Sense of control buffers against stress

Individuals have control when their actions are causally involved in achieving beneficial outcomes or avoiding undesired ones. Having control allows engaging in a suite of proactive goal-directed behaviours and offers rewards for exploration, which the absence of control does not (Moscarello and Hartley, 2017; Teodorescu and Erev, 2014). Decades of work have demonstrated the motivational significance of experiences of control over one’s environment (Maier and Seligman, 2016) and their fundamental role in psychological well-being (de Quadros-Wander et al., 2014) and resilience (Yang and Ma, 2020). The power of control to organise behaviour has been argued to originate from a fundamental need of humans (and many other species) to be effective in their interactions with the environment (Elliot and Dweck, 2005; Ryan and Deci, 2000; Skinner, 1996). A wealth of cross-species work has also identified having control as a crucial moderator of how potentially stressful events are processed (Gee et al., 2022; Maier and Seligman, 2016). Despite the significant risk stress poses to mental illness (Lupien et al., 2009), the relationship between the experience of stress and control remains poorly understood.

Two core questions remain poorly understood. First, a wealth of evidence suggests that subjective aspects of a range of phenomena, including maltreatment, social hierarchy, loneliness, and pain, appear to be highly predictive of outcomes, such as well-being and mental health, and often more so than objective classifications (Bzdok and Dunbar, 2022; Danese and Widom, 2020; Rivenbark et al., 2020; Wager and Atlas, 2015). Indeed, it has long been noted that the impact of objective control will only be relevant if it is perceived and recognised as such (Langer and Rodin, 1976). Thus, perceived or subjective dimensions of control play a crucial role in functioning across social, academic, and mental health domains throughout the lifespan (Bandura et al., 2003; Moscarello and Hartley, 2017; Rotter, 1966; Ryan and Deci, 2006). However, to date, the affective properties of experiences of control remain poorly understood (although see here for studies on perceptions of control and positive affect Leotti and Delgado, 2011; Ly et al., 2019; Wang et al., 2021; Wang and Delgado, 2019). In particular, it is unclear how momentary subjective sense of control relates to subjective reports of stress.

The second question is about the effect of increased control. Converging lines of evidence have shown that subjective control has a critical role in shaping the impact of stressors on a host of different outcomes (de Quadros-Wander et al., 2014; Maier and Seligman, 2016; Yang and Ma, 2020). Systematic experimental work in animals over the last 50 years has also causally demonstrated the critical role of control over stress in determining later outcomes (Maier and Seligman, 2016). In classic empirical assays, caged rodents are exposed to shocks that terminate irrespective of any action taken. As a result of such operationalised non-contingency between actions and outcomes, or uncontrollability of a stressor, rodents fail to learn to escape from subsequent stressors, more so than rodents previously not exposed to stress. Thus, an absence of control leads to learned helplessness in novel contexts. Additional effects of such uncontrollable stress include reduced aggression, social dominance, and extinction learning as well as increased fear conditioning (Maier and Watkins, 2005), a cascade of negative outcomes that has been interpreted as indexing a behavioural phenotype of internalising disorders (Maier and Seligman, 2016). Intriguingly, much less is known about the effects conferred by heightened control. Animal work found that exposure to controllable stress (compared to no stress at all) effectively inoculates against the negative impact of a subsequent stressor (Kubala et al., 2012). Similar empirical approaches in humans have shown that stressor controllability modulates fear extinction learning (Hartley et al., 2014). To date, however, it is unclear whether heightened control can actually buffer against the effect of a subsequent stressor in humans (Bhanji et al., 2016; Bhanji and Delgado, 2014).

