ]
• Schneiderman N. Pathophysiology in animals. In: Dembroski TM, Schmidt TH, Blümhen G, editors. Biobehavioral Bases of Coronary Heart Disease. Basel: Karger; 1983. pp. 304–364. [ Google Scholar ]
• Schneiderman N, Antoni MH. Learning to cope with HIV/AIDS. In: Kessel F, Rosenfield PL, Anderson NB, editors. Expanding the Boundaries of Health and Social Science. New York: Oxford Univ. Press; 2003. pp. 316–347. [ Google Scholar ]
• Schneiderman N, Antoni MH, Saab PG, Ironson G. Health psychology: psychosocial and biobehavioral aspects of chronic disease management. Annu. Rev. Psychol. 2001; 52 :555–580. [ PubMed ] [ Google Scholar ]
• Schneiderman N, McCabe P. Psychophysiologic strategies in laboratory research. In: Schneiderman N, Weiss SM, Kaufmann PG, editors. Handbook of Research Methods in Cardiovascular Behavioral Medicine. New York: Plenum; 1989. pp. 349–364. [ Google Scholar ]
• Schneiderman N, Saab PG, Catellier DJ, Powell LH, DeBusk RF, et al. Psychosocial treatment within gender by ethnicity subgroups in the enhancing recovery in coronary heart disease (ENRICHD) clinic trial. Psychosom. Med. 2004; 66 :475–483. [ PubMed ] [ Google Scholar ]
• Schnurr PP, Friedman J, Bernardy NC. Research on posttraumatic stress disorder: epidemiology, pathophysiology and assessment. Psychother. Pract. 2002; 58 :877–889. [ PubMed ] [ Google Scholar ]
• Segerstrom SC, Miller GE. Psychological stress and the human immune system: a meta-analysis of 30 years of inquiry. Psychol. Bull. 2004; 130 :601–630. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Selye H. The Stress of Life. New York: McGraw-Hill; 1956. [ Google Scholar ]
• Shalev AY. What is posttraumatic stress disorder? J. Clin. Psychiatry. 2001; 62 :4–10. [ PubMed ] [ Google Scholar ]
• Shapiro F. Eye Movement Desensitization and Reprocessing: Basic Principles, Protocols, and Procedures. New York: Guilford; 1995. [ Google Scholar ]
• Shaw JA. Children exposed to war/terrorism. Clin. Child Fam. Psychol. Rev. 2003; 6 :237–246. [ PubMed ] [ Google Scholar ]
• Short JL. The effects of parental divorce during childhood on college students. J. Divorce Remarriage. 2002; 38 :143–156. [ Google Scholar ]
• Stanton JM, Balzer WK, Smith PC, Parra LF, Ironson G. A general measure of work stress: the stress in general scale. Educ. Psychol. Meas. 2001; 61 :866–888. [ Google Scholar ]
• Thase ME. Treatment of severe depression. J. Clin. Psychiatry. 2000; 61 :17–25. [ PubMed ] [ Google Scholar ]
• Thase ME, Greenhouse JB, Frank E. Treatment of major depression with psychotherapy or psychotherapy-pharmacotherapy combinations. Arch. Gen. Psychiatry. 1997; 54 :1009–1015. [ PubMed ] [ Google Scholar ]
• Voordouw BC, van der Linden PD, Simonia S, van der Lei J, Sturkenboom MC, Stricker BH. Influenza vaccination in community-dwelling elderly: impact on mortality and influenza-associated morbidity. Arch. Intern. Med. 2003; 163 :1089–1094. [ PubMed ] [ Google Scholar ]
• Welch SL, Doll HA, Fairburn CG. Life events and the onset of bulimia nervosa: a controlled study. Psychol. Med. 1997; 27 :515–522. [ PubMed ] [ Google Scholar ]
• Writing Committee for ENRICHD Investigators. Effects of treating depression and low perceived social support on clinical events after myocardial infarction: the Enhancing Recovery in Coronary Heart Disease patients (ENRICHD) randomized trial. JAMA. 2003; 289 :3106–3116. [ PubMed ] [ Google Scholar ]
• Zimmerman P, Wittchen HU, Hofler M, Pfister H, Kessler RC, Lieb R. Primary anxiety disorders and the development of subsequent alcohol use disorders: a 4-year community study of adolescents and young adults. Psychol. Med. 2003; 33 :1211–1222. [ PubMed ] [ Google Scholar ]

• Search Menu
• Advance Articles
• Thematic Issues
• Clinical Practice Guidelines
• Supplements
• Endocrine Reviews
• Endocrinology
• Journal of the Endocrine Society
• The Journal of Clinical Endocrinology & Metabolism
• JCEM Case Reports
• Molecular Endocrinology
• Endocrine Society Journals
• Author Guidelines
• Submission Site
• Open Access
• Why Publish with the Endocrine Society
• Advertising & Corporate Services
• Reprints, ePrints, Supplements
• About The Journal of Clinical Endocrinology & Metabolism
• Editorial Board
• Author Resources
• Reviewer Resources
• Rights & Permissions
• Other Society Publications
• Member Access
• Journals Career Network
• Terms and Conditions
• Journals on Oxford Academic
• Books on Oxford Academic

Article Contents

What is stress, what is the stress response, how does chronic stress affect your health, how do you know you’re stressed out, what should you do with this information, stress and your health.

• Article contents
• Figures & tables
• Supplementary Data

Bruce McEwen, Robert Sapolsky, Stress and Your Health, The Journal of Clinical Endocrinology & Metabolism , Volume 91, Issue 2, 1 February 2006, Page E2, https://doi.org/10.1210/jcem.91.2.9994

• Permissions Icon Permissions

Generally speaking, stress means pressure or strain. Life constantly subjects us to pressures. In people, stress can be physical (e.g., disease), emotional (e.g., grief), or psychological (e.g., fear).

Individuals vary in their ability to cope with stress. How you see a situation and your general physical health are the two major factors that determine how you will respond to a stressful event or to repeated stress.

Genes and things that happen to you early in life (e.g., child abuse or neglect), even in the womb, can affect how you handle stressful situations, possibly making you more likely to over-react. Overeating, smoking, drinking, and not exercising, which can often result from being under stress, can also add to the negative effects of stress.

Allostasis is the process of how the body responds to stress, whether it is acute (short-term) or chronic (long-term).

