The effects of acute stress and stress hormones on social cognition and behavior: Current state of research and future directions


  • 1 Department of Biological and Clinical Psychology, University of Trier, Germany.
  • 2 Department of Biological and Clinical Psychology, University of Trier, Germany. Electronic address: [email protected].
  • PMID: 33301780
  • DOI: 10.1016/j.neubiorev.2020.11.026

Stress encompasses profound psychological and physiological changes that are observable on all levels, from cellular mechanisms, humoral changes, and brain activation to subjective experience and behavior. While the impact of stress on health has already been studied for decades, a more recent field of research has revealed effects of stress on human social cognition and behavior. Initial studies have attempted to elucidate the underlying biological mechanisms of these stress-induced effects by measuring physiological responses or by using pharmacological approaches. We provide an overview of the current state of research on the effects of acute stress induction or pharmacological manipulations of stress-related neuro circuitry on social cognition and behavior. Additionally, we discuss the methodological challenges that need to be addressed in order to gain further insight into this important research topic and facilitate replicability of results. Future directions may help to disentangle the complex interplay of psychological and biological stress variables and their effects on social cognition and behavior on health and in disorders with social deficits.

Keywords: Acute psychosocial stress; Adrenergic receptors; Catecholamines; Cortisol; Hydrocortisone; Hypothalamus-pituitary-adrenal axis; Social behavior; Social cognition; Trier social stress test.

Copyright © 2020 Elsevier Ltd. All rights reserved.

Publication types

  • Research Support, Non-U.S. Gov't
  • Hydrocortisone
  • Hypothalamo-Hypophyseal System
  • Pituitary-Adrenal System*
  • Social Cognition*
  • Stress, Psychological

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Research Article

Acute social and physical stress interact to influence social behavior: The role of social anxiety

Roles Conceptualization, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Supervision, Validation, Visualization, Writing – original draft, Writing – review & editing

* E-mail: [email protected]

Affiliations Department of Psychology, Laboratory for Biological and Personality Psychology, University of Freiburg, Freiburg, Germany, Department of Psychology, Biological and Clinical Psychology, University of Trier, Trier, Germany

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Roles Project administration, Writing – review & editing

Affiliation Department of Psychology, Laboratory for Biological and Personality Psychology, University of Freiburg, Freiburg, Germany

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

Affiliation Department of Psychology, Biological Psychology, Technical University of Dresden, Dresden, Germany

Affiliations Department of Economics, Applied Research in Economics, University of Konstanz, Konstanz, Germany, Thurgau Institute of Economics, Kreuzlingen, Switzerland

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

  • Bernadette von Dawans, 
  • Amalie Trueg, 
  • Clemens Kirschbaum, 
  • Urs Fischbacher, 
  • Markus Heinrichs


  • Published: October 25, 2018
  • Reader Comments

Fig 1

Stress is proven to have detrimental effects on physical and mental health. Due to different tasks and study designs, the direct consequences of acute stress have been found to be wide-reaching: while some studies report prosocial effects, others report increases in antisocial behavior, still others report no effect. To control for specific effects of different stressors and to consider the role of social anxiety in stress-related social behavior, we investigated the effects of social versus physical stress on behavior in male participants possessing different levels of social anxiety. In a randomized, controlled two by two design we investigated the impact of social and physical stress on behavior in healthy young men. We found significant influences on various subjective increases in stress by physical and social stress, but no interaction effect. Cortisol was significantly increased by physical stress, and the heart rate was modulated by physical and social stress as well as their combination. Social anxiety modulated the subjective stress response but not the cortisol or heart rate response. With respect to behavior, our results show that social and physical stress interacted to modulate trust, trustworthiness, and sharing. While social stress and physical stress alone reduced prosocial behavior, a combination of the two stressor modalities could restore prosociality. Social stress alone reduced nonsocial risk behavior regardless of physical stress. Social anxiety was associated with higher subjective stress responses and higher levels of trust. As a consequence, future studies will need to investigate further various stressors and clarify their effects on social behavior in health and social anxiety disorders.

Citation: von Dawans B, Trueg A, Kirschbaum C, Fischbacher U, Heinrichs M (2018) Acute social and physical stress interact to influence social behavior: The role of social anxiety. PLoS ONE 13(10): e0204665.

Editor: Alexandra Kavushansky, Technion Israel Institute of Technology, ISRAEL

Received: March 28, 2018; Accepted: September 12, 2018; Published: October 25, 2018

Copyright: © 2018 von Dawans 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.

Data Availability: All relevant data are within the paper and its Supporting Information files.

Funding: This research was supported by a research grant from the German Research Foundation (DFG DA1416/2) to Bernadette von Dawans and Markus Heinrichs. The funders had no 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.


Chronic stress reduces wellbeing, exacerbates mental disorders, and can be a significant risk factor for several diseases [ 1 – 3 ]. The stress response comprises several psycho-biological levels or parameters. These psycho-physiological adaptations help the organism adjust to environmental demands that may require increases in blood sugar or other metabolic alterations. These metabolic changes ensure the maintenance of homeostasis in the body [ 1 ]. The hypothalamus pituitary axis (HPA) with salivary cortisol as its most prominent marker, the sympathetic adrenomedullary system (SAM) (e.g heart rate), as well as the subjective psychological stress response measured via questionnaire represent important branches and variables of the stress response that should be captured in state-of-the-art research. While these axes are characterized by various complex feedback mechanisms and interactions, they may also respond quite independently, meaning that increases in one stress system do not necessarily lead to the same increases in all other stress systems—evident in the largely weak correlations between psychological and physiological stress responses [ 4 ]. It is the type of stressor that seems to modulate the three stress-response dimensions, with social evaluation being the key feature driving the cortisol stress response [ 5 , 6 ]. Moreover, several ‘features’ of the subject itself mediate the effectiveness of stressors regarding their varying levels of stress response. Gender, the menstrual cycle phase, or oral contraceptives, age or body weight [ 7 , 8 ] but also psychological variables such as personality traits or different psychopathological symptoms have exhibited an influence on all three stress levels [ 9 – 13 ]. One important situational variable affecting the stress response is ‘social evaluation’ [ 5 ]. This effect is dependent on one`s subjective appraisal and personal experiences, and is closely associated with social anxiety. Social evaluation is the feature of the TSST [ 14 ] or the Socially Evaluated Cold Pressor Test (SECPT) [ 6 ] that characterizes these paradigms as ‘social’ stress paradigms compared to non-social, physical stress paradigms like the Cold Pressor Test (CPT) [ 15 ], which lacks a social component. Manifold concepts from different decades and fields of sciences reveal the diversity of the concept ‘stress’ [ 16 – 20 ]. They attempt to provide a framework of mechanistic physiological action and behavioral consequences of stress. Although the fight-or-flight concept [ 21 , 22 ] represents for acute stress the dominant theoretical framework in both animal and human stress research, recent studies provide evidence that acute stressors can also lead to an increase in prosocial behavior [ 23 – 28 ]. They are derived from a theory called the tend-and-befriend concept [ 29 , 30 ]. The latter introduced the neuropeptide oxytocin and opioids as being involved in stress regulation and in the behavioral consequences of the stress response that may be affiliatory. These concepts highlight the diversity of behavioral findings in stress research, and reveal the ambiguity of research on the effects of stress on behavior. There is evidence supporting the fight-or-flight response to stress: e.g. Steinbeis and colleagues [ 31 ] report stressed participants as being less trusting. There is evidence that stress leads to less antisocial risk aversion in healthy subjects [ 32 ], and that stress reduced donations to a charitable organization [ 33 ]. With regard to moral decision-making, one study revealed no group differences between the stress and control group, but documented a positive correlation between the cortisol responses and egoistic decision-making in emotional dilemmas [ 34 ]. On the other hand, there are studies supporting the tend-and-befriend reaction to stress entailing higher levels of trust, trustworthiness, or sharing after acute stress [ 27 ], studies linking stress reactivity to better social cognition (already implying gender differences) [ 25 , 26 , 28 ], and studies indicating an association among stress induction, cortisol increase, and prosocial or affiliatory behaviors [ 23 , 35 ]. In the context of moral decision-making, a recent study reported higher levels of altruistic decisions in the stress than the control group [ 36 ].

Whether acute stress leads to prosocial, antisocial, or risky behavior depends upon various situational aspects, the kind of stressor, and the individual [ 24 , 33 , 37 , 38 ]. Several aspects of the study design (e.g. situational factors, the time gap between stressor and dependent variables) are known to be relevant [ 33 , 38 ] but the kind of stressor (social vs. nonsocial) has not been investigated yet. Individual differences also contribute to variations in stress reactivity per se [ 39 ] and may also modulate the behavioral consequences of stress; in particular, social anxiety may be a key factor in understanding the behavioral responses to acute stress exposure [ 40 – 45 ]. As social behavior itself is modulated by the social-anxiety trait [ 43 , 46 , 47 ], and the fear of social evaluation is the key problem associated with social anxiety, we set out to disentangle the effects of standardized physical versus social stress and the impact of social anxiety on social decision-making. Are the effects of acute stress on social decision-making mediated by the social aspects (social evaluation) of acute stress? Does social anxiety influence the effects of stress on behavior? We hypothesized that only social stress would increase prosocial behavior, and that this effect would be moderated by the level of social anxiety, i.e. participants presenting lower levels of social anxiety should exhibit increased prosocial behavior following acute psychosocial stress exposure, while participants with higher levels of social anxiety would not reveal an increase in prosocial behavior.


Online and telephone interviews were used to exclude potential participants who were not fluent in the German language, had acute or chronic psychiatric or medical illness, were taking prescription medication, worked the night shift, abused drugs or alcohol, or smoked more than five cigarettes per day. Potential participants completed the Social Interaction Anxiety Scale (SIAS) [ 48 ] online prior to the experiment and were stratified into four groups to ensure a normal distribution of social anxiety symptoms in each of four experimental groups. Depending on their score in the SIAS, participants were included as low (score of 0–23) or highly (score of > 23) socially anxious, in order to ensure an equal distribution of social anxiety among the experimental groups. An SIAS-score of 24 was chosen as an optimal point for differentiation in high and low social anxiety, based on Stangier et al. [ 28 ]. High and low socially anxious participants were then randomly assigned to the four experimental groups: warm water test (WWT: no social stress and no physical stress, N = 31), socially-evaluated warm water test (SEWWT: social stress but no physical stress, N = 34), cold pressor test (CPT: no social stress but physical stress, N = 44), and socially evaluated cold pressor test (SECPT: social stress and physical stress, N = 47). We decided to test more participants in the physical stress conditions according to the reported non-responder rates [ 6 ]. Moreover, participants needed to be naïve to the stress protocols employed (see Physical and social stress induction ) and similar stress paradigms (Trier Social Stress Test (TSST) and the TSST-G (group version); [ 14 , 49 ]. Participants could not be students of psychology or economics and had to be unfamiliar with other participants and the experimenters. An exclusively male sample was recruited in order to circumvent the previously-reported modulatory effects of female menstrual cycle on the psychobiological stress response [ 7 ] as well as the effects of gender in social interaction paradigms [ 50 , 51 ]. As we regard the cortisol stress response as a prerequisite reflecting a robust physical stress response, we only included participants from our cold pressor and socially evaluated cold pressor task who revealed a minimum increase of 2 nmol/l (for details see [ 6 ]). Four out of the originally 156 healthy men between 18 and 40 years of age were outliers (+/- 2 SD) in social anxiety symptoms and therefore excluded from our analyses. Hence, those participants we screened and randomized to the four experimental groups are called target participants . They received 20€ for participating in the study and additional earnings from the social interaction task (mean = 5.59€, SD = 0.80€). The study was approved by the institutional review board of the University of Freiburg, Germany. A second group of participants was recruited as interaction partners for the target participants. This second group was involved only in the interaction games.

Psychometric measures

We used the German version of the Social Interaction Anxiety Scale (SIAS) [ 48 , 52 ] to assess individual levels of social anxiety. This scale has 20 items rated on a 4 point Likert scale from 0 (not at all) to four (extremely). The items refer to situations feared by those with high social anxiety, eg, “I have difficulty making eye contact with others” or “I am nervous mixing with people I don’t know well”. The scale has good internal consistency with Cronbachs α between .88 and .93 and a sum score between 0 and 80. The German version of the Beck Depression Inventory (BDI) [ 53 ] was used to assess depressive symptoms in the participants with Cronbachs α ranging between 0.89 and 0.93 [ 54 ]. This standard scale assesses the cognitive affective and somatic aspects of depressive symptomatology on a 21-item scale. With the Wortschatztest with Cronbachs α = 0.94 we measured a proxy of verbal intelligence (verbal IQ) in our target participants [ 55 ]. The questionnaires were filled out online before the experiment via the platform Qualtrics.

Physical and social stress induction

To compare biobehavioral responses to socio-evaluative and physical stress, we used standardized laboratory paradigms. Social evaluation (control condition: no evaluation) has been repeatedly shown to induce psycho-physiological stress responses in humans and is one core feature of the Trier Social Stress Test [ 14 , 49 ]. Cold water at a temperature of 0–4°C (control condition: warm water) has been used as a physical stressor since the 1970s [ 15 ]. Our study design thus consisted of four conditions: warm water test (WWT: no social and no physical stress), socially-evaluated warm water test (SEWWT: social evaluation but no physical stress), cold pressor test (CPT: no social stress but physical stress) and socially-evaluated cold pressor test (SECPT: social stress and physical stress). Schwabe and colleagues [ 6 ] designed these conditions recently adapted to accommodate the group setting [ 56 ]. We tested participants in groups of four to six individuals. We chose this group size in order to investigate social interaction paradigms that we already tested with the TSST-G procedure originally set up for groups of six participants [ 6 , 56 ]. We decided to test groups containing four to six people since the group size itself might affect the stress response and social interaction [ 49 , 57 ]. Participants were separated by mobile walls and were not able to interact or evaluate each other. In detail, in the physical stress condition participants were instructed to immerse their non-dominant hand in 0–4°C water (warm water condition: 37–40°C). They were told to keep their hand in the water as long as possible. After 3 minutes they were instructed to remove their hand. In the social-evaluation condition, participants were told they would be videotaped and that their facial expressions would be analyzed in these recordings; the two experimenters wore white coats and observed the participants constantly (no social evaluation: the experimenters wore no white coats, did not observe the participants, and there were no video cameras).