To address these questions, we designed a novel task (the ‘Wheel Stopping’ task or WS task) requiring carefully timed actions to achieve a reward or avoid reward losses that allows inducing and measuring different states of subjective control. We first show that the task has excellent psychometric properties with high internal consistency and external validity. We then show strong and consistent associations between sense of control and stress in a non-clinical adult sample (N=473, Study 1; N=295, Study 2). Manipulating control has often presented challenges given potential confounds of task difficulty, predictability (Ligneul, 2021), and the probability of action and reward outcomes (Dorfman and Gershman, 2019). Existing tasks manipulate the degree of control rather coarsely through entirely present or absent control affordances (Dorfman and Gershman, 2019; Hartley et al., 2014; Ligneul, 2021; Ligneul et al., 2022; Raab et al., 2022). Here, we verify that the relationship between subjective control and stress is apparent above and beyond the variance accounted for by perceived task difficulty. We then use the task to examine the effect of heightened control on the response to future stressors. By manipulating subjective control during the task, we show that heightened sense of control buffers against the effects of a subsequent stressor (N=295; Study 2). Given the pervasive occurrence of stress and its wide-reaching negative impact, these findings have considerable translational potential.

We first investigate the internal consistency and external validity of the task. We also use a simple computational model to relate subjective control responses to the trial-specific parameters at the individual level. We then investigate the within-task associations of subjective stress and control in Study 1 and replicate this in Study 2. Finally, in Study 2, we investigate whether experiencing heightened control from the WS task, compared to watching videos, buffers responses to a subsequent stressor.

Predicting sense of control from task parameters

To establish whether the Wheel Stopping task parameters governing the difficulty and hence controllability of individual trials (speed of rotation, segment size, deceleration increment) affected participants’ subjective sense of control, we created a linear model relating trial-by-trial variation in task parameters to the time series of control ratings. The best model (lowest BIC, Figure 1—figure supplement 1) predicted control ratings from all three Wheel Stopping task parameters (deceleration increment, segment size, and speed of rotation), although all models performed similarly. The winning model contained an intercept term, a gamma term to discount previous control ratings at the current time point, and the beta weights for the three regressors. A histogram of the parameter estimates across all participants is shown in Figure 1a. Parameter estimates across the whole sample were significantly different from 0 (one-sampled t-tests, ps <0.001: Gamma t(673)=12.19, p<0.001, p_adj. <0.001; Deceleration t(673)=17.14, p<0.001, p_adj. <0.001; Segment Size t(673)=-20.71, p<0.001, p_adj. <0.001; Speed t(673)=-20.80, p<0.001, p_adj. <0.001; Intercept t(673)=76.82, p<0.001, p_adj. <0.001). On average, the beta coefficients for Segment Size (mean = –2.25, SD = 2.83) and Speed (mean = –3.09, SD = 3.86) were negative, showing that a faster speed and a smaller segment size (a larger fraction parameter) resulted in lower ratings of control. On the other hand, on average, the beta weight for deceleration increment was positive (mean = 2.33, SD = 3.53), showing that the wheel stopping faster predicted higher feelings of control. The median correlation between actual and fitted control responses across the whole sample was 0.60 (Study 1=0.54, Study 2=0.69, Figure 1b). The actual and predicted control responses over the course of the experiment can be seen for six randomly selected participants (three per study iteration) in Figure 1c. Overall, this modelling approach shows that the subjective control response can be captured well from the Wheel Stopping task parameters at the individual level, and that there is individual variation among how the task parameters are weighted to predict control, as well as variation in the intercept.

Figure 1 with 1 supplement see all

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Stress and control

During the WS task, we measured subjective stress ratings using a slider scale, assessed every 16 blocks (80 trials) in Study 1, and every 9 blocks (45 trials) in Study 2 (Supplementary file 5D). We also assessed subjective control and perceived difficulty during the WS task, assessed every 2 blocks (10 trials) in both studies. To investigate how subjective control related to feelings of stress during the WS task while accounting for perceived task difficulty, we took the mean control ratings and mean difficulty ratings preceding each stress rating, enabling us to have a value of control and difficulty corresponding to each stress timepoint. For Study 1 (n=473), there were four subjective stress ratings (timepoints) during the WS task. A linear mixed effects model including random intercepts of participant and timepoint showed that lower feelings of control (β=–0.13, p<0.001) and higher perceived task difficulty (β=0.38, p<0.001) were both uniquely associated with higher subjective stress during the WS task (Table 1, Figure 2). This effect replicated in Study 2 (n=201), with three (instead of four) timepoints, such that higher subjective stress during the WS task was uniquely associated with lower subjective control (β=–0.33, p<0.001) and higher perceived task difficulty (β=0.32, p<0.001; Supplementary file 3A, Figure 2).

