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Measurement of Human Stress: A Multidimensional Approach

Achsah Dorsey , Elissa Scherer , Randy Eckhoff , and Robert Furberg .

Stress is a multidimensional construct that comprises exposure to events, perceptions of stress, and physiological responses to stress. Research consistently demonstrates a strong association between stress and a myriad of physical and mental health concerns, resulting in a pervasive and interdisciplinary agreement on the importance of investigating the relationship between stress and health. Developing a holistic understanding of stress requires assessment of the three domains vital to the study of stress: (1) the presence of environmental stressors, (2) psychological and biological reactions to stressors, and (3) the length of time over which the stressor or stress response occurs. Research into all three domains requires multiple methods. Self-reports allow for subjective evaluations of stress that illuminate the duration and severity of the psychological response to stressors. Biomarkers, in turn, capture a more-objective measure of stress and create a deeper understanding of the biological response to chronic and acute stress. Finally, the use of digital biomarkers allows for further exploration of the physiological fluctuations caused by stress by measuring the changes occurring at the same time as the stressor. Future research on stress and health should favor a multidimensional approach that creates a triangulated picture of stress, drawing from each of the three aforementioned method groups.

Introduction

Stress is consistently associated with a myriad of physical and mental morbidities, as well as mortality. 1 Additionally, the financial burden of stress is estimated to be $300 billion per year in the United States alone. 2 As a result, there is pervasive and interdisciplinary agreement on the importance of understanding and alleviating stress to improve quality of life. However, the measurement of stress varies greatly within the large body of work linking stress and well-being. Researchers attempting to quantify stress should first understand the measurement strategies available to them and the strengths and limitations of each form of measurement. The goal of this paper is to define stress and offer an overview of measurement methods available to researchers interested in capturing stress.

Key Research Needs.

Defining Stress

The definition of stress has evolved over several decades, and a universally adopted definition has yet to be reached. Seminal models of stress proposed by Selye in the 1950s define stress as the “non-specific response of the body to any demand for change” or the “rate of wear and tear on the body.” 3 Proposed refinements to these definitions in the decades since have differentiated between stressors, defined as stimuli that challenge an organism’s biological and psychological equilibrium (i.e., homeostasis), and the stress response, defined as the process through which the organism attempts to restore homeostasis. 4 Although the revised definitions differentiate between the cause and effect of stress, they have frequently received critique for being too vague, as nearly all activities that an organism undertakes constitute a challenge to homeostasis. 5 One model created to further clarify a working definition of stress, the psychophysiological stress concept, has been widely adopted in stress-related research since its dissemination in 2011. 5 Developed by Koolhaas and colleagues, the psychophysiological model of stress defines stress as the perceived or anticipated inability to successfully cope with situations that are not predictable or controllable. 6 This inability to cope with an experience leads to both subjective feelings of stress and objective biological changes in the body. 6

In defining stress, it is also important to recognize that stress can be conceptualized both as an acute reaction and a chronically accumulated state throughout the life course. Taken with the information above, this highlights three domains vital to the study of stress: (1) the presence of environmental stressors, (2) psychological and biological reactions to stressors, and (3) the length of time over which the stressor or stress response occurs. 7 Many subjective and objective measures have been developed and validated to quantify these domains. The following sections will cover not only subjective measures that capture perception of environmental stressors and psychological response but also objective measures that capture biological change.

Measures of Self-Report

Self-report measures of stress consist of series of questions or prompts that inquire about respondents’ lived experience with various components of stress. Several measures have been developed to quantify both reactions to acute stressors and the accumulation of chronic stress ( Table 1 ).

Inventory of subjective (self-report) measures of acute and chronic stress.

Common measures to assess chronic stress include both the Life Events and Difficulties Schedule (LEDS) 20 and the Trier Inventory for Chronic Stress (TICS). 17 , 21 The LEDS captures exposure to severe acute events (i.e., those lasting less than 1 month) and severe chronic difficulties (i.e., those lasting longer than 1 month) over the previous year through a semi-structured interview that prompts the individual to recall 95 possible life events. The individual provides additional context around each experience; a trained expert then codes the context. LEDS stressors are grouped into 10 domains: education, work, reproduction, housing, money/possessions, crime/legal, health/treatment/accidents, marital/partner relationship, other relationships, and miscellaneous. The TICS attempts to capture chronic stress through a more-structured questionnaire covering nine factors of chronic stress: “work overload, social overload, pressure to perform, work discontent, excessive demands at work, lack of social recognition, social tensions, social isolation, and chronic worrying. Participants in these surveys rate 57 items covering how often situations within the nine domains occur (i.e., never, rarely, sometimes, often, or very often) over a recall period of 3 months.

Several measures have been designed to capture stress over a shorter period of time, including the Cohen Perceived Stress Scale (PSS) and the Stress Overload Scale (SOS), among others ( Table 1 ). The most commonly used measure for assessing global stress perceptions is the 10-item PSS. 15 This survey captures the degree to which a person views their life as uncontrollable, unpredictable, and overloaded in the past month. Scores are calculated using a five-point scale (0 = never, 1 = almost never, 2 = once in a while, 3 = often, and 4 = very often) that is summed for a total score, where higher scores represent a greater level of perceived stress. The PSS has been translated into a variety of languages, 22 , 23 which allows for its use in both English and non-English-speaking populations. As an alternative to the PSS, the SOS was designed to measure when stress overwhelms a person’s coping mechanisms. 13 Twenty-four statements touch on personal vulnerability and event load, and an additional six items are used to discourage inconsistent responses. A shorter version of the SOS (10 items) also exists. 24 Each of the statements is evaluated on a 5-point graded-response scale (1 = not at all, 5 = a lot) to investigate feelings and experiences from the prior week.

Though measures such as the PSS or the SOS capture stress over a shorter time than measures of more-chronic stress, they are still frequently criticized for having great potential for bias because individuals are asked to report retrospectively on cumulative stress experienced. In response to this limitation, the ecological momentary assessment (EMA) method was developed. EMA is the repeated measurement of an individual’s subjective experience of stress in the context of daily life. 25 This method can be used to capture momentary stress at multiple points throughout the day, which can then be aggregated to create a picture of stress levels over time. As technology has evolved, the smartphone has become a popular tool for conducting EMAs and contextualized survey items, including single-item measures. 26 For example, a question prompted by a beep on a responder’s phone, such as “How stressed were you right before the beep went off?” can capture real-time stress with a variety of response options (not at all, a little, moderately, quite a bit, and extremely). 27

One measure used for EMAs is the Photographic Affect Meter (PAM). PAM is a validated, one-item, mobile application–based measure of affect that correlates with the widely used Positive and Negative Affect Schedule (PANAS). 8 As shown in Figure 1 , subjects select an image from a grid of 16 pictures that best represents their current emotional state.

The Photographic Affect Meter (PAM).

PAM is used to construct a set of numbers for the purpose of quantitative analyses. The first is a categorical 1–16 score that maps on to the PANAS scale. 9 Consistent with the conceptualization of the PANAS, this affect scale ranges from low valence (the level of pleasure that an event generates) and arousal (the level of autonomic activation that an event creates) to high pleasure and arousal. Therefore, PAM also produces two separate affect scores for valence and arousal, which are calculated according to the chosen image’s position in the 16-image grid. Valence is computed using a 1 to 4 score (negative, slightly negative, slightly positive, positive) based on the column position of the image. Arousal is computed in a similar fashion using the row position of the image, with 1 representing calm or low arousal and 4 representing excitement or high arousal.