The best-known acute stress response is the “fight or flight” reaction that happens when you feel threatened. In this case, the stress response causes the body to release several stress hormones (e.g., cortisol and adrenaline) into the bloodstream. These hormones intensify your concentration, ability to react, and strength. Also, your heart rate and blood pressure increase, and your immune system and memory are shaper. After you have dealt with the short-term stress, your body returns to normal.

Chronic or long-term stress, however, poses a problem. If you repeatedly face challenges and your body is constantly producing higher levels of hormones, it doesn’t have time to recover. Stress hormones build up in the blood and, over time, can cause serious health problems.

Digestive system. Stomach ache is common due to a slow down in the emptying of the stomach; also diarrhea due to more activity in the colon.

Obesity. Increase in appetite, which can lead to weigh gain. (Being overweight or obese puts you at risk for diabetes and cardiovascular disease.)

Immune system. Weakening of the immune system so that you are more likely to have colds and other infections.

Nervous system. Anxiety, depression, loss of sleep and lack of interest in physical activity. Memory and decision-making can also be affected.

Cardiovascular system. Increase in blood pressure, heart rate, and blood fats (cholesterol and triglycerides). Also, increase in blood sugar (glucose) levels (especially in evening hours) and appetite (which contributes to weight gain). A(ll of these effects are risk factors for heart disease, atherosclerosis and stroke, as well as obesity and diabetes.)

Fatigue, depression

Chest pain or pressure, rapid heartbeat

Dizziness, shakiness, difficulty breathing

Menstrual cycle irregularities, erectile dysfunction (impotence), loss of libido (sex drive)

These symptoms may also lead to loss of appetite, overeating and poor sleep, all of which can have serious consequences for your health.

Usually these symptoms are minor and may be relieved through coping skills such as learning to relax, removing yourself for a time from the things that stress you out, and exercising. If the symptoms are severe, however, you may need to seek medical help to be able to identify the source of your stress and the best way to manage it.

There are practical steps you can take to cut back on stress. Regular, moderate exercise improves thought process and mood. So are relaxing, getting a good night’s sleep, and seeking emotional support from family and friends. You can also reduce the long-term effects of chronic stress by eating a healthy, low-fat diet and avoiding smoking and excessive drinking. However, if your symptoms continue or worsen, you should see your doctor.

Find-an-Endocrinologist (physician referral): www.hormone.org or call 1-800-HORMONE

Introduction to the Endocrine System, Hormones and Glands: www.hormone.org

Medline Plus (NIH): http://www.nlm.nih.gov/medlineplus/stress.html

U.S. Dept. of Health and Human Services: http://www.4woman.gov/faq/stress.htm

For more information on how to find an endocrinologist, download free publications, translate this fact sheet into other languages, or make a contribution to The Hormone Foundation, visit www.hormone.org/bilingual or call 1-800-HORMONE. The Hormone Foundation, the public education affiliate of The Endocrine Society ( www.endo-society.org ), serves as a resource for the public by promoting the prevention, treatment, and cure of hormone-related conditions. This page may be reproduced non-commercially by health care professionals and health educators to share with patients and students. Translation by MEDI-FLAG Corp.

Email alerts

Citing articles via.

• About The Journal of Clinical Endocrinology & Metabolism
• About the Endocrine Society
• Recommend to Your Librarian
• Advertising and Corporate Services

Affiliations

• Online ISSN 1945-7197
• Print ISSN 0021-972X
• Copyright © 2023 Oxford University Press
• About Oxford Academic
• Publish journals with us
• University press partners
• What we publish
• New features  
• Open access
• Institutional account management
• Rights and permissions
• Get help with access
• Accessibility
• Advertising
• Media enquiries
• Oxford University Press
• Oxford Languages
• University of Oxford

Oxford University Press is a department of the University of Oxford. It furthers the University's objective of excellence in research, scholarship, and education by publishing worldwide

• Copyright © 2023 Oxford University Press
• Cookie settings
• Cookie policy
• Privacy policy
• Legal notice

This Feature Is Available To Subscribers Only

Sign In or Create an Account

This PDF is available to Subscribers Only

For full access to this pdf, sign in to an existing account, or purchase an annual subscription.

Click through the PLOS taxonomy to find articles in your field.

For more information about PLOS Subject Areas, click here .

Loading metrics

Open Access

Study Protocol

Physiological stress in response to multitasking and work interruptions: Study protocol

Roles Conceptualization, Methodology, Project administration, Software, Supervision, Visualization, Writing – original draft, Writing – review & editing

* E-mail: [email protected]

Affiliation Department of Psychology, Chair of Health Psychology, Friedrich-Alexander University Erlangen-Nürnberg, Erlangen, Germany

Roles Conceptualization, Methodology, Writing – review & editing

Affiliation Institute and Clinic for Occupational, Social and Environmental Medicine, LMU University Hospital Munich, Munich, Germany

Roles Conceptualization, Funding acquisition, Methodology, Supervision, Writing – review & editing

Affiliations Institute and Clinic for Occupational, Social and Environmental Medicine, LMU University Hospital Munich, Munich, Germany, Institute for Patient Safety, University Hospital, Bonn, Germany

Roles Conceptualization, Funding acquisition, Methodology, Resources, Supervision, Writing – review & editing

• Linda Becker, 
• Helena C. Kaltenegger, 
• Dennis Nowak, 
• Matthias Weigl, 
• Nicolas Rohleder

• Published: February 8, 2022
• https://doi.org/10.1371/journal.pone.0263785
• Peer Review
• Reader Comments

The biopsychological response patterns to digital stress have been sparsely investigated so far. Important potential stressors in modern working environments due to increased digitalization are multitasking and work interruptions. In this study protocol, we present a protocol for a laboratory experiment, in which we will investigate the biopsychological stress response patterns to multitasking and work interruptions.

In total, N = 192 healthy, adult participants will be assigned to six experimental conditions in a randomized order (one single-task, three dual-task (two in parallel and one as interruption), one multitasking, and one passive control condition). Salivary alpha-amylase as well as heart rate as markers for Sympathetic Nervous System Activity, heart rate variability as measure for Parasympathetic Nervous System (PNS) activity, and cortisol as measure for activity of the hypothalamic-pituitary adrenal (HPA) axis will be assessed at six time points throughout the experimental session. Furthermore, inflammatory markers (i.e., IL-6, C-reactive protein (CRP), and secretory immunoglobulin-A) will be assessed before and after the task as well as 24 hours after it (IL-6 and CRP only). Main outcomes will be the time course of these physiological stress markers. Reactivity of these measures will be compared between the experimental conditions (dual-tasking, work interruptions, and multitasking) with the control conditions (single-tasking and passive control).

