Cognitive control and Mood in relation to Psychological Resilience: An Ecological Momentary Assessment Study

doi:10.21203/rs.3.rs-2217160/v1

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Cognitive control and Mood in relation to Psychological Resilience: An Ecological Momentary Assessment Study

https://doi.org/10.21203/rs.3.rs-2217160/v1

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published 12 Aug, 2023

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Psychological resilience - the ability to adapt to adversity - is associated with intact inhibitory control (IC) mechanisms, which support goal-directed behavior. To date, no study has examined the daily fluctuations of IC performance in relation to resilience. The purpose of this study is to examine the relationship between IC and mood in young adults in a stressful situation in relation to psychological resilience. A baseline resilience test was conducted on 156 female and male soldiers during their basic combat training. Afterward, participants completed a 2-week ecological momentary assessment protocol, which included reporting their momentary moods and completing an IC assessment twice/day. A hierarchical linear modeling (HLM) analysis revealed that psychological resilience moderated the relationship between momentary IC and momentary mood, with better IC only being associated with better mood for those with higher, but not lower, baseline psychological resilience. This association was present only for female, but not for male participants. The study demonstrates that psychological resilience manifests itself in the everyday association between IC and mood. Additionally, these results contribute to our understanding of resilient behavior in the real world by supporting cognitive models of resilience.

Trial Registration: MOH_2018-0-13_002451

Biological sciences/Neuroscience/Cognitive neuroscience

Biological sciences/Neuroscience/Emotion

Inhibitory control

emotion regulation

stressor

army

basic combat training

sex differences

momentary assessment

cognitive control

executive functions

mood variation

EMA

Psychological or mental resilience is broadly defined as one’s ability to successfully adapt to trauma, adversity, or other significant stressors during life [1]. The ability to “bounce back” from a stressful or chronic event further involves coping with one’s emotions given the adverse situation. Studies conducted over the years have not just revealed the effects of adversities on one’s well-being, but were also able to identify multiple psychosocial traits associated with resilience, including optimism, active coping, high self-efficacy, cognitive reappraisal and greater emotion regulation [2]. In addition to factors related to the individual, life and environmental features contribute to one’s capacity to overcome adversity and related trauma [3]. However, while some definitions of resilience view it as a fixed individual trait or as a pre-disposition, others suggest that the individual properties that define resilience may vary over time [1]. In addition, better mental resilience has been shown to be associated with good mental health [4], while reduced resilience is associated with increased risk for mental health disorders such as depression, anxiety, and post-traumatic stress disorder (PTSD) [5]. As such, the study of factors contributing to resilience is expected to further elucidate the potential effects of adverse life events on mental well-being.

Several recent models suggested a central role for cognitive control (CC) in resilience [6–8]. CC is defined as the mental processes underlying our goal-directed behavior, and is comprised of the mental abilities of working memory, inhibitory control and cognitive flexibility [9]. A recent model suggested by Parsons and colleagues highlights the central role of CC in supporting resilience, along with a sense of self-efficacy, and the ability to self-regulate emotional reactivity [6]. Similarly, Feder and colleagues outlined a biopsychosocial model of resilience in which brain circuitry function subserving reward responses and CC underlie key psychological factors associated with resilience, including optimism and the capacity for cognitive reappraisal [7]. Empirically, recent reports in the literature consistently find significant associations between higher levels of resilience and better CC abilities, such as more flexible problem-solving patterns in terms of coping strategies and inhibitory control [6, 10]. Our recent study showed that increased inhibitory control, measured using a Go-NoGo (GNG) task, was associated with better resilience among newly recruited soldiers during training [11]. In addition, neuroimaging studies have shown that resilience is associated with increased activity in the prefrontal cortex (PFC), which is subservient to the CC system during automatic threat processing, as well as to implicit emotion regulation [8, 12].