Self-report measures are useful tools in establishing subjective evaluations of stress levels. They are often cost-effective and correlated with clinical endpoints of interest, but they can be lengthy to administer and are subject to several types of bias. 28 – 30 Self-report measures are best used in combination with objective biological or digital markers of stress to understand the comprehensive impact on outcomes of interest. 6

Stressors cause a variety of biological responses. These physiological reactions can be measured using biomarkers that represent the stress response from the hypothalamic-pituitary-adrenal (HPA) axis, the autonomic nervous system (ANS), and the immune system ( Table 2 ). 48

Inventory of objective (chemical and digital) measures of acute and chronic stress.

The HPA axis is particularly responsive to psychosocial stress. One output of this system is cortisol, a hormone secreted from the adrenal gland that plays a vital role in cognition, metabolism, and immune function as well as the stress response. Levels of cortisol in the body fluctuate daily in response to routine events, unexpected stressors, and circadian patterns that render salivary cortisol highest in the morning and lowest at night. 49 , 50 In addition to daily variation, cortisol may be chronically high or low. Both the acute fluctuation and the chronic compounding of cortisol are of interest to researchers. Acute cortisol change can be reliably measured in saliva and blood, cortisol in urine can be used to establish daily cortisol secretion, 42 and cortisol in hair can be used to gather long-term cortisol levels over weeks or months. 51 Salivary and hair cortisol are commonly used in studies investigating stress because collection is relatively quick and easy. Assessment of cortisol in saliva captures acute cortisol production over the past 15–20 minutes and is often used to measure daily stress.

Collecting saliva samples is comparatively easy and painless (a cotton swab is placed in the mouth of a participant and then sealed in a container), but a single saliva cortisol sample tells little about levels of stress over an extended period of time, and collection time is incredibly important, as cortisol levels vary across the day. Therefore, multiple samples of salivary cortisol throughout the day are needed to accurately capture daily stress. Cortisol levels measured in hair are used as a longer-term biomarker of HPA axis activity because cortisol is incorporated into the hair as it grows. 52 Thus, hair cortisol captures a much longer period: a 1-cm hair segment reflects total cortisol secretion in the past month. These cumulative levels of hair cortisol do not provide information about HPA axis activity specific to any particular time within the measurement period.

The ANS modulates organ system activity through autonomic reflexes that respond to internal and external stimuli. Catecholamines, including norepinephrine and epinephrine, are hormones made by the adrenal glands that serve as strong biomarkers of ANS activity, specifically sympathetic-adrenal medullary (SAM) activity. 53 .SAM activity occurs as a rapid response to a stressor to produce alertness and aid in responsive decision making. By contrast, HPA axis function is more representative of exposure to repeated stressors. Catecholamines can be captured acutely through blood concentration and as a short-term biomarker of daily stress through a 24-hour urine collection protocol. 42 , 43 Alpha-amylase, an enzyme that breaks down starch, is another biomarker of ANS activity and can be detected in saliva samples. 40 Like cortisol, epinephrine, and norepinephrine found in the urine, alpha-amylase fluctuates over the day, so multiple measures are needed to properly understand changes in alpha-amylase in response to stressors. 40

Another way to capture stress response is to measure immune activation. 54 Cytokines are a group of proteins that serve as signaling molecules that help mediate and regulate immune function and can be measured from blood samples. 54 Interleukin (IL)-6 is one type of cytokine that plays a vital role in the development of fever and regulates the acute inflammatory response in the liver. 38 Although IL-6 is correlated with the development of cardiovascular disease and other chronic inflammatory disorders, it is very sensitive and easily elevated by exercise. When collecting samples, participants should refrain from exercise for approximately 12 hours to get an accurate reading.

C-reactive protein (CRP) is another substance integral to immune system response that is used to investigate stress. 44 CRP is made in the liver and released in reaction to inflammation, and it has been linked to stress response in humans. One advantage to using CRP as a measure of stress is that it lacks diurnal variation. However, CRP values can never be diagnostic on their own, and information about other pathological markers is vital to interpreting CRP levels.

Other immune measures of stress include the measurement of antibodies for common herpes viruses, including Epstein Barr virus antibodies, herpes simplex virus type 1 (HSV-1) antibodies, and cytomegalovirus antibodies. 45 , 55 , 56 These viruses are persistent infections that require adequate cell-mediated immunity to maintain in their latent states. 57 , 58 Longer-term stress can decrease the immune system’s ability to keep these viruses from reactivating. 57 , 58 As they reactivate, increased antibodies produced in response to circulating viral particles can be used as a measure of stress. 57 , 58

The biomarkers listed here provide quantifiable measures of the various physiological pathways that lead to a biological stress response. The use of these biomarkers in stress research allows for a more-objective measure of stress and a deeper understanding of the alterations in biological systems caused by chronic and acute stress. However, researchers often assume the validity of biomarkers despite the need for continued evaluation. 59 Many stress biomarkers indicate levels of inflammation, but many factors influence inflammation, and they should be considered in the analysis. 60

The methods for obtaining biological samples for analysis may be a limitation for many researchers. Both the investigator collecting the samples and the participant need appropriate training because of the need for valid and consistent collection procedures. 61 Correct processing after sample collection, shipping requirements, and the proper storage of the biological samples are also critical for reliable results but can prove difficult in resource-limited areas.

Digital Measurement of Biomarkers

The use of sensors, software tools, and signal processing methods to explore complex biological signals related to stress has increased with recent advances in computational methods and concurrent, widespread adoption of consumer electronics. 62

Although a broad range of systems influence cardiac performance and functions, the ANS is the most prominent. 63 Like some of the aforementioned biomarkers, pulse and heart rate variability (HRV) can be used as proxies for fluctuations in the ANS in response to external and internal stressors. Pulse represents the arterial palpitation of the heartbeat and is reported in beats per minute. When individuals are exposed to stressors, their breathing and pulse can temporarily change. The alteration in heartbeat is measured through touch at any place where an artery can be compressed; two of the common areas for measuring pulse are the wrist and neck. HRV, or the fluctuating time between heart beats, can also be used as a proxy for ANS response to regulatory impulses and stress. 31 Typically, when the ANS is stimulated, variation between heart beats is low, and during relaxed states, variability is high. Advantageously, fluctuations in HRV can be measured while other physiological markers of stress remain constant. 64

HRV, as well as pulse, can be captured through different techniques with varying validity and convenience. Electrical impulses cause cardiac muscle to squeeze and pump blood from the heart, which can be captured through electrical leads attached to an electrocardiogram (ECG). The ECG method is the gold standard for measuring electrical activity of the heart. However, it is difficult to reliably collect ECG data in a cost-efficient, ecologically valid manner. In response to these challenges, wearable device manufacturers have turned to photoplethysmography (PPG) sensors. PPG is an optical measurement of blood volume variations as capillaries expand and contract with each heartbeat. 65 Data collected using wearable PPG sensors has shown varied validity when compared with the gold-standard ECG. 66 This is mostly because of differences in what PPG and ECG measure. PPG measures variability in peripheral pulse, whereas ECG directly measures the electrical cycles of heart function. Several factors, including blood pressure and age-related changes to the vascular system, influence peripheral pulse. 67 Differing device quality and sensor placement can also explain differences between ECG and PPG. Placement is most commonly on the wrist, but can also be on the forehead, earlobes, upper arm, torso, fingertips, and ankles. Each of these locations experiences unique amounts of movement, which can limit the sensor’s ability to capture an accurate PPG reading. To counter the effect of movement on PPG sensors, wearable manufacturers are incorporating three-axis accelerometer data into their heart rate algorithms. 65 As ECG and PPG wearable technology improves, large-scale health studies are producing robust, evidence-based results using user-owned devices. 68