Table 1

	Subjective Stress(Study 1)
Predictors	Estimates (95% CI)	p
(Intercept)	31.13 (25.15–37.12)	<0.001
Subjective Control	–0.13 (−0.20–-0.07)	<0.001
Perceived Difficulty	0.38 (0.31–0.44)	<0.001
Random Effects
σ2	208.61
τ00	346.20 ppt
	3.63 timepoint
ICC	0.63
N	473 ppt
	4 timepoint
Observations	1892
Marginal R2 /Conditional R2	0.154/0.684

Figure 2 with 2 supplements see all

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To further isolate the relationship between subjective control and stress separate from perceived task difficulty or objective task performance, we also included the overall win rate (percentage of trials won during the WS task) in the models. In Study 1, lower feelings of control were related to higher levels of subjective stress (β=–0.12, p<0.001) even when controlling for both win rate (β=–0.06, p=0.220) and perceived task difficulty (β=0.37, p<0.001, Supplementary file 3B). This also replicated in Study 2, where lower subjective control was associated with higher feelings of stress (β=–0.32, p<0.001) when controlling for perceived task difficulty (β=0.31, p<0.001) and win rate (β=–0.11, p=0.428, Supplementary file 3A). This suggests that there is unique variance in subjective feelings of control, separate from task performance, relevant to subjective stress.

Study 2 also investigated how the loss domain (avoid losing bonus money) and win domain (winning 1 p per correct trial) influenced feelings of stress during the task. We included subjective control and perceived difficulty in the model as known covariates that influence stress in the task and accounted for random intercepts of participant and timepoint. We found that the loss domain (β=8.99, p=0.001) uniquely predicted higher feelings of stress, along with lower feelings of subjective control (β=–0.31, p<0.001) and higher perceived task difficulty (β=0.31, p<0.001), as before (Supplementary file 3A).

The final WS stress rating in both studies occurred after a STAI-S questionnaire following the final block of the WS task. To ensure that this delay in the final stress rating did not affect the results, we repeated the analyses excluding the final timepoint. Results in both studies replicated, showing that the within-task relationship between subjective control and subjective stress was robust (Supplementary file 3A and B).

Stressor controllability

As presented in the previous section, an increased sense of control related to lower levels of subjective stress during the Wheel Stopping task in both studies. We next examined in Study 2 whether this effect of heightened control generalised beyond the WS task in response to a subsequent stressor. To do so, we added a causal manipulation whereby one group of participants received a version of the WS task inducing high levels of control ratings. While high control is often contrasted to low control conditions, we were here interested in a stronger test to ask whether the experience of control itself might have a protective effect in comparison to an intervention that might similarly reduce stress by itself. We hence compared the high control task to a simple video watching condition. During the video task, the mean of individuals’ valence ratings was 6.60 (SD = 1.53), where 1 represents unpleasantness and 9 represents pleasantness. A one-sided one-sampled t-test revealed this was significantly greater than the scale’s midpoint (t(93)=10.17, p<0.001). The mean of individuals’ arousal ratings was 3.94 (SD = 1.74), where 1 represents calmness and 9 represents excitement. A one-sided one-sampled t-test revealed this was significantly less than the scale’s midpoint (t(93)=-5.91, p<0.001). These suggest that participants indeed found the videos relaxing (pleasant and calm). These tasks were followed by a stressor of high or low intensity (the anticipatory Trier Social Stress Test or recipe comprehension task, respectively). The analyses in this section therefore focus on stress ratings from three timepoints: after the WS/video task, after the stressor, and after the stressor debrief, coded as timepoints 1, 2, 3, respectively. The subjective stress levels across the course of the entire experiment are shown in Figure 3a.

