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. Author manuscript; available in PMC: 2026 May 9.
Published in final edited form as: J Anxiety Disord. 2023 Jan 13;94:102670. doi: 10.1016/j.janxdis.2023.102670

Investigating the specific domains of the cognitive attentional syndrome that predict posttraumatic stress symptoms: The moderating effect of attentional control

Kate Clauss 1, Julia Y Gorday 1, Joseph R Bardeen 1,*
PMCID: PMC13154682  NIHMSID: NIHMS2170637  PMID: 36701955

Abstract

The metacognitive model of posttraumatic stress disorder (PTSD) suggests that persistent use of the maladaptive self-regulation strategies that comprise the cognitive attentional syndrome (CAS) increases the likelihood of developing PTSD symptoms following trauma exposure. The metacognitive model also suggests that flexible regulation of attention might be protective against developing maladaptive outcomes that are associated with the CAS. The aims of this study were to (1) examine associations between all seven domains of the CAS and PTSD symptoms using a recently developed, multidimensional measure of the CAS, and (2) examine the moderating effect of self-reported attentional control on associations between the CAS and PTSD symptoms. Participants were trauma-exposed community adults (N = 237) who completed a battery of self-report measures. Results from linear regression analyses showed that worry, substance use, and internal threat monitoring accounted for unique variance in PTSD symptoms when all seven CAS domains were entered into the same model. Moderation analyses showed that attentional control dampened the effect of the CAS, specifically external threat monitoring, on PTSD symptoms. Study results support attentional control as a protective factor against the maladaptive effects of the CAS on PTSD symptoms.

Keywords: Cognitive attentional syndrome, Posttraumatic stress disorder, PTSD, Attentional control, Metacognitive, Metacognition

The metacognitive model (Wells & Sembi, 2004b; Wells, 2009) provides a unique framework for understanding the development and maintenance of posttraumatic stress disorder (PTSD), by suggesting that the way in which one interacts with their thoughts, versus the thought content alone, influences the development of symptoms. Specifically, maladaptive beliefs about thinking, termed metacognitive beliefs, are proposed to activate a host of maladaptive self-regulatory strategies, which constitute the cognitive attentional syndrome (CAS; Wells, 2009; Wells & Sembi, 2004b). These include: external threat monitoring (e.g., scanning the environment), internal threat monitoring (e.g., paying attention to thoughts and emotions), behavioral avoidance (e.g., avoiding uncomfortable situations), substance use (e.g., using alcohol or drugs to avoid unwanted internal experiences), thought suppression (e.g., pushing uncomfortable thoughts away), rumination (e.g., repetitive negative thinking about past events), and worry (e.g., repetitive negative thinking about future events; Conboy et al., 2021; Wells, 2009). According to the metacognitive model of PTSD (see Fig. 1), consistent and inflexible use of these self-regulation strategies in the acute aftermath of a traumatic event exacerbates initial emotional distress, thus increasing the likelihood that posttraumatic stress (PTS) symptoms will develop and be maintained (Wells, 2009). However, in prior research in this area, specific domains of the CAS (e.g., thought suppression, rumination, worry) have been examined independently in relation to PTS symptoms because there has not been a psychometrically sound measure capable of assessing the CAS in its entirety. To address this limitation, Conboy et al. (2021) created the Multidimensional Cognitive Attentional Syndrome Scale (MCASS), which has exhibited strong psychometric properties and full content coverage of the CAS construct. Therefore, one purpose of the present study was to examine associations between all seven domains of the CAS and PTS symptoms. In addition, the metacognitive model of PTSD suggests that inflexible use of the CAS is particularly problematic, and that individuals with higher levels of attentional control (i.e., top-down regulation of attention in the face of conflicting attentional demands; Sarapas et al., 2017), may be able to use that ability in the service of adaptive goal-relevant pursuits (i.e., value-driven behavior). As such we also tested the hypothesis that attentional control would moderate the effect of the CAS on PTS symptoms, such that the positive association between the CAS and PTS symptoms would be attenuated at higher levels of attentional control.

