Is computerized psychoeducation sufficient to reduce anxiety sensitivity in an at-risk sample?: A randomized trial

Author’s Accepted Manuscript Is computerized psychoeducation sufficient to reduce anxiety sensitivity in an at-risk sample?: A randomized trial Aaron M. Norr, Brittany A. Gibby, Norman B. Schmidt www.elsevier.com/locate/jad

PII: DOI: Reference:

S0165-0327(16)31675-5 http://dx.doi.org/10.1016/j.jad.2017.01.032 JAD8752

To appear in: Journal of Affective Disorders Received date: 14 September 2016 Revised date: 23 December 2016 Accepted date: 23 January 2017 Cite this article as: Aaron M. Norr, Brittany A. Gibby and Norman B. Schmidt, Is computerized psychoeducation sufficient to reduce anxiety sensitivity in an atrisk sample?: A randomized trial, Journal of Affective Disorders, http://dx.doi.org/10.1016/j.jad.2017.01.032 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting galley proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

Running head: AS COMPUTERIZED PSYCHOEDUCATION

Is computerized psychoeducation sufficient to reduce anxiety sensitivity in an at-risk sample?: A randomized trial

Aaron M. Norr, Brittany A. Gibby, Norman B. Schmidt*

Department of Psychology, Florida State University, 1107 W. Call St., Tallahassee, FL, 32306, USA *

Correspondence concerning this article should be addressed to Norman B. Schmidt,

Department of Psychology, Florida State University, 1107 W. Call St., Tallahassee, FL 323064301. +1 (850) 645-1766. Email: [email protected].

Abstract Background: Anxiety sensitivity (AS), or a fear of anxiety-related sensations, has become one of the most well researched risk factors for the development of psychopathology and comprises three subfactors: physical, cognitive, and social concerns. Fortunately, research has demonstrated brief protocols can successfully reduce AS, and in turn improve psychopathological symptoms. Computerized AS reduction protocols have combined psychoeducation with interoceptive exposure (IE), but they have not been dismantled to evaluate the effects of psychoeducation alone.

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This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

AS COMPUTERIZED PSYCHOEDUCATION Method: The current study sought to determine the efficacy of a brief single-session psychoeducation intervention for AS, compared to a control intervention, in a sample of at-risk individuals (N = 54) with elevated AS cognitive concerns. Results: Individuals in the active condition displayed greater reductions in self-reported AS (β = .198, 95% CI [.065, .331]) and less fear reactivity (β = .278, 95% CI [.069, .487]) to the induction of AS cognitive-relevant sensations through a behavioral challenge compared to those in the control condition. Further, fear reactivity to the challenge was mediated by reductions in self-reported AS cognitive concerns. Limitations: Study limitations include use of an at-risk nonclinical student sample, lack of a long-term follow-up assessment, and inability to discern whether AS reductions due to CAST psychoeducation prevent future, or improve current, psychological symptoms. Conclusions: These results suggest that psychoeducation alone can produce significant AS reduction. Keywords anxiety sensitivity, computerized intervention, anxiety, prevention, treatment

Introduction Anxiety sensitivity (AS), or a fear of anxiety-related symptoms, is one of the most wellresearched risk factors for anxiety pathology. As part of Expectancy Theory, Reiss (1991) proposed that AS is one of three fundamental sensitivities (AS, fear of negative evaluation, and illness sensitivity) that are directly involved in the development of pathological anxiety. Consistent with Expectancy Theory, AS is reliably elevated across anxiety disorder diagnoses (Olatunji and Wolitzky-Taylor, 2009; Tayloret al., 1992). Recently, AS has also been shown to