The mechanism by which CC supports resilience may be via the exertion of control over emotional reactions. In that sense, robust PFC activation - i.e., activation of CC mechanisms - is linked with the capacity to inhibit and regulate limbic, emotional, and behavioral reactivity to stress and modulate amygdala activity to internal or external stressor are all associated with resilience [13]. This activation reduces emotional reactivity to negative stimuli and supports the use of adaptive cognitive reappraisal strategies [7, 14]. Indeed, individuals who exhibit better internal emotion regulation abilities are more likely to display resilience against adversity, compared with those with lower emotion regulation ability [15]. Moreover, better and more adaptive emotion regulation, involving activation of the anterior cingulate cortex and ventromedial PFC (vmPFC) is associated with greater CC, required to effectively respond to threat [12, 16]. In this regard, more flexibility in switching between emotional contexts was found to be associated with better resilience due to its supporting of better emotional adaption to unpleasant stimuli [17]. A recent study further found that for those with higher levels of working memory (WM) capacity at baseline, stressful events were associated with reduced daily negative affect, indicating that WM plays a role in emotion regulation [18]. Overall, the literature to date suggests that mental resilience is associated with activating CC mechanisms over emotional responses.

Despite views delineating resilience as a dynamic and interactive, rather than a static process [19] most studies to date have used a one-time, retrospective measurement of cognitive and emotional states in relation to resilience [10, 20]. However, such one-time lab-based measurements are limited in their ability to accurately characterize day-to-day variations in cognitive and emotional constructs [21]. Ecological momentary assessment (EMA) has been employed to effectively measure variations in affective and cognitive states in ecological, real-life situations [22, 23]. Using EMA, data can be collected in the natural environment and repeatedly across multiple time points, allowing for more accurate representation of momentary changes [23–25]. Indeed, daily positive affect was found to be associated with lower depressive and anxiety symptoms, through the enhancement of psychological resilience [23, 26]. Moreover, EMA studies found that large variability in daily mood reporting is a significant predictor of mental health status [23, 24, 27, 28]. Finally, higher mood variability over time was suggested reflect high emotional reactivity, combined with a lack of regulatory control that prevents the emotions from returning to their baseline level [29].

However, no study to date, to the best of our knowledge, has examined momentary changes in CC and mood in relation to resilience. The few EMA studies that did examine potential coupling between everyday mood fluctuations and changes in cognition show conflicting results [30, 31]. For example, studies conducted by Von stuum found no associations between changes in mood and concurrent cognitive function changes, suggesting that momentary experience of positive or negative mood state does not interfere with one’s thinking capacity [31, 32]. In contrast, other studies found that negative affect may be cognitively costly [33, 34], while positive affect may boost cognitive performance [35, 36]. None of these studies, however, has examined the associations between daily variations in CC and mood in relation to resilience.

The current study therefore aimed to examine the manifestation of CC and emotional states in daily life and their association with psychological resilience in a group of young adults in a stressful situation. To accomplish this goal, we used EMA of both mood reporting and CC – by measuring performance on a short inhibitory control (IC) task (a GNG task) from male and female soldiers during their Basic Combat Training (BCT) in the Israeli Defense Forces (IDF). Conducting the study in the mixed gender units of IDF, in which male and female recruits undergo the same training, allowed us to further assess the contribution of sex to resilience. Although female recruits have been part of combat units in the military for several years, data regarding their psychological resilience is still mixed [37, 38]. Specifically, while some studies report no differences in the degree of self-reported adversities in females compared to their male counterparts [39, 40], others find higher levels of self-reported adversities among newly-recruited female soldiers [41, 42]. Our previous investigation in this sample revealed that resilience did not differ between sexes, but that the variation of momentary mood was higher for female participants [43], both contributed to the prediction of quality of life. Here we examined whether momentary assessment of IC – a component of CC – in relation to mood is distinguished by different resilience characteristics, and whether this association is different for male and female participants.

A total of N = 144 participants were included in the present study. Participants were primarily female (n = 88, 61.1%) and between the ages of 19–21 (see Table 1 for sample characteristics). Baseline resilience was inversely associated with baseline mood (Pearson r = -0.30, P < .001), such that those with higher resilience has overall better mood (lower IMS-12 scores); However, it was not associated with baseline IC (Pearson r = -0.01, P = .927), nor with mood variability or with IC variability (P > .123). In addition, baseline IC was not associated with baseline mood (Pearson r = -0.073, P = .52). Age at baseline was not associated with any study measures (all Pearson r < 0.16, all Ps > .168).