Social and nonsocial decision paradigms

To disentangle the effects of social versus physical stress on social behavior, we used a social decision-making task previously described in the context of stress exposure [ 27 ]. A set of decisions was used to study prosocial behavior (trust, trustworthiness, sharing; four decisions each), aggressive behavior (punishment; four decisions), and nonsocial risk behavior (8 decisions). Fig 1 shows one variant of each paradigm (see S1 Fig , supporting information (SI) for detailed parameters). Target participants interacted anonymously with interaction partners that did not take part in the social or physical stress conditions and were invited to the lab separately. Each decision was a binary choice (eg, trust vs. no trust, trustworthiness vs. no trustworthiness).


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The target participant is presented by a red P, participant’s interaction partner is represented by black IP, respectively (interaction partners were not in any of the social or physical stress conditions). The red value indicates the outcome for the target participant, the black value the outcome for the interaction partner. In the nonsocial risk game a die was rolled to determine the outcome.

The trust game and trustworthiness game were sequential two player games. The player with the first move could choose to trust or not to trust. If the first player trusted, a higher number of points could be gained depending on whether the second player was trustworthy or not. The subjects played four variants of the game as player with the first move (trust) and four variants thereof as player with the second move (trustworthiness). The second player had to decide whether to be trustworthy or not before he being informed about the first mover choice, which is called the strategy method.

The punishment game was again a sequential two-player game. The interaction partner always had the first move, and he could decide how to distribute 50 MU. He could either choose a fair or a given unfair distribution. If he chose the fair offer, there was no further choice. But if he chose the unfair offer, the target participant could either accept the offer or punish the interaction partner by refusing the offer. In the latter case, both players received 0 MU. We applied the strategy method again: the target participants decided whether to reject the unfair offer before knowing if that was the offer the first player chose.

In the sharing game , the target participant could either receive an amount for himself (leaving nothing for the interaction partner) or share the sum. There was no opportunity for the interaction partner to influence the outcome.

In the nonsocial risk game , the target participant played alone. In each of the eight rounds, he could choose between a low-risk gamble or a highly risky one. Next, the participant rolled a die to determine the outcome of the chosen gamble: Rolling a 1, 2, or 3 resulted in the higher outcome, whereas rolling a 4, 5, or 6 resulted in the lower outcome. Each participant played each variant once. The games were played in two sets. Each set involved a total of 12 decision rounds—6 were prosocial (2 rounds of the trust game, 2 of the trustworthiness game, and 2 of the sharing game), 2 were antisocial (punishment game), and 4 were nonsocial (nonsocial risk game)—and each round had a different payoff. To ensure that all decisions were made under acute psychosocial stress or under the effects of a control condition, we had target participants complete the first set of decisions immediately after the first stressor (or control condition) and the second set of decisions immediately after the second stressor (or control condition) (see Procedure). The set order was randomized. One example of each paradigm is shown in Fig 1 .

The number of decisions reflecting trust, trustworthiness, sharing, or punishment was counted. Thus, for these measures, the maximum score was 4, and the minimum score 0. For the nonsocial risk game, 1 point was given for each decision favoring the risky gamble, which resulted in a minimum of 0 and maximum of 8. Monetary units earned from all decisions were disbursed after the experiment according to the following exchange ratio: 100 MU = 0.95€. The experiment was programmed and conducted with z-Tree software [ 58 ]. The Online Recruitment System for Economic Experiments (ORSEE) was used for recruiting and scheduling the group experiment sessions the [ 59 ].

Psychological stress response

Psychological stress was measured with visual analogue scales [ 27 ]. Participants rated their level of stress, tension, physical symptoms, unpleasantness and pain at baseline (0 referring to the stressor’s onset), after the first and second parts of the decision paradigm, and +50 min after the second decision paradigm, respectively. We calculated one maximum increase value per subject from baseline to enable one dependent increase measure for each of the subjective ratings.

Endocrine and autonomic stress response

We measured the cortisol stress response using a commercially available sampling device (salivette; Sarstedt, Nümbrecht-Rommelsdorf, Germany) eight times over the course of the experiment: at baseline (0 referring to the stressor’s onset), after the first part of the decision paradigm, after the second part of the decision paradigm, +10 min, +20 min, +35 min, +50 min, and +65 min relative to end of the decision paradigm. After each experimental session, samples were stored at -20°C. For biochemical analyses of free cortisol concentration, saliva samples were thawed and spun at 3000 rpm for 10 min to obtain 0.5–1.0 ml clear saliva with low viscosity. Salivary cortisol concentrations were determined using a commercially available chemiluminescence immunoassay (CLIA; IBL-International, Hamburg, Germany). Inter-and intraassay coefficients of variation were 8.4% and 4.6%, respectively. As described in the participants section, we defined responders in the both physical stress conditions (CPT and SECPT) according to Schwabe and colleagues [ 6 ]. We calculated the maximum increase in cortisol for each participant from baseline and defined responders by a cortisol increase of ≥ 2 nmol/l. This resulted in 17 participants in the CPT (out of 44 = 39% responders) and 21 participants in the SECPT (out of 45 = 47% responders). The WWT comprised 31 participants, the SEWWT group 32 ( Table 1 ). Again, as we had done with the subjective stress response, we calculated the maximum increase per subject from baseline to enable one dependent increase measure for cortisol.


Heart rate was measured as a marker of the sympathetic stress system using a wireless chest heart rate transmitter and wrist monitor recorder (Polar RS800 TM, Polar Electro, Finland). We recorded beat-to-beat heart rate data and calculated one-minute mean values: In order to control for potential group differences regardless of our stress manipulation we used five minute mean values and aggregated them within the instruction phase (of the interaction paradigm) of our experiment when participants were not yet aware in which stress condition they will be. For baseline heart rate we calculated the five minute mean values directly before the start of the first stress manipulation. For comparison of the baseline between our groups we aggregated these five values into one mean value. For the two stressor manipulations lasting three minutes each, we put five-minute mean values into the analyses in order to represent the course of the heart rate with a one-minute increase and recovery to the manipulation. This resulted in five values for the first part of the stressor and five for the second part thereof. For the two stress manipulations we additionally recorded the maximum increase in each participant by subtracting the mean heart rate baseline from the individual maximum within the four-minute window. Due to technical problems, heart rate data were obtainable from 91 participants in the final sample only (WWT: n = 28, SEWWT: n = 29, CPT: n = 16, SECPT: n = 18).

Participants were told to abstain from alcohol, caffeine, smoking, and medication intake 24h prior to the experiment. They should have eaten a standard lunch on the day of the experiment, and not have eaten after 4:00 pm. All participants received an email-reminder including these criteria the day before the experiment. They were randomly assigned to one of the four experimental conditions and invited in groups of 4 to 6. The two-hour sessions took place between 5:00 and 7:00 pm in order to control for diurnal variations in cortisol secretion.

Upon arrival at the laboratory, target participants were randomly assigned a number between 1 and 6 and seated individually accordingly to the number on their computer. They were not allowed to communicate. They read and signed the informed-consent forms, were introduced to the saliva sampling method, and each was provided with a heart rate device (Polar RS800TM, Polar Electro, Oy, Kempele, Finland). The participants then had to read instructions of the social and nonsocial interaction paradigms and were asked to complete control tasks (examples of each type of game). All participants responded to the control tasks correctly, indicating full understanding of the interaction procedure. They were then provided with instructions for one of the four different conditions: WWT, SEWWT, CPT or SECPT. After 5 min, they were guided to the test room and given a summary of the procedure. On their way to the test room, they came across the group of interaction partners waiting in front of the computer laboratory. In the test room, the sequence of activities was the following: 3 min of either warm water or cold water immersion with or without social evaluation (WWT, SEWWT, CPT or SECPT; stressor part I), first set of 12 decisions (5 min), 3 min of either warm water or cold water immersion with or without social evaluation (WWT, SEWWT, CPT or SECPT; stressor part II), and finally the second set of 12 decisions (5 min). The games were pencil-and-paper tasks. While participants completed their subjective ratings and gave their saliva sample, their decisions were entered at the specific computer in the computer laboratory. The interaction partners were already sitting there and had been instructed about the paradigms and made their decisions. After the target participants finished the procedure in the test room, they were guided to the computer laboratory and re-seated in their cubicles. Their previous decisions were matched to the interaction partners’ decisions by computer to determine everyone’s outcomes. The instructions about the decision paradigms guaranteed that all interactions would involve real human partners who would enter the laboratory after the stress manipulation. There was no deception involved. The interaction partners were invited to interact with the target participant to ensure real human interaction. All participants were provided with detailed written information and signed an informed consent form. All participants were reimbursed for their participation. This guaranteed the entire procedure’s complete credibility. After the target participants re-entered the computer lab, the results of each of their 24 decisions were presented on their computer screen, including the sum of their profits. The interaction partners then received the money they had earned (the converted sum of the outcomes for all 24 decisions plus the flat fee, which was paid out anonymously), and left the laboratory. Target participants had to stay in the lab until the last saliva sample was taken (+65 min after the end of the decision paradigm) and were then debriefed. Finally, they were paid the converted sum of the outcomes for all 24 decisions plus the flat fee. The study was approved by the ethics committee of the University of Freiburg, Germany. Written informed consent was obtained from all participants. The experiment’s timeline is found in Fig 2 .


Statistical analyses

Descriptive data (depression, social anxiety, age, and verbal IQ were compared using two-way analyses of variance (ANOVAs) with physical stress (cold water, warm water) and social stress (social evaluation, no social evaluation) as between-group factors. In order to control for the level of social anxiety, the SIAS score was entered as covariate in all analyses of covariance (ANCOVA) models: baseline cortisol, heart rate during instructions, heart rate baseline, and subjective-stress ratings were compared in three-way ANCOVAs with the factors physical stress and social stress. Cortisol and heart rate responses were analyzed using three-way ANCOVAs with repeated measures. The factors in these analyses were again physical stress, social stress, and time (repeated factor; 8 cortisol samples, 10 heart rate measurements). For the individual increases in heart rate we used a MANCOVA model and reported Wilks lamda Λ with the above reported factors and with the individual increase to the first and the second part of the stressor as two dependent variables. For the subjective stress responses, we calculated two-way ANCOVAs with the factors physical stress, social stress, and the maximum increase as dependent measure. The cortisol increase was also entered in a two-way ANCOVA with the factors physical stress and social stress. For the behavioral paradigms, again ANCOVAS were performed. In cases of heterogeneity of covariance (Mauchly test of sphericity), we determined the significance of the results of the repeated measures ANOVAs and ANCOVAs following Greenhouse-Geisser corrections. Effect sizes are reported as η p 2 for ANOVAs and ANCOVAs. Post-hoc independent samples t-tests were run to detect specific differences between conditions. To explore the potential underlying mechanisms of behavioral effects of our stress manipulations, we decided to conduct stepwise regression models within each group with the behavioral variables as criteria and the subjective as well as biological stress measures as predictors. For the heart rate increase we calculated one mean measure by combining the two max increase mean values. Data were analyzed using SPSS Version 21 and 24. All tests were two-sided, with the level of significance set at p < .05.

Psychological trait and baseline measures

The four groups did not differ significantly in their level of social anxiety, depressive symptoms, age, or verbal IQ (all p > 0.050) ( Table 1 ). With regard to age and depressive symptoms (BDI) we observed differences on a trend level. Since social anxiety is correlated to depressive symptoms [ 60 ], we decided to add the BDI as another covariate into all of the following statistical models in order to control for possible confounding effects. The results reported below will therefore include social anxiety and depressive symptoms as covariates.

In addition, the groups did not differ in baseline levels of cortisol, heart heart rate during instructions, subjective stress, unpleasantness, physical symptoms, tension, or pain, respectively (all p ≥ 0.100). There was a trend towards an effect of social stress for baseline heart rate (F(1,85) = 3.17, p = 0.079, ηp2 = 0.036). For an overview of the baseline levels, please see Table 2 .


Psychological stress responses

We detected a significant effect of social stress on the subjective stress increase (F(1,95) = 5.55, p = 0.021, ηp2 = 0.055) ( Fig 3B ) and increase in tension (F(1,95) = 7.901, p = 0.006, ηp2 = 0.077) with higher levels in the social stress condition. Physical stress led to stronger increases in physical symptoms (F(1,95) = 28.05, p<0.001, ηp2 = 0.228), unpleasantness (F(1,95) = 58.41, p<0.001, ηp2 = 0.381) ( Fig 3B ), and pain (F(1,95) = 28.87, p<0.001, ηp2 = 0.233). The covariate social anxiety modulated the increase in subjective stress (F(1,95) = 3.40, p = 0.068, ηp2 = 0.035), and tension (F(1,95) = 3.60, p = 0.061, ηp2 = 0.036) on a trend level but not the increase in physical symptoms (p = 0.433), unpleasantness (p = 0.113) or pain (p = 0.443). The higher the level of social anxiety, the higher the subjective response in terms of stress and tension. There was no interaction between physical and psychological stress (all p>0.1). For depressive symptoms there were higher increases with higher levels of depressive symptoms on a trend level (F(1,95) = 3.88, p = 0.052, ηp2 = 0.039) ( Fig 3B shows the increase in subjective stress and unpleasantness. The course of all subjective responses is presented in S2 Fig . All stastistical values of all variables can be found in S2 Table .


A) mean values of salivary cortisol; solid bars: time of water immersion; shaded bars: decision making; B) mean values of increases in subjective stress and unpleasantness measured with VAS; C) increases in heart rate to the first and the second stressor. Error bars indicate standard errors of the mean; WWT = Warm Water Test, SEWWT = Socially Evaluated Warm Water Test, CPT = Cold Pressor Test, SECPT = Socially Evaluated Cold Pressor Test. * indicate significant differences with p≤0.05.

Physiological stress responses

All groups presented similar baseline cortisol levels and heart rates (all p<0.001) ( Table 2 ). We noted a significant increase in salivary cortisol over time (F(2.77, 262.95) = 9.52, p<0.001, ηp2 = 0.091) as well as a time x physical stress interaction (F(2.77, 262.95) = 36.91, p<0.001, ηp2 = 0.280), showing higher increases in the two physical stress conditions. There was also a main effect of physical stress (F(1, 95) = 17.193, p<0.001, ηp2 = 0.153) ( Fig 3A ). Social anxiety and depressive symptoms did not modulate the cortisol stress response. There was no time x physical x social stress interaction, nor any main effect from the physical x social stress interaction. The increase in cortisol was significantly higher in the physical stress conditions (F(1,95) = 83.19, p<0.001, ηp2 = 0.467). Again, neither social anxiety nor depression did modulate the increase in cortisol. We observed no effect from social stress or physical x social stress interaction.