Fig. 1.

Fig. 1.

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The Metacognitive Model of PTSD as per Wells (2009).

1. The metacognitive model of PTSD

Contrasting with popular cognitive models of PTSD (e.g., Ehler’s and Clark, 2000), Wells’s metacognitive model of PTSD (Wells & Sembi, 2004b; Wells, 2009) suggests that although negative beliefs about the self, others, and world are common following trauma exposure, negative thought content does not underlie PTSD. Rather, PTSD occurs as the result of how individuals respond to their thoughts and inner experiences (e.g., intrusive images, memories). Specifically, PTSD is more likely to occur when individuals respond with rumination, worry, or other avoidant coping strategies that make up the CAS. The CAS is proposed to be maladaptive because it increases threat perceptions and blocks emotional processing (Wells & Sembi, 2004a; Wells, 2009). As predicted by Wells’s metacognitive model of PTSD, specific domains of the CAS are positively associated with PTS symptoms. These include thought suppression (Amstadter & Vernon, 2008; Garland & Roberts-Lewis, 2013), rumination (Moulds et al., 2020; Seligowski et al., 2015), and worry (Bardeen et al., 2013; Roussis & Wells, 2006). These preliminary results suggest that the CAS may be important for understanding the pathogenesis and maintenance of PTSD. Until recently, research on the metacognitive model of PTSD has been impeded because existing measures of the CAS did not provide adequate coverage of the proposed domains. To address this limitation, Conboy et al. (2021) created the MCASS, which assesses the CAS in its entirety, allowing for the simultaneous examination of the effects of all seven domains of the CAS on PTS symptoms. Of note, the MCASS doesn’t measure the frequency of various behaviors (e.g., substance use, worry), but instead, measures the extent to which these behaviors are used in the service of avoidance coping.

2. The moderating effect of attentional control

In addition to the risk factors described above, the metacognitive model of PTSD accounts for the potential influence of cognitive control on PTS symptoms (Wells & Sembi, 2004b). The model posits that internal- and external-threat monitoring contribute PTS symptom maintenance. Moreover, it suggests that attentional control can be used to flexibly disengage attention from internal experience (e.g., worry, rumination, and other forms of self-focused attentional processes) and external stimuli that may get in the way of maintaining attentional focus on adaptive goal-relevant pursuits (i.e., value-driven behavior). In fact, Metacognitive Therapy devotes an entire module to attention training (i.e., the attention training technique [ATT]; Wells, 1990), to improve attentional control, which can then be used to disengage from rumination, worry, and other maladaptive forms of self-focused attention (see Fergus & Bardeen, 2016 for a review). Therefore, the metacognitive model acknowledges that greater attentional control can be used adaptively to reduce engagement with the CAS. Moreover, past research shows that self-reported attentional control buffers the effects of the CAS on anxiety and depression (Fergus et al., 2012). Thus, it stands to reason that individual differences in attentional control might moderate the relationship between the CAS and PTS symptoms, such that the strength of the relationship between the CAS and PTS symptoms decreases as attentional control increases.

3. Rationale and hypotheses

Given that theoretical models implicate the CAS in the pathogenesis of PTS symptoms, and empirical evidence supports associations between domains of the CAS and PTS symptoms, in the present study, associations between the MCASS and PTS symptoms were examined in a community sample of trauma-exposed adults. We hypothesized that the MCASS total and subscale scores would exhibit significant positive associations with PTS symptoms. Exploratory analyses were conducted to determine which of the seven CAS domains accounted for the most unique variance in PTS symptoms when they were modeled simultaneously. Additionally, we predicted that individuals with probable PTSD would endorse higher MCASS scores than individuals without probable PTSD. Finally, based on the role that attentional control is proposed to play in disengaging from the CAS in Wells’s metacognitive model and metacognitive therapy, as well as previous research (Fergus et al., 2012), we hypothesized that self-reported attentional control would interact with the CAS, such that the relationship between the CAS and PTS would become weaker as attentional control increased. We conducted exploratory analyses to determine whether the moderating effect of attentional control was specific to individual CAS domains.

