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. Author manuscript; available in PMC: 2023 Apr 1.
Published in final edited form as: J Anxiety Disord. 2022 Mar 5;87:102556. doi: 10.1016/j.janxdis.2022.102556

Executive Functioning Deficits Exacerbate Posttraumatic Stress Symptoms: A Longitudinal Mediation Model

Joseph R Bardeen 1, Julia Y Gorday 1, Frank W Weathers 1
PMCID: PMC8996315  NIHMSID: NIHMS1787466  PMID: 35276509

Abstract

Executive functioning (EF) consists of a set of related, but distinct, higher-level cognitive abilities that are used to organize and integrate lower-level processes in the service of engaging in goal-direct behavior. Evidence suggests that deficits in EF are a vulnerability factor for the development of posttraumatic stress (PTS) symptoms. Less understood, however, is the role that EF plays in symptom maintenance and exacerbation following trauma exposure. As such, the primary purpose of the present study was to determine whether EF deficits exacerbate PTS symptoms over the course of one year. A secondary aim of this study was to use a cross-lagged design to determine the directional relations among EF deficits and PTS. Trauma-exposed adults (N = 98) completed a clinical interview and self-report measures at an initial assessment session (Time 1 [T1]). Participants also completed self-report measures at 6- (Time 2 [T2]; n = 92) and 12-month (Time 3 [T3]; n = 91) follow-up sessions. As predicted, EF deficits at T2 mediated the relationship between PTS symptoms from T1 to T3, thus suggesting that EF deficits exacerbate PTS symptoms following trauma exposure. Results from a cross-lagged path analysis from T2 to T3 suggest that deficits in EF exert a stronger influence on the maintenance of PTS symptoms than vice versa. These results have implications for (a) identifying individuals that are at elevated risk for developing PTS symptoms, (b) developing precision medicine-based approaches for alleviating PTS symptoms, and (c) improving well-established PTSD treatments for those with relative deficits in EF.

Keywords: posttraumatic stress, trauma, PTSD, longitudinal, mediation, executive functioning, executive functioning deficits

1. Introduction

Posttraumatic stress disorder (PTSD; American Psychiatric Association, 2013) afflicts a sizable proportion of the population (e.g., 8.3% of adults in the United States; Kilpatrick et al., 2013). In addition to the intense emotional suffering that is associated with PTSD (Hancock & Bryant, 2018; Niziurski et al., 2018; Whiffen & MacIntosh, 2005), individuals with PTSD exhibit deficits in interpersonal (Cloitre et al., 2005; Nietlisbach & Maercker, 2009) and occupational functioning (Hunnicutt-Ferguson et al., 2018; Smith et al., 2005), and the disorder has a substantial negative financial impact on society (Bothe et al., 2020; Ferry et al., 2015; Wilson et al., 2016). As such, it is important to identify factors that may contribute to the maintenance of posttraumatic stress (PTS) symptoms. Executive functioning (EF) deficits are one such factor that may contribute to both the maintenance and exacerbation of PTS. Despite growing evidence that individuals with PTSD, versus those without, have relative deficits in EF (Aupperle et al., 2012; Polak et al., 2012; Scott et al., 2015), empirical evidence regarding the role that EF deficits play in the maintenance of PTS is lacking. To address this limitation, EF deficits were examined as a factor that may exacerbate PTS symptoms over the course of one year in the present study.

EF has been conceptualized as an overarching construct that consists of a set of related, but distinct higher-level cognitive abilities that are used to organize and integrate lower-level processes in the service of engaging in goal-direct behavior (Aupperle et al., 2012; Barkley, 2011; Crocker et al., 2018). There is a general consensus in the EF literature that set-shifting, working memory updating, and inhibition are three core executive functions (EFs), and these three EFs can be used to initiate other, more complex, EFs, such as problem solving, planning, and reasoning (Crocker et al., 2018; Diamond, 2013). EF has a profound impact on a wide variety of outcomes that are central to everyday life, for example, predicting success in school, likelihood of promotion at work, maintaining relationships, better health, greater economic prosperity, and better physical and mental health (Diamond & Ling, 2016). Additionally, EF deficits are associated with emotion regulation difficulties (Lantrip et al. 2016), which in turn, have been shown to put one at higher risk of developing PTS symptoms following trauma exposure (Bardeen et al., 2013).