Regarding the heart rate response to the various stressors: neither social anxiety nor depression did not modulate the response significantly. There was a significant increase in heart rate over time (F(4.96, 421.50) = 3.48, p = 0.004, ηp2 = 0.039) and a significant time x physical stress effect (F(4.96, 421.50) = 8.95, p<0.001, ηp2 = 0.095) with higher heart-rate increases in the physical stress condition. In addition, social stress revealed significant influence over time (time x social stress: F(4.96, 421.50) = 2.85, p = 0.015, ηp2 = 0.032) with higher increases over time in the social stress conditions. Moreover, there was a significant three-way interaction of time, social stress, and physical stress (F(4.96, 421.50) = 2.72, p = 0.020, ηp2 = 0.031) with the highest increases in heart rate in the SECPT condition. We also noted a trend towards a main social-stress effect (F(1,85) = 3.89, p = 0.052, ηp2 = 0.044), with overall higher heart-rate levels in the social stress conditions. There was no main effect of physical stress on heart rate. The MANCOVA model with the individual increases in heart rate yielded the following results: there was again no effect of social anxiety or depression. Physical stress led to significantly higher increases in heart rate (F(2, 84) = 6.00, p = 0.004, Wilk's Λ = 0.875 ηp2 = 0.125). With respect to the maximum increase we did not find a significant effect of social stress or a significant interaction between physical and social stress ( Fig 3C ).

Effects of social and physical stress on prosocial behavior, punishment, and nonsocial risk

Regarding the prosocial behaviors trust, trustworthiness, and sharing, we identified significant modulation by the covariate social anxiety only for trust, reflecting higher levels of trust with higher levels of social anxiety (F(1,95) = 12.52, p = 0.001, ηp2 = 0.116). Depression had no significant influence. We noted a trend towards higher levels of sharing in the social stress condition (F(1,95) = 3.79, p = 0.055, ηp2 = 0.038). While social stress or physical stress alone reduced prosocial behavior on the descriptive level, combining the two factors restored the level of prosociality: this means that one stressor alone (either social evaluation or cold water) reduced prosociality, while a combination of the two stressors triggers a level of prosociality similar to that in the group with no stressor. This result is reflected by a social x physical stress interaction with significant effects consistent for all three prosocial behaviors: trust (F(1, 95) = 4.49, p = 0.037, ηp2 = 0.045), trustworthiness (F(1,95) = 5.01, p = 0.027, ηp2 = 0.050) and sharing (F(1, 95) = 5.94, p = 0.017, ηp2 = 0.059). Regarding punishment: neither social anxiety nor depression did not modulate punishment behavior, but there was a trend towards the interaction between physical and social stress (physical x social stress: F(1,95) = 3.56, p = 0.062, ηp2 = 0.036). While social stress or physical stress alone increased punishment, the combination of the two factors again reduced the level of punishment. Regarding nonsocial risk behavior, again social anxiety or depression did not significantly modulate risky choices, but social stress did exhibit a significant effect: participants displayed lower levels of nonsocial risk if they were socially evaluated compared to the non-social condition (social stress: F(1,95) = 4.97, p = 0.028, ηp2 = 0.050). Physical stress revealed no significant effect on nonsocial risk behavior. Post-hoc t-tests tended to indicate difference towards lower trust in the SEWWT compared to the SECPT condition (t(51) = 1.707, p = 0.094). For trustworthiness we observed a trend towards lower levels in the CPT compared to the WWT condition (t(46) = 1.680, p = 0.100) and significantly higher levels in the SECPT compared to the CPT condition (t(36) = 2.126, p = 0.040). For sharing there were lower levels in the CPT condition than the WWT condition (t(46) = 1.976, p = 0.054) as well as compared to the SEWWT condition (t(47) = 1.851, p = 0.070), both on a trend level. The CPT condition revealed significantly lower levels of sharing than the SECPT condition (t(36) = 2.828, p = 0.008). For punishment there were significantly lower levels in the SECPT than the SEWWT condition (t(51) = 2.178, p = 0.034) and a trend towards lower levels of punishment in the SECPT than the CPT condition (t(36) = 1.741, p = 0.093). Risk was lower on a trend level in the SEWWT compared to the WWT condition (t(61) = 1.713, p = 0.092), lower in the SEWWT than the CPT condition (t(47) = 1.995, p = 0.052) and lower in the SECPT than the CPT condition (t(36) = 1.955, p = 0.058). All behavioral paradigm results are shown in Fig 4 .


Mean score as a function of condition for A) trust B) trustworthiness C) sharing D) punishment and E) nonsocial risk . Error bars indicate standard errors of the mean; * indicate post-hoc t tests with a p≤0.05, † with a p ≤0.10; WWT = Warm Water Test, SEWWT = Socially Evaluated Warm Water Test, CPT = Cold Pressor Test, SECPT = Socially Evaluated Cold Pressor Test.

For exploratory analyses of the potentially underlying mechanisms of the different stress systems and their magnitude, we calculated stepwise regression models in each of the four groups for each of the five behavioral variables. We entered all five VAS Increase Variables, the maximum cortisol increase and the mean heart rate increase into our models.

VAS Unpleasantness was positively related to trust in the SEWWT and CPT condition. In the SECPT condition two significant models were depicted. The first model including a negative relationship between cortisol increase and trust and in the second model a negative relationship between increase in cortisol as well as the VAS Stress increase and trust which revealed the highest adjusted R 2 ( S7 Table ). The cortisol increase was also negatively related to trustworthiness in the SECPT condition. No other model appeared to show significance for trustworthiness ( S8 Table ). For sharing, we again found a negative relation for the cortisol increase in the SECPT group. In addition the increase in heart rate was negatively related to sharing in the CPT condition ( S9 Table ). For punishment only one model was validated which shows a negative relationship between the increase in heart rate and the amount of punishment in the WWT group ( S10 Table ). With respect to risk behavior there was no significant model at all. Taken together these results do not reveal clear consistent patterns.

This is the first study to investigate the effects of social stress, physical stress, and social anxiety on social behavior. Social stress increased subjective stress and tension, whereas physical stress increased physical symptoms, unpleasantness, and pain. There was no interaction between social and physical stress with regard to the subjective stress ratings. Participants high in social anxiety reported stronger increases in stress and tension on a trend level, but did not differ in their reported increases in unpleasantness, physical symptoms or pain. Cortisol was increased by physical stress, but there was no stronger effect for the interaction of social and physical stress and no effect of social stress alone. In terms of the cardiovascular response there were increases by physical stress and social stress over time, but again no interaction. Social anxiety revealed no association with the physical stress response. The level of depressive symptoms did not influence the psychobiological stress response significantly.

For our baseline measure before the start of the stress manipulation we documented slightly higher levels for heart rate in the social stress conditions on a trend level. This may be interpreted as an anticipatory stress response in this system as the introduction to the stress manipulation has already been given at that point.

For the behavioral variables our study demonstrates that the physical and social components of stress exposure interacted to modulate social behavior in men. In particular, social stress alone reduced prosocial behavior, while the lowest levels of prosocial behavior became apparent following physical stress exposure alone. Importantly, combining both stressors led to the restoration of trust, trustworthiness, and sharing, as well as a trend towards less punishment compared to the physical stress condition. We cannot interpret the effects of the social stress or physical stress separately, since their effects did not appear significant in our model. But the significant interactions are evidence that the behavioral effects of acute stress are stressor modality-dependent. The effects of social evaluation on behavior differ depending whether a person is subjected to a cold stressor at the same time or not (and vice versa).

In addition we found that social stress alone reduced risky nonsocial decisions and increased sharing behavior. Moreover, social anxiety modulated trust behavior significantly, with higher social anxiety levels being associated with increased trust. Depressive symptoms had no significant effect on any behavioral variable.

Group-to-group comparisons confirmed the aforementioned results: among all four groups the clearest finding was lower levels of trustworthiness and sharing in the CPT versus the SECPT group. On a trend level the group-to-group comparisons confirm the finding that social and physical stress alone slightly reduce prosocial behavior, while their combination restores prosociality. These results should be interpreted with caution because of possible α error cumulation due to multiple comparisons and the fact that the level of social anxiety was not taken into account.

Our findings highlight the notion that men seek positive social encounters when faced with threatening circumstances [ 27 , 61 ], which supports the tend-and-befriend hypothesis in the context of stress-induced social behavior [ 29 ]. But this is only the case when individuals face a stressor with a specific threat pattern: in our study it was the combination of a physical (cold water) and social component (social evaluation). When confronted with a physical (non-social) stressor, participants exhibited reduced levels of prosocial behavior, thus replicating a recent study’s findings [ 62 ].

Social evaluation is a potent stressor known to lead to stronger cortisol increases when combined with other stressor elements [ 5 ]. It was added to the cold pressor stressor to increase its impact on the stress response and thus form a new method for stress induction, the SECPT [ 6 , 56 ]. We expected it to demonstrate efficacy in humans depending on the level of social anxiety, since social evaluation is the core annoyance these individuals try to avoid and fear [ 63 ]. Although we found effects on the subjective stress response (higher increases in subjective stress and tension), we noted only a trend towards an increase in sharing behavior and no other social-evaluation effects on socially interactive behaviors alone. One could speculate that our social evaluation manipulation was not strong enough compared to the variant used in the TSST-G [ 49 ]. This could be responsible for the lack of effect on the cortisol stress response. Regarding the combination with physical stress, we noted effects that might be comparable to effects observed with other social stressors [ 27 ]. We could not prove this effect to be driven by the cortisol increase as previous studies demonstrated [ 23 , 36 , 64 ], but this might be due to the stressors varying in intensity, or to qualitative differences in the psychophysiological stress responses to diverse stressor paradigms–all factors deserving investigation in future studies. Interestingly, we detected significantly fewer nonsocial high-risk choices under social stress or social evaluation, a result that falls in line with studies showing that even pictures of human eyes may already induce prosocial and normative behavior [ 65 – 67 ].

Social anxiety modulated several aspects of the subjective stress response but not the physical stress response, findings that concur with studies reporting discordance between physiological and subjective stress parameters [ 42 , 45 ] in social-anxiety patients. Our results underline the importance of studying the psychobiological mechanisms that trigger the effects of stress on behavior, as subjective differences in situational interpretations may be important even when they are not accompanied by biological differences, e.g. in cortisol. Moreover, social anxiety modulated trust in our participants, with the highest levels of social anxiety being associated with the highest trust scores, a finding in line with a study on patients with social anxiety disorder that reported more submissive behavior in socially anxious individuals [ 68 ]. Participants high in social anxiety may trust more because they have too little self-confidence to withhold their trust. They may not differ in their levels of sharing or trustworthiness since such decisions are one-shot decisions that do not depend on another participant’s decision. The sharing game resembles a dictator game, whereas our trust game may be better compared to an ultimatum game of slightly different structure. There is evidence that behavior in these games differs with higher prosociality in the ultimatum game compared to the dictator game where no other decision or response than the proposer´s is accountable [ 69 , 70 ]. One explanation for this difference beyond differences in fairness motivation may be the fear of rejection that comes into play in the ultimatum and trust game, but not in the dictator game. Participants with high levels of social anxiety may have trusted more because they harbor an elevated fear of rejection and not because they are necessarily more motivated to demonstrate greater general fairness. Future studies should investigate further the role of maladaptive beliefs that could lead to differences in prosocial behavior in social anxiety [ 71 ]. Furthermore, comparison between patients with social anxiety disorder and subclinical levels of social anxiety would lead to deeper understanding of the modulation of social behavior under stress on health and pathology terms.

With regard to the possible underlying mechanisms of our behavioral results: we detected no clear pattern in our results. We found positive associations for the increase in VAS Unpleasantness with the increase in the SEWWT and the CPT condition what would go in line with the concept of tend-and-befriend response. Surprisingly, we found negative associations for the increase in cortisol with trust, trustworthiness and sharing in the SECPT condition. Also VAS Stress increase was related negatively to trust in the SECPT condition. Maybe this reflects possible magnitude effect. As all participants within the SECPT condition show stress increases, it may be that prosocial behavior is shown especially by the moderate to low responders while high responders may tend to reduce their prosocial behavior. This was accompanied by a negative relation between heart rate increase and sharing in the CPT condition. For the WWT condition there was a negative association between heart rate increase and punishment. Since these analyses only have exploratory character and bear methodological limitations (e.g. small sample size) we will not draw conclusions here. Because we had some data loss in the heart rate condition as described in the methods section, the regression analyses included only these participants with respect to all other stress measures due to listwise exclusion. We recommend interpreting these findings with caution; it will be up to future studies to reveal the underlying mechanisms in study designs enabling a causal inference, e.g. by activating or blocking different physiological stress systems with pharmaceutical agents [ 64 ]. In addition sample sizes will need to be increased substantially.

The present study shows that the behavioral effects of stress on social behavior depend on the stressor’s quality that can more intensely activate either the fight-or-flight or tend-and-befriend response pattern. Our results could lead one to speculate that both concepts characterize distinct variants of stress-related behavioral action: whether one or both behavioral aspects are activated depends on the quality of the stressor, specific behavioral options, and on individual characteristics (eg, the trait level of social anxiety). In addition, a direct comparison of men and women in one study would be needed to clarify any gender-associated dominance of one or the other behavioral concept. In the current study, we did identified no significantly increased prosocial behavior in the stress (SEWWT, CPT, SECPT) compared to the control condition (WWT) [ 27 ]. One might speculate that this is due to the quality of the stress induction and responses in our study. The SEWWT and SECPT differ from the TSST-G in its socio-evaluative component with lower levels of social threat in the SEWWT and SECPT than in the TSST-G, which requires the participant to present himself and perform on several levels. This involves deeper ego-involvement and the potential for personal embarrassment. On the other hand, the SECPT includes a physical stressor. As these situations and behaviors differ so strongly from one another, future studies will need to test a wider range of stressors of varying intensity and qualities on social behavior in order to identify any dose-dependent effects of stress on behavior, as well as which specific qualitative aspects modulate social behavior under stress. Interestingly, even traumatic events seem to have the potential to prompt prosocial behavioral tendencies in people [ 72 ], a factor that might initially appear strange: although traumatic events (reflecting strong psychobiological stressors) bear the risk of developing posttraumatic stress disorder, most affected people exhibit resilience [ 73 , 74 ]—another influencing factor linked to social support. Better understanding of the interplay between differential contextual and psychopathological factors of stress, their psychobiological underpinnings, and their behavioral consequences might help us to understand resilience better.