With this study protocol, we present a comprehensive experiment, which will enable an extensive investigation of physiological stress-responses to multitasking and work interruptions. Our planned study will contribute to a better understanding of physiological response patterns to modern (digital) stressors. Potential risks and limitations are discussed. The findings will have important implications, especially in the context of digital health in modern working and living environments.

Citation: Becker L, Kaltenegger HC, Nowak D, Weigl M, Rohleder N (2022) Physiological stress in response to multitasking and work interruptions: Study protocol. PLoS ONE 17(2): e0263785. https://doi.org/10.1371/journal.pone.0263785

Editor: Eva M. J. Peters, Justus-Liebig University, GERMANY

Received: September 3, 2021; Accepted: January 26, 2022; Published: February 8, 2022

Copyright: © 2022 Becker et al. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Funding: This study is part of the research project "Identifikation biomedizinischer und gesundheitlicher Wirkweisen von positiven und negativen Auswirkungen von digitalem Stress und dessen Bewältigung“ [Identification of biomedical and health effects of positive and negative effects of digital stress and coping with it] which is part of the Bavarian Research Association on Healthy Use of Digital Technologies and Media (ForDigitHealth), funded by the Bavarian Ministry of Science and Arts. Linda Becker has been partly funded by the Emerging Talents Initiative of the Friedrich-Alexander University Erlangen-Nürnberg. Matthias Weigl and Dennis Nowak have been partly funded by the Munich Centre for Health Sciences (MC-Health). We acknowledge support by Deutsche Forschungsgemeinschaft and Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU) within the funding program Open Access Publishing. The funders had and will not have a role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Competing interests: The authors have declared that no competing interests exist.

Introduction

Stress is one important factor influencing human health [e.g., 1 , 2 ]. Stress is part of everyday private and working life, is experienced by almost everyone, and is increasingly having an impact on health and life expectancy [ 3 , 4 ]. In modern, technology-driven working and living environments, new potential stressors related to digitalization (i.e., digital stressors) are more and more present. In the following, we will–similar to the concepts of techno strain and technostress [ 5 , 6 ]–refer to stress that is related to the usage of digital technology and media as digital stress. Important potential digital stressors are multitasking and work interruptions [e.g., due to flooding text messages or emails; 7 – 11 ]. Both can be perceived as stressful and overwhelming [ 12 – 14 ] and cannot be avoided in many situations. However, this does not necessarily indicate that the feeling of being stressed or overwhelmed when being faced with these demands is also associated with a physiological stress response [ 15 , 16 ]. Although the biopsychological effects of several acute [e.g., social evaluation; 17 ] and chronic psychosocial stressors [e.g., caregiving; 18 , 19 ] and psychological determinants of biological stress-response patterns in general are well understood, only few attempts have been made so far to use this knowledge to understand the effects of stressors such as multitasking and work interruptions on biological stress system-activity. The aim of our planned study is to close this research gap.

The interpretation of a situation as threatening activates stress centers in the brain, which use stress systems to prepare the entire organism for dealing with the situation [ 20 ]. The Sympathetic Nervous System (SNS) activates systems throughout the body through noradrenergic innervation, which leads to the release of epinephrine and norepinephrine from the adrenal medulla and, among other things, results in an increase in heart rate and blood pressure [ 20 , 21 ]. The up-regulation of the SNS is accompanied by a down-regulation of the Parasympathetic Nervous System [PNS; 1 , 21 ]. The slower response of the hypothalamic-pituitary adrenal (HPA) axis modulates the effects of the SNS and PNS by releasing the stress hormone cortisol from the adrenal cortex [ 21 , 22 ]. With a further delay [e.g., about 1.5–2 hours for interleukin-6 (IL-6); 23 , 24 ], complex effects of the immune system are activated with up-regulation of some components (most importantly inflammatory pathways) and down-regulation of others [most importantly cellular immunity; 2 , 25 ]. Temporarily, all these physiological stress responses are adaptive. Potentially harmful consequences arise when stress becomes chronic, i.e., when long-term stress exposure occurs [e.g., 19 , 26 – 28 ], or when so-called maladaptive stress-response patterns are used [e.g., 29 – 31 ]. We refer to stress-responses patterns as being maladaptive–in contrast to adaptive [e.g., 32 , 33 ]–when they do not allow the organism to efficiently cope with or to adjust the individual’s physiological responses or behavior to the situation.

With regard to stress effects on health, SNS, PNS, and HPA axis interact with patho-physiologically relevant systems, of which the inflammatory system is seen–beside e.g., glucocorticoids [ 34 ]–as one key factor [ 35 ]. Inflammatory processes are one of the central mechanisms in mediating the negative effects of stress on health [ 35 ]. Ultimately, acute stress exposure leads to systemic low-grade inflammation, which is–in the long-term–a key factor for the development of the most important diseases in industrialized nations such as cardiovascular diseases, type-2 diabetes, and cancer [ 35 , 36 ]. Moreover, these patho-physiological stress-related processes are associated with a large number of other diseases such as chronic dermatological conditions (e.g., skin aging [ 37 ], urticaria [ 38 , 39 ], or skin tumors; [ 40 ]), asthma bronchiale [ 41 , 42 ], or obesity [ 43 , 44 ], and many more.

Although physiological responses can be triggered by stressors in principle, the actual stress response is associated with the nature of the stressor [so-called specificity hypothesis; 45 , 46 ]. According to this hypothesis, specifically situations that are perceived as threatening in contrast to challenging trigger HPA axis responses. Moreover, situations which are shameful or in which the social self is devaluated are associated with strong HPA responses [so-called social self-preservation theory; 47 – 49 ]. For cognitive stressors, both SNS and HPA axis responses have been reported [ 50 , 51 ], depending on task difficulty and on the presence of further stressors [ 52 ]. In a recent systematic review and meta-analysis from our group, which is currently under review [ 53 ], we found that SNS activity is significantly higher and PNS activity is significantly lower during dual- or multitasking than during single tasking. We identified no associations with HPA axis activity. However, the number of studies in which HPA axis reactivity to dual- or multitasking was investigated was small. We found no eligible studies in which immune system (re-) activity was investigated.

To summarize, so far, laboratory experiments in which the potential stressors multitasking and work interruptions are systematically induced are rare. Moreover, they vary in their potential how the biological stress systems are modulated and investigated. Multitasking and work interruptions differ from commonly investigated stressors in their nature as they primarily include a cognitive component in contrast to a psychosocial one, especially when induced digitally (i.e., without the presence of further persons). Therefore, with regard to the specificity hypothesis, it remains an open question whether physiological stress responses to multitasking and work interruptions differ between digital and non-digital stressors. In our planned study, we will therefore, differentiate between pure digital multitasking as well as work interruptions and comparable tasks in which another person is involved.