Multiple studies have shown that individuals with PTSD exhibit relative deficits in EF compared to control participants (Aupperle et al., 2012; Polak et al., 2012; Scott et al., 2015). Cross-sectional designs have been used in the majority of studies in which the link between EF deficits and PTS has been examined. As described by Aupperle et al. (2012), this is one of the most serious limitations in this area of research. Longitudinal study designs are needed to help researchers determine whether (a) EF deficits that exist prior to a trauma serve as a vulnerability factor for developing PTSD (i.e., the EF deficit vulnerability theory), (b) EF deficits are a consequence of trauma exposure and/or PTSD, or (c) there is a more complex bidirectional relationship between EF deficits and PTSD.

Of these three theories, the EF deficit vulnerability theory has received the most attention in the extant literature. For example, Aupperle et al. (2012) suggested that relative deficits in attentional inhibition and shifting might make it more difficult to disengage attention from trauma-related stimuli (Bardeen et al., 2016), thus increasing the likelihood that one will develop PTSD following trauma exposure. Some evidence supports this hypothesis, as disengaging and shifting attention from threat-related stimuli leads to the down-regulation of sympathetic nervous system arousal and alleviates negative affective states (Bardeen & Daniel, 2017). Moreover, those with relatively worse pre-trauma attentional inhibition are more likely to develop PTS following trauma exposure (Bardeen et al., 2015). In a slightly different conceptualization, Brewin and Smart (2005) suggested that those with greater working memory capacity may be better able to suppress trauma-related memories and intrusive thoughts that promote the development of PTSD. It is also possible that relative deficits in working memory may increase the likelihood that trauma memories will be convoluted or fragmented, thus resulting in retrieval of the trauma narrative that is compromised (Marx et al., 2009).

Another possibility is that the development of PTSD may directly lead to EF deficits (Vasterling et al., 2002). This hypothesis is based on the idea that symptoms of PTSD, such as sleep difficulties, concentration problems, hyperarousal, and intrusive re-experiencing may impair working memory and inhibitory ability. Because several of these symptoms are behavioral indicators of both PTSD and EF dysfunction, this hypothesis would be difficult to test without assessing both constructs over multiple time points and controlling for each in the same analytic model. To our knowledge, such an examination has yet to be conducted.

Finally, some have suggested that the relationship between EF deficits and PTSD is bidirectional in that EF deficits serve as a vulnerability factor for the development of PTSD, and in turn, PTSD symptoms exacerbate EF deficits (Aupperle et al., 2012; Crocker et al., 2018). For example, Vasterling and Brailey (2005) hypothesized that subtle pre-trauma deficits in EF limit one’s ability to cope effectively with trauma-related distress, thus increasing the likelihood that one will engage in maladaptive avoidance behaviors, which increase the likelihood of developing PTSD. These subtle EF deficits may then become more severe due to alterations in the neural circuitry that are associated with PTSD. As EF becomes increasingly impaired, so too does the ability of the individual to cope effectively with the emotional distress that they are experiencing.

Additionally, EF deficits may maintain and exacerbate PTS symptoms by making treatment adherence more difficult and increasing the likelihood of treatment dropout. The planning and problem solving issues that are common among those with EF deficits may make it difficult to work through basic logistic considerations that are necessary to attend regularly scheduled appointments and complete treatment (e.g., finding childcare, negotiating transportation issues or time off with an employer; Crocker et al., 2018). Moreover, EF is essential for effectively engaging in gold-standard treatments for PTSD (Mohlman & Gorman, 2005; Nijdam et al., 2011; Wild & Gur, 2008). For example, cognitive processing therapy (CPT; Resick & Schnicke, 1992), and other cognitive behavioral therapies, require clients to engage EF in the service of identifying and challenging maladaptive trauma-related cognitions. As such, in addition to the logistic considerations associated with treatment adherence, participating in treatment sessions may also be negatively impacted by EF deficits. Consistent with this hypothesis, Crocker et al. (2018) found that, among 74 Veterans with PTSD and traumatic brain injury, those who exhibited the largest deficits in EF (i.e., working memory, inhibition, set-shifting) prior to beginning a course of CPT were more likely to drop out of treatment and have smaller treatment gains than those who had relatively less pre-treatment deficits in EF. Of note, intellectual ability was assessed prior to treatment and accounted for in study analyses, thus ensuring that the observed effects were specific to EF.

Although there are relatively few longitudinal studies examining the temporal relation among EF deficits and PTS symptoms, the little evidence that exists suggests that EF deficits are a vulnerability factor for the development of PTS. Parslow and Jorm (2007) assessed neurocognitive functioning in a large sample (N = 1,599) of Australian young adults (ages 20-24) prior to the occurrence of a widespread natural disaster (i.e., a brushfire). A five-item trauma screening questionnaire that assessed re-experiencing and arousal symptoms was administered to participants within 12-82 weeks of the brushfire. Parslow and Jorm (2007) found that poorer pretrauma performance on tests that assessed general intelligence and abilities such as working memory and processing speed predicted higher levels of trauma-related re-experiencing and arousal symptoms at the follow-up assessment session.