Table 1

Demographic and clinical characteristics of the sample (N = 144).
Variable	M (SD)	Range
Sex (female; n, %)	88 (61.1%)
Age (years)	19.07 (0.58)	18.10–21.59
Immediate Mood Scale (IMS-12 )^a	-67.16 (12.42)	-91 - -23
Baseline IC (GNG target accuracy)^a	0.61 (0.19)	0.25–0.95
Resilience (Stress-resilience total score)	13.43 (3.75)	2–20
^a mean estimate based on LMM
EMA data

Participants completed in total 1,153 assessment points (Mean [M] = 7.49, standard deviation [SD] = 2.95) across 2,002 days, for an overall compliance rate of 57.6%. Although this indicates a large proportion of missing data, this rate is still within the range of other studies [44, 45]. There were no patterns of missing data to suggest that data were missing not at random.

Unconditional ICCs were 0.309 (95% CI = 0.245, 0.380) for the IMS-12 and 0.529 (95% CI = 0.441, 0.615) for GNG, respectively. This suggests that approximately 69.1% of the variance in mood and 47.1% of the variance in CC can be attributed to within-person variability. There was no change in GNG performance over time (P = .76); however, participants reported decreased mood over time (sr = 0.07, |t| = 2.65, P = .008).

Primary analysis

Results from the LMMs can be found in Table 2. In the first step, IC had a small, inverse association with IMS-12 (sr = 0.08, |t| = 2.06, P = .04), such that better IC was associated with better mood. Model fit improved with the inclusion of baseline resilience as a moderator of IC and mood (second step), although this improvement was small per conventional guidelines (\({f}^{2}\)= 0.04; Cohen, 1988). IC was no longer independently associated with mood (sr = 0.07, |t| = 1.87, P = .06); however, there was a significant interaction between IC and baseline resilience (sr = 0.19, |t| = 2.03, P = .04). An examination of simple slopes (see Fig. 1A) revealed that there was no association between IC and mood when baseline resilience was low (defined as -1 SD; b = 1.34, |t| = 0.19, P = .85), or when baseline resilience was average (defined as the mean; b = -8.49, |t| = 1.87, P = .061), but that there is an association between IC and mood when baseline resilience is high (defined as + 1 SD; b = -18.32, |t| = 2.89, P = .004).

Table 2

Linear mixed-effects models testing the association between cognitive control and baseline resilience on mood.
	Step 1				Step 2
Variable	B (SE)	\|t\|	P	sr^a	B (SE)	\|t\|	P	sr^a
Intercept	-67.16 (1.04)	64.61	< .001	--	-67.11 (1.02)	66.00	< .001	--
IC (GNG Target Accuracy)	-9.32 (4.53)	2.06	.04	0.08	-8.51 (4.55)	1.87	.06	0.07
Baseline Resilience					-0.80 (0.27)	2.96	.004	0.18
IC (GNG Target Accuracy) X Baseline Resilience					-2.60 (1.28)	2.03	.043	0.19
Marginal R²/Conditional R²	0.006/ 0.331				0.044/ 0.338

^a sr = semi-partial correlation.

Exploratory analysis

We next examined sex effects in the data. Males and females did not differ on baseline resilience (|t| = 1.12, P = .26, Cohen’s d = 0.19), mood (|t| = 1.21, P = .23, Cohen’s d = 0.19), or IC (|t| = 0.15, P = .88, Cohen’s d = 0.03). Furthermore, there was no difference in average mood or IC overall assessment points (|t| ≤ 1.45, P ≥ .15). Unconditional ICCs for mood differed between males (ICC = 0.509, 95% CI = 0.397, 0.620) and females (ICC = 0.236, 95% CI = 0.166, 0.324), indicating that females reported greater within-person variability in mood than males over the course of the study. Thus, exploratory models were tested with and without individual-level variability (as measured by the Root Mean Square of Successive Differences; RMSSD) as a fixed covariate. Because the pattern of differences did not change when including RMSSD as a covariate, results below are from unadjusted models.

The results are summarized in Table 3. Including sex as a moderator had a small improvement in overall model fit (Cohen’s \({f}^{2}\)= 0.02). There was a significant three-way interaction between sex, IC, and baseline resilience on mood (sr = 0.20, |t| = 2.53, P = .012). Simple slopes analysis indicated that males did not exhibit an association between IC and mood (all P ≥ .215), but females observed an association between IC and mood at average and high levels of baseline resilience (b = -11.20, |t| = 2.17, P = .03 and b = -27.88, |t| = 3.75, P < 0.001; see Fig. 1B).