Electrodermal activity (EDA) is another physiological measure of stress response that can be captured through sensor-based measurement. 69 , 70 EDA is the variation in electrical characteristics of the skin. These fluctuations in conductivity are caused by the changes in the ANS and are considered the most-useful index of ANS arousal. 64 EDA is measured through continuous monitoring of the involuntary changes in skin conductivity. EDA is particularly useful when assessing changing impacts of stress because of the continuous alterations in skin conductance 71 and because it is the only ANS variable associated with psychosocial stress that is not correlated with other parasympathetic markers. 64 Researchers can capture EDA through wearable devices such as the Empatica. 69

Like biomarkers, sensor-based measures provide an objective method for quantifying the physiological response to psychosocial stress. Gathering complex, multisensory data on pulse, HRV, and EDA is easy and minimally invasive because of advances in technology. The development of small, reliable, and cost-effective biometric devices has created an increase in access and interest among consumers. However, these digital measures can only capture the stress response contemporaneously. In addition, the accuracy of some commercially available biometric devices is questionable, and assessment of the data quality is needed when using this technology.

Relationships Between Subjective and Objective Measurement of Stress

Subjective and objective measures of stress are related, but not identical, constructs. The psychological experience of stress may not always translate to measurable biological change and vice versa. 5 Limited research exploring associations between subjective and objective measures exists, and that which does suggests notable, but weak, associations between the two types of measures. For example, a recent study by Weckesser and colleagues found that only 16% of the variance in hair cortisol was explained by the subjective Weekly Hassle Scale, and that hair cortisol was not significantly related to the PSS or the TICS. 6 In contrast, other studies have found statistically significant relationships between cortisol and the PSS, 72 and other self-report measures such as the SOS 13 , 73 or aggregated subjective stress measures built from a combination of other measures. 74 The relationship between perceived and objective measures of stress may be further explained by other factors, such as resilience. For example, a recent study by Lehrer and colleagues found that psychological resilience moderates the association between perceived stress (measured by the PSS) and hair cortisol; higher resilience reduces the association between perceived stress and hair cortisol. 75 Further exploration of the relationships between self-report and objective measures of stress is needed to provide greater understanding of the impacts of stress on health.

Future Research Needs

Stress is a multidimensional construct that comprises exposure to events, perceptions of stress, and physiological responses to stress. A nuanced understanding of the links between stress and health requires assessment of each of these components in both acute and chronic scenarios. Employing self-reports allows for subjective evaluations of stress that illuminate the duration and severity of the psychological response to stressors. This information is vital to understanding the physiological stress response measured by biomarkers. Biomarkers, in turn, capture a more-objective measure of stress and create a deeper understanding of the biological response to chronic and acute stress. Finally, the use of digital biomarkers allows for further exploration of the physiological fluctuations caused by stress by measuring the changes occurring at the same time as the stressor. Future research should therefore favor a multidimensional approach that creates a triangulated picture of stress, drawing from perceived measures of stress as well as chemical and digital biomarkers. This will enable a more-comprehensive and holistic understanding of environmental stress triggers and corresponding psychological and biological responses.

Achsah Dorsey , PhD, is an assistant professor of Anthropology at the University of Massachusetts—Amherst.

Elissa Scherer is a public health analyst at RTI International.

Randy Eckhoff is a research programmer at RTI International.

Robert Furberg , PhD MBA, is a clinical informaticist.

RTI International is an independent, nonprofit research organization dedicated to improving the human condition. The RTI Press mission is to disseminate information about RTI research, analytic tools, and technical expertise to a national and international audience. RTI Press publications are peer-reviewed by at least two independent substantive experts and one or more Press editors.

Suggested Citation

Dorsey, A., Scherer, E., Eckhoff, R., and Furberg, R. (2022). Measurement of Human Stress: A Multidimensional Approach . RTI Press Publication No. OP-0073-2206. Research Triangle Park, NC: RTI Press. https://doi.org/10.3768/rtipress.2022.op.0073.2206

RTI International is an independent, nonprofit research institute dedicated to improving the human condition. We combine scientific rigor and technical expertise in social and laboratory sciences, engineering, and international development to deliver solutions to the critical needs of clients worldwide.

RTI Press Associate Editor

Valerie Williams

This work is distributed under the terms of a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 license (CC BY-NC-ND), a copy of which is available at https://creativecommons.org/licenses/by-nc-nd/4.0

Cite this Page Dorsey A, Scherer E, Eckhoff R, et al. Measurement of Human Stress: A Multidimensional Approach [Internet]. Research Triangle Park (NC): RTI Press; 2022 Jun. doi: 10.3768/rtipress.2022.op.0073.2206
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Published: 17 October 2024

Virtual stressors with real impact: what virtual reality-based biobehavioral research can teach us about typical and atypical stress responsivity

Elizabeth A. Shirtcliff ORCID: orcid.org/0000-0002-7097-9547 1 ,
Tor T. Finseth ORCID: orcid.org/0000-0002-4170-9986 2 ,
Eliot H. Winer ORCID: orcid.org/0000-0001-9672-7172 3 ,
David C. Glahn 4 ,
Roselynn A. Conrady ORCID: orcid.org/0000-0002-0727-8852 5 &
Stacy S. Drury 6

Translational Psychiatry volume 14 , Article number: 441 ( 2024 ) Cite this article

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Predictive markers

Stress contributes to transdiagnostic morbidity and mortality across a wide range of physical and mental health problems. VR tasks have been validated as stressors with robust effect sizes for VR-based stressors to evoke stress across the most common autonomic and adrenocortical stress biomarkers. However, meta-analytic validation of VR stressors have resulted in inconsistent logic: why should something that isn’t real evoke a very real suite of stress responses? This review posits that conceptually addressing this question requires differentiating a cause, “stressor”, from effects, “stress”. Stress comprises a series of well-delineated perturbations in biological systems, such as autonomic and adrenocortical biomarkers in response to stressors. Despite their ubiquity, decades of literature have back-calculated stressor intensity based on the magnitude of a stress response. This causal directionality is not logical, yet remains pervasive because seemingly objective stress indices have generated a wealth of findings showing how stress gets under the skin and skull. This has created challenges for providing clear guidance and strategies to measure acute stressor intensity. Binary thinking about whether something is (not) real has stifled advances in understanding how to measure the dosage of a stressful environment. As a function of being programmed, individualizable, and titrated, virtual reality (VR) based stressors offer the field a platform for quantifying the dose of a stressor and generating reliable dose-response curves. This also raises the possibility to safely and ethically integrate psychosocial stressor administration into clinical and therapeutic settings. For example, Social Evaluative Threat experiments effectively trigger a stress response both in a laboratory setting and in built environments, while also upholding hard-fought trust and rapport with care providers. By focusing attention on the measurement of the stressor, VR paradigms can advance tangible understanding of stressors themselves and the pathways to the stress response.