Physical and social stress interact to modulate social interaction in men, and social stress alone reduces nonsocial risk behavior. A recent meta-analysis of imaging data on physical and psychosocial stress documented that physical and psychosocial stressors lead to similar subjective and physiological results, but display different underlying brain activation patterns. While physical stress is associated with motoric fight-or-flight responses, psychosocial stress leads to a shift towards emotion regulation, goal-directed behavior, and a reduction in reward processing [ 75 ]. Our results support that notion with the reductions in prosocial behavior in the CPT condition, which could be interpreted as fight-or-flight behavior. Interestingly, the psychosocial stress component seems to compensate this effect and restore prosocial tendencies irrespective of the level of social anxiety. Imaging studies should reveal the underlying brain activity patterns in the SECPT compared to CPT and a psychosocial stress like the Montreal Imaging Stress Task (MIST) [ 76 ].

Our study shows that both the fight-or-flight and tend-and-befriend tendencies are part of the human behavioral repertoire under stress, and that they may be differentially activated. Deeper insights into the underlying mechanisms will inspire researchers and clinicians to adopt more specific diagnostic and treatment approaches for patients with social anxiety disorder to successfully tailor individual therapy approaches.

Supporting information

S1 fig. all payoff structures for the games assessing prosocial behaviors and antisocial and nonsocial risk behaviors..

The target participant and that participant’s interaction partner are represented by a red P and black IP, respectively (interaction partners were not in either the stress or control condition). The pairs of numeric values are examples of the outcomes (in monetary units) received by the target participant (red values) and interaction partner (black values). In the nonsocial risk game, target participants rolled a die, and its value determined which outcome resulted.

S2 Fig. Course of subjective increases for all VAS.

Mean values and standard errors of the mean; solid bars: time of water immersion; shaded bars: decision making; A) stress B) unpleasantness C) tension D) physical symptoms E) pain; WWT = Warm Water Test, SEWWT = Socially Evaluated Warm Water Test, CPT = Cold Pressor Test, SECPT = Socially Evaluated Cold Pressor Test.

S1 Table. Stastical values of baseline characteristics.

F an p values of baseline characteristics.

S2 Table. Stastical values of psychological stress response.

F an p values of psychological stress response.

S3 Table. Stastical values of physiological stress response with repeated measures–Within subject results.

F and p values of physiological stress response within subjects results.

S4 Table. Stastical values of physiological stress response with repeated measures–Between subjects main effects.

F and p values of physiological stress response between subjects effects.

S5 Table. Stastical values of physiological stress response–maximum increases of cortisol and heart rate.

F values, Wilk'sΛ and p values.

S6 Table. Stastical values of ANCOVA models for behavioral paradigms.

All F and p values.

S7 Table. Stepwise regression to explore relationships between of stress systems and trust.

All parameters of significant models.

S8 Table. Stepwise regression to explore relationships between of stress systems and trustworthiness.

S9 Table. Stepwise regression to explore relationships between of stress systems and sharing.

S10 Table. Stepwise regression to explore relationships between of stress systems and punishment.

S11 Table. Stepwise regression to explore relationships between of stress systems and risk.


We thank Kristina Dworsky and Antonia Vehlen for their skilled assistance in conducting the experiment.

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Recent developments in stress and anxiety research

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  • Volume 128 , pages 1265–1267, ( 2021 )

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Stress and anxiety are virtually omnipresent in today´s society, pervading almost all aspects of our daily lives. While each and every one of us experiences “stress” and/or “anxiety” at least to some extent at times, the phenomena themselves are far from being completely understood. In stress research, scientists are particularly grappling with the conceptual issue of how to define stress, also with regard to delimiting stress from anxiety or negative affectivity in general. Interestingly, there is no unified theory of stress, despite many attempts at defining stress and its characteristics. Consequently, the available literature relies on a variety of different theoretical approaches, though the theories of Lazarus and Folkman ( 1984 ) or McEwen ( 1998 ) are relatively pervasive in the literature. One key issue in conceptualizing stress is that research has not always differentiated between the perception of a stimulus or a situation as a stressor and the subsequent biobehavioral response (often called the “stress response”). This is important, since, for example, psychological factors such as uncontrollability and social evaluation, i.e. factors that may influence how an individual perceives a potentially stressful stimulus or situation, have been identified as characteristics that elicit particularly powerful physiological stressful responses (Dickerson and Kemeny 2004 ). At the core of the physiological stress response is a complex physiological system, which is located in both the central nervous system (CNS) and the body´s periphery. The complexity of this system necessitates a multi-dimensional assessment approach involving variables that adequately reflect all relevant components. It is also important to consider that the experience of stress and its psychobiological correlates do not occur in a vacuum, but are being shaped by numerous contextual factors (e.g. societal and cultural context, work and leisure time, family and dyadic systems, environmental variables, physical fitness, nutritional status, etc.) and dispositional factors (e.g. genetics, personality, resilience, regulatory capacities, self-efficacy, etc.). Thus, a theoretical framework needs to incorporate these factors. In sum, as stress is considered a multi-faceted and inherently multi-dimensional construct, its conceptualization and operationalization needs to reflect this (Nater 2018 ).

The goal of the World Association for Stress Related and Anxiety Disorders (WASAD) is to promote and make available basic and clinical research on stress-related and anxiety disorders. Coinciding with WASAD’s 3rd International Congress held in September 2021 in Vienna, Austria, this journal publishes a Special Issue encompassing state-of-the art research in the field of stress and anxiety. This special issue collects answers to a number of important questions that need to be addressed in current and future research. Among the most relevant issues are (1) the multi-dimensional assessment that arises as a consequence of a multi-faceted consideration of stress and anxiety, with a particular focus on doing so under ecologically valid conditions. Skoluda et al. 2021 (in this issue) argue that hair as an important source of the stress hormone cortisol should not only be taken as a complementary stress biomarker by research staff, but that lay persons could be also trained to collect hair at the study participants’ homes, thus increasing the ecological validity of studies incorporating this important measure; (2) the incongruence between psychological and biological facets of stress and anxiety that has been observed both in laboratory and field research (Campbell and Ehlert 2012 ). Interestingly, there are behavioral constructs that do show relatively high congruence. As shown in the paper of Vatheuer et al. ( 2021 ), gaze behavior while exposed to an acute social stressor correlates with salivary cortisol, thus indicating common underlying mechanisms; (3) the complex dynamics of stress-related measures that may extend over shorter (seconds to minutes), medium (hours and diurnal/circadian fluctuations), and longer (months, seasonal) time periods. In particular, momentary assessment studies are highly qualified to examine short to medium term fluctuations and interactions. In their study employing such a design, Stoffel and colleagues (Stoffel et al. 2021 ) show ecologically valid evidence for direct attenuating effects of social interactions on psychobiological stress. Using an experimental approach, on the other hand, Denk et al. ( 2021 ) examined the phenomenon of physiological synchrony between study participants; they found both cortisol and alpha-amylase physiological synchrony in participants who were in the same group while being exposed to a stressor. Importantly, these processes also unfold over time in relation to other biological systems; al’Absi and colleagues showed in their study (al’Absi et al. 2021 ) the critical role of the endogenous opioid system and its relation to stress-related analgesia; (4) the influence of contextual and dispositional factors on the biological stress response in various target samples (e.g., humans, animals, minorities, children, employees, etc.) both under controlled laboratory conditions and in everyday life environments. In this issue, Sattler and colleagues show evidence that contextual information may only matter to a certain extent, as in their study (Sattler et al. 2021 ), the biological response to a gay-specific social stressor was equally pronounced as the one to a general social stressor in gay men. Genetic information is probably the most widely researched dispositional factor; Kuhn et al. show in their paper (Kuhn et al. 2021 ) that the low expression variant of the serotonin transporter gene serves as a risk factor for increased stress reactivity, thus clearly indicating the important role of dispositional factors in stress processing. An interesting factor combining both aspects of dispositional and contextual information is maternal care; Bentele et al. ( 2021 ) in their study are able to show that there was an effect of maternal care on the amylase stress response, while no such effect was observed for cortisol. In a similar vein, Keijser et al. ( 2021 ) showed in their gene-environment interaction study that the effects of FKBP5, a gene very closely related to HPA axis regulation, and early life stress on depressive symptoms among young adults was moderated by a positive parenting style; and (5) the role of stress and anxiety as transdiagnostic factors in mental disorders, be it as an etiological factor, a variable contributing to symptom maintenance, or as a consequence of the condition itself. Stress, e.g., as a common denominator for a broad variety of psychiatric diagnoses has been extensively discussed, and stress as an etiological factor holds specific significance in the context of transdiagnostic approaches to the conceptualization and treatment of mental disorders (Wilamowska et al. 2010 ). The HPA axis, specifically, is widely known to be dysregulated in various conditions. Fischer et al. ( 2021 ) discuss in their comprehensive review the role of this important stress system in the context of patients with post-traumatic disorder. Specifically focusing on the cortisol awakening response, Rausch and colleagues provide evidence for HPA axis dysregulation in patients diagnosed with borderline personality disorder (Rausch et al. 2021 ). As part of a longitudinal project on ADHD, Szep et al. ( 2021 ) investigated the possible impact of child and maternal ADHD symptoms on mothers’ perceived chronic stress and hair cortisol concentration; although there was no direct association, the findings underline the importance of taking stress-related assessments into consideration in ADHD studies. As the HPA axis is closely interacting with the immune system, Rhein et al. ( 2021 ) examined in their study the predicting role of the cytokine IL-6 on psychotherapy outcome in patients with PTSD, indicating that high reactivity of IL-6 to a stressor at the beginning of the therapy was associated with a negative therapy outcome. The review of Kyunghee Kim et al. ( 2021 ) also demonstrated the critical role of immune pathways in the molecular changes due to antidepressant treatment. As for the therapy, the important role of cognitive-behavioral therapy with its key elements to address both stress and anxiety reduction have been shown in two studies in this special issue, evidencing its successful application in obsessive–compulsive disorder (Ivarsson et al. 2021 ; Hollmann et al. 2021 ). Thus, both stress and anxiety are crucial transdiagnostic factors in various mental disorders, and future research needs elaborate further on their role in etiology, maintenance, and treatment.

In conclusion, a number of important questions are being asked in stress and anxiety research, as has become evident above. The Special Issue on “Recent developments in stress and anxiety research” attempts to answer at least some of the raised questions, and I want to invite you to inspect the individual papers briefly introduced above in more detail.

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Nater, U.M. Recent developments in stress and anxiety research. J Neural Transm 128 , 1265–1267 (2021).

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Published : 01 September 2021

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Impact of Stress on Human Body: A Review

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the effects of stress on human behavior research paper


the effects of stress on human behavior research paper

Every inherent or external incentive which involves natural reactions, is recognized as stress. Extenuatory reaction to these pressures is known as stress reactions. Stress contributes to broad variety of diseases including hypertension and superior plasma cortisol, cardiac and CVDs, inflammatory bowel syndromes, type 2 diabetes, and a reduced quality of life among those suffering with cancer. Stress happens in 3 stages. The first stage is an initial stage of alarm, which produces an increase of adrenaline. Living organisms can withstand intense stress and stay alive. Second phase is a brief conflict process that the body puts up to handle the problem. Last phase is the tiredness phase, which arises when the body has utilized every part of its accessible assets. Stress affects the different organs of the whole body. As far as chronic stress is concerned, it stimulates infection in the vasculature, particularly in the coronary arteries, also can alter cholesterol levels and excessive activation of sympathetic nervous system (depletes the system of neurotransmitters, peptides, cofactors, and other mediators). Regarding, endocrine stress, it affects the hypothalamus in brain. The stress condition in n individuals experiencing pressure needs a healthy and regular eating including important supplements, moreover, physical exercise and mind rest are regularly suggested for averting stress induced anxiety-linked objections and disease.

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the effects of stress on human behavior research paper

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  • Published: 27 January 2022

The future of human behaviour research

  • Janet M. Box-Steffensmeier 1 ,
  • Jean Burgess 2 , 3 ,
  • Maurizio Corbetta 4 , 5 ,
  • Kate Crawford 6 , 7 , 8 ,
  • Esther Duflo 9 ,
  • Laurel Fogarty 10 ,
  • Alison Gopnik 11 ,
  • Sari Hanafi 12 ,
  • Mario Herrero 13 ,
  • Ying-yi Hong 14 ,
  • Yasuko Kameyama 15 ,
  • Tatia M. C. Lee 16 ,
  • Gabriel M. Leung 17 , 18 ,
  • Daniel S. Nagin 19 ,
  • Anna C. Nobre 20 , 21 ,
  • Merete Nordentoft 22 , 23 ,
  • Aysu Okbay 24 ,
  • Andrew Perfors 25 ,
  • Laura M. Rival 26 ,
  • Cassidy R. Sugimoto 27 ,
  • Bertil Tungodden 28 &
  • Claudia Wagner 29 , 30 , 31  

Nature Human Behaviour volume  6 ,  pages 15–24 ( 2022 ) Cite this article

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Human behaviour is complex and multifaceted, and is studied by a broad range of disciplines across the social and natural sciences. To mark our 5th anniversary, we asked leading scientists in some of the key disciplines that we cover to share their vision of the future of research in their disciplines. Our contributors underscore how important it is to broaden the scope of their disciplines to increase ecological validity and diversity of representation, in order to address pressing societal challenges that range from new technologies, modes of interaction and sociopolitical upheaval to disease, poverty, hunger, inequality and climate change. Taken together, these contributions highlight how achieving progress in each discipline will require incorporating insights and methods from others, breaking down disciplinary silos.