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be associated with non-anxiety conditions such as cigarette smoking, substance use, depression, and suicide, demonstrating the importance of AS from a transdiagnostic perspective (Buckner et al., 2011; Capron et al., 2012a; Otto et al., 1995; Schmidt et al., 2007a; Zvolensky et al., 2005). Consistent with the conceptualization of AS as a risk factor, studies have demonstrated that AS prospectively predicts the development of psychopathology. In one study, individuals with high AS were five times more likely to develop a future anxiety disorder than those with low AS (Maller and Reiss, 1992). Other studies have also shown that AS prospectively predicts symptoms of panic attacks, posttraumatic stress disorder (PTSD), eating disorders, and suicidal ideation (Anestis et al., 2008; Capron et al., 2012a; Schmidt et al., 1999, 1997; Verreault et al., 2012). Furthermore, research has also shown that even after controlling for trait anxiety, individuals with high AS are more likely to develop DSM-IV Axis I pathology than individuals with low AS (Schmidt et al., 2006). While often analyzed as a unidimensional construct, research has demonstrated that AS comprises three subfactors: physical concerns, cognitive concerns, and social concerns (Rodriguez et al., 2004; Zinbarg et al., 1997). AS physical concerns center around exaggerated interpretations of bodily sensations. Individuals with high AS physical concerns might find an elevated heart rate to be frightening, interpreting it as an impending heart attack. AS cognitive concerns are focused on feelings of cognitive dyscontrol that stem from anxiety. Individuals with high AS cognitive concerns might fear that if they have difficulty concentrating, it means they are going crazy or losing control. Finally, AS social concerns are fears of negative social evaluation due to anxiety symptoms. Individuals with high AS social concerns may fear negative evaluation by others if symptoms of anxiety (e.g., blushing, sweating) are observable.

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Fortunately, studies have demonstrated that AS is malleable and can be reduced via lowcost interventions. These AS interventions have come in different forms and appear to mitigate AS, lead to reductions in symptoms, and a lower incidence of psychopathology. Gardenswartz and Craske’s (2001) one day workshop led to significant reductions in AS and lower rates of panic disorder diagnoses by follow-up. Group AS interventions for undergraduates (Watt et al., 2006), cigarette smokers (Feldner et al., 2008), and individuals with substance abuse/dependence (Worden et al., 2015) led to improvements including decreased AS, increased motivation to quit smoking, and increased percentage of days abstinent from substances. Telephone- and exercisebased interventions have been effective in reducing AS as well as anxiety, PTSD and depression symptoms (Broman-Fulks and Storey, 2008; Olthuis et al., 2014; Smits et al., 2008). Computer-based interventions have also demonstrated efficacy in the reduction of AS. For example, the single session, computer-assisted, Anxiety Sensitivity Amelioration Training (ASAT; Schmidt et al., 2007b) led to a 30% reduction in AS and lower incidence of Axis I disorders at the 12- and 24-month follow-ups compared to controls. In a follow-up study, ASAT was adapted to include interoceptive exposure (IE) homework that was tailored based on participant reactivity. This protocol also led to significant reductions in AS (Keough and Schmidt, 2012), which mediated reductions in anxiety and mood symptoms at a 1-month followup (Norr et al., 2014). Recent work suggests the potential importance of the AS cognitive concerns subfactor in the development and maintenance of PTSD and suicidal ideation (Boffa et al., 2016; Capron et al., 2013, 2012b; Elwood et al., 2009; Marshall et al., 2010; Norr et al., 2016a, 2016b). Such findings led to the development of a more specific AS reduction protocol, called Cognitive Anxiety Sensitivity Treatment (CAST), which was designed to focus on these concerns (Schmidt

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et al. , 2014). This fully computerized intervention was based on ASAT and includes psychoeducation and computer-guided IE (i.e., hyperventilation). The CAST intervention has been shown to effectively reduce overall AS and AS cognitive concerns. (Schmidt et al., 2014). Further, the AS reductions due to CAST have been shown to result in decreased symptoms of anxiety, depression, insomnia, suicide, and PTSD (Mitchell et al., 2014; Raines et al., 2015; Schmidt et al., 2014; Short et al., 2015). As in CAST, the majority of AS interventions use IE as a component of treatment, most often in the form of aerobic exercise (e.g., brisk walking, jogging, or running) or voluntary hyperventilation (Broman-Fulks and Storey, 2008; Deacon et al., 2012; Smits et al., 2008; Watt et al., 2006). Other less commonly used forms of IE include straw breathing and rapid head lifts (Feldner et al., 2008), and those designed to induce mild dizziness (Worden et al., 2015). There are several AS intervention studies using cognitive bias modification (CBM) that do not include an IE component, with some finding robust AS reductions compared to control interventions (Capron and Schmidt, 2016; Steinmen and Teachman, 2010) and others finding no differences between conditions (Clerkin et al., 2015; MacDonald et al., 2013). With the vast majority of interventions using IE, it is unclear whether IE is essential to achieve significant AS amelioration, though some CBM work suggests IE may not be necessary. Therefore, the current study sought to extend the literature by examining the efficacy of the psychoeducation component of CAST in the absence of the IE component. To further extend our understanding of CAST, we incorporated a behavioral challenge to determine if the effects of CAST extend beyond self-reported AS. Experimental psychopathology work has often used biological challenge paradigms to study AS. In such paradigms, researchers induce physiological symptoms, such as through voluntary