Advances in the use of virtual reality to treat mental health conditions

Virtual reality: a powerful technology to provide novel insight into treatment mechanisms of addiction

Longitudinal studies support the safety and ethics of virtual reality suicide as a research method

Introduction.

Current treatments for psychological illnesses can involve exposure to environmental cues meant to trigger symptoms with the goal to then work with therapists to practice distress management, behavioral control, and extinction of fear/anxiety cues in vivo. Distress tolerance skill development requires some distress to learn requisite skill sets. Unfortunately, accessible methods to trigger symptoms elude the field. Moreover, many stressful environments are salient despite being imagined, felt, implied, inferred, accentuated, or anticipated threats and psychosocial stressors. Despite being unreal, biomarkers that “get under the skin” show these stressors are salient. Differentiating between stressor inputs and stress outputs can advance insights about the very real intangible stressors that exacerbate and mitigate psychiatric morbidity.

This paper questions whether actually “being there” is necessary to evoke stress. A deep dive into triggering environmental cues serves the goal to identify necessary ingredients of a stressor and to critically explore if environmental cues require a real environment. Recent technological advancements in virtual and augmented reality (VR) are leveraged to question why benchmarks for reality assume built environments. This moves past hyperbolic claims that VR is “the next big thing” and also not as good as “the real thing”. Importantly, suspending an implicit understanding for reality being physically real maps onto current understandings of stress psychobiology; validated stress biomarkers illuminate threat cues and key dimensions of stress that exert tangible biological effects across environmental cues that are real, imagined, or somewhere in between. Questioning stressors’ requirements for reality is not merely a fun thought experiment. There is an urgent need to measure the immersiveness of an environment in order to advance understanding of exacerbators for onset and worsening of psychopathology symptoms. Perhaps counterintuitively, this focus on stressor administration and interpretation advances understanding about the outputs of stress-related transdiagnostic mental and physical illnesses and their treatment.

The circular tautological spline curve of stressor inputs and stress outputs

Stress was coined by Hans Selye to acknowledge the ubiquity for psychosocial stress to worsen health and wellbeing [ 1 ]. The concept of stress was borrowed from engineering to describe the amount of force exerted onto a system. As a physiologist, Selye measured stress using endocrine, immune, physiologic, behavioral, and cognitive metrics. This created tautological slippage where the magnitude of environmental inputs or demands was defined according to their outputs. Falling into this tautology, Selye famously wrote, “ it is not stress that kills us, it is our reaction to it .” [ 2 ] To resolve the bait-and-switch, Selye proposed the term stressor to describe salient environmental demands (inputs) as opposed to stress which characterized the entirety of nonspecific responses of the body to a demand placed upon it. I.E., the outputs.

Stress plays a role in most (if not all) mental and physical health concerns by exerting a wear and tear on physiological systems that, when left unchecked, culminate in allostatic load [ 3 ]. The cardinal symptoms of mental illness (e.g., depression, anxiety, psychosis) are characterized with altered stress physiology including aberrant stress reactivity and recovery. Traditionally, stress has been framed as a hierarchy where low threshold, fast acting systems are quick to alert the organism to perturbations. Rapidly reactive systems often prove insufficient to re-establish equilibrium when resources are maxed. Overwhelmed systems call in the cavalry when more sluggish biomarkers come online to complete the cycle of alerting, orienting, and then disengaging in preparation for the next environmental perturbation.

This conceptualization for an ordinal relationship between stressor inputs and stress outputs relies on several basic tenets: (1) stressor dose is measurable and roughly linear; (2) stress response corresponds to stressor dose; and (3) stress responses are evoked by tangible stressor elements. Unfortunately, this conceptualization has not been supported empirically, and several conceptual difficulties make this simplistic model untenable. Short of an extreme dose where everyone’s ability to adapt is eventually tapped out, titrated individual differences in stress do not typically systematically correspond to how much of a stressor (intensity, frequency, duration of exposure) is needed to overwhelm physiologic resources [ 1 ]. Linear relationships are only evident when the implied index for a stressor’s intensity or force is interpolated from stress outputs. Allostatic realities of wonky spline curves for regulation and counter-regulation are complicated, yet necessary.

Ample reactive and regulatory processes act fast to efficiently avoid stress burden; yet when enough stressor cues accumulate, activation of stress counter-regulation and negative feedback processes are needed to prevent overshoot and recurrence [ 4 ]. The appearance of circular reasoning could be minimized with a thesaurus’s hackneyed intervention, yet the field is still left with the understanding of stress(or) being that stress occurs after a stressor, proximal to stressor exposure, and long before a new stressor is avoided. Intriguingly, only one of these putative purposes involves real exposure to an actual stressor. This stress(or) circularity is perplexing until framed functionally: the purpose of stress is to mitigate damages from a prior stressor and avoid those consequences in the future. Stress reflects a seemingly ambiguous culmination of salient cues that are largely representational for possible future threats—best mitigated early and long before challenges become real. Put another way, if stress biomarkers help avoid adverse consequences of future stressors, why would the body wait until full-blown stressor administration to mount an adaptive response?

Do virtual stressors evoke real stress?

Stress theories exemplify how stressor cues are frequently not real [ 5 , 6 ]. Anticipation, threat, judgment, anxiety, avoidance, risk, perception, evaluation—all of these facets modify stress, but none rely on the built environment or physical space to evoke stress. In fact, the same build environment may be interpreted wildly differently by healthy individuals and those with psychopathology. Even clearly dangerous stressors like skydiving reflect perceived risk rather than experience of adverse consequences [ 7 ]. The limiting factor for VR is likely not whether the virtual environment seems real, but whether that context is sufficiently immersive with salient consequences and performance feedback.

The appeal of VR rests on the notion that it may be possible to systematically alter and precisely measure the intensity of a threat or risk probability by creating and adapting paradigms that evoke real stress from virtual environments. This appeal appears to pan out. Empirical evidence thus far shows that the stress effect of virtual environments is very real. Building on our prior work [ 8 , 9 , 10 ], we conducted a systematic review which found most stress biomarkers are reactive to VR stressors. Analyses like the failsafe N and funnel plots showed that, even though VR stressor research is still emerging, many nonsignificant studies would need to be pulled from a file drawer to wipe out these robust sample sizes. Across most biomarkers, medium effect sizes were observed for VR reactivity to stressors in healthy human populations [ 11 ].

We expected but did not find, that stress reactivity increased incrementally as stressor exposure magnified. Instead, ample heterogeneity in effect sizes across studies and individual differences in stress reactivity were plentiful but largely nonsystematic [ 12 ]. Effect size moderators, including metrics like presence or stressor severity, proved underwhelming for explaining who and why VR triggered stress: Some tasks were better than others, but it is not clear why. Generalized autonomic biomarkers like heart rate, which encodes challenge and engagement stressor elements, proved the exception in that 42 studies converged on the notion that more intense VR challenges evoked greater heart rate reactivity.