Genuine progress in understanding human behaviour can only be achieved through a multidisciplinary community effort. Five years after the launch of Nature Human Behaviour , twenty-two leading experts in some of the core disciplines within the journal’s scope share their views on pressing open questions and new directions in their disciplines. Their visions provide rich insight into the future of research on human behaviour.

the effects of stress on human behavior research paper

Artificial intelligence

Kate Crawford

Much has changed in artificial intelligence since a small group of mathematicians and scientists gathered at Dartmouth in 1956 to brainstorm how machines could simulate cognition. Many of the domains that those men discussed — such as neural networks and natural language processing — remain core elements of the field today. But what they did not address was the far-reaching social, political, legal and ecological effects of building these systems into everyday life: it was outside their disciplinary view.

Since the mid-2000s, artificial intelligence (AI) has rapidly expanded as a field in academia and as an industry, and now a handful of powerful technology corporations deploy these systems at a planetary scale. There have been extraordinary technical innovations, from real-time language translation to predicting the 3D structures of proteins 1 , 2 . But the biggest challenges remain fundamentally social and political: how AI is widening power asymmetries and wealth inequality, and creating forms of harm that need to be prioritized, remedied and regulated.

The most urgent work facing the field today is to research and remediate the costs and consequences of AI. This requires a deeper sociotechnical approach that can contend with the complex effect of AI on societies and ecologies. Although there has been important work done on algorithmic fairness in recent years 3 , 4 , not enough has been done to address how training data fundamentally skew how AI models interpret the world from the outset. Second, we need to address the human costs of AI, which range from discrimination and misinformation to the widespread reliance on underpaid labourers (such as the crowd-workers who train AI systems for as little as US $2 per hour) 5 . Third, there must be a commitment to reversing the environmental costs of AI, including the exceptionally high energy consumption of the current large computational models, and the carbon footprint of building and operating modern tensor processing hardware 6 . Finally, we need strong regulatory and policy frameworks, expanding on the EU’s draft AI Act of 2021.

By building a more interdisciplinary and inclusive AI field, and developing a more rigorous account of the full impacts of AI, we give engineers and regulators alike the tools that they need to make these systems more sustainable, equitable and just.

Kate Crawford is Research Professor at the Annenberg School, University of Southern California, Los Angeles, CA, USA; Senior Principal Researcher at Microsoft Research New York, New York, NY, USA; and the Inaugural Visiting Chair of AI and Justice at the École Normale Supérieure, Paris, France.


Laura M. Rival

The field of anthropology faces fundamental questions about its capacity to intervene more effectively in political debates. How can we use the knowledge that we already have to heal the imagined whole while keeping people in synchrony with each other and with the world they aspire to create for themselves and others?

The economic systems that sustain modern life have produced pernicious waste cultures. Globalization has accelerated planetary degradation and global warming through the continuous release of toxic waste. Every day, like millions of others, I dutifully clean and prepare my waste for recycling. I know it is no more than a transitory measure geared to grant manufacturers time to adjust and adapt. Reports that most waste will not be recycled, but dumped or burned, upset me deeply. How can anthropology remain a critical project in the face of such orchestrated cynicism, bad faith and indifference? How should anthropologists deploy their skills and bring a sense of shared responsibility to the task of replenishing the collective will?

To help to find answers to these questions, anthropologists need to radically rethink the ways in which we describe the processes and relations that tie communities to their environments. The extinction of experience (loss of direct contact with nature) that humankind currently suffers is massive, but not irreversible. New forms of storytelling have successfully challenged modernist myths, particularly their homophonic promises 7 . But there remain persistent challenges, such as the seductive and rampant power of one-size-fits-all progress, and the actions of elites, who thrive on emulation, and in doing so fuel run-away consumerism.

To combat these challenges, I simply reassert that ‘nature’ is far from having outlasted its historical utility. Anthropologists must join forces and reanimate their common exploration of the immense possibilities contained in human bodies and minds. No matter how overlooked or marginalized, these natural potentials hold the key to what keeps life going.

Laura M. Rival is Professor of Anthropology of Nature, Society and Development, ODID and SAME, University of Oxford, Oxford, UK .

Communication and media studies

Jean Burgess

The communication and media studies field has historically been animated by technological change. In the process, it has needed to navigate fundamental tensions: communication can be understood as both transmission (of information), and as (social) ritual 8 ; relatedly, media can be understood as both technology and as culture 9 .

The most important technological change over the past decade has been the ‘platformization’ 10 of the media environment. Large digital platforms owned by the world’s most powerful technology companies have come to have an outsized and transformative role in the transmission (distribution) of information, and in mediating social practices (whether major events or intimate daily routines). In response, digital methods have transformed the field. For example, advances in computational techniques enabled researchers to study patterns of communication on social media, leading to disciplinary trends such as the quantitative description of ‘hashtag publics’ in the mid-2010s 11 .

Platforms’ uses of data, algorithms and automation for personalization, content moderation and governance constitute a further major shift, giving rise to new methods (such as algorithmic audits) that go well beyond quantitative description 12 . But platform companies have had a patchy — at times hostile — relationship to independent research into their societal role, leading to data lockouts and even public attacks on researchers. It is important in the interests of public oversight and open science that we coordinate responses to such attempts to suppress research 13 , 14 .

As these processes of digital transformation continue, new connections between the humanities and technical disciplines will be necessary, giving rise to a new wave of methodological innovation. This next phase will also require more hybrid (qualitative and quantitative; computational and critical) methods 15 , not only to get around platform lockouts but also to ensure more careful attention is paid to how the new media technologies are used and experienced in everyday life. Here, innovative approaches such as the use of data donations can both aid the ‘platform observability’ 16 that is essential to accountability, and ensure that our research involves the perspectives of diverse audiences.

Jean Burgess is Professor of Digital Media at the School of Communication and Digital Media Research Centre (DMRC), Queensland University of Technology, Brisbane, Queensland Australia; and Associate Director at the Australian Research Council Centre of Excellence for Automated Decision-Making and Society (ADM+S), Melbourne, Victoria, Australia .

Computational social science

Claudia Wagner

Computational social science has emerged as a discipline that leverages computational methods and new technologies to collect, model and analyse digital behavioural data in natural environments or in large-scale designed experiments, and combine them with other data sources (such as survey data).

While the community made critical progress in enhancing our understanding about empirical phenomena such as the spread of misinformation 17 and the role of algorithms in curating misinformation 18 , it has focused less on questions about the quality and accessibility of data, the validity, reliability and reusability of measurements, the potential consequences of measurements and the connection between data, measurement and theory.

I see the following opportunities to address these issues.

First, we need to establish privacy-preserving, shared data infrastructures that collect and triangulate survey data with scientifically motivated organic or designed observational data from diverse populations 19 . For example, longitudinal online panels in which participants allow researchers to track their web browsing behaviour and link these traces to their survey answers will not only facilitate substantive research on societal questions but also enable methodological research (for example, on the quality of different data sources and measurement models), and contribute to the reproducibility of computational social science research.

Second, best practices and scientific infrastructures are needed for supporting the development, evaluation and re-use of measurements and the critical reflection on potentially harmful consequences of measurements 20 . Social scientists have developed such best practices and infrastructural support for survey measurements to avoid using instruments for which the validity is unclear or even questionable, and to support the re-usability of survey scales. I believe that practices from survey methodology and other domains, such as the medical industry, can inform our thinking here.

Finally, the fusion of algorithmic and human behaviour invites us to rethink the various ways in which data, measurements and social theories can be connected 20 . For example, product recommendations that users receive are based on measurements of users’ interests and needs: however, users and measurements are not only influenced by those recommendations, but also influence them in turn. As a community we need to develop research designs and environments that help us to systematically enhance our understanding of those feedback loops.

Claudia Wagner is Head of Computational Social Science Department at GESIS – Leibniz Institute for the Social Sciences, Köln, Germany; Professor for Applied Computational Social Sciences at RWTH Aachen University, Aachen, Germany; and External Faculty Member of the Complexity Science Hub, Vienna, Austria .


Daniel S. Nagin

Disciplinary silos in path-breaking science are disappearing. Criminology has had a longstanding tradition of interdisciplinarity, but mostly in the form of an uneasy truce of research from different disciplines appearing side-by-side in leading journals — a scholarly form of parallel play. In the future, this must change because the big unsolved challenges in criminology will require cooperation among all of the social and behavioural sciences.

These challenges include formally merging the macro-level themes emphasized by sociologists with the micro-, individual-level themes emphasized by psychologists and economists. Initial steps have been made by economists who apply game theory to model crime-relevant social interactions, but much remains to be done in building models that explain the formation and destruction of social trust, collective efficacy and norms, as they relate to legal definitions of criminal behaviour.

A second opportunity concerns the longstanding focus of criminology on crimes involving the physical taking of property and interpersonal physical violence. These crimes are still with us, but — as the daily news regularly reports — the internet has opened up broad new frontiers for crime that allow for thefts of property and identities at a distance, forms of extortion and human trafficking at a massive scale (often involving untraceable transactions using financial vehicles such as bitcoin) and interpersonal violence without physical contact. This is a new and largely unexplored frontier for criminological research that criminologists should dive into in collaboration with computer scientists who already are beginning to troll these virgin scholarly waters.

The final opportunity I will note also involves drawing from computer science, the primary home of what has come to be called machine learning. It is important that new generations of criminologists become proficient with machine learning methods and also collaborate with its creators. Machine learning and related statistical methods have wide applicability in both the traditional domains of criminological research and new frontiers. These include the use of prediction tools in criminal justice decision-making, which can aid in crime detection, and the prevention and measuring of crime both online and offline, but also have important implications for equity and fairness due to their consequential nature.

Daniel S. Nagin is Teresa and H. John Heinz III University Professor of Public Policy and Statistics at the Heinz College of Information Systems and Public Policy, Carnegie Mellon University, Pittsburgh, PA, USA .

Behavioural economics

Bertil Tungodden

Behavioural and experimental economics have transformed the field of economics by integrating irrationality and nonselfish motivation in the study of human behaviour and social interaction. A richer foundation of human behaviour has opened many new exciting research avenues, and I here highlight three that I find particularly promising.

Economists have typically assumed that preferences are fixed and stable, but a growing literature, combining field and laboratory experimental approaches, has provided novel evidence on how the social environment shapes our moral and selfish preferences. It has been shown that prosocial role models make people less selfish 21 , that early-childhood education affects the fairness views of children 22 and that grit can be fostered in the correct classroom environment 23 . Such insights are important for understanding how exposure to different institutions and socialization processes influence the intergenerational transmission of preferences, but much more work is needed to gain systematic and robust evidence on the malleability of the many dimensions that shape human behaviour.

The moral mind is an important determinant of human behaviour, but our understanding of the complexity of moral motivation is still in its infancy. A growing literature, using an impartial spectator design in which study participants make consequential choices for others, has shown that people often disagree on what is morally acceptable. An important example is how people differ in their view of what is a fair inequality, ranging from the libertarian fairness view to the strict egalitarian fairness view 24 , 25 . An exciting question for future research is whether such moral differences reflect a concern for other moral values, such as freedom, or irrational considerations.

A third exciting development in behavioural and experimental economics is the growing set of global studies on the foundations of human behaviour 26 , 27 . It speaks to the major concern in the social sciences that our evidence is unrepresentative and largely based on studies with samples from Western, educated, industrialized, rich and democratic societies 28 . The increased availability of infrastructure for implementing large-scale experimental data collections and methodological advances carry promise that behavioural and experimental economic research will broaden our understanding of the foundations of human behaviour in the coming years.

Bertil Tungodden is Professor and Scientific Director of the Centre of Excellence FAIR at NHH Norwegian School of Economics, Bergen, Norway .

Development economics

Esther Duflo

The past three decades have been a wonderful time for development economics. The number of scholars, the number of publications and the visibility of the work has dramatically increased. Development economists think about education, health, firm growth, mental health, climate, democratic rules and much more. No topic seems off limits!

This progress is intimately connected with the explosion of the use of randomized controlled trials (RCTs) and, more generally, with the embrace of careful causal identification. RCTs have markedly transformed development economics and made it the field that it is today.

The past three decades (until the COVID-19 crisis) have also been very good for improving the circumstances of low-income people around the world: poverty rates have fallen; school enrolment has increased; and maternal and infant mortality has been halved. Although I would not dare imply that the two trends are causally related, one of the reasons for these improvements in the quality of life — even in countries where economic growth has been slow — is the greater focus on pragmatic solutions to the fundamental problems faced by people with few resources. In many countries, development economics researchers (particularly those working with RCTs) have been closely involved with policy-makers, helping them to develop, implement and test these solutions. In turn, this involvement has been a fertile ground for new questions, which have enriched the field.

I imagine future change will, once again, come from an unexpected place. One possible driver of innovation will come from this meeting between the requirements of policy and the intellectual ambition of researchers. This means that the new challenges of our planet must (and will) become the new challenges of development economics. Those challenges are, I believe, quite clear: rethinking social protection to be better prepared to face risks such as the COVID-19 pandemic; mitigating, but unfortunately also adapting to, climate changes; curbing pollution; and addressing gender, racial and ethnic inequality.

To address these critical issues, I believe the field will continue to rely on RCTs, but also start using more creatively (descriptively or in combination with RCTs) the huge amount of data that is increasingly available as governments, even in poor countries, digitize their operations. I cannot wait to be surprised by what comes next.

Esther Duflo is The Abdul Latif Jameel Professor of Poverty Alleviation and Development Economics at the Department of Economics, Massachusetts Institute of Technology, Cambridge MA, USA; and cofounder and codirector of the Abdul Latif Jameel Poverty Action Lab (J-PAL) .

Political science

Janet M. Box-Steffensmeier

Political science remains one of the most pluralistic disciplines and we are on the move towards engaged pluralism. This takes us beyond mere tolerance to true, sincere engagement across methods, methodologies, theories and even disciplinary boundaries. Engaged pluralism means doing the hard work of understanding our own research from the multiple perspectives of others.

More data are being collected on human behaviour than ever before and our advances in methods better address the inherent interdependencies of the data across time, space and context. There are new ways to measure human behaviour via text, image and video. Data creation can even go back in time. All these advancements bode well for the potential to better understand and predict behaviour. This ‘data century’ and ‘golden age of methods’ also hold the promise to bridge, not divide, political science, provided that there is engaged methodological pluralism. Qualitative methods provide unique insights and perspectives when joined with quantitative methods, as does a broader conception of the methodologies underlying and launching our research.

I remain a strong proponent of leveraging dynamics and focusing on heterogeneity in our research questions to advance our disciplines. Doing so brings in an explicit perspective of comparison around similarity and difference. Our questions, hypotheses and theories are often made more compelling when considering the dynamics and heterogeneity that emerges when thinking about time and change.

