Life stress is central to many contemporary theories of human health and behavior. Despite this fact, numerous conceptual and measurement issues remain unresolved. The present article explores these topics by first summarizing several key definitional and conceptual matters that are important for life stress research. Second, I introduce stressnology, defined herein as the fictitiously named, but otherwise very real and problematic approach to studying life stress exposure that involves measuring only the superficial contours of this very complex construct. Finally, I review some recent methodological advancements that have the potential to move us past primitive approaches to conceptualizing and assessing life stress. Ultimately, although the influence that life stress has on human health and behavior is profound, our understanding of this construct-and how it affects wellbeing, functioning, and development-is still very limited. Using state-of-the-art instruments for assessing life stress exposure, especially across the entire life course, should therefore be a top scientific and clinical priority.

Many of life's most impactful experiences involve either social safety (e.g., acceptance, affiliation, belonging, inclusion) or social threat (e.g., conflict, isolation, rejection, exclusion). According to Social Safety Theory, these experiences greatly impact human health and behavior because a fundamental goal of the brain and immune system is to keep the body biologically safe. To achieve this crucial goal, social threats likely gained the ability to activate anticipatory neural-immune responses that would have historically benefited reproduction and survival; the presence of social safety, in turn, likely dampened these responses. Viewing positive and negative social experiences through this lens affords a biologically based evolutionary account for why certain stressors are particularly impactful. It also provides an integrated, multi-level framework for investigating the biopsychosocial roots of psychopathology, health disparities, aging, longevity, and interpersonal cognition and behavior. Ultimately, this work has the potential to inform new strategies for reducing disease risk and promoting resilience.

Social Signal Transduction Theory of Depression is a biologically plausible, multi-level theory that describes neural, physiologic, molecular, and genomic mechanisms that link experiences of social-environmental adversity with internal biological processes that drive depression pathogenesis, maintenance, and recurrence. Central to this theory is the hypothesis that interpersonal stressors involving social threat (e.g., social conflict, evaluation, rejection, isolation, and exclusion) upregulate inflammatory processes that can induce several depressive symptoms, including sad mood, anhedonia, fatigue, psychomotor retardation, and social-behavioral withdrawal. The original article describing this formulation (Psychol Bull 140:774-815, 2014) addressed critical questions involving depression onset and recurrence, as well as why depression is strongly predicted by early life stress and comorbid with anxiety disorders and certain physical disease conditions, such as asthma, rheumatoid arthritis, chronic pain, and cardiovascular disease. Here, we extend the theory to help explain sex differences in depression prevalence, which is a defining feature of this disorder. Central to this extension is research demonstrating that ovarian hormone fluctuations modulate women's susceptibility to stress, brain structure and function, and inflammatory activity and reactivity. These effects are evident at multiple levels and are highly context-dependent, varying as a function of several factors including sex, age, reproductive state, endogenous versus exogenous hormones, and hormone administration mode and dose. Together, these effects help explain why women are at greater risk for developing inflammation-related depressed mood and other neuropsychiatric, neurodevelopmental, and neurodegenerative disorders during the reproductive years, especially for those already at heightened risk for depression or in the midst of a hormonal transition period.

Major life stressors, especially those involving interpersonal stress and social rejection, are among the strongest proximal risk factors for depression. In this review, we propose a biologically plausible, multilevel theory that describes neural, physiologic, molecular, and genomic mechanisms that link experiences of social-environmental stress with internal biological processes that drive depression pathogenesis. Central to this social signal transduction theory of depression is the hypothesis that experiences of social threat and adversity up-regulate components of the immune system involved in inflammation. The key mediators of this response, called proinflammatory cytokines, can in turn elicit profound changes in behavior, which include the initiation of depressive symptoms such as sad mood, anhedonia, fatigue, psychomotor retardation, and social-behavioral withdrawal. This highly conserved biological response to adversity is critical for survival during times of actual physical threat or injury. However, this response can also be activated by modern-day social, symbolic, or imagined threats, leading to an increasingly proinflammatory phenotype that may be a key phenomenon driving depression pathogenesis and recurrence, as well as the overlap of depression with several somatic conditions including asthma, rheumatoid arthritis, chronic pain, metabolic syndrome, cardiovascular disease, obesity, and neurodegeneration. Insights from this theory may thus shed light on several important questions including how depression develops, why it frequently recurs, why it is strongly predicted by early life stress, and why it often co-occurs with symptoms of anxiety and with certain physical disease conditions. This work may also suggest new opportunities for preventing and treating depression by targeting inflammation.