The 14 studies that examined cortisol reactivity revealed robust medium effect sizes that are unlikely to be explained away any time soon. Six studies that tested blood pressure indices of systolic and diastolic reactivity expanded VR to ionotropic autonomic stress reactivity measures. Although very different types of biomarkers, sympathetic reactivity to VR was revealed across 19 studies that tested galvanic skin response (GSR) and/or salivary alpha-amylase which measure sympathetic activation. Biomarkers with a low threshold for activation such as measures of parasympathetic withdrawal were expected to be easy to evoke reactivity but these proved the most temperamental. Indeed, the least consistent metrics to elicit VR reactivity were the fastest acting and most easily triggered stress biomarkers that tap into vagal or parasympathetic withdrawal (N = 18 studies with RSA, LF/HF, and/or RSA). It is practical and timely to expand VR stressors to additional stress biomarkers including salivary measures (e.g., sIgA, dehydroepiandrosterone, or testosterone), passively collected biomarkers (e.g., pupil dilation, fEMG, eye gaze), or neuroimaging-based biomarkers (e.g., MRI, fNIRS). Based on stress theory [ 13 ] and this empirical data, future studies on established and novel stress biomarkers will continue to reveal prospects for VR stressors.

Putting the mental in environmental: stressor demands are unrealistic and nonspecific

VR stressors seem to work despite lacking tangible grounding in reality. However, it is not yet known why nor for whom VR stressors evoke stress. Even in reality, it is unclear why most stressors work. It may come as some surprise to laypersons and scientists alike that triggering stress is difficult in practice [ 14 ]. Stressor design amounts to an appeal to the masses with authority by favoring stressors that most experts agree belong in the toolbox. It is difficult to overestimate the dramatic ways this approach has shaped stress research [ 15 , 16 ], including VR-based stressors [ 17 ]. It is also difficult to overestimate the sheer willpower needed for scientists to collectively agree on anything. Unfortunately, the practicality of this logical appeal becomes unclear when stressors that seem like they should work, do not (e.g., noise administration; emotion induction; cyberball; conflict) [ 18 ] or when stress reactivity to one task is uncorrelated to a different (or even the same) stressor. This tried-and-true approach limits innovation and exploration of novel stressors. It also relegates VR-stressors towards pixelated reflections of stressors already designated as real.

Even for established tasks, individual differences in stress reactivity are large, so an adaptive stress response is typically defined as the most common or prototypic profile in normative populations [ 19 ]. Maladaptive or dysregulated stress is ascribed to an afflicted group creating a situation in which deviation from the control group is, de facto , interpreted as problematic: too high, too low, too flat, too variable, too coordinated, too specific. Tautological slippage between stressor and stress extends further when any profile that differs from the control group is, simply by being different, characterized as dysregulated. Such an approach fails to advance understanding of typical and atypical stress responses and resorts to ableist deficit models. This also magnifies a challenge for therapy and treatment efforts as the presumptive adaptive response is a return to “normal” per-se, instead of an adaptive allostatic response where physiological system setpoints “maintain stability through change” [ 20 ].

Rather than pit real stressors against nebulous stress perceptions, it is essential to differentiate stressor metrics from stress. Stressors—the inputs—must be defined according to the context and its affordances for minimizing risk and maximizing benefits. This definitive stance about inputs versus outputs is softened to acknowledge that it isn’t precisely clear where ecological inputs end and individual characteristics begin to shape stress responses [ 21 ]. A solution to the stress maladaptation quandary has been to extrapolate valenced stress reactivity using further downstream physiological outcomes that are well known to have adverse health consequences [ 22 ]; for example, high cortisol is “bad” if linked with cardiovascular disease. This alters stress reactivity metrics from outcomes to intermediaries [ 23 ]. This approach expands understanding of the diversity of stress-reactive processes, yet stays firmly on the stress side of the stressor-stress metrics and introduces practical challenges of measuring even more sluggish biomarkers. The converse—increasingly cognitive, emotion, or brain-based stress metrics—suffers the same causal flaws in that stress is not a stressor. Notwithstanding this blurred boundary, measures of stress do not become stressor measures.

White coat cardiologists and disciplinary diagnostics: challenges of challenging the system

Just as stress pioneers borrowed from engineering, there may be functional value in borrowing from psychiatry and medicine to understand the intersection of stress with mental health and physical wellbeing. Medical models measure dose; Perhaps stress scientists should as well. Pharmacological and behavioral treatment efforts require careful titration of a dose with desired ameliorative effects. Psychiatric decision-trees may be driven by outcome-based medicine, yet it is clear when a dose increases or decreases because the dose is measured . When those efforts fail and should be abandoned, new targeted treatments still necessitate dose management. Concerns about reverse causality—where the stress response determines stressor exposure—also apply here insofar as whatever treatment works is the best one and treatment failures are chalked up to individual (weaknesses) differences instead of mismatch between administration choice and dose-response. Medicinal scattershot approaches with little regard for treatment type, dose, and timing culminates with poorly justifiable treatment fits and starts that fail to iteratively reach an optimal benefit. Admittedly, this describes an oversimplified dystopian understanding of medical professions. The point is that the medical model is valuable in its insistence on measuring dose and response.

Uncovering the stressor dose needed to overwhelm regulatory resources is tantamount to advancing understanding of what and how much, in practice, manages to get under the skin. This may sound ethically dubious, but stressing systems to reveal weaknesses and targets for treatment is common throughout medicine. Consider the observation that cardiologists have implemented for decades: white coat hypertension shows that physiological systems operate fundamentally differently when stressed or at rest [ 24 ]. One approach to sussing out a stressed cardiovascular system is to measure biomarkers in ambulatory settings [ 25 ] and wait for naturalistic events to filter out day-to-day annoyances from the real vagaries of life. This approach can lead to novel insights about real-world stressors but can also produce spurious stressors: my heart rate is elevated, it must be the traffic. Acute stressor administration complements naturalistic ambulatory approaches because both learn what makes the heart tick by making it tick faster. Running a treadmill for its diagnostic value has been implemented for decades [ 26 ] and continues to reveal prognostic value especially for those with cardiovascular disease [ 27 ]. Importantly, in addition to being feasible in lab settings, challenges like treadmills measure the force needed to elicit cardiovascular effects which allows individual differences to be described in terms of both stressor dose and stress outcomes.

A corollary for mental health in which systems are challenged by acute stressors in the laboratory can be ethical and is needed. Unfortunately, current tools for administering psychosocial stressors are neither practical nor feasible in medical settings. “Real” physical environments are not necessary to evoke stress. For example, the Trier Social Stress Test (TSST) [ 15 ] helped reveal that Social Evaluative Threat was often the key ingredient for stressors [ 6 ]. The TSST requires judges to maintain still-face while participants perform a speech and math challenge [ 16 ]. While clipboards, stop-watches, and camera tripods may be real, the stress itself is evoked by a social and emotional representation for one’s confidence in becoming likable. The exact same physical space and built environmental cues do not evoke stress when the context is stripped of social and emotional consequences for poor performance [ 28 , 29 ]. Similarly, adding nonphysical yet salient performance cues enhances stress reactivity [ 30 ]. As another example, physical stressors such as the cold pressor test are largely effective due to Social Evaluative Threat [ 31 , 32 ]. This confluence of physical and psychosocial threats also plague white coat effects. While the name implies that medical fashion choices and the physical setting of a clinic are pivotal for heightened cardiovascular stress [ 33 , 34 ], the person wearing the white coat is key given that the white coat effect is larger in response to doctors than nurses [ 35 , 36 ]. While neither physical nor built, intangible contextual cues exert a very real impact on stress and health.