Striving for a better understanding of gender, race and ethnicity is driving deeper and fuller understandings of central questions in the social sciences. The diversity of the research teams themselves across gender, sex, race, ethnicity, first-generation status, religion, ideology, partisanship and cultures also pushes advancement. One area that we need to better support is career diversity. Supporting careers in government, non-profit organizations and industry, as well as academia, for graduate students will enhance our disciplines and accelerate the production of knowledge that changes the world.

Engaged pluralism remains a foundational key to advancement in political science. Engaged pluralism supports critical diversity, equity and inclusion work, strengthens political scientists’ commitment to democratic principles, and encourages civic engagement more broadly. It is an exciting time to be a social scientist.

Janet M. Box-Steffensmeier is Vernal Riffe Professor of Political Science, Professor of Sociology (courtesy) and Distinguished University Professor at the Department of Political Science, Ohio State University, Columbus OH, USA; and immediate past President of the American Political Science Association .

Cognitive psychology

Andrew Perfors

Cognitive psychology excels at understanding questions whose problem-space is well-defined, with precisely specified theories that transparently map onto thoroughly explored experimental paradigms. That means there is a vast gulf between the current state of the art and the richness and complexity of cognition in the real world. The most exciting open questions are about how to bridge that gap without sacrificing rigour and precision. This requires at least three changes.

First, we must move beyond typical experiments. Stimuli must become less artificial, with a naturalistic structure and distribution. Similarly, tasks must become more ecologically valid: less isolated, with more uncertainty, embedded in natural situations and over different time-scales.

Second, we must move beyond considering individuals in isolation. We live in a rich social world and an environment that is heavily shaped by other humans. How we think, learn and act is deeply affected by how other people think and interact with us; cognitive science needs to engage with this more.

Third, we must move beyond the metaphor of humans as computers. Our cognition is deeply intertwined with our emotions, motivations and senses. These are more than just parameters in our minds; they have a complexity and logic of their own, and interact in nontrivial ways with each other and more typical cognitive domains such as learning, reasoning and acting.

How do we make progress on these steps? We need reliable real-world data that are comparable across people and situations, reflect the cognitive processes involved and are not changed by measurement. Technology may help us with this, but challenges surrounding privacy and data quality are huge. Our models and analytic approaches must also grow in complexity — commensurate with the growth in problem and data complexity — without becoming intractable or losing their explanatory power.

Success in this endeavour calls for a different kind of science that is not centred around individual laboratories or small stand-alone projects. The biggest advances will be achieved on the basis of large, rich, real-world datasets from different populations, created and analysed in collaborative teams that span multiple domains, fields and approaches. This requires incentive structures that reward team-focused, slower science and prioritize the systematic construction of reliable knowledge over splashy findings.

Andrew Perfors is Associate Professor and Deputy Director of the Complex Human Data Hub, University of Melbourne, Melbourne, Victoria, Australia .

Cultural and social psychology

Ying-yi Hong

I am writing this at an exceptional moment in human history. For two years, the world has faced the COVID-19 pandemic and there is no end in sight. Cultural and social psychology are uniquely equipped to understand the COVID-19 pandemic, specifically examining how people, communities and countries are dealing with this extreme global crisis — especially at a time when many parts of the world are already experiencing geopolitical upheaval.

During the pandemic, and across different nations and regions, a diverse set of strategies (and subsequent levels of effectiveness) were used to curb the spread of the disease. In the first year of the pandemic, research revealed that some cultural worldviews — such as collectivism (versus individualism) and tight (versus loose) norms — were positively associated with compliance with COVID-19 preventive measures as well as with fewer infections and deaths 29 , 30 . These worldview differences arguably stem from different perspectives on abiding to social norms and prioritizing the collective welfare over an individual’s autonomy and liberty. Although in the short term it seems that a collectivist or tight worldview has been advantageous, it is unclear whether this will remain the case in the long term. Cultural worldviews are ‘tools’ that individuals use to decipher the meaning of their environment, and are dynamic rather than static 31 . Future research can examine how cultural worldviews and global threats co-evolve.

The pandemic has also amplified the demarcation of national, political and other major social categories. On the one hand, identification with some groups (for example, national identity) was found to increase in-group care and thus a greater willingness to sacrifice personal autonomy to comply with COVID-19 measures 32 . On the other hand, identification with other groups (for example, political parties) widened the ideological divide between groups and drove opposing behaviours towards COVID-19 measures and health outcomes 33 . As we are facing climate change and other pressing global challenges, understanding the role of social identities and how they affect worldviews, cognition and behaviour will be vital. How can we foster more inclusive (versus exclusive) identities that can unite rather than divide people and nations?

Ying-yi Hong is Choh-Ming Li Professor of Management and Associate Dean (Research) at the Department of Management, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China .

Developmental psychology

Alison Gopnik

Developmental psychology is similar to the kind of book or band that, paradoxically, everyone agrees is underrated. On the one hand, children and the people who care for them are often undervalued and overlooked. On the other, since Piaget, developmental research has tackled some of the most profound philosophical questions about every kind of human behaviour. This will only continue into the future.

Psychologists increasingly recognize that the minds of children are not just a waystation or an incomplete version of adult minds. Instead, childhood is a distinct evolutionarily adaptive phase of an organism, with its own characteristic cognitions, emotions and motivations. These characteristics of childhood reflect a different agenda than those of the adult mind — a drive to explore rather than exploit. This drive comes with motivations such as curiosity, emotions such as wonder and surprise and remarkable cognitive learning capacities. A new flood of research on curiosity, for example, shows that children actively seek out the information that will help them to learn the most.

The example of curiosity also reflects the exciting prospects for interdisciplinary developmental science. Machine learning is increasingly using children’s learning as a model, and developmental psychologists are developing more precise models as a result. Curiosity-based AI can illuminate both human and machine intelligence. Collaborations with biology are also exciting: for example, in work on evolutionary ‘life history’ explanations of the effects of adverse experiences on later life, and new research on plasticity and sensitive periods in neuroscience. Finally, children are at the cutting edge of culture, and developmental psychologists increasingly conduct a much wider range of cross-cultural studies.

But perhaps the most important development is that policy-makers are finally starting to realize just how crucial children are to important social issues. Developmental science has shown that providing children with the care that they need can decrease poverty, inequality, disease and violence. But that care has been largely invisible to policy-makers and politicians. Understanding scientifically how caregiving works and how to support it more effectively will be the most important challenge for developmental psychology in the next century.

Alison Gopnik is Professor of Psychology and Affiliate Professor of Philosophy at the Department of Psychology, University of California at Berkeley, Berkeley, CA, USA .

Science of science

Cassidy R. Sugimoto

Why study science? The goal of science is to advance knowledge to improve the human condition. It is, therefore, essential that we understand how science operates to maximize efficiency and social good. The metasciences are fields that are devoted to understanding the scientific enterprise. These fields are distinguished by differing epistemologies embedded in their names: the philosophy, history and sociology of science represent canonical metasciences that use theories and methods from their mother disciplines. The ‘science of science’ uses empirical approaches to understand the mechanisms of science. As mid-twentieth-century science historian Derek de Solla Price observed, science of science allows us to “turn the tools of science on science itself” 34 .

Contemporary questions in the science of science investigate, inter alia, catalysts of discovery and innovation, consequences of increased access to scientific information, role of teams in knowledge creation and the implications of social stratification on the scientific enterprise. Investigation of these issues require triangulation of data and integration across the metasciences, to generate robust theories, model on valid assumptions and interpret results appropriately. Community-owned infrastructure and collective venues for communication are essential to achieve these goals. The construction of large-scale science observatories, for example, would provide an opportunity to capture the rapidly expanding dataverse, collaborate and share data, and provide nimble translations of data into information for policy-makers and the scientific community.

The topical foci of the field are also undergoing rapid transformation. The expansion of datasets enables researchers to analyse a fuller population, rather than a narrow sample that favours particular communities. The field has moved from an elitist focus on ‘success’ and ‘impact’ to a more-inclusive and prosopographical perspective. Conversations have shifted from citations, impact factors and h -indices towards responsible indicators, diversity and broader impacts. Instead of asking ‘how can we predict the next Nobel prize winner?’, we can ask ‘what are the consequences of attrition in the scientific workforce?’. The turn towards contextualized measurements that use more inclusive datasets to understand the entire system of science places the science of science in a ripe position to inform policy and propel us towards a more innovative and equitable future.

Cassidy R. Sugimoto is Professor and Tom and Marie Patton School Chair, School of Public Policy, Georgia Institute of Technology, Atlanta, GA, USA .

Sari Hanafi

In the past few years, we have been living through times in which reasonable debate has become impossible. Demagogical times are driven by the vertiginous rise of populism and authoritarianism, which we saw in the triumph of Donald Trump in the USA and numerous other populist or authoritarian leaders in many places around the globe. There are some pressing tasks for sociology that can be, in brief, reduced to three.

First, fostering democracy and the democratization process requires disentangling the constitutive values that compose the liberal political project (personal liberty, equality, moral autonomy and multiculturalism) to address the question of social justice and to accommodate the surge in people’s religiosity in many parts in the globe.

Second, the struggle for the environment is inseparable from our choice of political economy, and from the nature of our desired economic system — and these connections between human beings and nature have never been as intimate as they are now. Past decades saw rapid growth that was based on assumptions of the long-term stability of the fixed costs of raw materials and energy. But this is no longer the case. More recently, financial speculation intensified and profits shrunk, generating distributional conflicts between workers, management, owners and tax authorities. The nature of our economic system is now in acute crisis.

The answer lies in a consciously slow-growing new economy that incorporates the biophysical foundations of economics into its functioning mechanisms. Society and nature cannot continue to be perceived each as differentiated into separate compartments. The spheres of nature, culture, politics, social, economy and religion are indeed traversed by common logics that allow a given society to be encompassed in its totality, exactly as Marcel Mauss 35 did. The logic of power and interests embodied in ‘ Homo economicus ’ prevents us from being able to see the potentiality of human beings to cultivate gift-giving practices as an anthropological foundation innate within social relationships.

Third, there are serious social effects of digitalized forms of labour and the trend of replacing labour with an automaton. Even if digital labour partially reduces the unemployment rate, the lack of social protection for digital labourers would have tremendous effects on future generations.

In brief, it is time to connect sociology to moral and political philosophy to address fundamentally post-COVID-19 challenges.

Sari Hanafi is Professor of Sociology at the American University of Beirut, Beirut, Lebanon; and President of the International Sociological Association .

Environmental studies (climate change)

Yasuko Kameyama

Climate change has been discussed for more than 40 years as a multilateral issue that poses a great threat to humankind and ecosystems. Unfortunately, we are still talking about the same issue today. Why can’t we solve this problem, even though scientists pointed out its importance and urgency so many years ago?

These past years have been spent trying to prove the causal relationship between an increase in greenhouse gas concentrations, global temperature rise and various extreme weather events, as well as developing and disseminating technologies needed to reduce emissions. All of these tasks have been handled by experts in the field. At the same time, the general public invested little time in this movement, probably expecting that the problem would be solved by experts and policy-makers. But that has not been the case. No matter how much scientists have emphasized the crisis of climate change or how many clean energy technologies engineers have developed, society has resisted making the necessary changes. Now, the chances of keeping the temperature rise within 1.5 °C of pre-industrial levels — the goal necessary to minimize the effects of climate change — are diminishing.

We seem to finally be realizing the importance of social scientific knowledge. People need to take scientific information seriously for clean technology to be quickly diffused. Companies are more interested in investing in newer technology and product development when they know that their products will sell. Because environmental problems are caused by human activity, research on human behaviour is indispensable in solving these problems.

Reports by the Intergovernmental Panel on Climate Change (IPCC) have not devoted many pages to the areas of human awareness and behaviour ( ). The IPCC’s Third Working Group, which deals with mitigation measures, has partially spotlighted research on institutions, as well as on concepts such as fairness. People’s perception of climate change and the relationship between perception and behavioural change differ depending on the country, societal structure and culture. Additional studies in these areas are required and, for that purpose, more studies from regions such as Asia, Africa and South America, which are underrepresented in terms of the number of academic publications, are particularly needed.

Yasuko Kameyama is Director, Social Systems Division, National Institute for Environmental Studies, Tsukuba, Japan .

Sustainability (food systems)

Mario Herrero

The food system is in dire straits. Food demand is unprecedented, while malnutrition in all its forms (obesity, undernutrition and micronutrient deficiencies) is rampant. Environmental degradation is pervasive and increasing, and if it continues, the comfort zone for humanity and ecosystems to thrive will be seriously compromised. From bruises and shapes to sell-by dates, we tend to find many reasons to exclude perfectly edible food from our plates, whereas in other cases not enough food reaches hungry mouths owing to farming methods, pests and lack of adequate storage. These types of inequalities are common and — together with inherent perverse incentives that maintain the status quo of how we produce, consume and waste increasingly cheap and processed food — they are launching us towards a disaster.

We are banking on a substantial transformation of the food system to solve this conundrum. Modifying food consumption and waste patterns are central to the plan for achieving healthier diets, while increasing the sustainability of our food system. This is also an attractive policy proposition, as it could lead to gains in several sectors. Noncommunicable diseases such as obesity, diabetes and heart disease could decline, while reducing the effects of climate change, deforestation, excessive water withdrawals and biodiversity loss, and their enormous associated — and largely unaccounted — costs.

Modifying our food consumption and waste patterns is very hard, and unfortunately we know very little about how to change them at scale. Yes, many pilots and small examples exist on pricing, procurement, food environments and others, but the evidence is scarce, and the magnitude of the change required demands an unprecedented transdisciplinary research agenda. The problem is at the centre of human agency and behaviour, embodying culture, habits, values, social status, economics and all aspects of agri-food systems. Certainly, one of the big research areas for the next decade if we are to reach the Sustainable Development Goals leaving no one behind.

Mario Herrero is Professor, Cornell Atkinson scholar and Nancy and Peter Meinig Family Investigator in the Life Sciences at the Department of Global Development, College of Agriculture and Life Sciences and Cornell Atkinson Center for Sustainability, Cornell University, Ithaca, NY, USA .