While the biopsychological effects of acute [e.g., social evaluation; 54 ] and chronic [e.g., caregiving; 18 , 19 ] psychosocial stressors and psychological determinants of biological stress-response patterns in general are well understood [e.g., 55 , 56 ], only few attempts have been made so far to use this knowledge to understand the effects of two prominent stressors in modern, digitalized working environments (i.e., multitasking and work interruptions) on biological stress systems. With this protocol, we present a study plan for a comprehensive experiment, in which responses of the SNS, PNS, HPA axis, as well as of the immune system to multitasking and work interruptions will be investigated in a controlled laboratory setting.

Our primary research questions are:

• Do dual- and multitasking conditions lead to physiological stress responses in comparison to a single-task control condition or a passive control condition?
• Do work interruptions lead to physiological stress responses in comparison to a single-task control condition or a passive control condition?
• Do the stress response patterns differ between digital and non-digital stressors? Additionally, the following secondary research question will be investigated exploratorily:
• Do dual- and multitasking lead to perceived stress responses in comparison to a single-task control condition or a passive control condition?
• Is the physiological stress response to dual- or multitasking, or work interruptions associated with person characteristics (e.g., age, sex, body-mass-index (BMI), education) and psychological variables (e.g., personality, coping style, self-efficacy, depression, anxiety, preference for multitasking [so-called polychronicity; 57 ]).

Because the associations with these factors will be investigated exploratorily (i.e., without specific hypotheses), only a subset, which is known to be highly relevant in stress research (i.e., age, sex, BMI), will be considered as covariates in the statistical analyses. The actual hypotheses are specified in the Materials and Methods section below.

Materials and methods

Study design.

The study design is a cross-sectional laboratory experiment, in which participants will be randomly assigned to one of six conditions (four experimental conditions and two control conditions; Table 1 ; Fig 1 ).

• PPT PowerPoint slide
• PNG larger image
• TIFF original image

Each participant will be randomly assigned to one of the six experimental conditions. In condition 5 and 6, an experimenter will be present in the same room as the participant to introduce a non-digital, social-evaluative stress component.

https://doi.org/10.1371/journal.pone.0263785.g001

https://doi.org/10.1371/journal.pone.0263785.t001

Participants

In total, N = 192 (32 per condition) healthy, German-speaking adults between 18 and 40 years will be recruited. Exclusion criteria are diagnosed physical or psychological disorders (operationalized as diagnosed within the last 2 years), regular medication intake (exception oral contraceptives), pregnancy, a BMI ≥ 35 kg/m 2 , regular smoking (more than 5 cigarettes per week), or being an employee of the Friedrich-Alexander University Erlangen-Nürnberg (FAU). The latter is a requirement from the workers’ council of the FAU.

Ethics approval

The study will be conducted according to the principles expressed in the Declaration of Helsinki and has been approved by the local ethics committee of the FAU (protocol number: 397_19 B).

Power analysis

An a-priori power analysis has been conducted using G*Power (version 3.1.9.6). We expect to find small, but relevant effects and therefore used an effect size of f = 0.14 for power calculation ( f 2 = 0.02). We intend to achieve a power of 1 – β = 0.95 and used a Bonferroni-adjusted α-level of α adjusted = 0.05/3 = 0.017 (see data preparation and statistical analysis). With these parameters a total sample size of N = 174 (29 per condition) is needed for an analysis of variance for repeated measurements (rmANOVA) with six measurement time points and six conditions. Based on our experience with similar studies, we expect a small drop-out rate of about 10% due to insufficient saliva or blood volumes and will, therefore, recruit additional 18 participants (3 per condition). This results in a total sample size of N = 192.

Status and timeline of the study

Recruitment has started in August 2021 and data collection has started at the end of September 2021. The first version of this study protocol has been submitted before start of data collection. All recommendations from the reviewers’ first reviews were considered. Data collection will last until the recruitment goal is fulfilled. The actual duration will depend on the development of the Covid-19 pandemic but is intended to last about one year. Data analysis will start after all data will have been collected. Preliminary analyses are not planned.

Experimental conditions

An overview about all experimental conditions is provided in Table 1 . Condition 1 will be a passive control condition, in which participants will watch a non-stressful video. Condition 2 will be an active control condition, in which participants will conduct a digital single-task, which is the primary task in the other (dual- and multitasking as well as the interruption) experimental conditions. In conditions 3 to 5, participants will conduct the primary task either in combination with a parallel secondary task or will be interrupted by a secondary task. Participants who are assigned to condition 6 will be engaged in multitasking, which will include three tasks, the primary task as well as a digital and a non-digital parallel task. All conditions are visualized in Fig 1 and are summarized in Table 1 .

Digital primary task.

A computerized continuous-performance task [CPT; 58 , 59 ] will be the primary task for the single-task as well as the dual-task and multitasking conditions (conditions 2–6 in Fig 1 ). The CPT is a measure for sustained attention [ 60 ]. We will use an AX-CPT variant [e.g., 61 ], i.e. that the target is the letter ‘X’ occurring after an ‘A’. In our version ( Fig 2 ), the letters A, B, X, and Y will be presented, and a response button should be pressed after every second letter, i.e., after a pair of letters. The cue letter is ‘A’ and the target letter is ‘X’, i.e., that one response button should be pressed after each A-X pair. In all other cases (after A-Y, B-X, B-Y pairs), the other response button should be pressed ( Fig 2 ). In our AX-CPT version, the letter presentation time is 2,000 ms and the inter-stimulus interval is 3,500 ms. The probability of an A-X pair is 0.50 and 0.17 for the other pairs.

In our version of the AX-CPT, the target pair will be A-X. A-Y, B-X, as well as B-Y pairs will be non-targets. This task will be used as the digital single-task and will be the primary task in the dual- and multitasking conditions.

https://doi.org/10.1371/journal.pone.0263785.g002

Digital secondary task.