Mental health practitioners are in a catch-22. They need to stress patients with the equivalence of the cardiologist’s treadmill, but to do so requires exposing patients effectively to Social Evaluative Threat [ 37 ]. Eroding “real” personal relationships with a patient may be too high a cost for capturing a stressor’s dose in clinical settings. Feeling judged or disliked by clinicians and their staff could destroy hard-fought trust and rapport with care providers. Prioritizing trust and rapport undermines the stressor given that minimizing judgment or providing social support obliterates stress [ 28 , 29 ]. This observation undermined the potential for wide implementation of the cold pressor test in spite of clinical utility [ 38 ] and predictive value for understanding health [ 39 , 40 ]. Additional weaknesses further undermine clinical application of socially evaluative stressors, such as the impracticality for staffing 2+ judges for tasks, mitigating habituation, and minimizing non-completer or dropout rates when patients feel deceived. Psychiatrists need the cardiologist’s treadmill, but one that patients will actually use. Social Evaluative Threat administered for medical purposes should not be so real as to erode personal relationships and trust. VR stress reduction tasks can help eliminate white coat effects [ 41 ] and the opposite may also be true: VR stressors can practically induce the requisite Social Evaluative Threat without eroding patient trust [ 11 ].

Virtually real treatment: tools for translational psychiatry

VR has come a long way from its early roots in the 1990s where virtual exposure therapy was implemented to treat phobias [ 42 , 43 ] and PTSD [ 44 ]. This historical research established that patients could be treated in a safe environment and virtual stimuli could be carefully controlled. Older virtual environments (e.g., 1980–1990s) tasked users with simply observing phenomena around them. Technological limitations meant research was performed using basic simulators with limited graphics. This approach was justified because symptoms were easily triggered, so high fidelity immersive graphics were not necessary for the virtual environment to serve as a treatment tool. However, not all patients were easily triggered, so a large swath of individuals could not benefit from these tools.

Current VR systems now can create high-fidelity—even photorealistic—graphics across a large viewing angle. A wealth of research on user interaction and usability [ 45 , 46 , 47 ] have been accompanied by hardware and software advances resulting in readily available, low cost systems that a novice user can set up and maintain. Advancements in 3D graphics and rendering techniques such as custom developed shaders and per pixel lighting have generated enormous flexibility in achieving realistic visual fidelities. Spatial audio allows a second sensory modality to be easily incorporated to create stimuli for a wider range of conditions and treatments [ 48 ]. The proliferation of readily available digital assets from model libraries simplifies populating virtual environments. Along with increased visual realism, enhanced interaction with a virtual environment permits greater control and immersion. Now, low cost controllers allow precise interaction with digital assets within a single virtual environment. Lastly, high fidelity graphics are provided with commodity hardware (e.g., head mounted displays—HMDs, monitors, and televisions). All of these advances come with counter-intuitive benefits of reduced cost and ease of use. Thus, it is practical to integrate VR as a treatment tool in point of care and at-home settings for a range of disorders to a much broader base of patients.

As VR became more feasible, cost-effective, flexible, and with greater hardware and software capabilities so too did the range of treatment applications in psychiatry [ 49 , 50 , 51 ]. To understand fear and phobias, studies exposed patients to virtual stimuli that were designed towards specific stressors and fears [ 52 ], such as spiders for arachnophobes [ 53 , 54 ], or combat scenarios in military veterans [ 55 , 56 ]. These studies reveal stress biomarkers that can reflect stressor intensity and behavioral propensities towards approach and avoidance of fear-inducing stimuli. VR tasks have also been designed for stress resistant or labile groups with the intent to induce threat, fear, and/or stress [ 57 , 58 ]. This work has shown, for example, that VR stressors can differentiate when antisocial behavior is comorbid with anxiety [ 59 , 60 ] compared to callous/unemotional individuals [ 61 , 62 ]. This latter observation is important because it is difficult to predict who will cope well with stressors and behave or perform optimally under challenging circumstances [ 63 ]. There may be diagnostic benefits for VR-based stressors that are not designed to treat or ameliorate symptoms.

Appropriating a medical model has been successful in prior VR-oriented studies that found heightened recovery across a multitude of stress biomarkers when participants relax after a stressor using, for example, virtual multisensory biodiverse nature simulations [ 64 , 65 , 66 , 67 , 68 ]. VR-based biofeedback has also proven to be engaging, therapeutically beneficial, and capable of titrating stress biomarkers [ 69 , 70 ]. Stress reduction interventions, largely meditation, have also shown beneficial mental and physiological effects [ 71 , 72 , 73 ]. Looking specifically towards psychiatric conditions, meta-analytic and systematic reviews have consistently revealed VR-based treatment efforts outperform waitlisted or no treatment and that VR was not less efficacious than “real” therapy. This pattern has been revealed across anxiety disorders [ 74 , 75 ], including public speaking [ 76 ], phobia [ 77 ], and PTSD [ 78 , 79 ], as well as depression [ 80 ], eating disorders [ 81 ], autism [ 82 ], and ADHD [ 83 ]. Systematic reviews [ 84 ] and individual studies [ 85 , 86 , 87 ] have shown that stress biomarkers can reflect these therapeutic benefits of VR. This research is important for showing that VR is sufficiently real to shift symptoms towards improved mental health, physical wellbeing, and stress physiology. Treatment tools could be argued to measure VR-dose with respect to quality, duration, and number of sessions needed to shift symptoms.

Even with these advancements, drawbacks to VR as a treatment tool persist [ 88 , 89 ]. One of the biggest is physical discomfort from physiological and technical sources. Motion sickness can be induced from a low frame-rate and too much switching between near and far field views in an environment. Triggered by a mismatch with one’s vestibular system, even a well-tuned virtual environment evokes motion sickness and nausea for many users. Another technical drawback is still the size of most HMDs. Size and weight have been tremendously reduced, but many users still find HMDs uncomfortable, hot, and sweaty—especially women and youth [ 90 , 91 ]. Few HMDs fit well for people with glasses [ 92 , 93 ]. While these discomforts seemingly enhance a stressor’s efficacy, in practice, drawbacks come at too large of a cost when participants break immersion or terminate a VR study.

Stressing immersion: lessons from engineering

Tackling virtual environments led to an intermediate conclusion that is deceptively simple but critically missing. To advance understanding of what works as a stressor, it is necessary to measure the stressor. Terminology from the engineering disciplines is borrowed, specifically VR researchers, to measure a stressor’s force. Immersion refers to an environment’s potential for total engrossment [ 94 ], often framed as the external context itself. Immersion can be viewed as analogous to the stressor. Several thematic elements have been identified that influence immersion [ 11 ]. Place illusion can be enhanced with technology that makes participants feel they are present in a space [ 94 ]. Environments are programmed with sufficient sensory fidelity to create audiovisually coherent, three-dimensional, stereophonic settings [ 95 ]. Additional sensorimotor modalities enhance place illusion, such as through smell [ 66 ] or touch [ 96 ]. Visual suppression of physical stimuli enhances place illusion by blocking out “real” stimuli [ 94 , 97 ]. Interface capabilities involve sensory stimulation and movement tracking for seamless sensory processes [ 97 , 98 ]. Virtual body ownership underlies a multisensory experience to create the illusion that foreign objects like game controllers are part of their body [ 94 ]. Body ownership is aided by first-person perspectives and self-representation [ 99 , 100 ], as well as synchronized sensory coordination that matches proprioceptive feedback from body movements with minimal lag between motor actions and system response [ 98 ]. Prediction and control requires consistency in the environment physics mechanisms (e.g., gravity, motion) as well as links to rewards or punishments [ 101 ]. Plausibility is the illusion that events in the virtual environment are really happening [ 102 ]. Plausibility is centered around the dynamics of events and situations—narrative, flow, and contingencies [ 103 ]. Immersion can be increased using ecologically valid tasks that involve environments and characters with high visual and interactive fidelity, close matching between the virtual environment and the user’s perceptual experience, and with cultural validity. Thematic elements illustrate the degree to which the user is a determining factor of immersion: including computer hardware with better haptic feedback enhances virtual body ownership without requiring mental gymnastics to validate the experience, whereas plausibility of a storyline requires a more attentive shared mental representation of what is deemed plausible.