Cultural evolution

Laurel Fogarty

Humans are the ultimate ‘cultural animals’. We are innovative, pass our cultures to one another across generations and build vast self-constructed environments that reflect our cultural biases. We achieve things using our cultural capacities that are unimaginable for any other species on earth. And yet we have only begun to understand the dynamics of cultural change, the drivers of cultural complexity or the ways that we adapt culturally to changing environments. Scholars — anthropologists, archaeologists and sociologists — have long studied culture, aiming to describe and understand its staggering diversity. The relatively new field of cultural evolution has different aims, one of the most important of which is to understand the mechanics in the background — what general principles, if any, govern human cultural change?

Although the analogy of culture as an evolutionary process has been made since at least the time of Darwin 36 , 37 , cultural evolution as a robust field of study is much younger. From its beginnings with the pioneering work of Cavalli-Sforza & Feldman 38 , 39 , 40 and Boyd & Richerson 41 , 42 , the field of cultural evolution has been heavily theoretical. It has drawn on models from genetic evolution 40 , 43 , 44 , 45 , ecology 46 , 47 and epidemiology 40 , 48 , extending and adapting them to account for unique and important aspects of cultural transmission. Indeed, in its short life, the field of cultural evolution has largely been dominated by a growing body of theory that ensured that the fledgling field started out on solid foundations. Because it underpins and makes possible novel applications of cultural evolutionary ideas, theoretical cultural evolution’s continued development is not only crucial to the field’s growth but also represents some of its most exciting future work.

One of the most urgent tasks for cultural evolution researchers in the next five years is to develop, alongside its theoretical foundations, robust principles of application 49 , 50 , 51 . In other words, it is vital to develop our understanding of what we can — and, crucially, cannot — infer from different types of cultural data. Where do we draw those boundaries and how can we apply cultural evolutionary theory to cultural datasets in a principled way? The tandem development of robust theory and principled application has the potential to strengthen cultural evolution as a robust, useful and ground-breaking inferential science of human behaviour.

Laurel Fogarty is Senior Scientist at the Department of Human Behaviour, Ecology, and Culture, Max Planck Institute for Evolutionary Anthropology, Leipzig, Germany .

Over the past decade, research using molecular genetic data has confirmed one of the main conclusions of twin studies: all human behaviour is partly heritable 52 , 53 . Attempts at examining the link between genetics and behaviour have been met with concerns that the findings can be abused to justify discrimination — and there are good historical grounds for these concerns. However, these findings also show that ignoring the contribution of genes to variation in human behaviour could be detrimental to a complete understanding of social phenomena, given the complex ways that genes and environment interact.

Uncovering these complex pathways has become feasible only recently thanks to rapid technological progress reducing the costs of genotyping. Sample sizes in genome-wide association studies (GWAS) have risen from tens of thousands to millions in the past decade, reporting thousands of genetic variants associated with different behaviours 54 , 55 , 56 , 57 . New ways to use GWAS results have emerged, the most important one arguably being a method to aggregate the additive effects of many genetic variants into a ‘polygenic index’ (PGI) (also known as a ‘polygenic score’) that summarizes an individual’s genetic propensity towards a trait or behaviour 58 , 59 . Being aggregate measures, PGIs capture a much larger share of the variance in the trait of interest compared to individual genetic variants 60 . Thus, they have paved the way for follow-up studies with smaller sample sizes but deeper phenotyping compared to the original GWAS, allowing researchers to, for example, analyse the channels through which genes operate 61 , 62 , how they interact with the environment 63 , 64 , and account for confounding bias and boost statistical power by controlling for genetic effects 65 , 66 .

Useful as they are, PGIs and the GWAS that they are based on can suffer from confounding due to environmental factors that correlate with genotypes, such as population stratification, indirect effect from relatives or assortative mating 67 . Now that the availability of genetic data enables large-scale within-family GWAS, the next big thing in behaviour genetic research will be disentangling these sources 68 . While carrying the progress further, it is important that the field prioritizes moving away from its currently predominant Eurocentric bias by extending data collection and analyses to individuals of non-European ancestries, as the exclusion of non-European ancestries from genetic research has the potential to exacerbate health disparities 69 . Researchers should also be careful to communicate their findings clearly and responsibly to the public and guard against their misappropriation by attempts to fuel discriminatory action and discourse 70 .

Aysu Okbay is Assistant Professor at the Department of Economics, School of Business and Economics, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands .

Cognitive neuroscience

Anna C. Nobre

Since the ‘decade of the brain’ in the 1990s, ingenuity in cognitive neuroscience has focused on measuring and analysing brain signals. Adapting tools from statistics, engineering, computer science, physics and other disciplines, we studied activity, states, connectivity, interactions, time courses and dynamics in brain regions and networks. Unexpected findings about the brain yielded important insights about the mind.

Now is a propitious time to upgrade the brain–mind duumvirate to a brain–mind–behaviour triumvirate. Brain and mind are embodied, and their workings are expressed through various effectors. Yet, experimental tasks typically use simple responses to capture complex psychological functions. Often, a button press — with its limited dimensions of latency and accuracy — measures anticipating, focusing, evaluating, choosing, reflecting or remembering. Researchers venturing beyond such simple responses are uncovering how the contents of mind can be studied using various continuous measures, such as pupil diameter, gaze shifts and movement trajectories.

Most tasks also restrict participants’ movements to ensure experimental control. However, we are learning that principles of cognition derived in artificial laboratory contexts can fail to generalize to natural behaviour. Virtual reality should prove a powerful methodology. Participants can behave naturally, and experimenters can control stimulation and obtain quality measures of gaze, hand and body movements. Noninvasive neurophysiology methods are becoming increasingly portable. Exciting immersive brain–mind–behaviour studies are just ahead.

The next necessary step is out of the academic bubble. Today the richest data on human behaviour belong to the information and technology industries. In our routines, we contribute data streams through telephones, keyboards, watches, vehicles and countless smart devices in the internet of things. These expose properties such as processing speed, fluency, attention, dexterity, navigation and social context. We supplement these by broadcasting feelings, attitudes and opinions through social media and other forums. The richness and scale of the resulting big data offer unprecedented opportunities for deriving predictive patterns that are relevant to understanding human cognition (and its disorders). The outcomes can then guide further hypothesis-driven experimentation. Cognitive neuroscience is intrinsically collaborative, combining a broad spectrum of disciplines to study the mind. Its challenge now is to move from a multidisciplinary to a multi-enterprise science.

Anna C. Nobre is Chair in Translational Cognitive Neuroscience at the Department of Experimental Psychology, University of Oxford, UK; and Director of Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, Department of Psychiatry, University of Oxford, UK .

Social and affective neuroscience

Tatia M. C. Lee

Social and affective neuroscience is a relatively new, but rapidly developing, field of neuroscience. Social and affective neuroscience research takes a multilevel approach to make sense of socioaffective processes, focusing on macro- (for example, social environments and structures), meso- (for example, social interactions) and micro (for example, socio-affective neural processes and perceptions)-level interactions. Because the products of these interactions are person-specific, the conventional application of group-averaged mechanisms to understand the brain in a socioemotional context has been reconsidered. Researchers turn to ecologically valid stimuli (for example, dynamic and virtual reality instead of static stimuli) and experimental settings (for example, real-time social interaction) 71 to address interindividual differences in social and affective responses. At the neural level, there has been a shift of research focus from local neural activations to large-scale synchronized interactions across neural networks. Network science contributes to the understanding of dynamic changes of neural processes that reflect the interactions and interconnection of neural structures that underpin social and affective processes.

We are living in an ever-changing socioaffective world, full of unexpected challenges. The ageing population and an increasing prevalence of depression are social phenomena on a global scale. Social isolation and loneliness caused by measures to tackle the current pandemic affect physical and psychological well-being of people from all walks of life. These global issues require timely research efforts to generate potential solutions. In this regard, social and affective neuroscience research using computational modelling, longitudinal research designs and multimodal data integration will create knowledge about the basis of adaptive and maladaptive social and affective neurobehavioural processes and responses 72 , 73 , 74 . Such knowledge offers important insights into the precise delineation of brain–symptom relationships, and hence the development of prediction models of cognitive and socioaffective functioning (for example, refs. 75 , 76 ). Therefore, screening tools for identifying potential vulnerabilities can be developed, and timely and precise interventions can be tailored to meet individual situations and needs. The translational application of social and affective neuroscience research to precision medicine (and policy) is experiencing unprecedented demand, and such demand is met with unprecedented clinical and research capabilities.

Tatia M. C. Lee is Chair Professor of Psychology at the State Key Laboratory of Brain and Cognitive Sciences and Laboratory of Neuropsychology and Human Neuroscience, The University of Hong Kong, Hong Kong Special Administrative Region, China .

Maurizio Corbetta

Focal brain disorders, including stroke, trauma and epilepsy, are the main causes of disability and loss of productivity in the world, and carry a cumulative cost in Europe of about € 500 billion per year 77 . The disease process affects a specific circuit in the brain by turning it off (as in stroke) or pathologically turning it on (as in epilepsy). The cause of the disabling symptoms is typically local circuit damage. However, there is now overwhelming evidence that symptoms reflect not only local pathology but also widespread (network) functional abnormalities. For instance, in stroke, an average lesion — the size of a golf ball — typically alters the activity of on average 25% of all brain connections. Furthermore, normalization of these abnormalities correlates with optimal recovery of function 78 , 79 .

One exciting treatment opportunity is ‘circuit-based’ stimulation: an ensemble of methods (optogenetic, photoacoustic, electrochemical, magnetic and electrical) that have the potential to normalize activity. Presently, this type of therapy is limited by numerous factors, including a lack of knowledge about the circuits, the difficulty of mapping these circuits in single patients and, most importantly, a principled understanding of where and how to stimulate to produce functional recovery.

A possible solution lies in a strategy (developed with G. Deco, M. Massimini and M. Sanchez-Vivez) that starts with an in-depth assessment of behaviour and physiological studies of brain activity to characterize the affected circuits and associated patterns of functional abnormalities. Such a multi-dimensional physiological map of a lesioned brain can be then fed to biologically realistic in silico models 80 . A model of a lesioned brain affords the opportunity to explore, in an exhaustive way, different kinds of stimulation to normalize faulty activity. Once a suitable protocol is found it can be exported first to animal models, and then to humans. Stimulation alone will not be enough. Pairing with behavioural training (rehabilitation) will stabilize learning and normalize connections.

The ability to interface therapy (stimulation, rehabilitation and drugs) with brain signals or other kinds of behavioural sensor offers another exciting opportunity, to open the ‘brain’s black box’. Most current treatments in neuroscience are given with no regard to their effect on the underlying brain signals or behaviour. Giving patients conscious access to their own brain signals may substantially enhance recovery, as the brain is now in the position to use its own powerful connections and learning mechanisms to cure itself.

Maurizio Corbetta is Professor and Chair of Neurology at the Department of Neuroscience and Director of the Padova Neuroscience Center (PNC), University of Padova, Italy; and Principal Investigator at the Venetian Institute of Molecular Medicine (VIMM), Padova, Italy .

Merete Nordentoft

Schizophrenia and related psychotic disorders are among the costliest and most debilitating disorders in terms of personal sufferings for those affected, for relatives and for society 81 . These disorders often require long-term treatment and, for a substantial proportion of the patients, the outcomes are poor. This has motivated efforts to prevent long-lasting illness by early intervention. The time around the onset of psychotic disorders is associated with an increased risk of suicide, of loss of affiliation with the labour market, and social isolation and exclusion. Therefore, prevention and treatment of first-episode psychosis will be a key challenge for the future.

There is now solid evidence proving that early intervention services can improve clinical outcomes 82 . This was first demonstrated in the large Danish OPUS trial, in which OPUS treatment — consisting of assertive outreach, case management and family involvement, provided by multidisciplinary teams over a two-year period — was shown to improve clinical outcomes 83 . Moreover, it was also cost-effective 84 . Although the positive effects on clinical outcomes were not sustainable after five and ten years, there was a long-lasting effect on use of supported housing facilities (indicating improved ability to live independently) 85 . Later trials proved that it is possible to maintain the positive clinical outcomes by extending the services to five years or by offering a stepped care model with continued intensive care for the patients who are most impaired 86 . However, even though both clinical and functional outcomes (such as labour market affiliation) can be improved by evidence-based treatments 82 , a large group of patients with first-episode psychosis still have psychotic symptoms after ten years. Thus, there is still an urgent need for identification of new and better options for treatment.

Most probably, some of the disease processes start long before first onset of a psychotic disorder. Thus, identifying disease mechanisms and possibilities for intervention before onset of psychosis will be extremely valuable. Evidence for effective preventive interventions is very limited, and the most burning question — of how to prevent psychosis — is still open.

The early intervention approach is also promising also for other disorders, including bipolar affective disorder, depression, anxiety, eating disorders, personality disorders, autism and attention-deficient hyperactivity disorder.

Merete Nordentoft is Clinical Professor at the Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark; and Principal Investigator, CORE - Copenhagen Research Centre for Mental Health, Mental Health Centre Copenhagen, Copenhagen University Hospital, Copenhagen, Denmark .


Gabriel M. Leung

In a widely anthologized article from the business field of marketing, Levitt 87 pointed out that often industries failed to grow because they suffered from a limited market view. For example, Kodak went bust because it narrowly defined itself as a film camera company for still photography rather than one that should have been about imaging writ large. If it had had that strategic insight, it would have exploited and invested in digital technologies aggressively and perhaps gone down the rather more successful path of Fujifilm — or even developed into territory now cornered by Netflix.

The raison d’être of epidemiology has been to provide a set of robust scientific methods that underpin public health practice. In turn, the field of public health has expanded to fulfil the much-wider and more-intensive demands of protecting, maintaining and promoting the health of local and global populations, intergenerationally. At its broadest, the mission of public health should be to advance social justice towards a complete state of health.

Therefore, epidemiologists should continue to recruit and embrace relevant methodology sets that could answer public health questions, better and more efficiently. For instance, Davey Smith and Ebrahim 88 described how epidemiology adapted instrumental variable analysis that had been widely deployed in econometrics to fundamentally improve causal inference in observational epidemiology. Conversely, economists have not been shy in adopting the randomized controlled trial design to answer questions of development, and have recognized it with a Nobel prize 89 . COVID-19 has brought mathematical epidemiology or modelling to the fore. The foundations of the field borrowed heavily from population dynamics and ecological theory.