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hyperventilation or inhalation of carbon dioxide enriched air (Zvolensky and Eifert, 2001). These challenges produce physical symptoms akin to those produced by anxiety such as increased heart rate, dizziness, and shortness of breath. Research has demonstrated that participants’ fear in response to the induction of these symptoms is robustly associated with AS (e.g., Eke and McNally, 1996; Zinbarg et al., 2001; Zvolensky et al., 2002), and that biological challenges can capture change due to an AS intervention (e.g., Deacon et al., 2012; Schmidt et al., 2007b). However, these challenges primarily induce physical anxiety symptoms (e.g., racing heart, dizziness), and fear reactivity to biological challenges is most closely associated with selfreported AS physical concerns (Zvolensky et al., 2001), suggesting these paradigms would not be ideal in indexing changes in AS cognitive concerns. In order to examine behavioral reactivity relevant to AS cognitive concerns, which is of interest with regard to the CAST intervention, a behavioral paradigm that induces AS cognitive relevant sensations is needed. One method by which feelings of anxiety relevant cognitive dyscontrol could be examined is through the induction of dissociative symptoms. Symptoms of dissociation (e.g., feelings of unreality, feeling “spaced out”, difficulty concentrating) are similar to cognitive symptoms of anxiety, and panic attacks can even induce states of dissociation (American Psychiatric Association, 2013). Previous research has shown that dissociative symptoms can be reliably induced using audio-visual stimulation (Digital Audio-Video Integration Device; DAVID; Leonard et al., 1999). The DAVID includes a motherboard, glasses that produce flashing LED lights, and headphones that play binaural beats. Supporting the potential utility of using this paradigm to examine changes in AS cognitive concerns, research has demonstrated that AS was predictive of fear reactivity to the DAVID dissociation program

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(Leonard et al., 2000). Therefore, a behavioral challenge using the DAVID program was included after the intervention in the present investigation. Current Study The purpose of the current study was to examine the efficacy of the psychoeducation component of CAST, without the IE component, in a sample of at-risk undergraduate students with elevated levels of AS cognitive concerns. The study sought to evaluate the effects of the psychoeducation on both self-reported AS and fear reactivity to the induction of sensations of cognitive dyscontrol via a dissociation challenge. We hypothesized that: (1) consistent with prior work, individuals in the active (CAST psychoeducation) condition would experience significant decreases in self-reported AS compared to those in the control condition, (2) individuals in the active condition would experience significantly less fear in response to the dissociation challenge as compared to those in the control condition, and (3) that changes in AS cognitive concerns would mediate the relationship between treatment condition and fear reactivity to the challenge, while changes in AS physical and AS social concerns would not. Method Participants A total of 98 participants were recruited from a pool of 2,256 Introductory Psychology students at a large university in the southeastern United States completed a department-wide screening battery. Based on their responses, 453 individuals were invited to participate in the current study via email, of which 98 elected to come in for an appointment. At the appointment, 43 participants were excluded for failing to meet inclusionary criteria (ASI-3 cognitive score > 7) and one participant was excluded due to a history of epilepsy, resulting in a final sample size of 54. Power analysis using G*Power (Faul et al., 2007) indicated that 54 participants were needed