Marx et al. (2009) extended the work of Parslow and Jorm (2007) by assessing PTSD symptoms, in their entirety, both prior to and following deployment to Iraq in 668 active duty US Army soldiers. They found that poorer pre-trauma visual working memory, but not inhibition or set-shifting, predicted higher levels of PTS symptoms following trauma-exposure even after controlling for pre-deployment PTS symptoms, combat intensity, test-retest interval, and demographic covariates. Marx et al. (2009) hypothesized that the ability to form and maintain a visual image in working memory may promote visual processing of traumatic events, thus increasing habituation to threat stimuli and decreasing the likelihood of developing PTSD.

Samuelson et al. (2020) built on the work of Marx et al. (2009) by adding an additional follow-up assessment session. Specifically, active-duty US Army personnel (N = 473) were assessed two weeks prior to being deployed to Afghanistan (T1), immediately upon returning from deployment (T2), and 10 months post-deployment (T3). PTS symptoms were assessed at all time points while EF was only assessed at T1 via performance-based tasks completed online. Samuelson et al. (2020) found that poorer pre-deployment EF (i.e., inhibition, working memory, set-shifting) predicted higher levels of PTS symptoms at T3 even after controlling for number of deployments, childhood trauma exposure, PTS at T1, and demographic variables.

Taken together, the results from these longitudinal studies suggest that EF deficits are a vulnerability factor for the development of PTS; however, they do not tell us about the role that EF plays in the maintenance and exacerbation of PTS following trauma exposure. As has been shown in previous research, risk factors for developing PTS symptoms can be different from those that are involved in maintaining PTS symptoms (Dunmore et al., 1999; Koenen et al.,2003; Schnurr et al., 2004). As such, the primary aim of the present study was to determine whether EF deficits exacerbate PTS symptoms over the course of one year. In the present study, participants completed an initial in-person assessment session (T1) and two follow-up assessments online 6- (T2) and 12- (T3) months later. Based on the logic described above (Vasterling & Brailey, 2005), we predicted that EF deficits would mediate the relationship between PTS symptoms at T1 and PTS symptoms at T3 even after accounting for PTS symptoms at T2. PTS symptoms were assessed at all three time-points in the present study, while EF deficits were assessed at T2 and T3. This allowed us to test a cross-lagged model between T2 and T3 to determine the directional relations among EF deficits and PTS symptoms over the course of six months. Although there is a lack of empirical evidence surrounding the prospective relations among PTS and EF deficits following trauma exposure, we tentatively hypothesized that the relationship between these constructs would most likely be bidirectional and mutually reinforcing. That is, we expected T2 PTS symptoms to be a significant predictor of EF deficits at T3 and vice versa.

2. Method

2.1. Participants

Recruitment consisted of posting flyers in public places (e.g., mental health clinics, hospitals) and advertising in local newspapers. To determine their eligibility to participate in the advertised study, potential participants who had experienced at least one “stressful life event” were instructed to contact study staff via phone. Approximately 350 individuals contacted study staff and completed the phone screen. Eligible participants (a) had normal or corrected vision, (b) were between the ages of 18-65, (c) were native English speakers, (d) reported experiencing at least one potentially traumatic event (defined as per Criterion A of the DSM-5 PTSD diagnosis; APA, 2013), and (e) obtained a score < 2 or > 4 on the Primary Care PTSD Screen for DSM-5 (PC-PTSD-5; Prins et al., 2016). One-hundred and thirty of the 350 potential participants who were screened met these eligibility criteria and 109 participants attended the T1 laboratory session. At the T1 laboratory session, eleven participants did not pass the secondary screening for inclusion in this study for one or more of the following reasons: reporting a current diagnosis of bipolar disorder (n = 7), having current psychosis (n = 2; First et al., 2015) or cognitive impairment (n = 1; Folstein et al., 1975), or having difficulty completing the study protocol (n = 1; e.g., falling asleep repeatedly during the session).

The average age of the T1 sample (N = 98; 75.5% female) was 31.5 years (SD = 13.7). In terms of race, 77% self-identified as White, 20% as Black, 1% as Asian, and 2% endorsed “other”. Additionally, 8% of the sample reported being of Hispanic or Latino/a ethnicity. Regarding education, 99% of the sample reported earning their high school diploma or GED, 89% reported taking part in at least some higher education, and 46% reported earning a 4-year college degree. The majority of the sample identified their relationship status as single (54%), with a household income of less than $50,000 (54%), and were either currently employed (50%) or full-time students (35%).