4. Method

4.1. Participants and procedure

Participants were recruited through Amazon’s Mechanical Turk (MTurk) and were eligible to participate if they were 18–64 years old, fluent in English, and located in the United States. As a data quality measure, only MTurk users with a 95% or better approval rating and who had completed 50 tasks in the past were allowed to participate. Bots (i.e., computer programs that automatically complete online studies; Yarrish et al., 2019), were identified through the examination of open-ended responses. Responses identified as bots were removed (n = 33). Regarding the quality of MTurk data, research suggests that MTurk users are more attentive to manipulation checks than undergraduate samples (Hauser & Schwarz, 2016) and the quality measures described above have been shown to produce high quality data (Peer et al., 2014). MTurk samples are also more demographically diverse than those recruited via social media or on college campuses (Casler et al., 2013; Chandler & Shapiro, 2016), which improves the generalization of study findings.

The final trauma-exposed sample (N = 237) was 55.7% female and reported an average age of 36.68 (SD = 10.68) years. The majority of the sample identified as White (78.9%) followed by Black or African American (11.8%), Asian (5.1%), American Indian or Alaska Native (1.7%), Native Hawaiian or other Pacific Islander (1.3%), and not listed (1.3%). In addition, 12.7% of the sample identified as Hispanic or Latino. Finally, the majority of the sample identified as Heterosexual or Straight (80.2%), followed by Bisexual (12.7%), Homosexual, Gay, or Lesbian (3.4%), Asexual (1.7%), Pansexual (1.3%), and Questioning (.8%).

Study procedures were approved by the local institutional review board. Participants could complete the study from any device with internet access. Informed consent and study measures were presented using Qualtrics, an online survey program. Self-report measures were presented in random order. Participants were debriefed and financially compensated for study participation (Buhrmester et al., 2016; Crump et al., 2013).

4.2. Measures

The Multidimensional Cognitive Attentional Syndrome Scale (MCASS; Conboy et al., 2021) is a 21-item measure of the seven factors that make up cognitive attentional syndrome (CAS; i.e., worry, substance use, rumination, thought suppression, behavioral avoidance, internal threat monitoring, and external threat monitoring). The MCASS is scored on a 6-point scale from 1 (strongly disagree) to 6 (strongly agree) with higher scores indicating greater activation of the CAS. Example items include “When unpleasant memories come to me, I try to put them out of my mind” and “I stay alert or watchful at all times”. In its initial validation, the MCASS exhibited adequate internal consistency (total score α = .93; subscale scores αs =.74 to.93), as well as convergent, discriminant, and criterion-related validity (Conboy et al., 2021). In a follow-up examination of the MCASS, results from a bifactor analysis suggested that the MCASS is multidimensional, has a strong general factor, and distinct domain-specific factors (Bardeen et al., in press). Taken together, these studies indicate that the MCASS has strong psychometric properties and is capable of assessing the proposed multidimensional nature of the CAS. The total (α = .93) and subscale scores (αs =.77–.95) exhibited acceptable internal consistency in the present study. See Table 1 for descriptive statistics.

Table 1.

MCASS Descriptive Statistics.

Variable Range M SD α
MCASS Total 23–121 79.08 20.40 .93
Worry 3–18 9.96 4.41 .90
Substance Use 3–18 8.81 5.15 .95
Rumination 3–18 11.95 4.05 .90
Thought Suppression 3–18 12.48 3.27 .85
Behavioral Avoidance 3–18 11.97 3.64 .86
Internal Threat Monitoring 3–18 12.17 3.51 .77
External Threat Monitoring 3–18 11.73 3.78 .84
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Note. N = 237