As a digital secondary task, questions and five answer possibilities, of which one is correct, will be presented to the participants. The answer possibilities will be assigned to five answer buttons, and the instruction is that the correct answer should be chosen as fast as possible. As questions, items from the Intelligenz-Struktur-Test 2000R [IST- 2000R; 62 , 63 ] will be used and will be presented in a randomized order. The following sub-tasks will be chosen: sentence addition ( Satzergänzung ), analogies ( Analogien ), and figure selection ( Figurenauswahl ). In condition 3 (digital interruptions), the primary task will be interrupted by questions from the IST 2000R, which will appear on the same monitor. The primary task will stop and will be overlayed by the secondary one during the presentation of the secondary task and will automatically continue after a response is given by the participant. In condition 4 (dual-task, parallel condition), participants will have to perform the IST 2000R on a separate computer screen parallel to the primary task. The participants will be instructed that both tasks are equally relevant, i.e., that none of the tasks should be prioritized, and that both tasks should be performed as accurately as possible.

Non-digital secondary task.

As non-digital secondary task, participants will have to conduct a verbal-fluency task [VFT; e.g., 50 , 64 ]. The instruction, which will be verbally given by the experimenter, is to name as many words as possible that belong to a given category or which begin with a given letter. The time per category/letter will be 2 minutes, and time between two rounds will be 1 minute. Each participant will conduct six rounds with the same categories/letters in a randomized order. This secondary task will be conducted in parallel to the primary task (i.e., the AX-CPT; condition 5 in Fig 1 ). The experimenter will be in the same room as the participant to introduce a social-evaluative component. As for the digital parallel task, participants will be instructed that both tasks are equally relevant, i.e., that none of the tasks should be prioritized, and that both tasks should be performed as accurately as possible.

In the multitasking condition (condition 6 in Fig 1 ), all three tasks (AX-CPT, the digital parallel task, as well as the VFT) should be performed in parallel and, again, none of the tasks should be prioritized.

Passive control condition.

The (digital) passive control condition will be to watch a non-stressful documentary video (condition 1 in Fig 1 ). The content of the video is landscapes and animals. These videos have been successfully used in previous studies and evaluated as being non-arousing [ 65 , 66 ].

Biological and physiological outcome measures

Main outcomes will be measures for physiological stress responses, which will be assessed via saliva and capillary blood samples as well as by means of electrocardiogram (ECG) recordings. An overview is provided in Table 2 . As measures for SNS re-activity, salivary alpha-amylase [ 67 ] as well as the participants’ heart rate will be used. PNS re-activity will be assessed from heart rate variability (HRV) measures [e.g., root mean square of successive differences of consecutive R-R intervals (RMSSD); 68 ]. Activity of the HPA axis will be assessed via salivary cortisol measurements, which will be collected by means of Salivettes (Sarstedt, Nümbrecht, Germany). IL-6 and CRP will be assessed from capillary blood samples, which will be measured in Dried Blood Spots [ 69 , 70 ], which is an established procedure in our group [e.g., 71 , 72 ]. s-IgA will be measured in unstimulated saliva samples, which will be collected by means of Salicaps (IBL international, Hamburg, Germany).

https://doi.org/10.1371/journal.pone.0263785.t002

Assessment of sample characteristics

Demographic, anthropometric, socio-economic, lifestyle, as well as health-related variables will collected via questionnaires (e.g., age, sex, ethnicity, education, occupation, mother tongue, smoking status, diseases, medication intake). Some of these characteristics (e.g., smoking status and mother tongue) will be only collected to double-check whether inclusion criteria are fulfilled. A full item list is provided as Supplementary Material in S1 File .

Stress perception, affect and anxiety during the experiment

During the experimental session, stress perception, anxiety, and affect as measures for the perceived (non-physiological) stress response will be assessed via the following instruments:

Positive and negative affect will be measured four times during the experiment by means of the Positive and Negative Affect Schedule [PANAS; 73 , 74 ]. Assessment time points will be before the task, immediately after it, 20 minutes after the task, as well as 90 minutes later.

State anxiety.

State anxiety and depression before and immediately after the task will be measured by using the state items from the State-Trait Anxiety-Depression Inventory [STADI-S; 75 ].

Stress perception.

Perceived stress will be assessed throughout the experiment at the time points of the saliva samples by means of 10-point Likert scales with the anchors “not stressed at all” and “extremely stressed”. This scale has been successfully used in previous studies from our group [e.g., 76 – 79 ]. Additionally, participants are asked about their perceived exertion as well as their level of tiredness, again on 10-point Likert scales. All three scales are provided as Supplementary Material in S2 File .

Psychological variables

Beside demographic, anthropometric, and health -related variables (see above), the acute stress response is related with a variety of psychological variables [e.g., 55 ]. Therefore, psychological variables as well as lifestyle factors, which might be related with the stress responses under study, will be assessed additionally. The following standardized questionnaires or in-house developed items will be used.

The Maslach Burnout Inventory [MBI; 80 ] will be used for assessment of burnout symptoms.

Coping will be assessed by means of the German 24-item version of the Coping Inventory for Stressful Situations [CISS; 81 , 82 ]. The scale assesses task-oriented, emotion-focused, as well as avoidance-oriented coping. The avoidance-oriented coping scale can be further divided into distraction coping and social-diversion coping subscales.

Depression.

Depression will be assessed by means of the German version of the long form of the depression scale from the Center for Epidemiological Studies [CES-D; 83 , 84 ].

Emotion regulation.

A German version of the Emotion Regulation Questionnaire [ERQ; 85 , 86 ] will be used to assess the emotion regulation dimensions reappraisal and suppression.

Habitual multimedia consumption.

For assessment of habitual television and internet usage, items from a questionnaire for the assessment of habitual media consumption by Koch [2010; 87 ] will be used. Each subscale consists of 8 items that should be answered on 7-point Likert-scales. A further scale, which assesses habitual mobile phone usage, has been developed analogously based on the items by Koch [2010, 87 ] for habitual television and internet usage.

Multimedia usage.

Self-developed items will be used to assess time of day at which media is used, separately for weekdays and weekends. A German version of the Media and Technology Usage and Attitudes Scale [MTUAS; 88 ] will be used to assess frequency of multimedia usage, social media activity, as well as attitudes towards media usage. The polychronicity (i.e., the preference for multitasking) items from the MTUAS will be left out. Polychronicity will be assessed by means of the Multitasking Preference Inventory [MPI; 57 ] instead.

Multitasking.

The amount and causes of multitasking behavior in everyday life will be assessed by means of 8 self-developed items, which will be answered on 5-point Likert Scales. The items are provided as Supplementary Material in S3 File .

Perceived stress.

Perceived stress during the last month will be assessed by means of a German translation of the 10-item version of the Perceived Stress Scale [PSS; 89 , 90 ].