2.2. Measures

Screening measures.

To ensure that potential participants had experienced at least one traumatic event (as per Criterion A of the DSM-5; APA, 2013), the trauma screening questions from the Structured Clinical Interview for DSM-5 were administered during the phone screen (Bardeen et al., 2015). Additionally, the PC-PTSD (Prins et al., 2016), a 5-item screening tool for PTSD, was used during the phone screen to ensure that a substantial proportion of the final sample had relatively high levels of PTS symptoms. Specifically, once 50 participants with relatively low PTS symptoms were scheduled to participate in the T1 session (i.e., a score on the PC-PTSD-5 < 2), potential participants were then required to have a score on the PC-PTSD that maximizes efficiency in identifying probable cases of PTSD (i.e., a PC-PTSD-5 score > 4; Prins et al., 2016). Additionally, the Mini Mental Status Exam (MMSE; Folstein et al., 1975) and the psychosis screener from the SCID-5 (First et al., 2015) were administered during the T1 session to ensure that participants were not cognitively impaired or did not have a current psychotic disorder.

Life Events Checklist for DSM-5 (LEC-5; Weathers, Blake, et al., 2013b).

Lifetime trauma exposure was assessed with the LEC-5. Seventeen potentially traumatic events are listed on the LEC-5 (e.g., sexual assault, combat, motor vehicle accident). Respondents indicate whether any of the events on the list happened to them, they witnessed it, they learned about it, it was part of their job, they are unsure, or the event did not apply to them. The LEC-5 was used in the present study to identify the Criterion A event that would serve as the index event when assessing current PTS symptoms. The three most commonly endorsed event types in this sample that met DSM-5 Criterion A were sexual assault (29.6%), physical assault (16.3%), and transportation accident (14.3%). The remaining 39.8% of the sample endorsed index Criterion A events that were spread across 11 of the remaining 14 event type categories on the LEC-5.

Clinician-Administered PTSD Scale for DSM-5 (CAPS-5; Weathers, Blake, et al., 2013a).

The CAPS-5, the gold-standard clinical interview for assessing PTSD symptoms as defined in DSM-5, was administered by graduate level clinical psychology students under the supervision of a licensed clinical psychologist (i.e., the last author). The CAPS-5 has exhibited adequate psychometric properties (Weathers et al., 2018). Twenty percent of the recorded CAPS-5 interviews were independently reviewed by the last author for evaluation of interrater reliability. Excellent interrater reliability was observed in the present study (i.e., an intraclass correlation for total severity of .97; Cicchetti, 1994). The 20 items of the CAPS-5 were summed to create an overall total score for use as a continuous variable because evidence suggests that PTSD is a dimensional construct rather than a discreet clinical syndrome (Forbes et al., 2005; Ruscio et al., 2002). Considerable variability in symptom expression was observed in the present study (M symptoms = 6.09 [SD = 5.00], range = 0-16). Importantly, 87% of the sample reported at least one symptom that met DSM-5 criteria for PTSD.

PTSD Checklist-5-Civilian Version (PCL-5; Weathers, Litz, et al., 2013).

The PCL-5, a 20-item self-report measure that assesses DSM-5 PTSD symptom criteria (APA, 2013), was administered at all three time points. Participants use a 5-point scale (0 = not at all to 4 = extremely) to indicate how much they have been bothered by each symptom in the past month. Symptoms were rated in relation to the traumatic event that was identified by each participant as most distressing on the LEC-5. The 20 items of the PCL-5 were summed to create an overall total score. In the present sample, internal consistency of the PCL Total score was adequate at all three time points (T1 α = .93, T2 α = .95, T3 α = .95). Considerable variability in symptom expression was reported on the PCL-5 at all three time points (T1 M = 29.50 [SD = 17.43], T2 M = 26.81 [SD = 15.99], and T3 M = 24.25 [SD = 16.61]). Additionally, a substantial proportion of the sample reported clinically relevant PTS symptoms at all three time points (i.e., 55% at T1, 41% at T2, and 36% at T3 using the cut score of 28 identified by Blevins et al., 2015).

Barkley Deficits in Executive Functioning Scale-Short Form (BDEFS-SF; Barkley, 2011).