The Extended Version of the Life Events Checklist for DSM-5 (LEC-5; Weathers et al., 2013) is a self-report measure of trauma exposure to 17 different types of potentially traumatic events (e.g., natural disaster, sexual assault). For each event type, participants indicated whether the event happened to them, they witnessed it happen to someone else, they learned about it happening, it happened as part of their job, they do not know, or it does not apply to them. The top five most commonly endorsed index event categories were transportation accident (16.9%), natural disaster (11.8%), sexual assault (11.8%), life-threatening illness or injury (10.1%) and serious accident (8%). Participants then completed a series of questions about the event types they endorsed, including a brief narrative, which aided in identifying events that met Criterion A for a diagnosis of PTSD as per the Diagnostic and Statistical Manual of Mental Disorders – Fifth Edition (DSM-5; American Psychiatric Association, 2013). Participants were included in the final sample if they reported experiencing at least one event that met Criterion A.

The PTSD Checklist (PCL-5; Weathers & Litz, 2013) is a 20-item self-report measure used to assess past-month PTS symptoms. Participants rated how much each symptom bothered them in the past month from 0 (not at all) to 4 (extremely). Higher scores indicate greater PTS symptoms. The PCL-5 has exhibited adequate psychometric properties in past research including internal consistency and construct validity (Blevins et al., 2015; Bovin et al., 2016). In the present study, the PCL-5 exhibited acceptable internal consistency (α = .98, M = 28.99, SD = 23.00, range = 0–75).

The Attentional Control Scale (ACS; Derryberry & Reed, 2002) is a 20-item self-report measure of perceived attentional control. Participants are asked to rate how often or how much each item (e.g., “After being interrupted or distracted, I can easily shift my attention back to what I was doing before”) applies to them from 1 (almost never) to 4 (always). Higher scores indicate better attentional control. The ACS has exhibited adequate psychometric properties including internal consistency and construct validity (Derryberry & Reed, 2002). In the present study, the ACS exhibited acceptable internal consistency (α = .81, M = 53.26, SD = 8.67, range = 28–79).

4.3. Data analytic strategy

Analyses were conducted using IBM SPSS Statistics 26. Bivariate correlations were calculated to evaluate associations between the MCASS and PCL-5. The calculator provided by Lee and Preacher (2013) was used to evaluate whether specific correlations were statistically different from one another. The calculator uses Steiger (1980) calculations to produce a z-test of the difference between two correlations. Additionally, the MCASS subscales were examined as predictors of PTSD symptoms using linear regression. All seven MCASS subscales were entered into the first step of the model with the PCL-5 total score as the dependent variable.

Next, we examined whether individuals with probable PTSD differed from those with low or no PTSD symptoms in their endorsements of MCASS scales. Research suggests that scores greater than or equal to 31 on the PCL-5 are indicative of probable PTSD (Bovin et al., 2016). Two groups were created based on this assumption, a “probable PTSD” group with PLC-5 total scores of 31 or higher, and a “non PTSD” group with PCL-5 total scores below 31. The sample was evenly distributed between the probable PTSD (50.6%) and non PTSD (49.4%) groups. One-way analysis of variance (ANOVA) was used to examine mean differences in MCASS total and subscale scores between the two groups.

To examine whether the MCASS interacts with an established protective factor (i.e., attention control) in a manner that is consistent with past research (Fergus et al., 2012), the moderating effect of attentional control on the relationship between the MCASS total score and the PCL-5 was examined using hierarchical regression. The predictor (MCASS total score) and moderator (ACS total score) variables were mean-centered, and the interaction term was calculated as the product of the predictor and moderator variables (Aiken et al., 1991). Main effects (i.e., MCASS, ACS) were entered into the first step of the model and the interaction term (MCASS by ACS) was entered into the second step of the model. Significant interactions were examined using simple slopes analysis (Aiken et al., 1991), which tests the effects of the predictor variable (MCASS) at high (+1 SD) and low (−1SD) levels of the moderator (ACS). To better understand which aspects of the CAS interact with attentional control, we also examined the moderating effect of attentional control on the relationship between each of the MCASS subscales and the PCL-5.