AS COMPUTERIZED PSYCHOEDUCATION to achieve 80% power at an alpha level of .05 based on the large effects found in the initial CAST trial (Schmidt et al., 2014). All participants were eighteen years of age or older and received course credit for their participation. Participants ranged from 18 to 25 years old (M = 19.09, SD = 1.59) and were 85.5% female. The racial/ethnic breakdown of the sample was as follows: 80.0% Caucasian, 14.5% Hispanic, 3.6% Black, 3.6% Asian, 1.8% Native American, and 1.8% other (participants could select multiple designations). Measures Acute Dissociation Inventory – Short (ADI-S). The full ADI is a 35-item self-report questionnaire developed to measure participants’ experience of dissociative symptoms in response to a dissociation challenge (Leonard et al., 1999). This study used a subsample of 6 questions that were chosen for their relevance to the dissociation challenge (e.g., “Did your surroundings seem like they were fading away?”), which we are calling the “Acute Dissociation Inventory – Short” (ADI-S). The ADI-S was used to measure changes in state dissociation during the experiment. Participants rate items on an 11-point scale ranging from 0 to 100 by 10 point increments. The full ADI has demonstrated excellent internal consistency in prior studies (α = .94-.96; Leonard et al., 2000, 1999), however, psychometric data have not yet been published on the ADI-S. In the current sample, internal consistency for the ADI-S was adequate at pre-challenge (α = .79), and excellent at post-challenge (α = .91). Anxiety Sensitivity Index 3 (ASI-3). The ASI-3 is an 18-item self-report questionnaire designed to measure the degree to which individuals are concerned about the potential negative effects of experiencing anxiety symptoms (Taylor et al., 2007). The ASI-3 was used to investigate the relationship between AS and fear reactivity to dissociative symptoms. Derived from the original ASI (Reiss et al., 1986), the ASI-3 provides a more stable assessment of the

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most commonly replicated subfactors (physical, cognitive, and social concerns) of AS (Taylor et al., 2007). Respondents read a series of statements (e.g. “It scares me when my heart beats rapidly”, “When I cannot keep my mind on a task I worry I might be going crazy”, “It is important to me not to appear nervous”) and rate the degree to which they agree with each statement using a 5-point Likert scale ranging from 0 (very little) to 4 (very much). Higher scores represent a greater fear of anxiety symptoms. Research has shown the ASI-3, and its subscales, to be a reliable and valid measure of AS (α = .73-.91; Taylor et al., 2007). In the current study, the ASI-3 total (α = .85), ASI-3 physical (α = .82), and social (α = .80) subscales showed good internal consistency and the cognitive (α = .70) was adequate at baseline. The ASI-3 total (α = .93) and all subscales demonstrated good to excellent internal consistency at post-treatment (physical, α = .90; cognitive, α = .90; social, α = .88). State Trait Anxiety Inventory – Trait (STAI-T). The STAI-T was used to measure participants’ tendency to experience anxiety symptoms (Spielberger, 1985). The STAI-T is a 20item scale that asks respondents to indicate how they generally feel based on a 4-point Likert scale ranging from 1 (not at all) to 4 (very much so). The STAI-T is widely used and has demonstrated adequate psychometric properties (α = .87; Knight et al., 1983). In the current study, the STAI-T demonstrated excellent internal consistency (α = .93). Subjective Units of Distress (SUDs). A SUDs rating was used to measures participants’ fear reactivity to the dissociation challenge. Participants rate the maximum level of fear they experienced from 0 (no fear) to 100 (extreme fear). SUDs ratings are commonly used to index fear reactivity in biological challenge studies (Feldner et al., 2003; Fyer et al., 1987; Schmidt et al., 2005; Schmidt and Zvolensky, 2007). Procedure

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Individuals who scored at least a seven on the ASI-3 cognitive subscale during a psychology department research study screening battery were contacted via email and invited to participate in exchange for Introductory Psychology class credit. Factor mixture modeling work has demonstrated that individuals in the moderate risk (for anxiety and mood pathology) AS class scored on average a 6.30 on the ASI-3 cognitive subscale (Allan et al., 2014). Therefore, a cutoff of seven ensured that individuals participating in the current study were at elevated risk for anxiety and mood pathology based on their ASI-3 cognitive scores. Upon arrival to the lab, ASI-3 cognitive scores were re-assessed and written informed consent was obtained. All study procedures were approved by the university’s Institutional Review Board. Participants began the experiment by completing a battery of self-report questionnaires. Participants were then randomly assigned to the active (CAST psychoeducation; n = 30) or control condition (n = 24) using a random number generator. The active condition consisted of 35 minutes of computerized psychoeducation from the CAST program. The program was designed to dispel exaggerated thoughts surrounding the danger of the experience of anxiety symptoms, specifically focusing on fears regarding feelings of cognitive dyscontrol (Schmidt et al., 2014). The CAST psychoeducation portion contains video animation and audio narration throughout, as well as some interactive features (e.g., brief quizzes to promote comprehension). Participants are provided with corrective information about the experience of anxiety-related sensations, with a particular focus on dispelling myths commonly held by individuals with high AS cognitive concerns (e.g., “I will lose control”, “I am going crazy”). Participants are taught that anxiety-related sensations are not dangerous and that they may have developed a conditioned fear to these symptoms of arousal, which is indicated by their elevated ASI-3 score.