The BDEFS-SF is a 20-item self-report measure that assesses cognitive and behavioral manifestations of executive dysfunction. Participants use a 4-point scale (1 = never or rarely to 4 = very often) to indicate how often they exhibited behaviors associated with daily activities that are indicative of EF deficits over the past six months (i.e., time management, organization and problem solving, self-restraint, self-motivation, and self-regulation of emotions). The BDEFS–SF has exhibited adequate psychometric properties in previous research, including evidence of internal consistency and criterion-related validity to both self-report (Clauss et al., 2021;Feldman et al., 2013) and performance measures (Gray et al., 2014). Additionally, the BDEFS-SF has exhibited large magnitude correlations with measures of PTS symptoms (e.g., r = .56; Bardeen & Fergus, 2018), and factor analytic evidence supports the use of the BDEFS-SF total score (Clauss et al., 2021). In the present sample, internal consistency of the BDEFS-SF total score was adequate (T2 α = .90 [T2 M = 39.40, SD = 10.62], T3 α = .92 [T3 M = 39.90, SD = 11.39]).

2.3. Procedure

The local institutional review board approved study procedures prior to data collection. Participants completed a battery of self-report measures and the CAPS-5 clinical interview as part of a larger in-person laboratory study (i.e., T1; Bardeen et al., 2020). Upon completion of the T1 session, participants were debriefed and paid $90 as compensation. Participants, all of whom consented to being contacted for additional opportunities to participate in the longitudinal portion of this study, received an invitation to complete a battery of self-report measures online 6- and 12-months after completing T1 (i.e., T2 and T3). Participants were paid $30 for completion of each follow-up session. These assessment sessions could be completed from any computer with internet access. Participants who completed all three sessions received a bonus payment of $20. The retention rate was high (i.e., 94% at T2 [n = 92] and 93% at T3 [n = 91]).

3. Results

3.1. Path Analysis

Path analysis was conducted in MPlus 8.4 (Muthén & Muthén, 2017). Maximum likelihood estimation was used to account for missing data points and all variables were modeled as manifest indicators. PTS symptoms were assessed at all three time-points, whereas EF deficits were assessed at Times 2 and 3. This resulted in a partially cross-lagged model (i.e., from Time 2 to Time 3). More specifically, T1 PTS symptoms served as the only endogenous variable in the model, while PTS symptoms and EF deficits served as exogenous variables at Times 2 and 3 (see Figure 1). The manifest indicators within each time-point (T2 and T3) were allowed to correlate (MacKinnon, 2008). To ensure continuity in the measurement of PTS symptoms over time, the PCL-5 (Weathers, Litz, et al., 2013) was used to model PTS symptoms for each time point rather than modeling PTS symptoms at T1 with the CAPS-5 (Weathers, Blake, et al., 2013a). Of note, the magnitude of the correlations between the PCL-5 total score and CAPS-5 total symptom and severity scores at T1 serve as evidence of convergent validity between the CAPS-5 and PCL-5 (rs = .88 and .89, respectively, ps < .001). To assess the significance of indirect effects, bias-corrected bootstrapping, with 5,000 samples, was used to estimate the 95% confidence intervals around indirect effect parameters. Significant mediating effects are those for which confidence intervals do not include zero (Hayes & Scharkow, 2013). Fit statistics were not computed because a just-identified model provides perfect fit to the data. Standardized path coefficients are presented in Figure 1.1

Figure 1.

Figure 1.

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Path model with standardized path coefficients. Dashed lines indicate paths with nonsignificant coefficients.

*p < .05. ***p < 001.

As expected, each variable (PTS symptoms and EF deficits) predicted its subsequent measurement (βs from .54 to .63, ps < .001). Additionally, significant effects were observed for the direct paths from (a) T1 PTS symptoms to T2 EF deficits (β = .36, p < .001), (b) T1 PTS symptoms to T3 PTS symptoms (β = .20, p = .04), and (c) T2 EF deficits to T3 PTS symptoms (β = .17, p =.02). The direct paths from T1 PTS symptoms to T3 EF deficits and from T2 PTS symptoms to T3 EF deficits were not significant (β = .15, p = .10 and β = .04, p = .68, respectively). Of primary importance to the present study, T2 EF deficits mediated the relationship between T1 PTS symptoms and T3 PTS symptoms [indirect effect (95% CI) = .061 (0.015–0.140)].

4. Discussion

The primary aim of this study was to examine the role that EF deficits play in the pathogenesis of PTS. We utilized a three-wave study design with a community sample of trauma survivors who were prescreened to ensure that there were substantial PTS symptoms in the final sample. As predicted, EF deficits at T2 (six months post baseline) mediated the relationship between PTS symptoms from T1 to T3 (one year post baseline), thus suggesting that EF deficits are one possible mechanism underlying the maintenance of PTS symptoms over the course of one year. It is especially noteworthy that the mediating effect of EF deficits on the relation between T1 and T3 PTS symptoms was observed when simultaneously accounting for PTS symptoms at T2 because large autoregressive effects are typical when measuring PTS over time, and thus, can obscure smaller, but potentially important longitudinal effects. Additionally, as described above, there is some overlap in the behavioral indicators of these two constructs. Thus, simultaneously modeling both constructs at the point of mediation increases confidence that the observed mediation effect is specific to EF deficits rather than being a byproduct of the shared variance in these constructs.