5. Results

5.1. Associations between the MCASS and PCL-5

Correlations between study variables are displayed in Table 2. All associations between the MCASS total and subscale scores and the PCL-5 total and subscale scores were significant and positive. The MCASS behavioral avoidance subscale correlated most strongly with the PCL-5 avoidance subscale, versus the other PCL-5 subscales. However, the only statistically significant difference between the magnitude of these significant correlations was for the association between the MCASS behavioral avoidance and the PCL-5 avoidance subscales versus the MCASS behavioral avoidance and the PCL-5 reexperiencing subscales. Comparisons of the magnitude of the other MCASS behavioral avoidance correlations with various PCL-5 subscales were not significantly different. The MCASS external threat monitoring subscale was most strongly associated with the PCL-5 hyperarousal subscale as compared to the other PCL-5 subscales; however, the differences in the magnitude of these significant correlations were not statistically significant.

Table 2.

Bivariate correlations between MCASS and PCL-5 total and subscale scores.

1 2 3 4 5 6 7 8 9 10 11 12 13
1. MCASS Total Score
2. Worry .85
3. Substance Use .67 .58
4. Rumination .78 .61 .37
5. Thought Suppression .60 .42 .17 .42
6. Behavioral Avoidance .71 .52 .26 .51 .50
7. Internal Threat Monitoring .79 .62 .38 .61 .40 .55
8. External Threat Monitoring .73 .56 .40 .50 .34 .40 .56
9. PCL Total Score .70 .72 .66 .44 .29 .36 .53 .45
10. Reexperiencing .64 .67 .63 .40 .26 .32 .49 .42 .97
11. Avoidance .66 .65 .57 .46 .32 .40 .50 .43 .89 .86
12. NACM .68 .72 .63 .46 .28 .37 .52 .42 .98 .92 .85
13. Hyperarousal .68 .71 .68 .40 .28 .34 .51 .47 .97 .92 .83 .92
14. ACS Total Score −.42 −.49 −.24 −.44 −.07 −.32 −.38 −.17 −.43 −.40 −.38 −.45 −.41
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Note. N = 237.

*

All bolded correlations significant at p < .05. MCASS = Multidimensional Cognitive Attentional Syndrome Scale, PCL-5 = PTSD Checklist, ACS = Attentional Control Scale.

5.2. Do the MCASS subscales predict PTSD symptoms?

Linear regression was used to examine the specific contributions of the MCASS subscale scores in predicting PTSD symptoms. All seven MCASS subscales were entered into the first step of the model with the PCL-5 total score as the dependent variable. The overall model was significant F(7, 229) = 52.87, p < .001, and explained 61% of the variance in the PCL-5 total score. Worry (β = .47, p < .001, 95% CI: 1.77, 3.12), Substance Use (β = .36, p < .001, 95% CI: 1.16, 2.05), and Internal Threat Monitoring (β = .15, p = .02, 95% CI:.18, 1.73) exhibited significant, positive associations with the PCL-5 total score. All other MCASS subscales (i.e., rumination, thought suppression, behavioral avoidance, and external threat monitoring) did not significantly predict the PCL-5 total score (ps > .05).

5.3. Mean Differences in the MCASS total score by PTSD group

One-way analysis of variance (ANOVA) was used to examine mean differences in the MCASS total and subscale scores between the probable PTSD and non PTSD groups. The PTSD grouping variable was entered as the independent variable and the MCASS total and subscale scores were entered as the dependent variables. The probable PTSD group had significantly higher MCASS total and subscale scores than the non PTSD group (all ps <.01, see Table 3).

Table 3.

Differences in MCASS total and subscale scores between PTSD and non PTSD groups.