Table 3

Exploratory Linear mixed-effects model testing the association between IC and baseline resilience on mood as a function of sex.
Variable		B (SE)	\|t\|	P	sr
Intercept		-68.67 (1.66)	41.38	< 0.001	--
IC (GNG Target Acc)		-6.83 (9.61)	0.71	.48	0.03
Sex (Female)		2.62 (2.09)	1.255	.21	0.08
Resilience		-1.34 (0.44)	3.05	.003	0.18
GNG Target Acc X Sex		-4.41 (10.91)	0.40	.69	0.08
GNG Target Acc X Resilience		3.61 (2.86)	1.29	.20	0.18
Resilience X Sex		0.89 (0.56)	1.61	.11	0.20
GNG Target Acc X Resilience X Sex		-8.08 (3.20)	2.53	.012	0.20
Marginal R²/Conditional R²	0.068/0.354

Note. sr = semipartial correlation.

In the current study, we examined the manifestation of psychological resilience in everyday life in a group of young adults under stress, during their basic combat training in the military. Using ecological momentary assessment (EMA) of IC and of mood, we found that for those with higher levels of self-reported resilience, higher daily IC was associated with better daily mood. However, no such association existed for those with medium or lower levels of resilience. In addition, these effects were present only for female, but not for male, participants in our sample. To the best of our knowledge, this study is the first to show that higher levels of resilience are associated with specific associations between IC and mood in daily life. As such, it validates and broadens the conceptualizations of current models of resilience, which suggest a central role for cognitive control – and mainly IC processes – in contributing to resilient outcomes in the face of adversity or during stressful life situations [6, 8]. Specifically, the model by Parsons and colleagues suggests that resilience relies on one’s ability to apply appropriate CC processing in each situation, using an overarching mapping system, which guides the application of information processing based on situations and perceived needs [6]. Previous studies have indeed provided validation for this and related models, using a one-time measurement in the lab, which showed the expected association between CC and resilience [11, 46]. Similarly, literature related to resilient outcomes following childhood trauma or malfunctioning also suggests that those that show psychological resilience are those who can better activate frontoparietal areas and that are able to exert better emotion regulation strategies [46, 47]. Here, we show for the first time the ecological aspect of this assertion, by showing that the momentary level of IC is related to the current emotional state only in those who are more resilient.

The results of our study are also in line with recent imaging studies, which have shown a link between increased resilience and prefrontal control of limbic system areas. The results suggest that cognitive control mechanisms are closely related to mood and resilience. As an example, Admon and colleagues (2009) investigated resilience in Israeli soldiers using a threat-relevant paradigm. Researchers found that lower amygdala reactivity pre-deployment predicted lower PTSD symptoms post-deployment, as well as greater hippocampal-vmPFC functional coupling post-deployment [48]. Using a different measure of threat and reward responses, researchers found that resilient soldiers maintained a balance between threat and reward responses after military service [49]. A recent study by Demers and colleagues included a sample of healthy adults with and without a history of childhood trauma and found that across the entire sample, better adaptive Demers and colleagues conducted a recent study of healthy adults with and without childhood trauma histories. They found that more IC over negatively-valenced distractors and higher activation of the prefrontal (right frontal pole) were associated with better adaptive functioning in everyday contexts across the entire sample. [50] Our results are consistent with this conclusion.

The results of the current study further substantiate the definition of resilience into a real-life stressful situation, showing that not only CC in general is associated with resilience, but that the momentary association between IC and mood underlies self-reported resilience. As such, these results provide the first ecological validation of the definition of resilience, which relies on the IC ability to inhibit variations and momentary mood reductions. As cognitive abilities, including IC, have been shown to fluctuate over time, given different levels of fatigue, stress and external conditions [51, 52], a one-time measurement of IC may not provide the full picture of IC abilities, stressing the need for a repeated, ecological assessment of IC and its association with momentary mood provides additional information.