Figure 3

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We designed a novel Wheel Stopping task to assess subjective sense of control and its relationship with subjective stress in a large sample of adult participants across two separate studies. Across both studies, we could show that task features designed to manipulate subjective control, namely wheel speed, segment size, and deceleration increment, were highly effective at doing so. Further, the task possessed excellent psychometric properties, including high internal consistency as well as high external validity, as demonstrated by relationships with state anxiety, locus of control, and mental health measures. We also showed that the subjective sense of control, as elicited by task parameters and experienced stress, was tightly coupled throughout the task for our participants. In a final step, we sought to causally manipulate and heighten subjective sense of control and to test its impact on subjective stress in response to a subsequent stressor. We could show that experimentally increased sense of control buffered subjectively experienced stress to a psychosocial stressor and also led to greater stress relief compared to a neutral video task.

Given the different parameter combinations of our task, we were able to elicit a considerable range in the subjective experience of control. Notably, there was a tight coupling between subjectively experienced control and subjectively experienced stress during the task. While our WS task was in and of itself not designed to elicit feelings of stress, these results are striking as clearly the variable sense of control, as elicited through changes in the achievability of obtaining instrumental rewards, was highly predictive of subjective stress levels. Importantly, during the task, we also obtained ratings of perceived task difficulty. While subjective stress was partly accounted for by task difficulty, there was also a unique relationship with perceived control. These findings demonstrate how closely subjective control tracks subjective stress independently of any stressful task properties, which in the present case were minimal and reinforce that perceived control presumably not only moderates subjective stress but impacts it directly. Mean levels of subjective sense of control during the task also correlated with a cluster of self-reports and questionnaires such as state anxiety, locus of control, trait anxiety, depression, and social phobia, replicating prior work on perceived control and mental health (Gee et al., 2022).

In a crucial set of experiments (Study 2), we tested whether causally manipulating and increasing participants’ sense of control through our task impacts not just presently but also subsequently experienced stress. To elicit stress, we used a well-known psychosocial stressor (Kirschbaum et al., 1993; Steinbeis et al., 2015), which presently also led to a clear increase in subjective stress and subsequent relief after being debriefed. Thus, compared to participants in a neutral control condition (watching videos), participants who had been exposed to the WS task designed to give them an increased sense of control showed a reduced subjective stress response following the stressor and greater relief after the debrief. These findings demonstrate that heightened control impacts subsequent stress levels. Whereas prior work in humans has shown that experimentally induced increases in experiences of control lead to greater fear extinction, a core regulatory process (Hartley et al., 2014), the present findings provide direct evidence that heightened control buffers against later stress.

Stress is causally implicated in the emergence and maintenance of multiple mental health conditions across the lifespan (Lupien et al., 2009); however, the nature of stressors and how we respond to them significantly impacts mental health symptomatology (Dickerson and Kemeny, 2004; Koss and Gunnar, 2018). Stressors are most potent when uncontrollable, as demonstrated through decades of research on learned helplessness (Maier and Seligman, 2016). By implication, there has been a growing interest in how heightened control over stressful events may mitigate their impact and lead to resilient outcomes even in response to future stressors (Bhanji et al., 2016; Bhanji and Delgado, 2014; Hartley et al., 2014; Ly et al., 2019; Wang and Delgado, 2021). While some cross-species work has been able to provide some initial support for this idea (Maier and Seligman, 2016), clear causal evidence in humans has so far been lacking. Here, we were able to show that experimentally increasing experiences of control through our WS task and thereby heightening participants’ subjective sense of control led to reductions in stress following a subsequent stressor. While we were presently unable to differentiate whether this is driven by objective or subjective dimensions of control, we speculate that, similar to other domains of mental health (Bzdok and Dunbar, 2022; Danese and Widom, 2020; Rivenbark et al., 2020), subjective elements of control are more impactful. This raises the possibility of targeting subjective control beliefs to reduce the likely impact of stress. Previously, similar interventions have been designed to target other types of beliefs implicated in mental health symptomatology (i.e. optimism, causal attribution; Malouff and Schutte, 2017; Roesch and Weiner, 2001). Given the high degree of comorbidity among many mental health disorders (Caspi and Moffitt, 2018) and the crucial role of subjective sense of control across a host of mental health disorders (Gee et al., 2022; Kubala et al., 2012; Wade et al., 2019), the present work implicates a highly relevant target for possible intervention.