Variable Non PTSD Group PTSD Group
Mean SD Mean SD F η2
MCASS Total Score 66.43 17.76 91.41 14.40 141.76** .38
Worry 6.94 3.70 12.91 2.74 200.06** .46
Substance Use 5.52 4.06 12.03 3.95 156.44** .40
Rumination 10.43 4.63 13.43 2.68 37.43** .14
Thought Suppression 11.77 3.69 13.18 2.65 11.41* .05
Behavioral Avoidance 10.89 4.20 13.03 2.61 22.27** .09
Internal Threat Monitoring 10.56 3.78 13.75 2.32 61.89** .21
External Threat Monitoring 10.32 4.30 13.10 2.54 36.87** .14
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Note. N = 237. MCASS = Multidimensional Cognitive Attentional Syndrome Scale. Non PTSD Group = PTSD Checklist Scores < 31. PTSD Group = PTSD Checklist Scores ≥ 31.

*

p < .01,

**

p < .001.

Cohen’s (1988) η2 conventions:.01 small,.06 medium,.14 large.

5.4. The moderating effect of attentional control on the relationship between the MCASS and PCL-5

5.4.1. MCASS total score

In the first step of the regression model (adjusted R2 =.50, p < .001), the MCASS total score (β = .63, p < .001, 95% CI:.59, 82) and the ACS total score (β = −.17, p < .01, 95% CI: −.71, −.18) significantly predicted the PCL-5 total score. In the second step of the model (ΔR2 =.02, p = .003), the interaction between the MCASS total score and the ACS total score significantly predicted the PCL-5 total score (β = −.15, p < .01, 95% CI: −.03, −.01). Simple slopes analysis revealed a positive association between the MCASS total score and the PCL-5 total score that was stronger at lower (β = .78, p < .001, 95% CI:.72, 1.03), versus higher (β = .50, p < .001, 95% CI:.42,.71), levels of attentional control (see Fig. 2).

Fig. 2.

Fig. 2.

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The interactive effect of the MCASS and ACS on PCL-5. Note. MCASS = Multidimensional Cognitive Attentional Syndrome Scale, ACS = Attentional Control Scale, PCL-5 = PTSD Checklist for DSM-5. Low and High AC refer to scores +/− 1 SD above and below the mean.

5.5. MCASS subscale scores

In the first step of the regression model (adjusted R2 =.62, p < .001), Worry (β = .40, p < .001, 95% CI: 1.38, 2.80), Substance Use (β = .37, p < .001, 95% CI: 1.21, 2.09), Internal Threat Monitoring (β = .13, p = .03, 95% CI:.08, 1.61) and the ACS total score (β = −.14, p = .01, 95% CI: −.64, −.12) significantly predicted the PCL-5 total score. In the second step of the model (ΔR2 =.03, p = .03), only the interaction between External Threat Monitoring and the ACS total score significantly predicted the PCL-5 total score (β = −.12, p = .03, 95% CI: −.12, −.01). Simple slopes analysis revealed a positive association between External Threat Monitoring and PCL-5 total score that was significant at lower (β = .15, p = .03, 95% CI:.08, 1.78), but not higher (β = −.03, p = .61, 95% CI: −1.01,.60), levels of attentional control.

6. Discussion

Using the recently developed MCASS, the present study provides support for the theoretical assumption from the metacognitive model of PTSD that CAS-related coping is associated with greater PTS symptoms (Wells & Sembi, 2004b). Moreover, regarding the clinical significance of these findings, individuals with PTS symptoms that met the threshold for probable PTSD endorsed greater CAS-related coping than individuals with subthreshold symptoms. Worry, substance use, and internal threat monitoring accounted for unique variance in PTSD symptoms when all seven subscales were modeled simultaneously. This highlights an essential contribution of the MCASS to the larger literature, namely the ability to measure all aspects of the CAS within a single measure (i.e., content validity). Finally, results extend past research demonstrating the buffering effect of attentional control on the association between the CAS and psychopathology (Fergus et al., 2012). Specifically, the association between the MCASS and PTS symptoms increased in strength as self-reported attentional control decreased. An exploratory follow-up analysis suggests that, of the seven domains of the CAS, external threat monitoring was driving this effect.