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Participants in the control condition watched a similar computerized presentation called Physical Health Education Training (PHET), which focuses on information on general healthy living (Schmidt et al., 2014). The PHET program contains information on nutrition, alcohol, water consumption, exercise, sexual health, hygiene, stress management, life organization, social support, positive outlook, and sleep. For more information on the CAST or PHET programs, please refer to Schmidt et al. (2014). Following completion of their assigned presentation, all participants filled out the ASI-3 a second time to assess for changes in self-reported AS. All participants were then given five minutes to relax in a sound-attenuated room prior to completing measures to assess for baseline levels of state fear (SUDs) and state dissociative symptoms (ADI-S). The dissociation challenge was then completed for 12 minutes using the DAVID (comprised of a motherboard, LED glasses, and headphones; supplied by Mind Alive Inc.). Participants closed their eyes while glasses flashed LED lights (8-12Hz) and headphones played binaural beats. Previous research has demonstrated that this program successfully induces symptoms of dissociation, and that AS significantly predicts fear reactivity to this induction (Leonard et al., 2000, 1999). After the dissociation challenge, all participants completed postchallenge self-report measures (i.e., ADI-S, SUDs) to assess for changes in state dissociative symptoms and fear during the challenge. Data Analytic Plan Descriptive statistics were first computed for all variables. Outliers were examined and corrected if they were ± 3 SD from the mean. Following this, skew and kurtosis values were examined. Scores are considered significantly skewed or kurtotic if skew over standard error of skew exceeds 1.98 (Tabachnick and Fidell, 2007). As a manipulation check, a repeated measures ANOVA was conducted in SPSS version 18.1 to ensure successful induction of dissociative

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symptoms during the dissociative challenge. All other analyses were conducted in Mplus version 7.2 (Muthén and Muthén, 1996-2012) and used maximum likelihood estimation. Bootstrapped (5,000 resamples) asymmetric confidence intervals (CIs) were created for all indirect effects in the mediation models. Overall model fit for the mediation models was assessed using the likelihood ratio test, for which a nonsignificant χ2 value indicated good model fit. The comparative fit index (CFI) and root mean square error of approximation (RMSEA), which are considered approximate fit indices, were also provided. CFI values greater than .95 indicate good fit. RMSEA values less than .05 indicate good fit and values less than .08 indicate adequate fit (Hu and Bentler, 1999; MacCallum et al., 1996). Mediation results are reported in unstandardized values by convention. To ensure that reactivity to the challenge was not simply due to levels of trait anxiety, STAI-T scores were included as a covariate in all of the analyses involving reactivity to the challenge. Consistent with prior AS challenge studies, pre-challenge SUDs ratings were included as a covariate in all analyses to examine residualized change in SUDs ratings as an index of fear reactivity. For all analyses, condition was coded as follows: 1 = active, 2 = control. Results Descriptive Statistics The means, standard deviations, and intercorrelations for all variables can be found in Table 1. Missing data were minimal (i.e., 3.6% for pre-challenge ADI-S, 1.8% for pre-challenge SUDs, and 1.8% for post-challenge ADI-S). Full information maximum likelihood was used to handle missing data in all analyses except the manipulation check, which used listwise deletion. Results were not different with regard to the significance of relationships when analyses were conducted excluding all participants with any missing data. During the investigation of outliers,

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it was determined that one data point fell greater than 3 SD above the mean for pre-challenge ADI-S scores, which was brought in to 3 SD above the mean. There was no evidence of nonnormaility based on a visual inspection of the data, as well as skewness and kurtosis values falling within acceptable ranges. No threats to, or violations of, homoscedasticity or multicollinearity were found. T-tests revealed no significant differences between conditions across baseline variables (i.e., STAI-T, ASI-3 total and subscales). Manipulation Check To ensure that the dissociation challenge successfully induced symptoms of dissociation, a repeated measures ANOVA was conducted using pre-challenge and post-challenge ADI-S scores. The ANOVA revealed that dissociation scores at post-challenge (M = 35.90, SD = 23.84) were significantly greater than at pre-challenge (M = 16.22, SD = 13.87), F(1,51) = 50.71, p < .001, partial η2 = .50, 95% CI (.29, .63), with a large effect (Cohen, 1988). ANCOVA was used to examine whether the induction of dissociative symptoms was equitable across conditions, controlling for trait anxiety. This model explained 41.9% (R2 95% CI [.214, .624]) of the variance in post-challenge ADI-S scores. Pre-challenge ADI-S scores (β = .459, SE = .104, 95% CI [.254, .664]) and STAI-T scores (β = .339, SE = .105, 95% CI [.133, .545]) were significant predictors of post-challenge ADI-S scores, while condition was not (β = .087, SE = .109, 95% CI [-.126, .301]), indicating comparable levels of dissociative symptom induction across conditions. Primary Analyses To test the hypothesis that individuals in the active condition would experience significant decreases in self-reported AS compared to those in the control condition, multiple regression was used. Four models were computed to examine the effect of the psychoeducation on ASI-3 total, ASI-3 cognitive, ASI-3 physical, and ASI-3 social scores, respectively. In all