Personality.

For personality assessment, the short version of the Big Five Inventory [BFI-K; 91 ] will be used. This questionnaire enables assessment of the big-five personality-dimensions extraversion, neuroticism, agreeableness, conscientiousness, and openness to experience by means of 21 items.

Resilience.

For assessment of resilience, the German 11-item resilience scale [RS-11; 92 ] will be used.

Self-efficacy.

Self-efficacy will be assessed by means of a German scale for general self-efficacy [SWE; 93 ]. The scale includes ten items, with which self-efficacy is rated on 4-point Likert scales.

Social anxiety.

Social anxiety will be assessed by means of the Social Interaction Anxiety Scale (SIAS) as well as the Social Phobia Scale [SPS; 94 ].

Social support.

The 14-item version of the Fragebogen zur sozialen Unterstützung [FSozU-K14; 95 ] will be used to assess social support.

Trait anxiety.

Trait anxiety and depression will assessed by means of the trait-items from the State-Trait Anxiety-Depression Inventory [STADI-T; 75 ]. Note that we will use the CES-D as main outcome measure for depression. However, we will leave in the depression items to not alter the psychometric properties of the STADI-T.

Experimental setting and procedure

After providing informed and written consent, participants will be equipped with the heart rate monitors and will be familiarized with the saliva collection procedure via Salivettes (i.e., the collection of the stimulated saliva samples), and a practice saliva sample (s 0 ) will be collected, which will not be used for later analyses. After this, all participants–irrespective of the actual group assignment–will conduct practice trials of the VFT and the CPT and will be informed that they will possibly have to repeat these tasks throughout the session. This will be followed by a resting period of about 20 minutes. At the end of the resting period, the first blood spot sample (DBS 1 ) and the next stimulated saliva sample (s 1 ) as well as the first unstimulated saliva sample (us 1 ) will be collected. After this, the main task will be introduced to the participants and will then start immediately and will last about 21 minutes. Introduction of the task and the actual task will take a total of about 25 minutes. Immediately after the end of the main task, participants will provide the second saliva sample (s 2 ; i.e., end of the main task +0 minutes). The subsequent stimulated saliva samples will be collected at the following time points: +10 (s 3 ), +20 (s 4 ), +45 (s 5 ), and +90 (s 6 ) minutes after the end of the main task. The second Dried Blood Spot (DBS 2 ) as well as the second unstimulated saliva sample (us 2 ) will also be collected at + 90 minutes post task. During the time window between the task and the last saliva and blood sample, participants will rest and will fill out questionnaires until the end of the session and will be allowed to take as many breaks as they prefer. The goal of this period is not to stress the participants while conducting a non-stressful task (i.e., filling-out the questionnaires). The timeline of the whole experiment is shown in Fig 3 . The entire session will last about 3 hours. Additionally, participants will provide another blood sample (DBS 3 ) 24 hours after the first one. This DBS collection will be conducted by the participants themselves at their homes and samples will be send back via mail.

The entire session will last about 3 hours. A further Dried Blood Spot Sample (DBS 3 ) will be collected 24 hours after DBS 1 (not shown). Note . CPT: continuous performance task; DBS i : Dried Blood Spot # i; HRV: heart rate variability; s i : stimulated saliva sample # i , which will be collected by means of Salivettes; us i : unstimulated saliva sample # i ; VFT: verbal-fluency task.

https://doi.org/10.1371/journal.pone.0263785.g003

Outcome measures

Primary outcomes..

Primary outcomes will be the physiological stress measures for SNS, PNS, HPA axis, and immune system reactivity (i.e., sAA, HR, RMSSD, cortisol, CRP, s-IgA, and IL-6).

Secondary outcomes.

Secondary outcomes will be subjective stress perception, state anxiety, and affect as well as associations between the time course of the primary outcomes with person characteristics (e.g., age and sex) and psychological variables (e.g., personality, coping style, self-efficacy, depression, anxiety, polychronicity).

Main hypotheses.

With regard to the specificity hypothesis [ 45 , 46 ], we expect that pure digital stressors will trigger physiological responses of the SNS (i.e., an up-regulation), PNS (i.e., a down-regulation), as well as an activation of the immune system, but not of the HPA axis (due to the absence of a social-evaluative component). An additional activation of the HPA axis (i.e., an increase of cortisol levels) is expected for the conditions 5 and 6 (non-digital parallel dual-tasking and multitasking), in which we included a social-evaluative component by the presence of an experimenter.

Our main hypotheses, that are associated with research questions 1, 2, and 3 are:

• Conditions 3 and 4 (digital work interruptions and digital parallel dual-tasking) will trigger responses of the SNS, PNS, and the immune system that are stronger than in the passive control condition 1 and the single-task control condition 2. No HPA axis response are expected for conditions 3 and 4.
• Conditions 5 and 6 (non-digital parallel dual-tasking and multitasking) will trigger responses of the SNS, PNS, HPA axis, and the immune system that are stronger than in the passive control condition 1 and the single-task control condition 2.

Regarding the time course of the physiological responses (if any will be found), we hypothesize fast responses of the SNS and PNS with a maximum immediately after the tasks. The HPA axis response is expected to be delayed with a maximum 20 minutes after the tasks. Slower responses are expected for the immune system with a maximum of 90 minutes after the task for IL-6 and s-IgA and 24 hours after the experimental session for CRP.

Secondary hypotheses.

We hypothesize that conditions 3, 4, 5, and 6 will induce the perception of being stressed and that perceived stress will be stronger in these conditions than in the passive control condition 1 and the single-task control condition 2 immediately after the stressor. Furthermore, we expect to find an increase in state anxiety and in negative affect as well as a decrease in positive affect immediately after the tasks, which will be stronger than in the passive control condition 1 and the single-task control condition 2. Moreover, we expect that the physiological stress response patterns will be associated with person characteristics [e.g., age and sex; e.g., 55 ] and psychological variables (e.g., personality, coping style, self-efficacy, depression, anxiety, and polychronicity).

Sample handling and laboratory analysis of blood and saliva samples

The saliva and blood samples will be analyzed in our in-house laboratory (FAU, Chair of Health Psychology, Biopsychological Laboratory, Nürnberg, Germany) by trained staff using established procedures [e.g., 71 ]. After collection, Salivettes and Salicaps will be stored at -30°C. On the analysis day, they will be thawed and centrifuged at 2,000 g at 4°C before further processing. The DBS samples will be dried for at least 8 hours at room temperature before they will be stored at -30°C. The further handling during analysis will also be conducted according to established procedures [e.g., 69 , 71 , 96 ]. In short, a circle with a diameter of 3.5 mm will be punched out and will be eluted overnight in phosphate buffered saline which contains 0.1% Tween 20 solution. The next morning, samples will be shaken at 300 rpm for one hour before further processing.