A secondary aim of the present study was to examine the directional relations among EF deficits and PTS symptoms over the course of six months (between Time 2 and 3) using a cross-lagged panel design. The value in this type of analytic approach is that stronger causal inferences can be made regarding the nature of temporal relations among study variables (Cole & Maxwell, 2003). We tentatively hypothesized that the relationship between these constructs would be bidirectional and mutually reinforcing. Instead, the results from the cross-lagged paths from T2 to T3 suggest that EF deficits exert a stronger influence on the maintenance of PTS symptoms than PTS symptoms exert on EF deficits.

As described, EF deficits may contribute to the maintenance and exacerbation of PTS symptoms in a number of ways. First, EF deficits may maintain and exacerbate PTS symptoms because EFs can be used to down-regulate trauma-related distress (e.g., trauma-related negative affect and physiological arousal; Bardeen & Daniel, 2017). An individual who can no longer use EFs to successfully regulate trauma-related distress may turn to more extreme, less adaptive forms of self-regulation (e.g., rigid behavioral avoidance of trauma reminders), which in turn, maintains and exacerbates PTS symptoms. Second, EFs are essential for successfully planning and solving problems surrounding basic logistic considerations that one must attend to before receiving treatment, or simply before engaging in health-promoting behaviors (Crocker et al., 2018). As such, EF deficits may get in the way of natural recovery following trauma exposure, or of receiving treatment once symptoms have become clinically significant. Finally, for those who do initiate treatment, EF deficits may decrease treatment effectiveness and increase the likelihood of premature termination (Crocker et al., 2018).

In combination with the results from earlier studies that assessed EF pre-but not posttrauma (e.g., Marx et al., 2009; Parslow & Jorm, 2007; Samuelson et al., 2020), results from the present study support a model of the link between EF and PTS in which EF deficits contribute to both the development and maintenance of PTS symptoms. These results have important implications for prevention and treatment. Given that a large majority of the population will experience at least one potentially traumatic event (Bardeen & Benfer, 2019; Kilpatrick et al., 2013), it may be beneficial to identify at-risk individuals prior to trauma exposure so that these individuals can be offered a primary prevention to improve EF (e.g., the attention training technique; Wells, 1990, 2011; also see Fergus & Bardeen, 2016, for a review) that might reduce the likelihood of developing PTS symptoms. Through institution-wide screenings (e.g., brief screenings in academic settings), those with relative deficits in EF, and especially those with other vulnerability factors that have been shown to interact with EF deficits to predict PTS (e.g., maladaptive metacognitive beliefs; Bardeen & Fergus, 2018), could be identified and offered early intervention. However, the cost of conducting wide-scale testing may seem prohibitive to stakeholders; in which case, screening individuals for EF deficits in the acute aftermath of potentially traumatic events may be a financially viable option that would allow trauma-exposed individuals to receive treatment before PTS symptoms become clinically significant, chronic, and/or treatment resistant.

The reader will recall that EF is important for effectively engaging in empirically supported therapies for PTSD (Mohlman & Gorman, 2005; Nijdam et al., 2011; Wild & Gur, 2008). Cognitive behavioral treatments, such as CPT (Resick & Schnicke, 1992), rely heavily on EF processes to (a) monitor thoughts and emotions while inhibiting irrelevant internal and external stimuli, (b) evaluate the logic of potentially distorted thoughts, and (c) develop flexible alternatives to these maladaptive, symptom-maintaining cognitions. Because deficits in EF may decrease treatment effectiveness and increase the likelihood of premature termination (Crocker et al., 2018; Falconer et al., 2013), it might be beneficial to use a battery of standard neuropsychological measures to assess EF prior to the beginning of treatment to identify individuals who may benefit from alternate treatments that rely less heavily on EF. For example, prolonged exposure (PE; Foa & Rothbaum, 1998), another commonly used empirically supported CBT for PTSD, does not require clients to monitor or directly challenge maladaptive trauma-related cognitions, and thus, may rely less on EFs to facilitate treatment adherence and symptom reduction. Through a precision medicine-based approach, individuals with PTSD and relative deficits in EF could be referred to receive PE, whereas both CPT and PE may be equally effective for individuals with PTSD and relatively better EF. Because both treatments (CPT and PE) have exhibited efficacy in reducing PTS symptoms among individuals with PTSD and comorbid traumatic brain injury (see Rosen & Ayers, 2020, and Tanev et al., 2014, for reviews), it will be important to test the hypothesis that EF may be an important moderator of the relationship between treatment type and outcome in future studies.