While to the best of our knowledge, no previous study has examined the association between momentary IC and momentary mood in relation to mental resilience, our results are still in line with some of the previous literature on EMA which shows association between CC and mood in clinical and healthy samples. For example, a recent study by Smith and colleagues [53] examined daily IC and momentary mood in relation to binge eating behavior in 40 women with eating disorders. To that end, they tested the associations between intra-individual variability in self-regulatory capacity with negative affect. The authors found that among those who reported regular compensatory behaviors, binge eating was more likely on days with lower momentary negative affect when food-related IC was better. Conversely, lower momentary negative affect was related to lower likelihood of binge eating on days with poorer IC. However, since IC was examined only once per day, it is unclear whether negative affect impairs momentary ICs' capacity or vice versa [53]. Other studies included a group of young adults and found that on days with more reported negative affect and reduced motivation, performance on a WM task was also reduced [see also 33, 34, 35].

However, the literature in this regard is somewhat mixed, and other studies failed to find such associations between momentary cognition and momentary mood [31, 32, 51, 54]. For example, recent studies by Von Stumm showed no effect of mood on working memory (WM) performance [31]. Similarly, Small and colleagues found no associations between inter-subject variability of self-reported depressed mood and performance on working memory tasks; however, they did find a link between self-reported average scores of fatigue and cognitive tests in a small sample of cancer survivors [54]. A potential account for this lack of association between momentary cognition and mood given our current results is that baseline resilience has not been considered. Thus, it could be that for participants with higher levels of psychological resilience, such associations would have been found. Future studies are needed to further elucidate the link between CC and mood in ecological setting in relation to psychological resilience, in both clinical and non-clinical populations.

There was a significant sex effect in our study: momentary IC was associated with momentary mood in females with higher levels of resilience, but not in males. Because the study included an unequal number of males and females, this finding should be interpreted with caution. Since all participants were in the exact same environment, it is unlikely that sex differences in this study can be explained by differences in adversity type or severity. This may be due to the fact that resilience outcome measures are not sex sensitive. Due to the fact that existing conceptualizations of resilience do not account for how sex roles, social expectations, perceptions, and the environment interact to differentially shape women's and men's experiences of adversity and their responses to it, men are typically higher on measures of resilience than women [55].

Previous studies further suggested that mood variability may impact CC. The sex difference found in the current study might therefore be linked to our previous findings suggesting that females reported higher levels of variability in mood during the two-week tracking period than males [43]. Indeed, sex differences in the prevalence of mental illness - such as rates of depression among females compared to higher prevalence of impulse control disorders among males [56, 57] may also account for the differences we see in our current investigation. Finally, sex differences were also reported in the CC brain circuitry, using neuroimaging and electrophysiology studies among healthy samples [58, 59]. Our EMA-based results provide additional evidence for sex differences from a real-time ecological perspective.

This study has a few limitations that should be considered in future studies of ecological manifestation of resilience. A main limitation is that due to the field conditions of the study, the number of EMA samples per participant was rather low and may limit the generalizability of the findings. Although the number of samples suffices for the analyses conducted, denser sampling, as was done is other studies [e.g., 27, 60] is advised and may have significantly strengthened the analytical approach and the validity of the findings. Second, our sample, of young adults from a distinct mixed-gender unit of the IDF, is relatively homogeneous in terms of age and nationality, and includes twice as many female participants. This may limit the generalizability of the findings and calls for replication studies in broader samples.

The findings of the current study, which used “in the field” measurement of daily IC and mood, further substantiate the definition of resilience into a real-life stressful situation, showing general CC association with resilience, as well as momentary association between IC and mood underlies self-reported resilience. Our results provide the first ecological validation of the definition of resilience, which relies on the IC ability to inhibit variations and momentary mood reductions. Consequently, these results lend valuable support to cognitive models of psychological resilience and may contribute to our understanding of resilient behavior in the real world.

There are two significant implications for these results. First, they emphasize the importance of including smartphone-based EMA tools in studying cognition and emotion. The increasing use of smartphones and related mobile technology over the last decade [28] makes it easier to deliver EMA assessments remotely and provide significant data with high ecological validity. As noted previously, the use of mobile assessments allows the integration of multiple sources of contextual and cognitive data and hence may improve the precision of the data collected [25]. In addition, the results may have implications for interventions which aim to strengthen psychological resilience under stressful situations. Given the malleability of resilience, it is considered a potential intervention target which may improve one’s ability to cope with stressful situations and adversities [7]. Our results suggest that incorporating ecological momentary interventions (EMIs; [21]) to improve or build resilience may help bridge the gap in current mental health care for youth and young adults by enabling better access to interventions “in each moment” and in an appropriate context in daily life [61]. Thus, novel interventions may incorporate EMI with existing interventions to achieve better resilience amidst stress in young adults. Future studies should examine the utility of such interventions on resilience, taking into consideration sex differences in underlying resilience mechanisms.