The long-term value of immunopsychiatry will be based on its ability to translate basic science into effective clinical interventions. In this article, we discuss a key obstacle to achieving this important translational goal-namely, the preponderance of studies that are cross-sectional, or that have months-to-years long follow-up periods. Immunopsychiatric processes such as stress, inflammation, and depression symptoms are inherently dynamic and fluctuate over hours, days, and weeks. This fact suggests that higher-density data collection with only days between measurements is necessary to capture-with adequate resolution-the actual dynamics of these systems, determine optimal time lags with which to observe associations between variables of interest, and maximize the translational potential of these data. To illustrate these points, we use pilot data from our own intensive longitudinal immunopsychiatric study. We then conclude by making several recommendations for future research. By learning how to better use existing data for dynamically informative studies as well as collecting intensive longitudinal data, we believe immunopsychiatry will be much better positioned to advance our causal understanding of the interplay between the immune system and health.

Psychoneuroimmunology and immunopsychiatry are quickly approaching a critical point where the clinical translatability of their evidence base will be tested. To maximize chances for translational success, we believe researchers must adopt causal inference techniques that augment the causal relevance of estimates given theorized causal structures. To illustrate the utility of incorporating causal inference perspectives into psychoneuroimmunology, we applied directed acyclic graphs and a combination of empirical and simulated data to demonstrate the consequences of controlling for adiposity when testing the association between inflammation and depression under the plausible causal structure of increases in adipose tissue leading to greater inflammation that in turn promotes depression. Effect size estimates were pulled from a dataset combining the Midlife in the United States 2 (MIDUS-2) and MIDUS Refresher datasets. Data were extracted and used to simulate data reflecting an adiposity → inflammation → depression causal structure. Next, a Monte Carlo simulation study with 1,000 iterations and three sample size scenarios (Ns = 100, 250, and 500) was conducted testing whether controlling for adiposity when estimating the relation between inflammation and depression influenced the precision of this estimate. Across all simulation scenarios, controlling for adiposity reduced precision of the inflammation → depression estimate, suggesting that researchers primarily interested in quantifying inflammation → depression associations should not control for adiposity. This work thus underscores the importance of incorporating causal inference approaches into psychoneuroimmunological research.

Background

Psychological stress is a well-known risk factor for poor health, and recent research has suggested that the emotion-focused coping process of forgiveness may help mitigate these effects. To date, however, no studies have examined how levels of forgiveness, stress, and health fluctuate and interrelate over time.

Purpose

We addressed this issue by examining how forgiveness, stress, and mental and physical health symptoms change and relate to one another over 5 weeks. We hypothesized that increases in state levels of forgiveness would be associated with decreases in perceptions of stress, which would in turn be related to decreases in mental and physical health symptoms. A reverse effects model was also tested.

Methods

We recruited a large, community-based sample of 332 young, middle-aged, and older adults (16-79 years old; M _age = 27.9). Each week for 5 weeks, participants reported on their levels of state forgiveness, perceived stress, and mental and physical health symptoms.

Results

Levels of forgiveness, stress, and mental and physical health symptoms each showed significant change and individual variability in change over time. As hypothesized, increases in forgiveness were associated with decreases in stress, which were in turn related to decreases in mental (but not physical) health symptoms (i.e., forgiveness → stress → health). The reverse effects model (i.e., health → stress → forgiveness) provided a relatively poorer fit.