Our set of studies is not without its limitations. As stated above, we operationalised variations in task controllability through task difficulty, while technically each of our WS iterations was controllable. Our intention was to selectively target subjective control, which we were able to achieve, while simultaneously statistically controlling for perceived task difficulty. Future work will need to find ways of operationalising controllability in a graded fashion while accounting for other confounds such as predictability (Ligneul, 2021). Further, similar to other task designs comparing control conditions (Dorfman and Gershman, 2019), these conditions were not matched for associated rewards. Previous research typically accounts for different outcomes (e.g. punishment) by yoking controllable and uncontrollable conditions (Maier and Seligman, 2016), although other work has manipulated the controllability of rewards by changing the reward rate (e.g. Dorfman and Gershman, 2019) where a decoy stimulus is rewarded 50% of the time in the low control condition but 80% in the high control condition. While our task design does not separate control from obtained reward, we are able to do so in the statistical analyses. Like with perceived difficulty, we statistically accounted for reward rate and showed that the relationship between subjective control and stress was not accounted for by reward rate, for example. Similarly, participants received feedback after every trial, and thus feedback valence may contribute to stress perception. However, given that overall win rate (which captures the feedback received during the task) did not predict stress over and above perceived difficulty or subjective control, it suggests that feedback is unlikely to relate to stress over and above difficulty. Future work will need to disentangle this further to rule out such potential confounds. Another avenue for future research would be to test how control buffers against stress when compared to a neutral control scenario of higher stress levels, akin to the loss domain in the WS Task, given that participants found the video condition generally relaxing. However, given that we found no differences dependent on domain for the stress induction in the WS Task conditions, it is possible that different versions of a neutral control condition would not impact the stress induction.

We designed a novel experimental task to track and induce subjective sense of control in a highly graded fashion. While this task possessed excellent psychometric properties, we were also able to show that momentary sense of control was tightly coupled with subjective stress levels as well as state anxiety and symptoms of mental ill health. Crucially, compared to a relaxation control condition, an experimental and task-induced increase in sense of control led to reduced subjective stress in response to a subsequent stressor, as well as greater stress relief after participants were debriefed. Our findings demonstrate a causal role of subjective control in mitigating the negative impact of stress and identify a highly valuable and potentially modifiable target for interventions aimed at reducing the detrimental consequences of stressors in everyday life.

All data and analysis code are publicly available on the Open Science Framework at https://doi.org/10.17605/OSF.IO/39JSC.

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Author details

1. Jennifer C Fielder

   Division of Psychology and Language Sciences, London, United Kingdom

   Contribution

   Conceptualization, Formal analysis, Investigation, Visualization, Writing – original draft, Writing – review and editing

   For correspondence

   jennifer.fielder.21@ucl.ac.uk

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-5360-0494

2. Jinyu Shi

   1. Department of Experimental Psychology, University of Oxford, Oxford, United Kingdom
   2. Anna Freud, London, United Kingdom

   Contribution

   Formal analysis, Investigation, Methodology, Writing – review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-0111-2050

3. Daniel McGlade

   1. Division of Psychology and Language Sciences, London, United Kingdom
   2. Anna Freud, London, United Kingdom
   3. Yale Child Study Center, Yale School of Medicine, Yale University, New Haven, United States

   Contribution

   Writing – review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0009-0005-8864-9692

4. Quentin JM Huys

   1. Applied Computational Psychiatry Lab, Mental Health Neuroscience Department, Division of Psychiatry and Max-Planck UCL Centre for Computational Psychiatry and Ageing Research, Queen Square Institute of Neurology, London, United Kingdom
   2. North London NHS Foundation Trust, London, United Kingdom

   Contribution

   Conceptualization, Formal analysis, Supervision, Methodology, Writing – original draft, Writing – review and editing

   Contributed equally with

   Nikolaus Steinbeis

   Competing interests

   has obtained fees and options for consultancies for Aya Technologies and Alto Neuroscience

   "This ORCID iD identifies the author of this article:" 0000-0002-8999-574X

5. Nikolaus Steinbeis

   Division of Psychology and Language Sciences, London, United Kingdom

   Contribution

   Conceptualization, Supervision, Funding acquisition, Methodology, Writing – original draft, Writing – review and editing

   Contributed equally with

   Quentin JM Huys

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0001-8650-4725

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