All methods in this study were in accordance with relevant guidelines and regulations of the medical the IDF medical corps. The study was IRB approved by the IDF in accordance with the Helsinki Declaration.

Participants

A convenience sample of IDF soldiers (n = 154) was recruited for the study. Participants were from two recruiting cycles of the border defense infantry battalions, who were studied during their basic combat training (BCT), between April 2018 and October 2019. Data collection was conducted at the recruits’ military base in the southern part of Israel. The border defense infantry recruits both male and female soldiers who undergo similar training together. All participants provided written informed consent before engaging in the tasks, and none received monetary compensation for their participation.

Study Design

Participants completed baseline assessments (t0) and then completed two weeks of EMA, which included momentary mood reporting and a real-time IC task. The study then continued with repetition of the baseline assessments (t1), followed by 2 weeks of cognitive training The results reported here refer to a subset of the data collected during t0 (psychological resilience) and the 2 weeks of EMA. Results from other parts of the study are reported elsewhere [11, 43, 62–64].

Measures

Baseline psychological resilience (t0)

We used the Hebrew version of the self-assessed resilience scale [65]. This 5-item scale asks participants to rate their ability to cope with stress on a 4-point Likert scale on each of the 5 items (0 = low ability, 4 = excellent ability). Items include questions regarding their ability to “keep calm and think of the right thing to do in a crisis,” “manage stress,” “try new approaches if old ones don’t work,” “get along with people when you have to,” and “keep your sense of humor in tense situations”. The total score for the scale is derived from the sum of scores of all five items, and ranges between 0 and 20, with higher scores reflecting better self-perceived psychological resilience. The scale had an acceptable internal consistency in our sample (Cronbach’s alpha = 0.732). Previous studies reported slightly higher internal consistency for this scale (Cronbach’s alpha of 0.86–0.89) [66].

Ecological Momentary Assessment (EMA)

EMA data of mood and IC was collected during a 2-week period following t0 using the Moodify app (Nahum et al., 2017). The app was installed on participant’s mobile phones, and they were asked to provide, twice/day during weekdays (i.e., Sunday-Thursday), a momentary mood reporting and then complete a short IC task. Since the soldiers participating in the study did not have their mobile phones with them, their commanders were requested by the study staff to provide them with their phones twice/day, once in the morning and once in the evening, to allow them to complete the EMA tasks. Due to their varying schedule during BCT, we provided a relatively broad time window of 4.5 hours in the morning (6am − 10:30am) and in the evening (6pm- 10:30pm) for completion of the EMA assessments during the day. Participants could complete the EMA assessments only once during each time window and assessments were unavailable in times outside these two time windows. Daily reminders were sent to the commanders by the study staff, reminding them to give the soldiers their phones during the relevant time window. Participants were contacted by study staff in case they missed several consecutive assessments, to help with any technical issues they encountered. The overall completion time for each EMA session was ~ 3 min.

Momentary mood reporting was collected using the Immediate Mood Scale [IMS-12; 24], a 12-item measure which was developed to assess the dynamic components of mood. The IMS-12 scale prompts participants to rate their current mood state on a continuum using 12 items (e.g., happy-sad, distracted-focused, sleep-alert, fearful-fearless), each with a 7-point Likert scale. For each item, an integer score between 1 and 7 was derived. The total score for this scale is the sum of the scores on all 12 items. To be consistent with other scales assessing mental health status (e.g., PHQ-9, GAD-7), the total score is multiplied by -1, such that where higher scores reflect worse (i.e., more negative) mood states.