Concentration of sAA will be measured with an enzyme kinetic assay, as described elsewhere [e.g., 97 ]. For salivary cortisol, CRP, as well as s-IgA measurement, high-sensitive Enzyme-linked Immunosorbant Assays [ELISA; e.g., 98 , 99 ] will be used. For IL-6 measurement, a ProQuantum-Immunoassay-Kit (ThermoFisher Scientific, USA) will be used. For determination of absolute CRP concentrations, linear regressions will be conducted which been validated in-house. sAA, cortisol, CRP, and s-IgA analyses will be conducted in duplicates and IL-6 analyses in triplicates. Analyses will be repeated if inter- or intra- coefficients of variation will be greater than 10%.

Heart-rate variability analysis

Several HRV parameters can be derived from the ECG signal. The most prominent one, that is calculated in the time domain of the signal, is the RMSSD which is usually used as a marker for PNS activity [ 68 ]. The RMSSD will be the main HRV measure for our analyses and will be used for main hypotheses testing. Yet, there are further HRV parameters that can be extracted from the HRV signal, e.g., in the very-low frequency (VLF), low frequency (LF), and high-frequency (HF) range, which can be derived from the power spectrum of the HRV signal [ 68 , 77 ]. It has been suggested that VLF power is associated with SNS activity, LF power with both SNS and PNS activity, and HF power with PNS activity [ 68 ]. However, there remains a debate whether all these components in the frequency domain reflect parts of both, SNS and PNS activity [ 100 ]. Therefore, these components will not be included in our main analyses, but additional analyses will be conducted. Another frequently used HRV parameter as a measure for sympatho-vagal balance is the ratio LF/HF [ 101 ], which will also be used for additional analyses in our study. For all these additional HRV analyses (besides the RMSSD) an adjusted alpha-level of α adjusted = .001 will be applied.

Randomization

For randomization, computer-generated randomization lists will be used, which will be stored in closed envelopes and will be handed out to the experimenters immediately prior to the experimental sessions. A team member who is not involved in data collection is responsible for randomization. Subjects are blinded and are informed that the intention of the study is the assessment of physiological responses to interaction with digital devices. Participants’ sex will be considered in the randomization process to ensure an equal sex distribution.

Data preparation and statistical analysis

For statistical analysis, IBM SPSS Statistics (version 26 or higher for Windows) will be used. Data will be screened for outliers, and outliers which differ more than 3 standard deviations from the participants’ mean will be excluded from further analysis. Test of normality will be conducted by means of the Kolmogorov-Smirnov test. If necessary, data will be transformed (e.g., by means of the natural logarithm or square root transformation) to achieve a normality distribution.

For main hypotheses testing (research questions 1, 2, and 3), rmANOVAs will be conducted. In the analyses, the between-subjects factor ‘Condition’ (with six levels, see above) as well as the within-subjects factor ‘Time’ (with either six levels (for sAA, cortisol, and ECG measures), two for CRP and IL-6, and two for s-IgA) will be included. Three separate analyses will be conducted, one for SNS and PNS markers (i.e., sAA, HR, and RMSSD) and six measurement time points (s 1 to s 6 ), one for cortisol as the only HPA-axis marker with the same six time points, and one for the immune parameters (i.e., IL-6, CRP, and s-IgA) and two measurement time points. An additional factor ‘Measure’ (e.g., with the levels IL-6, CRP, and s-IgA for immune parameters) will be included if necessary. A Bonferroni-adjusted α-level of α adjusted = 0.05/3 = 0.017 will be used for the main analyses, because three separate rmANOVAs will be conducted. The potential confounders age, sex, BMI, use of oral contraceptives and menstrual cycle phase for female participants, as well as time of day will be included in all statistical analyses as covariates.

Research question 4 (i.e., perceived stress, state anxiety, and affect) will be investigated analogously to research questions 1 to 3 by means of a further rmANOVA. The same α adjusted = 0.017 as for main hypothesis testing will be used. For analysis of research question 5 (i.e., associations with person characteristics and psychological variables), nominal scaled variables (e.g., sex and education) will be included as additional factors in further rmANOVAs. For metric variables, multivariate regression analyses will be conducted in which the potential moderator variables will be included as moderator variables. For these analyses, the SPSS macro PROCESS [ 102 ] will be used. For these analyses which refer to research question 5, an adjusted α-level of α adjusted = 0.001 will be used.

Data management plan

To protect the participants’ privacy and to maintain confidentiality, all personal data is stored in password-protected files and secured against unauthorized access by third parties. The raw data and materials are only accessible to project-team members. Each participant is assigned a randomly generated code that does not allow any conclusions to be drawn about the person. Only this code is used for naming files and samples. Only completely anonymized data will be made available to other researchers after completion of the study or in data repositories. Only mean values and group statistics will be reported in publications.

Dissemination and analysis plans

Data analyses will start after data collection is completed. Interim analyses are not planned. At least one paper will be submitted to a leading journal in the field. The pre-processed and anonymized data will be made publicly available at the Open Science Framework (OSF) after an Embargo period of about 5 years.

Psychosocial stress and its immediate and long-term biological effects have been studied relatively well, but a link between psychobiological-oriented stress research and the effects of digital stress has largely been lacking. The aim of our study is to apply the methods of psychobiological stress research in the context of digital stress (i.e., the widespread phenomena multitasking and work interruptions), with the overarching goal to provide the foundations for a better understanding of the health effects of digital stress. We describe a study protocol of a comprehensive experiment that investigates effects of multitasking and work interruptions on physiological stress response patterns including SNS, PNS, HPA axis, and the immune system.

Strengths of the planned study

So far, acute psychobiological stress response patterns have been well researched in the context of “classic” stress research for non-digital stressors. In contrast, psychobiological stress reaction patterns in the context of digital stress have hardly been studied so far [ 103 ]. The aim of the presented study is to bring digital stress from every day and working life into the laboratory context, and thus to make it experimentally investigable. Our experimental approach is the key strength of our study. It enables us to systematically induce multitasking demands or work interruptions and compare them with single-task and passive control conditions.