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models post-treatment, ASI-3 scores were regressed on condition and the corresponding pretreatment ASI-3 scores (to examine residualized change). Results from these analyses can be found in Table 2. Consistent with our hypothesis, individuals in the active condition demonstrated significantly greater reductions than the control condition, with large effects (Cohen, 1988), for ASI-3 total (d = .81, 95% CI [.24, 1.36]), cognitive (d = .79, 95% CI [.22, 1.33]), physical (d = .57, 95% CI [.02, 1.11]), and social scores (d = .56, 95% CI [< .01, 1.10]). To test the hypotheses that individuals in the active condition would experience less fear reactivity to the dissociation challenge than those in the control condition a multiple regression analysis were conducted. Post-challenge SUDs scores were regressed on condition, and controlled for STAI-T scores and pre-challenge scores (to examine residualized change). The model explained 41.8% (R2 95% CI [.217, .620]) of the variance in post-challenge SUDs scores. Consistent with hypotheses, both pre-challenge SUDs scores (β = .369, SE = .104, 95% CI [.166, .573]), STAI-T scores (β = .382, SE = .101, 95% CI [.184, .581]), and condition (β = .278, SE = .107, 95% CI [.069, .487]) were significant predictors of post-challenge SUDs scores, such that those in the active condition displayed less fear reactivity than those in the control condition. To determine whether the relationship between the experimental condition and fear reactivity to the challenge was mediated by changes in self-reported ASI-3 total scores, a mediation model was conducted controlling for baseline ASI-3 total scores (to examine residualized change in ASI-3 total scores), STAI-T, and challenge SUDs scores (to examine residualized change in SUDs). The mediation model provided good fit to the data (χ2 (3, N = 54) = 2.57, p = .46, CFI = 1.00, RMSEA < .01, 90% CI [.00, .22]) and accounted for 77.6% and 48.1% of the variance in post-treatment ASI-3 total and post-challenge SUDs scores, respectively. As predicted, in this model, there was a significant indirect effect from condition

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through post-treatment ASI-3 scores to post-challenge SUDs (indirect = 2.470, 95% CI [0.528, 6.108]). Unstandardized model parameter estimates are provided in Figure 2. To determine which AS subfactor was driving the significant mediation found in the previous analysis, a mediation model was conducted controlling for baseline ASI-3 subscale scores, STAI-T, and pre-challenge SUDs scores, with all three AS subscales as parallel mediators. The mediation model provided good fit to the data (χ2 (15, N = 54) = 23.49, p = .07, CFI = .97, RMSEA = .10, 90% CI [.00, .18]). The RMSEA value was slightly elevated, however, RMSEA has been shown to perform poorly in models with few degrees of freedom (Kenny et al., 2014). The model accounted for 54.1% (ASI-3 cognitive), 77.8% (ASI-3 physical), 61.3% (ASI3 social), and 51.1% (post challenge SUDs) of the variance in the endogenous variables. As predicted, in this model, there was a significant indirect effect from condition through posttreatment ASI-3 cognitive scores to post-challenge SUDs (indirect = 4.388, 95% CI [1.058, 11.017]), but not through either ASI-3 physical (indirect = 0.218, 95% CI [-1.292, 2.588]) or social scores (indirect = -0.977, 95% CI [-4.860, 0.883]). Also as hypothesized, only posttreatment ASI-3 cognitive scores significantly predicted fear reactivity to the challenge. Unstandardized model parameter estimates are provided in Figure 3. Discussion The current study provided an initial examination of the efficacy of the CAST psychoeducation component in the absence of the IE component through self-report and response to a behavioral challenge. Consistent with our initial hypothesis, participants in the active condition exhibited significantly greater reductions in self-reported AS than those in the control condition. Participants in the active condition demonstrated a 34% reduction in overall selfreported AS, as well as significant reductions on each AS subfactor (25-42%). These reductions