Because EF can be improved through clinical intervention (Bherer et al., 2008; Jha et al., 2007; Klingberg, 2010; McDermott et al., 2016), it may be beneficial to modify empirically supported treatments for PTSD by adding a component that directly targets EF deficits. As suggested by Crocker et al. (2018), having clients complete cognitive training to strengthen EF prior to engaging in empirically supported treatments may allow treatment-seeking trauma survivors to more fully engage in and benefit from components of treatment that are more cognitively taxing (e.g., cognitive restructuring in CPT). Finally, when working with clients with EF deficits, some have suggested modifying treatments that rely heavily on the use of EF by providing a more directive and structured environment, and incorporating the following strategies: repeating key points frequently, using concrete language, simplifying worksheets, and providing written summaries and reminder cards (Bryant & Litz, 2012; Crocker et al., 2018).

Multi-wave longitudinal studies are strikingly rare in the extant literature. Instead, cross-sectional study designs are often used to test mediational hypotheses. Testing mediation with cross-sectional data fails to account for the time precedence that is required of mediational hypotheses (Cole & Maxwell, 2003; O’Laughlin et al., 2018; Pitariu & Ployhart, 2010). Additionally, as described by Maxwell & Cole (2007), “the substantial bias that typically exists in cross-sectional analyses of mediation can render p values or confidence intervals obtained from cross-sectional data essentially meaningless” (p. 40). While our longitudinal study design, with three assessment sessions, is a noteworthy strength of the present study, having a measure of EF deficits at every time point would have been ideal. Because this study was part of a larger study (Bardeen et al., 2020), concerns regarding participant fatigue precluded the assessment of self-reported EF deficits, and other potentially relevant constructs, at the initial laboratory session (T1). Additionally, because of the unexpected nature of traumatic events, EF deficits were not assessed prior to trauma exposure in the present study. Although evidence suggests that EF deficits are a pretrauma risk factor for the development of PTS symptoms (Marx et al., 2009; Parslow & Jorm, 2007; Samuelson et al., 2020), it will be important in future research to use a fully cross-lagged study design to examine the prospective associations among PTS symptoms and EF deficits. More specifically, stronger causal inferences can be made regarding the temporal relations among EF deficits and PTS symptoms by incorporating a pretrauma assessment session and at least three-waves of data collection (i.e., pretrauma, peritraumatic, and posttrauma measurements; Kumpula et al., 2011; Maxwell & Cole, 2007; Preacher, 2015).

In the present study, EF deficits were assessed via self-report (BDEFS-SF; Barkley, 2011) rather than with performance-based measures. This is in contrast to the few other longitudinal studies that have been published in which the associations among PTS symptoms and EF were examined (Marx et al., 2009; Parslow & Jorm, 2007; Samuelson et al., 2020). While some may perceive the use of self-report to assess EF deficits as a relative weakness of the present study, there are a number of benefits of using this approach rather than assessing EF deficits via performance measures. For example, some have argued that performance measures of EF have poor ecological validity and do not consistently relate to scores on measures of constructs that they should be theoretically associated with (Barkley & Murphy, 2010). In contrast, EF deficits assessed via self-report have been shown to be associated with EF deficits assessed using performance measures (Burgess et al., 1998; Gray et al., 2014), and the BDEFS total score has exhibited large magnitude correlations, as expected, with measures of PTS symptoms (Bardeen & Fergus, 2018). Additionally, previous longitudinal studies in which EF deficits were assessed at baseline via performance-based measures did not assess EF at subsequent time points (Marx et al., 2009; Parslow & Jorm, 2007; Samuelson et al., 2020). It seems likely that EF was not assessed following the initial baseline session in these previous studies because of potential logistic difficulties. That is, there would have been substantial additional cost and retention difficulties had participants been required to attend in-person follow-up sessions to complete performance measures of EF. Thus, assessing EF deficits via self-report allowed us to circumvent this potential methodological issue and conduct a true test of mediation. Finally, performance measures that require button press to respond to task stimuli introduce additional error variance because individual differences in motor speed contribute to the scores that are calculated from these tasks. Ultimately, it would be ideal to have participants complete both performance-based and self-report measures of EF in future studies to ensure that study findings are robust to these different assessment methods. The development of performance measures of EF that can be completed from one’s home computer may increase the feasibility of meeting this goal in future studies (e.g., the Cambridge Neuropsychological Test Automated Battery; Lowe & Rabbitt, 1998).