Moreover, our study will enable to differentiate between stress responses to pure digital stressors and stressors that also include a non-digital component (operationalized by the presence of an experimenter). Nevertheless, all active tasks–the digital and the non-digital ones–include a cognitive component and therefore our study design does not allow to differentiate between digital and cognitive stressors. However, this is not a restriction of our study with respect to our definition of digital stress as being related to the usage of digital technology and media, which is independent of the (e.g., mental) processes being involved.

Potential risks

From a practical point of view, there is a risk that the blood and saliva volumes will be too low for analysis. However, this has been included in the sample size-calculation and will be minimized by training the experimenters by experienced researchers. A further potential risk is that the recruitment goal might not be fulfilled, e.g., due to the Covid-19 pandemic. In the case that another lockdown will be imposed, recruitment will be paused.

Limitations

In our study, we will focus on multitasking and work interruptions as highly relevant modern stressors. Nevertheless, a variety of further digital stressors is conceivable [e.g., techno insecurity, techno overload, or techno invasion; 104 ]. Moreover, our operationalization of multitasking and work interruptions is just one of many possibilities and many more are possible.

A further limitation is that we cannot assess certain factors which might be related with the physiological stress response to multitasking and work interruptions. One of these are primary and secondary appraisal [ 105 ], which are known to be associated with acute stress responses in general. However, assessing them between the introduction of the task and the beginning of the task [e.g., by means of the Primary and Secondary Appraisal Scale; 106 ] would disrupt the procedure too much. A further and related factor which we cannot assess is executive functioning, of which especially attentional control has been shown to be related with HPA axis responses after acute stressors [ 107 ]. Furthermore, although we assess intelligence during some of the sub tasks, a comprehensive assessment [including emotional intelligence; 108 ] would be even more meaningful. A further potential limitation is the chosen passive control condition as we cannot rule out that watching the videos unintendedly leads to either stress induction or relaxation. However, the videos’ contents have been rated as being low arousing in previous studies [ 65 , 66 ]. Moreover, this task is better suited than other potential control tasks in which participants are instructed to do nothing at all, which are–in our opinion–more likely to induce relaxation and which are also much more difficult to control.

We will use a pragmatic age restriction of 40 years, because this has been shown to be suitable in previous studies from our group for recruiting healthy participants who do meet all inclusion criteria. Other age groups (older than 40 years as well as children and adolescents) would be interesting target groups for future follow-up studies. Besides, non-healthy participants with diseases which are known to be associated with stress reactivity or being associated with chronic stress development [e.g., depression or post-traumatic stress disorder, 109 ] should be subject of further investigations.

Implications

Nevertheless–despite these limitations–, we deem that our study contributes to a deeper understanding on influences of stressors associated with the use of digital technology on humans’ health-outcomes. Specifically, our results are expected to expand our current knowledge base on the impact of multitasking and information load on humans’ psychobiological stress responses with particular focus on physiological response patterns. Stress exerts a strong influence on health via well-described processes [e.g., conceptualized in the Allostatic Load Model; 3 , 32 , 110 ]. In the long-term, stress is negatively associated with quality of life, health, and longevity of individuals and, thus, productivity of society [ 111 , 112 ]. Therefore, our study is of high relevancy.

Given the ubiquitous applications of digital technologies in modern workplaces and living environments, our findings will help to further understand the mechanisms between digital stressors in various occupational settings and adverse health outcomes [ 113 ]. Eventually, examination of job-related risks will inform policy and practice interventions in occupational health. Overall, the findings from our study will have important implications for better understanding the long-term health effects of the potential stressors multitasking and work interruptions in several settings.

Conclusions

Our planned study will expand our understanding of the physiological response patterns due to the modern (digital) stressors multitasking and work interruptions. By quantifying objective parameters of biological stress responses and, thus, patho-physiologically relevant markers of digital stress, the health effects of digital stress will be made assessable. The findings will have important implications, especially in the context of health in digitalized working environments.

Supporting information

S1 file. questionnaire sample characteristics..

Questionnaire that will be used for the assessment of sample characteristics. In the actual study, a German version will be used.

https://doi.org/10.1371/journal.pone.0263785.s001

S2 File. Visual-analogous scales.

Visual-analogous scales with which perceived stress, tiredness, and exertion will be assessed. In the actual study, a German version will be used.

https://doi.org/10.1371/journal.pone.0263785.s002

S3 File. Multitasking questionnaire.

Questionnaire that will be used for the assessment of multitasking. In the actual study, a German version will be used.

https://doi.org/10.1371/journal.pone.0263785.s003

Acknowledgments

We thank Laura Carolina Manns for assisting the development of the multitasking items and Janek Ruß for supporting translation of the MTUAS. Furthermore, we thank Swathi Hassan Gangaraju for programming the tasks and Katharina Hahn for supporting setting-up the experiment.

• View Article
• PubMed/NCBI
• Google Scholar
• 10. Hefner D, Vorderer P. Digital stress: Permanent connectedness and multitasking. In: The Routledge handbook of media use and well-being: Routledge; 2016. p. 255–67.
• 12. Mark G, Wang Y, Niiya M, editors. Stress and multitasking in everyday college life: an empirical study of online activity. CHI; Toronto, ON, Canada; 2014.
• 62. Amthauer R, Brocke B, Liepmann D, Beauducel A. IST 2000 R: Intelligenz-Struktur-Test 2000 R: Hogrefe, Verlag für Psychologie; 2001.
• 75. Laux L, Hock M, Bergner-Köther R, Hodapp V, Renner K-H. Das State-Trait-Angst-Depressions-Inventar: STADI; Manual 2013.
• 82. Kälin W, Semmer N. Coping-Inventar zum Umgang mit Stress-Situationen: Deutschsprachige Adaptation des Coping Inventory for Stressful Situations (CISS) von Norman S. Endler und James D. A. Parker: Hogrefe; 2020.
• 84. Hautzinger M, Bailer M, Hofmeister D, Keller F. ADS: Allgemeine Depressionsskala: Testhandbuch (2te Ausgabe): Göttingen: Hogrefe; 2012.
• 95. Fydrich T, Sommer G, Brähler E. Fragebogen zur sozialen Unterstützung: F-SozU: Hogrefe; 2007.
• 98. Becker L, Rohleder N, Schultheiss O. Salivary Hormone Assays. In: APA, editor. APA Handbook Of Research Methods In Psychology; in press. xx-yy.
• 102. Hayes AF. Mediation, moderation, and conditional process analysis. Introduction to Mediation, Moderation, and Conditional Process Analysis: A Regression-Based Approach edn. New York: Guilford Publications 2013:1–20.