Little consideration has been devoted towards deeply quantifying or measuring immersive elements. Hardware specifications (e.g., display resolution) measures aspects of immersion, but lack the ability to quantify more liminal context, such as plausibility and place illusion. Conversely, defining immersion solely as a psychological concept is confounded by individual responses. Like muddling stress and stressor, this practice has reinforced the dichotomy that immersion is either an objective system-oriented (e.g., audiovisual fidelity) [ 94 ] or psychological concept (e.g., subjective perception of being immersed, ratings of imagination use and flow) [ 104 ]. Updates must be made to traditional immersion metrics to reflect a spectrum across liminal space between mental and physical environments which are independent of an individual’s evaluation and response to the environment. In other words, the context required for an immersive dose may not stop at the physical realm, but also extend into the conceptual realm, insofar as it does not become a response . Mental health practitioners may benefit from immersive design and measurement that give credence to imagined or anticipated threats as being very real.

Tautological quandary: unpack the presence

Extant theory takes an important step towards measuring immersion, but falters in the same tautological quandary as stress(ors). The Sensory, Challenge-based and Imaginative immersion (SCI) model [ 95 ] describes mental processes involved in gameplay in a way that includes desires, anticipations and previous experiences, as well as interpretations/reflections of the experience. Self-representation, sensory fidelity and other SCI components highlight contextual cues but in many ways recapitulates a hardware-oriented focus on immersion. The SCI questionnaire goes on to span system-oriented and psychological immersion metrics. Unfortunately, this blurs the environment and the response to that environment. While an integral component of virtual and real environments alike and despite its name, psychological immersion, imagination, and flow are not immersion metrics. To unpack this tautological quandary where the environment’s immersion is influenced by psychological engagement, engineering disciplines have coined a term analogous to appraisals of stress. Presence involves the individual’s evaluation and response to the environment including perceptual and consequential illusion of “being there” [ 104 , 105 ]. Individual differences in presence are measured via self-report and can arguably extend to other quality metrics such as biomarkers.

Like stress, presence reflects how much “environment” has gotten “under the skin and skull”. Engineering disciplines differentiate between objective contexts compared to mental representations of what people know and how they perceive the real world around them via presence. Technologies along the virtual continuum rely on the degree to which an individual’s mental representations or mental model for how reality “works” seamlessly to integrate with a virtual environment. Mental models provide predictive and explanatory power of how the user expects the external world to behave; these are continuously updated with observations of how the world is actually behaving [ 106 ]. A summation of presence scores across individuals may help quantify immersion and validate tasks, though more is needed. Measuring presence is important, but does not replace the urgent need to design and quantify immersion.

Through these themes and the SCI model, VR research has uncovered environment-perceptual relationships to help design and measure immersive environments (Fig. 1 ). A combination of immersive elements with varying dosage levels encompass immersion , which then presence validates through mental models and mental representations to assess alignment with user expectations. The application of the spectrum for VR requires (1) technical hardware specifications and system capabilities that enable sensory-motor inputs from users, (2) environment functions programed within the software that map the virtual environment to the system sensory-motor inputs, (3) consistent environment quality/features including rules and constraints that add validity and plausibility, followed by (4) a internal process involving perception of the stimuli, salience, and affordances to assess presence.

From left, sensorimotor contingencies are involved with immersion and as the continuum becomes more conceptual, mental models and representations involve presence (at right).

Methods to determine dosage of immersion need further research, but several insights can be gained for medical practitioners. The number and quality of sensory modalities can enhance immersion of “real” and virtual environments alike. This clearly benefits VR studies, and adds immersion criteria to real environments as well. Place illusion can be enhanced in real-world stressors by eliminating distractions like wall-art, windows, and background music as well as providing audio and visual cues that draw attention to stressor elements. For example, our previous study asked participants to stand on a small stage with dimmed background lighting combined with directed LED lights to ensure attention to TSST judges [ 30 ]. Self-representation (Body ownership) has bearing with real-world stressors, for example, when personalized performance feedback works better than canned feedback such as when the MIST shifts math equations to optimize error rates for that individual [ 107 ], or when coded performance feedback heightens stress [ 108 ]. Plausibility is familiar to psychological sciences in studies that require deception [ 109 ]. We have anecdotally reported that VR can enhance real-world Social Evaluative Threat when virtual dance judgments were projected onto real research assistants [ 9 ]. Plausibility or believability in VR may outperform real-world tasks. For example, Guldager and colleagues [ 110 ] used a virtual party simulation because a teen avatar is far more immersive than adult researchers role-playing promiscuous advances and flirtatious offers for drugs and alcohol [ 111 , 112 ].

Back to the future directions

Virtual reality now has decades of supportive research. This establishes VR as a useful tool yet also tarnishes the glitz if solely used to enhance appeal. This creates a pivotal moment for VR stressor research as there is enough historical precedence to validate its utility while still opening opportunities to address novel research directions that leverage technological advancements.

First, there is a clear need for stressor immersion measurement across real and virtual settings. By shifting from a binary focus about whether the environment is real or not, a continuum of immersion allows stimuli to vary in quality and quantity that can be empirically probed long before secondary validation with stress biomarkers. Gamified immersion can and should be augmented with transdisciplinary insights about stress(ors) to identify expectations for human and nonhuman research [ 5 , 6 ]. Indexing stressors solely on their stress outputs obfuscates whether sources of individual variation stem from the person, their context, or a mix of both. This risks missing both the dose of a stressor and the titration of the stress response to that dose. It also renders decisions about adaptive or typical responsivity to be a mere judgment call. Achieving measurement goals will help solidify insights about stress postulated since Selye first appropriated the term from engineering.

Second, anchoring stressor design in technology like VR offers several clear avenues for growth. It is feasible to integrate performance consequences in real-time and within task design. This has proven beneficial for stressors like the MIST [ 113 ] and MAST [ 114 ] as well as real world tasks that evoke frustration through provocation [ 115 ]. With VR-based stressors, performance feedback can extend beyond audiovisual modalities to include sensory modalities like haptics. Feedback can be adaptive, based on performance, physiological signals, or real-time cues. This has proven feasible in biofeedback work [ 69 ]. Electronic feedback can be participant driven which bypasses a need for conscious appraisal of stress intensity [ 43 , 116 , 117 ]. Precise behavioral measures can also take place during real-world stressors which is still emerging technology [ 118 ].