Conclusions

This study is the first to provide prospective, longitudinal evidence showing that greater forgiveness is associated with less stress and, in turn, better mental health. Strategies for cultivating forgiveness may thus have beneficial effects on stress and health.

There is increasing appreciation that certain biological processes may not be equally related to all psychiatric symptoms in a given diagnostic category. Research on the biological phenotyping of psychopathology has begun examining the etiological and treatment implications of identified biotypes; however, little attention has been paid to a critical methodological implication of these results: measurement noninvariance. Measurement invariance is the ability of an instrument to measure the same construct, the same way, across different people, or across different time points for the same individual. If what a measure quantifies differs across different people (e.g., those with or without a particular biotype) or time points, then it is invalid to directly compare means on that measure. Using a running example of inflammatory phenotypes of depression, we first describe the biological phenotyping of psychopathology. Second, we discuss three types of measurement invariance. Third, we demonstrate how differential biology-symptom associations invariably creates measurement noninvariance using a theoretical example and simulated data (for which code is provided). We also show how this issue can lead to false conclusions about the broader diagnostic construct. Finally, we provide several suggestions for addressing these important issues to help advance the field of biological psychiatry.

Although prior research has examined how early adversity and chronic stress exposure relate to hypothalamic-pituitary-adrenal (HPA) axis responses to acute stress, to date, no studies have examined how stressors occurring over the entire lifespan predict such responses. To address this issue, we recruited 61 healthy young adults and measured their exposure to 55 different types of acute life events and chronic difficulties occurring over the lifespan. In addition, we characterized differences in participants' HPA axis responses to acute stress by measuring their salivary cortisol and DHEA responses to the Trier Social Stress Test for Groups. Greater cumulative stress exposure was associated with a blunted cortisol response, but a heightened DHEA response, to the acute stressor. Moreover, it was participants' exposure to these stressors (i.e., lifetime count), not their perceived severity, which predicted their cortisol and DHEA responses to acute stress. Furthermore, differential effects were observed by stress exposure domain. Notably, only adulthood and marital/partner stressors significantly predicted cortisol responses to acute stress, whereas stress was more uniformly associated with DHEA responses to the acute stressor. These results thus reveal how cumulative stress exposure is associated with HPA axis responsivity to acute stress, while highlighting the fact that different stressors may have substantially different associations with these biological outcomes.

Background

Although characterizing associations between inflammation and depression may prove critical for informing theory, research, and treatment decisions, extant research has been limited by ignoring the possibility that inflammation may be simultaneously associated with depression broadly and with a subset of symptoms. This lack of direct comparison has hampered attempts to understand inflammatory phenotypes of depression and critically fails to consider that inflammation might be uniquely associated with both depression broadly and individual symptoms.

Methods

We used moderated nonlinear factor analysis in 5 NHANES (National Health and Nutrition Examination Survey) cohorts (N = 27,730, 51% female, mean age = 46 years).

Results

C-reactive protein (CRP) is simultaneously associated with latent depression, appetite, and fatigue. Specifically, CRP was associated with latent depression in all 5 samples (rs: 0.044-0.089; ps: < .001-.002) and was associated with both appetite (significant rs: 0.031-0.049, significant ps: .001-.007) and fatigue (significant rs: 0.030-0.054, significant ps: < .001-.029) in 4 samples. These results were largely robust to covariates.

Conclusions

Methodologically, these models indicate that the Patient Health Questionnaire-9 is scalar noninvariant as a function of CRP (i.e., identical Patient Health Questionnaire-9 scores may represent different constructs in those with high vs. low CRP levels). Therefore, mean comparisons of depression total scores and CRP might be misleading without accounting for symptom-specific associations. Conceptually, these findings indicate that studies investigating inflammatory phenotypes of depression should examine how inflammation is simultaneously related both to depression broadly and to specific symptoms, and whether these relations function via different mechanisms. This has the potential to yield new theoretical insights and may lead to the development of novel therapies for reducing inflammation-related symptoms of depression.