The use of samples that consist largely of undergraduate students and/or asymptomatic participants is common in this literature. For example, only 38 (2.4%) of the 1,599 participants who reported exposure to the natural disaster of interest in Parslow and Jorm (2007) screened positive for fire-related PTSD. This issue was addressed in the present study by recruiting trauma-exposed community members who were prescreened to ensure the presence of substantial PTS symptoms in the final sample. An additional strength of the present study is that the gold-standard structured clinical interview for assessing PTS symptoms was used to confirm baseline symptoms at T1 (Weathers, Blake, et al., 2013a). However, it is worth noting that although empirical evidence supports a dimensional, rather than categorical conceptualization of PTS (e.g., Broman-Fulks et al., 2006; Forbes et al., 2005; Ruscio et al., 2002), replicating study findings in a clinical sample will be important to ensure that these findings are generalizable to individuals who meet DSM-5 criteria for PTSD (APA, 2013). Additionally, it will be important to assess co-occurring psychopathology in future studies in this line of research to determine the degree to which the effects observed in this study are specific to PTS symptoms.

One additional limitation is worth considering. Our sample size may not have been large enough to produce ideal stability. While some structural equation modeling guidelines suggest that five participants per parameter is sufficient to have adequate power (e.g., Bentler & Chou), others recommend using upwards of 10 participants or more per parameter (Schreiber et al., 2006). As such, it will be important to replicate study findings with a larger sample, using longitudinal methods, in future researcher. Additionally, using a much larger sample will allow researchers to examine the specific domains of EF as they relate to PTSD symptom clusters over time. This is important because the directional relations among PTSD symptom clusters and certain types of EF deficits may be different than what was observed in the present study.

To our knowledge, this is the first longitudinal study to identify the mediating role of EF deficits as a possible mechanism underlying the maintenance of PTS symptoms over the course of one year. Moreover, the results of this study suggest that EF deficits exert a stronger influence on the maintenance of PTS symptoms than PTS symptoms exert on the maintenance of EF deficits. Given the overreliance on cross-sectional study designs that exists in this area of research, as well as the noted limitations of the available longitudinal studies in this area, the current longitudinal design, with three assessment sessions, and oversampling of symptomatic community members represent unique strengths of this study. As described, the results of this study have potentially important implications for the prevention and treatment of PTS. These include using EF assessments to identify at-risk individuals prior to and in the immediate aftermath of trauma exposure, developing a precision-medicine approach to PTSD treatment based on the assessment of EF, and modifying well-established PTSD treatments for those who have relative deficits in EF.

Highlights.

  • Longitudinal examination of executive functioning (EF) and posttraumatic stress (PTS)

  • EF deficits and PTS symptoms assessed at three time points over one year period

  • Time 2 EF deficits mediated relation between PTS symptoms from Time 1 to Time 3

  • EF deficits exacerbate PTS symptoms following trauma exposure

  • EF deficits exert stronger influence on the maintenance of PTS symptoms than vice versa

Acknowledgements

This research was supported by a grant from the National Institute of Mental Health awarded to the first author (R21MH112929). We thank Natasha Benfer, Kate Clauss, Kelsey Thomas, Victoria Swaine, Natalie Conboy, and Kaylin Farmer for their assistance with data collection.

Footnotes

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1

At the request of an anonymous Reviewer, who was interested in whether the effects observed in the path analysis would remain significant after controlling for demographic and trauma-related variables, covariates were examined for inclusion in the primary analysis and the model was run a second time. Race and ethnicity (White and non-Hispanic [69.4%] versus all other participants [30.6%]), income (< or > $50,000 per year [54% and 46%, respectively]), and education (< or > a 4-year college degree [54% and 46%, respectively]) were collapsed into dummy coded variables. Additionally, the event types endorsed on the LEC-5 were summed to serve as an index of cumulative trauma (Clauss et al., 2021). Bivariate correlations were calculated in order to examine associations among descriptive and trauma-related statistics (i.e., race/ethnicity, age, income, education, cumulative trauma) and variables of interest (PTS symptoms at T1, T2, and T3, EF deficits at T2 and T3). Among potential covariates, race/ethnicity (0 = all other participants/1 = White and non-Hispanic) was associated with T1 PTS symptoms (r = −.21, p = .037) and cumulative trauma was associated with T2 PTS symptoms (r = .23, p = .03). As such, we repeated our primary analysis including race/ethnicity and cumulative trauma in the path model. Results were consistent with our initial analysis; statistically significant findings remained significant and nonsignificant findings were unchanged.

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