Third, VR stressors have largely been designed to recapitulate real-world tasks like the TSST [ 119 ]. This makes intuitive sense as it naturally extends knowledge about stressors in the built environment to virtual settings. Nevertheless, VR is not limited with the same plausibility constraints. Like with other media, impossible scenarios like flying or falling can be simulated [ 120 , 121 , 122 ] and such interactions can be titrated to individual’s fears and phobias [ 52 ]. Scenarios with impossible yet plausible threats can be immersive without implying that creatures such as aliens, vampires, zombies, or dementors exist. Combat scenarios do not require real war to evoke stress [ 55 , 56 ]. We [ 1 ] and others [ 123 , 124 , 125 , 126 ] have designed VR-stressors to mirror physical threats most common in animal research. This improves the match with translational works that often evokes stress using extrinsic morbidity/mortality cues (e.g., open field; elevated plus maze).

Fourth, it is possible for VR to enhance stressors that largely rely on physical challenge. Inclusion of multiple sensorimotor modalities enhance immersion. VR haptics have been shown to enhance stress reduction, for example, by allowing participants to “feel the breeze” or “touch the grass” [ 71 , 127 ]. Most psychosocial stressors prioritize audiovisual modalities or use haptic enhancements secondary to audiovisual place illusion [ 8 , 128 , 129 ]. Augmenting VR with additional sensorimotor modalities can enhance stressor immersion [ 130 ] when, for example, firefighting simulations include heat, weight, smell, and wearing gear [ 131 ] or emotion engagement is heightened with vibrotactile actuation [ 132 , 133 ]. Haptic feedback is generally thought to enhance VR simulations by adding the number and quality of sensory modalities [ 134 ]. VR likewise helps create immersive place illusion by blocking “real” distracting audiovisual information. Rather than posit that VR stressors are enhanced by haptic feedback, it is possible for physical challenges to be augmented through audiovisual stimuli [ 135 , 136 ] delivered via VR. For example, the cold pressor task may be more immersive in an icy, treacherous river, or the cardiologist’s treadmill may be psychosocially stressful if it involves running from predators.

Lastly, biofeedback systems can be augmented with adaptive systems to enhance dosage management. Biofeedback involves shifting contextual cues, often virtual, based on some biomarker like heart rate. This creates a static feedback loop between context and biosignal where the biomarker increasingly stabilizes [ 137 ]. Immersion measurement with changing contextual cues helps identify where an individual setpoint for stress is established and maintained. Going one step further involves “moving the needle” for stressor-stress administration. VR introduces the potential to evoke higher levels of stress through user or clinician directed authority over feedback information. Whereas traditional biofeedback is fixed at the system design stage, with constrained flexibility for simulated event-based scenarios, adaptive systems eliminate such limits. Adaptive systems shift their behavior to meet the user’s needs without explicit instruction [ 138 ], autonomously changing the stressor’s dosage of the virtual environment for stress inoculation or stress management. The result is personalized physiological detection of stress with the ability to change the virtual stressor’s function, scheduling, interaction style, and/or content. In practice, this enables users to be gradually exposed to increasing levels of stressors while developing coping and regulation skills, following the guidelines of Stress Inoculation Training [ 139 ] and Stress Exposure Training. [ 140 , 141 ] We have previously designed and demonstrated a real-time adaptive VR stress training system to build resilience in healthy individuals [ 142 ]. Others have proposed adaptive systems for psychotherapy [ 143 ]. More work needs to be done validating adaptive systems for clinical use, yet these systems may also be beneficial in the future for managing levels of user immersion as immersive element dosage levels are honed.

Stress research burgeoned when clearly delineated biomarkers were shown to be reliable measurement tools of the magnitude and diversity of stress responses. This corpus of work has been able to show that stress is a key transdiagnostic risk factor for many mental and physical health problems. Stressed physiological systems are not synonymous with basal or at-rest states [ 20 ] so it is imperative for clinically-oriented works to ethically stress physiological systems. To do so requires adequate measurement of the stressor and its dose. In addition to having the scientific appeal for being “the next big thing,” Virtual reality based stressors also hold the potential for addressing an old yet largely unaddressed challenge about stressors: just how much was it?

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EAS contributed to conceptualization, writing, reviewing and editing, investigation, visualization, supervision, and project administration. TTF contributed to conceptualization, writing, reviewing and editing, investigation, and visualization. EHW, DCG, RAC, and SSD contributed to conceptualization, writing—original draft preparation; writing—reviewing and editing, investigation.

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Shirtcliff, E.A., Finseth, T.T., Winer, E.H. et al. Virtual stressors with real impact: what virtual reality-based biobehavioral research can teach us about typical and atypical stress responsivity. Transl Psychiatry 14 , 441 (2024). https://doi.org/10.1038/s41398-024-03129-x

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DOI : https://doi.org/10.1038/s41398-024-03129-x

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Stress Research: Past, Present, and Future

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First Online: 18 October 2022
pp 2717–2748
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E. Ronald de Kloet 4 &
Marian Joëls 5 , 6

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This chapter starts with highlighting the evolution of the stress concept and the discovery of mediators that coordinate stress adaptation. Next, progress in the unraveling of the mechanism underlying the action of these stress mediators is discussed, focusing on glucocorticoids as the end product of the hypothalamus-pituitary-adrenal (HPA) axis. This action exerted by the glucocorticoids is mediated by a dual receptor system: mineralocorticoid (MR) and glucocorticoid receptors (GR). With these receptors as leading theme we present five highlights that illustrate the serendipitous nature of stress research. These five highlights are integrated in the final section which culminates in reflections on the role of stress in mental health. In these reflections we merge the mind-boggling complexity of molecular signaling pathways with neuroendocrine communication, integrating body and brain functions. The new insights will be used during the next decennium to target, in an individual-specific fashion, the stress system with the objective to enhance the quality of life.

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The Anatomy and Physiology of the Human Stress Response

Abbreviations.

5-Hydroxytryptamine = serotonin

Serotonin transporter

Adrenocorticotropic hormone

Adrenalectomy

Apomorphine-susceptible

Corticosterone

Basolateral amygdala

Corticotropin releasing hormone

Dexamethasone

Extracellular regulated kinase 1/2

Glucocorticoid receptor

Hypothalamic-Pituitary-Adrenal axis

Long-term potentiation

Multidrug resistance

Miniature excitatory postsynaptic current

Mineralocorticoid receptor

Pro-opiomelanocortin

Prepulse inhibition

Paraventricular nucleus

Stress hyporesponsive period

Single nucleotide polymorphism

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Department of Medicine, Division of Endocrinology, Leiden University Medical Center, Leiden, The Netherlands

E. Ronald de Kloet

Department of Neuroscience and Pharmacology, University Medical Center Utrecht Rudolf Magnus Institute of Neuroscience, Utrecht, The Netherlands

Marian Joëls

University of Groningen, University Medical Center Groningen, Groningen, The Netherlands

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Laboratory of Neurobiology and Behavior, The Rockefeller University, New York, NY, USA

Donald W. Pfaff

National Institute on Drug Abuse, Rockville, MD, USA

Nora D. Volkow

Department of Psychiatry, University of California, San Francisco, San Francisco, CA, USA

John L. Rubenstein

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de Kloet, E.R., Joëls, M. (2022). Stress Research: Past, Present, and Future. In: Pfaff, D.W., Volkow, N.D., Rubenstein, J.L. (eds) Neuroscience in the 21st Century. Springer, Cham. https://doi.org/10.1007/978-3-030-88832-9_72

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