As described, results of the present study suggest that of the seven domains of CAS-based coping, worry, substance use, and internal threat monitoring share particularly strong associations with PTS symptoms. The MCASS is a measure of maladaptive self-regulatory strategies. It is posited that this avoidance contributes to greater emotional disorder (Wells & Sembi, 2004b). Existing models conceptualize substance use and worry in a similar manner. For example, negative reinforcement models of substance use posit that substances are used to escape emotional distress (Blume, 2001). In the context of PTSD, individuals may dampen their emotional response to intrusions, unwanted internal experiences, or external threat detection via substances. Similarly, the cognitive avoidance model of worry suggests that worry is used as an avoidance strategy in response to threat detection (Sibrava & Borkovec, 2006). Specifically, individuals with PTSD may perceive potential future threats for which there is no solution and utilize worry to alleviate anxious arousal in the short term. Thus, conceptual accounts support the notion that these domains of the CAS are used in the service of maladaptive avoidance, thereby contributing to greater PTS symptoms. Much like substance use and worry, it is hypothesized that internal threat monitoring serves as an avoidance coping strategy. Specifically, it is often maladaptively applied in an inflexible manner to avoid an unlikely catastrophic event. Some evidence suggests that rigid and inflexible internal threat monitoring may play a role in psychopathology. For example, Benfer et al. (2017) found that greater involuntary internal threat monitoring exacerbated the maladaptive effect of emotional distress intolerance on anxiety. In contrast, voluntary and flexibility applied attention to thoughts and emotions reduced the impact of emotional distress intolerance on anxiety. Taken together with the results of the present study, these findings suggest that internal threat monitoring may be a potentially important avoidant coping strategy for understanding the development and maintenance of PTSD.

Finally, the moderating effect of self-reported attentional control on the association between the CAS, specifically external threat monitoring, and PTS symptoms can be understood within the context of dual process models of attention (Eysenck et al., 2007). Such models are supported by evidence showing that, among individuals with elevated PTS symptoms, those with relatively better attentional control disengage and shift attention from threat stimuli, while those with relatively worse attentional control tend to maintain attention on threat (Bardeen & Daniel, 2017; Bardeen & Orcutt, 2011; Bardeen & Tull, 2016; Bardeen et al., 2020; Clauss et al., 2021). The results of this study are consistent with these previous findings and suggest that relatively better attentional control may buffer the impact of CAS-based coping on PTS symptoms. As described, the metacognitive model posits that the consistent and inflexible use of the CAS is problematic (Wells, 2009). Better attentional control might allow for more flexible regulation of attention in the context of perceived threat. Consistent with this conceptualization, the attention training technique (Wells, 1990; see Fergus & Bardeen, 2016 for a review), a component of metacognitive therapy, seeks to reduce the rigid threat monitoring that is characteristic of the CAS by strengthening attentional control through attentionally demanding auditory monitoring exercises (Wells, 2009). In future research, it may be important to not only measure perceived attentional control, but also the ability to use executive control flexibly and adaptively.

6.1. Clinical and research implications

Study findings suggest that individuals who endorse greater activation of the CAS, specifically, worry, substance use, and internal threat monitoring, may be at greater risk for PTS symptoms. Identifying CAS-related coping, via the MCASS, may provide clinicians with opportunities to intervene on maintenance factors that are most relevant to each specific client. For example, a client with PTSD who reports using substances to avoid emotional distress may benefit from an intervention designed to simultaneously address substance use and PTS symptoms such as Concurrent Treatment of PTSD and Substance Use Disorders using Prolonged Exposure (COPE; Back et al., 2014). Similarly, a client with PTSD who reports excessive internal threat monitoring, may benefit from the addition of a brief intervention such as Cognitive Anxiety Sensitivity Treatment (CAST), which has been shown to reduce PTS symptoms (Mitchell et al., 2014). Additionally, the MCASS could be used to monitor CAS-related changes over the course of treatment, which could contribute to a better understanding of mechanisms of change underlying PTS symptom reduction. This might be particularly relevant for metacognitive therapy, which was designed to reduce PTS symptoms through reductions in metacognitive beliefs and the CAS.