In future, classical epidemiology, which has mostly focused on studying how the exposome associates with the phenome, needs to take into simultaneous account the other layers of the multiomics universe — from the genome to the metabolome to the microbiome 90 . Another area requiring innovative thinking concerns how to harness big data to better understand human behaviour 91 . Finally, we must consider key questions that are amenable to epidemiologic investigation arising from the major global health challenges: climate change, harmful addictions and mental wellness. What new methodological tools do we need to answer these questions?

Epidemiologists must keep trying on new lenses that correct our own siloed myopia.

Gabriel M. Leung is Helen and Francis Zimmern Professor in Population Health at WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, LKS Faculty of Medicine, The University of Hong Kong; Chief Scientific Officer at Laboratory of Data Discovery for Health, Hong Kong Science and Technology Park; and Dean of Medicine at the University of Hong Kong, Hong Kong Special Administrative Region, China .

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Department of Political Science, Ohio State University, Columbus, OH, USA

School of Communication and Digital Media Research Centre (DMRC), Queensland University of Technology, Brisbane, Queensland, Australia

Australian Research Council Centre of Excellence for Automated Decision-Making and Society (ADM+S), Melbourne, Victoria, Australia

Department of Neuroscience and Padova Neuroscience Center (PNC), University of Padova, Padova, Italy

Venetian Institute of Molecular Medicine (VIMM), Padova, Italy

Annenberg School for Communication and Journalism, University of Southern California, Los Angeles, CA, USA

Microsoft Research New York, New York, NY, USA

École Normale Supérieure, Paris, France

Department of Economics, Massachusetts Institute of Technology, Cambridge, MA, USA

Department of Human Behavior, Ecology, and Culture, Max Planck Institute for Evolutionary Anthropology, Leipzig, Germany

Department of Psychology, University of California at Berkeley, Berkeley, CA, USA

American University of Beirut, Beirut, Lebanon

Department of Global Development, College of Agriculture and Life Sciences and Cornell Atkinson Center for Sustainability, Cornell University, Ithaca, NY, USA

Department of Management, The Chinese University of Hong Kong, Hong Kong, Hong Kong Special Administrative Region, China

Center for Social and Environmental Systems Research, Social Systems Division, National Institute for Environmental Studies, Tsukuba, Japan

State Key Laboratory of Brain and Cognitive Sciences and Laboratory of Neuropsychology and Human Neuroscience, The University of Hong Kong, Hong Kong, Hong Kong Special Administrative Region, China

WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong, Hong Kong Special Administrative Region, China

Laboratory of Data Discovery for Health, Hong Kong Science and Technology Park, Hong Kong, Hong Kong Special Administrative Region, China

Heinz College of Information Systems and Public Policy, Carnegie Mellon University, Pittsburgh, PA, USA

Department of Experimental Psychology, University of Oxford, Oxford, UK

Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, Department of Psychiatry, University of Oxford, Oxford, UK

CORE - Copenhagen Research Centre for Mental Health, Mental Health Centre Copenhagen, Copenhagen University Hospital, Copenhagen, Denmark

Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark

Department of Economics, School of Business and Economics, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands

Complex Human Data Hub, University of Melbourne, Melbourne, Victoria, Australia

ODID and SAME, University of Oxford, Oxford, UK

School of Public Policy, Georgia Institute of Technology, Atlanta, GA, USA

Centre of Excellence FAIR, NHH Norwegian School of Economics, Bergen, Norway

GESIS – Leibniz Institute for the Social Sciences, Köln, Germany

RWTH Aachen University, Aachen, Germany

Complexity Science Hub Vienna, Vienna, Austria

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Correspondence to Janet M. Box-Steffensmeier , Jean Burgess , Maurizio Corbetta , Kate Crawford , Esther Duflo , Laurel Fogarty , Alison Gopnik , Sari Hanafi , Mario Herrero , Ying-yi Hong , Yasuko Kameyama , Tatia M. C. Lee , Gabriel M. Leung , Daniel S. Nagin , Anna C. Nobre , Merete Nordentoft , Aysu Okbay , Andrew Perfors , Laura M. Rival , Cassidy R. Sugimoto , Bertil Tungodden or Claudia Wagner .

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Box-Steffensmeier, J.M., Burgess, J., Corbetta, M. et al. The future of human behaviour research. Nat Hum Behav 6 , 15–24 (2022).

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Social Media Use and Its Connection to Mental Health: A Systematic Review

Fazida karim.

1 Psychology, California Institute of Behavioral Neurosciences and Psychology, Fairfield, USA

2 Business & Management, University Sultan Zainal Abidin, Terengganu, MYS

Azeezat A Oyewande

3 Family Medicine, California Institute of Behavioral Neurosciences and Psychology, Fairfield, USA

4 Family Medicine, Lagos State Health Service Commission/Alimosho General Hospital, Lagos, NGA

Lamis F Abdalla

5 Internal Medicine, California Institute of Behavioral Neurosciences and Psychology, Fairfield, USA

Reem Chaudhry Ehsanullah

Safeera khan.

Social media are responsible for aggravating mental health problems. This systematic study summarizes the effects of social network usage on mental health. Fifty papers were shortlisted from google scholar databases, and after the application of various inclusion and exclusion criteria, 16 papers were chosen and all papers were evaluated for quality. Eight papers were cross-sectional studies, three were longitudinal studies, two were qualitative studies, and others were systematic reviews. Findings were classified into two outcomes of mental health: anxiety and depression. Social media activity such as time spent to have a positive effect on the mental health domain. However, due to the cross-sectional design and methodological limitations of sampling, there are considerable differences. The structure of social media influences on mental health needs to be further analyzed through qualitative research and vertical cohort studies.

Introduction and background

Human beings are social creatures that require the companionship of others to make progress in life. Thus, being socially connected with other people can relieve stress, anxiety, and sadness, but lack of social connection can pose serious risks to mental health [ 1 ].

Social media

Social media has recently become part of people's daily activities; many of them spend hours each day on Messenger, Instagram, Facebook, and other popular social media. Thus, many researchers and scholars study the impact of social media and applications on various aspects of people’s lives [ 2 ]. Moreover, the number of social media users worldwide in 2019 is 3.484 billion, up 9% year-on-year [ 3 - 5 ]. A statistic in Figure  1  shows the gender distribution of social media audiences worldwide as of January 2020, sorted by platform. It was found that only 38% of Twitter users were male but 61% were using Snapchat. In contrast, females were more likely to use LinkedIn and Facebook. There is no denying that social media has now become an important part of many people's lives. Social media has many positive and enjoyable benefits, but it can also lead to mental health problems. Previous research found that age did not have an effect but gender did; females were much more likely to experience mental health than males [ 6 , 7 ].

An external file that holds a picture, illustration, etc.
Object name is cureus-0012-00000008627-i01.jpg

Impact on mental health

Mental health is defined as a state of well-being in which people understand their abilities, solve everyday life problems, work well, and make a significant contribution to the lives of their communities [ 8 ]. There is debated presently going on regarding the benefits and negative impacts of social media on mental health [ 9 , 10 ]. Social networking is a crucial element in protecting our mental health. Both the quantity and quality of social relationships affect mental health, health behavior, physical health, and mortality risk [ 9 ]. The Displaced Behavior Theory may help explain why social media shows a connection with mental health. According to the theory, people who spend more time in sedentary behaviors such as social media use have less time for face-to-face social interaction, both of which have been proven to be protective against mental disorders [ 11 , 12 ]. On the other hand, social theories found how social media use affects mental health by influencing how people view, maintain, and interact with their social network [ 13 ]. A number of studies have been conducted on the impacts of social media, and it has been indicated that the prolonged use of social media platforms such as Facebook may be related to negative signs and symptoms of depression, anxiety, and stress [ 10 - 15 ]. Furthermore, social media can create a lot of pressure to create the stereotype that others want to see and also being as popular as others.

The need for a systematic review

Systematic studies can quantitatively and qualitatively identify, aggregate, and evaluate all accessible data to generate a warm and accurate response to the research questions involved [ 4 ]. In addition, many existing systematic studies related to mental health studies have been conducted worldwide. However, only a limited number of studies are integrated with social media and conducted in the context of social science because the available literature heavily focused on medical science [ 6 ]. Because social media is a relatively new phenomenon, the potential links between their use and mental health have not been widely investigated.

This paper attempt to systematically review all the relevant literature with the aim of filling the gap by examining social media impact on mental health, which is sedentary behavior, which, if in excess, raises the risk of health problems [ 7 , 9 , 12 ]. This study is important because it provides information on the extent of the focus of peer review literature, which can assist the researchers in delivering a prospect with the aim of understanding the future attention related to climate change strategies that require scholarly attention. This study is very useful because it provides information on the extent to which peer review literature can assist researchers in presenting prospects with a view to understanding future concerns related to mental health strategies that require scientific attention. The development of the current systematic review is based on the main research question: how does social media affect mental health?

Research strategy

The research was conducted to identify studies analyzing the role of social media on mental health. Google Scholar was used as our main database to find the relevant articles. Keywords that were used for the search were: (1) “social media”, (2) “mental health”, (3) “social media” AND “mental health”, (4) “social networking” AND “mental health”, and (5) “social networking” OR “social media” AND “mental health” (Table  1 ).

Out of the results in Table  1 , a total of 50 articles relevant to the research question were selected. After applying the inclusion and exclusion criteria, duplicate papers were removed, and, finally, a total of 28 articles were selected for review (Figure  2 ).

An external file that holds a picture, illustration, etc.
Object name is cureus-0012-00000008627-i02.jpg

PRISMA, Preferred Reporting Items for Systematic Reviews and Meta-Analyses

Inclusion and exclusion criteria

Peer-reviewed, full-text research papers from the past five years were included in the review. All selected articles were in English language and any non-peer-reviewed and duplicate papers were excluded from finally selected articles.

Of the 16 selected research papers, there were a research focus on adults, gender, and preadolescents [ 10 - 19 ]. In the design, there were qualitative and quantitative studies [ 15 , 16 ]. There were three systematic reviews and one thematic analysis that explored the better or worse of using social media among adolescents [ 20 - 23 ]. In addition, eight were cross-sectional studies and only three were longitudinal studies [ 24 - 29 ].The meta-analyses included studies published beyond the last five years in this population. Table  2  presents a selection of studies from the review.

IGU, internet gaming disorder; PSMU, problematic social media use

This study has attempted to systematically analyze the existing literature on the effect of social media use on mental health. Although the results of the study were not completely consistent, this review found a general association between social media use and mental health issues. Although there is positive evidence for a link between social media and mental health, the opposite has been reported.

For example, a previous study found no relationship between the amount of time spent on social media and depression or between social media-related activities, such as the number of online friends and the number of “selfies”, and depression [ 29 ]. Similarly, Neira and Barber found that while higher investment in social media (e.g. active social media use) predicted adolescents’ depressive symptoms, no relationship was found between the frequency of social media use and depressed mood [ 28 ].

In the 16 studies, anxiety and depression were the most commonly measured outcome. The prominent risk factors for anxiety and depression emerging from this study comprised time spent, activity, and addiction to social media. In today's world, anxiety is one of the basic mental health problems. People liked and commented on their uploaded photos and videos. In today's age, everyone is immune to the social media context. Some teens experience anxiety from social media related to fear of loss, which causes teens to try to respond and check all their friends' messages and messages on a regular basis.

On the contrary, depression is one of the unintended significances of unnecessary use of social media. In detail, depression is limited not only to Facebooks but also to other social networking sites, which causes psychological problems. A new study found that individuals who are involved in social media, games, texts, mobile phones, etc. are more likely to experience depression.

The previous study found a 70% increase in self-reported depressive symptoms among the group using social media. The other social media influence that causes depression is sexual fun [ 12 ]. The intimacy fun happens when social media promotes putting on a facade that highlights the fun and excitement but does not tell us much about where we are struggling in our daily lives at a deeper level [ 28 ]. Another study revealed that depression and time spent on Facebook by adolescents are positively correlated [ 22 ]. More importantly, symptoms of major depression have been found among the individuals who spent most of their time in online activities and performing image management on social networking sites [ 14 ].

Another study assessed gender differences in associations between social media use and mental health. Females were found to be more addicted to social media as compared with males [ 26 ]. Passive activity in social media use such as reading posts is more strongly associated with depression than doing active use like making posts [ 23 ]. Other important findings of this review suggest that other factors such as interpersonal trust and family functioning may have a greater influence on the symptoms of depression than the frequency of social media use [ 28 , 29 ].

Limitation and suggestion

The limitations and suggestions were identified by the evidence involved in the study and review process. Previously, 7 of the 16 studies were cross-sectional and slightly failed to determine the causal relationship between the variables of interest. Given the evidence from cross-sectional studies, it is not possible to conclude that the use of social networks causes mental health problems. Only three longitudinal studies examined the causal relationship between social media and mental health, which is hard to examine if the mental health problem appeared more pronounced in those who use social media more compared with those who use it less or do not use at all [ 19 , 20 , 24 ]. Next, despite the fact that the proposed relationship between social media and mental health is complex, a few studies investigated mediating factors that may contribute or exacerbate this relationship. Further investigations are required to clarify the underlying factors that help examine why social media has a negative impact on some peoples’ mental health, whereas it has no or positive effect on others’ mental health.


Social media is a new study that is rapidly growing and gaining popularity. Thus, there are many unexplored and unexpected constructive answers associated with it. Lately, studies have found that using social media platforms can have a detrimental effect on the psychological health of its users. However, the extent to which the use of social media impacts the public is yet to be determined. This systematic review has found that social media envy can affect the level of anxiety and depression in individuals. In addition, other potential causes of anxiety and depression have been identified, which require further exploration.

The importance of such findings is to facilitate further research on social media and mental health. In addition, the information obtained from this study can be helpful not only to medical professionals but also to social science research. The findings of this study suggest that potential causal factors from social media can be considered when cooperating with patients who have been diagnosed with anxiety or depression. Also, if the results from this study were used to explore more relationships with another construct, this could potentially enhance the findings to reduce anxiety and depression rates and prevent suicide rates from occurring.

The content published in Cureus is the result of clinical experience and/or research by independent individuals or organizations. Cureus is not responsible for the scientific accuracy or reliability of data or conclusions published herein. All content published within Cureus is intended only for educational, research and reference purposes. Additionally, articles published within Cureus should not be deemed a suitable substitute for the advice of a qualified health care professional. Do not disregard or avoid professional medical advice due to content published within Cureus.

The authors have declared that no competing interests exist.


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