Momentary IC, a sub-construct of CC, was assessed using an abbreviated version of an affective GNG task, which provides an objective measure of IC, as it measures prepotent response inhibition (the ability to withhold or cancel a speeded motor response), considered a central component of IC [67]. The task included a total of 100 trials and takes ∼2.5 min to complete. On each trial, participants are asked to tap a button appearing on the screen as fast as possible whenever a frequent (80% of the time) foil picture was presented, and to withhold response to rare (20% of the time) target pictures. The task began with the presentation of a “start” button at the center of the screen. Once the user clicked on the ‘start’ button, the pictures were presented sequentially, each for a time of 1,000ms, with an inter-stimulus interval (ISI) of either 500, 1,000, and 1,000 or 1,500 or 2,000ms (randomly chosen for each trial). The presented stimuli were pictures of emotional expressions produced by Posit Science Inc. Target pictures were of neutral facial expressions, while foil stimuli were of emotional facial expressions (either sad or happy faces). Of the 80 foil images, 40 included faces with happy expressions and 40 with sad expressions. Auditory feedback was provided after each trial to indicate the correctness of response. For analysis, we derived the metric of target accuracy (accuracy in withholding on No-Go trials; range: 0–1), comprising an acceptable measure for prepotent IC, compared to commission errors [68].

Statistical Analyses

We tested whether the relationship between IC and mood varies as a function of resilience through linear mixed-effects models (LMM), as it tolerates observations that are missing at random (MAR). For all analyses, restricted maximum likelihood (REML) was used, and Kenward-Roger degrees of freedom were implemented for small-sample adjustment [69]. Prior to running primary analyses, we examined variability in mood and IC (per the IMS-12 and GNG, respectively) via Intraclass Correlations (ICC) using an unconditional LMM. The ICC provides an estimate of the proportion of variance that can be attributed to between-person variability (1-ICC, therefore, is the proportion of variance that can be attributed to within-person variability). We then tested two LMMs hierarchically: in the first step, cognitive control (participant mean-centered) was included as a time-varying predictor; in the second step, resilience at baseline (group mean-centered) and its interaction with cognitive control were included. As an exploratory analysis, we also examined whether the association between cognitive control and baseline resilience on mood varies as a function of sex. The method proposed by Stoffel, Nakagawa, and Schielzeth (2021) was used to provide effect size estimates for all predictors via squared semi-partial correlations (\({sr}^{2}\)). In brief, their approach iteratively removes predictors from a model and examines the change in the variance of the linear predictor, and the difference to the full model provides an estimate of the unique variance explained by individual predictors [70]. We took the square root of these estimates for it to be consistent with the traditional correlation coefficient effect size estimate. Because REML is incompatible with traditional indices of relative model fit (such as change in the Bayesian Information Criterion), model goodness-of-fit was examined through marginal and conditional R², where marginal R² represents the proportion of variance explained by fixed factors and conditional R² represents the proportion of variance explained by fixed and random factors[71]. Improvement in model fit (with the inclusion of baseline resilience as a moderator) was examined via Cohen’s \({f}^{2}\), where change in marginal \(R{}^{2}\)served as the measure of model fit [72]. Significant interaction terms were probed via simple slopes analysis. Statistical significance was evaluated at a two-sided alpha = 0.05. All analyses were conducted in R [73] with the lme4 [74], lmerTest [75, 76], interactions [77], psych [78], and partR2 [70] packages.

Additional Information:

BCT - Basic Combat Training

CC - Cognitive Control

EMA - Ecological Momentary Assessment

EMI - Ecological Momentary Interventions

GNG - Go-NoGo

HLM - Hierarchical linear Modeling

IC - Inhibitory Control

ICC - Intraclass Correlations

IDF - Israeli Defense Forces

IMS - Immediate Mood Scale

LMM - linear mixed-effects models

PFC - Prefrontal Cortex

PTSD - Post-traumatic stress disorder

REML- restricted maximum likelihood

WM - Working Memory

Conflicts of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

A Data Availability Statement:

The datasets generated during and analyzed during the current study are not publicly available due to IDF restrictions but are available from the corresponding author on reasonable request.

Acknowledgments

This work was supported by the Israeli Ministry of Defense, Directorate of Defense Research and Development (Grant Number 4440836450).

We would like to thank the many research assistants that helped with data collection and management: Chenanit Hamami, Nili Sarussi, Naomi Schottig, Michal Glikin, Tamar Wechsler, and Stav Ben Zagmi.

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No competing interests reported.

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Cognitive control and Mood in relation to Psychological Resilience: An Ecological Momentary Assessment Study

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Baseline psychological resilience (t0)

Ecological Momentary Assessment (EMA)

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