The present study also has implications for future research. First, study findings contribute to growing support for the strong psychometric properties of the MCASS. For example, the total and subscale scores exhibited adequate internal consistency. Moreover, this study provides evidence of criterion-related validity with a measure of PTS symptoms. Second, a unique strength of the MCASS compared to other measures of the CAS, is its ability to simultaneously measure all seven CAS domains. In this way, the MCASS addresses the call for a measure with better content coverage of the CAS that could potentially account for more variance in psychopathology (Mitchell et al., 2014). Additionally, the MCASS will allow researchers to simultaneously examine increasingly complex associations between CAS domains, which has the potential to dramatically advance our understanding of the metacognitive model of PTSD. Finally, the metacognitive model puts forth the CAS as a risk factor for the development emotional disorder. The longitudinal nature of the model has yet to be tested. With a multidimensional measure of the CAS in place, associations between metacognitive beliefs, CAS domains, and psychopathology can be examined to an extent that was not previously possible. This will help determine whether CAS domains serve as risk versus maintenance factors in the pathogenesis of PTSD. In the present study, the MCASS accounted for a substantial portion (61%) of the variance in PTS symptoms. However, using a longitudinal study design to examine the metacognitive model in its entirety would help determine what additional variance might be accounted for by other aspects of the model (e.g., metacognitive beliefs). It may also be that other well-established risk factors for PTSD (e.g., social support; repeated trauma exposure, pre-existing psychiatric conditions; Vogt et al., 2007) account for the remaining variance in PTS symptoms.

7. Limitations

Study limitations should be acknowledged. First, this study was conducted in an unselected community sample via an online crowd-sourcing service. Although online data collection has advantages, including ease of data collection, increased sample diversity (Casler et al., 2013; Chandler & Shapiro, 2016), and increased attentiveness compared to undergraduate samples (Hauser & Schwarz, 2016), there has been increasing concern about data quality in recent years (Chmielewski & Kucker, 2020). Moreover, the unselected sample used in the present study limits our ability to draw conclusions about how the MCASS relates to PTSD diagnostic status. We attempted to address this concern by grouping participants into a probable PTSD group and non PTSD group based on their PCL-5 scores (Bovin et al., 2016). Approximately half of the sample had PCL-5 scores indicative of probable PTSD. As expected, the probable PTSD group endorsed higher MCASS scores than the non PTSD group, but future research should examine associations between the MCASS and PTS symptoms in a clinical sample with a diagnosis of PTSD. Additionally, because our sample was unselected, it is unclear the extent to which study participants may have had comorbid psychiatric conditions. PTSD is highly comorbid with anxiety, mood, and substance use disorders (Galatzer-Levy et al., 2013). To rule out the influence of comorbidity on the observed effects, it would be beneficial in future research to re-examine the associations between the MCASS and PTS symptoms, while statistically controlling for comorbid symptoms. Finally, we note the use of a self-report measures as a limitation of the present study. Use of clinician administered interviews could provide a more accurate measure of PTS symptoms in future research. Further, self-reported and behaviorally assessed attentional control variables have shown suboptimal associations in past research (Quigley et al., 2017); therefore, it will be important to replicate these findings using behavioral measures of attentional control.

8. Conclusions

The present study is the first to examine associations between all seven CAS domains and PTS symptoms. Study results show that higher MCASS scores are associated with higher PTS symptoms and suggest that worry, substance use, and internal threat monitoring may be particularly relevant to PTS. The present study is also the first to show that attentional control moderates the effect of the CAS on PTS symptoms. Taken together, these data support assumptions from the metacognitive model of PTSD that CAS activation is associated with greater PTS symptoms, but that the ability to flexibly regulate attentional control may be protective against such effects. Due to its ability to simultaneously measure all seven CAS domains, the MCASS is well-positioned to advance research on the metacognitive model of PTSD. Examining longitudinal associations between the MCASS, attentional control, and psychopathology is an important next step in advancing this line of research.

Data availability

Data will be made available on request.

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Data Availability Statement

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