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in overall AS are commensurate with those found in the original CAST trial (32%; Schmidt et al., 2014), prior single-session protocols utilizing computer-assisted psychoeducation and IE (2830%; Keough and Schmidt, 2012; Schmidt et al., 2007b), and other more intensive AS reduction protocols with IE (29-45%; Deacon et al., 2012; Feldner et al., 2008; Worden et al., 2015). These reductions are also comparable to those found by Steinman and Teachman (2010) using CBM without IE (29%), though Capron and Schmidt (2016) found greater reductions (62%) using a similar protocol. Overall, these results suggest the possibility that the CAST psychoeducation component is sufficient for the immediate reduction of AS. These results carry potential clinical implications, as by definition patients with elevated AS find the induction of bodily sensations via IE to be aversive (Schmidt & Trakowski, 2005). Thus, the ability to reduce AS through psychoeducation alone could be especially useful for patients who are unwilling to engage in IE. However, future work should establish whether AS reduction protocols without IE have similar long-term effects on AS, as well as similar reductions in psychopathological symptoms. Also consistent with our initial hypothesis, participants in the active AS reduction condition displayed less fear reactivity to the dissociation challenge compared to those in the control condition, with no difference between conditions in the experience of dissociative symptoms, per se. Thus, it appears that this challenge successfully captured changes in fearful reactivity to the experience of AS-relevant sensations of cognitive dyscontrol, and that the effects of the CAST psychoeducation component generalized beyond self-reported AS. Further, changes in self-reported overall AS and AS cognitive concerns significantly mediated the relationship between manipulation condition and fear reactivity to the challenge, such that those with higher post-manipulation overall AS and AS cognitive concerns displayed greater fear reactivity to the challenge, even after controlling for participants’ trait anxiety. These results are consistent with

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prior work showing that AS treatment protocols with IE (e.g., Deacon et al., 2012; Schmidt et al., 2007b), as well as some CBM programs without IE (e.g., Capron and Schmidt, 2016), lead to reductions in fearful responding to behavioral challenges. These findings are also consistent with prior research that found a relationship between overall AS and fear reactivity to the dissociation challenge (Leonard et al., 2000). Additionally, the current study significantly builds on the results from Leonard et al. (2000) by demonstrating that differences in fear reactivity to the dissociation challenge were specific to changes in AS cognitive concerns, and not related to changes in AS physical or social concerns. With regard to the potential use of this dissociation paradigm in experimental psychology work relating to AS cognitive concerns, it appears this paradigm provides significant benefits over other AS-related challenge paradigms (e.g., voluntary hyperventilation, straw breathing, CO2 inhalation). As other challenge paradigms are more closely associated with AS physical concerns (see Zvolensky et al., 2001 for a review), this dissociation paradigm provides an opportunity to study AS cognitive concerns more directly (i.e., independent of physical or social concerns), and in an experimental psychopathology framework. Given the growing evidence that AS cognitive concerns may play an important role in the etiology and maintenance of various psychopathological symptoms (e.g., Capron et al., 2012a; Schmidt, et al., 2014, 2006), developing a greater understanding of how AS cognitive concerns confers risk is clearly indicated. Similarly, given that the results of the current study demonstrated fear activation in the context of the dissociation challenge was specific to AS cognitive concerns, it is possible that this paradigm could be used clinically as an IE to reduce fear among patients with elevated AS cognitive concerns. However, future research is needed to determine the efficacy of the dissociation paradigm as an IE.

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The results of the current study should be viewed in the context of several limitations. First, the current sample included undergraduate students with elevated levels of AS, and the results of the current study may not generalize to a clinical population. However, given that elevated AS is a risk factor for the development of a broad range of psychopathology, treatments that demonstrate efficacy in the reduction of AS in a subclinical or nonclinical at-risk population is also critical from a prevention standpoint. Second, the current study design did not allow for an investigation of the long term durability of AS reductions. Though the post-treatment reductions were comparable to those found in the initial CAST trial using IE, it is possible that without the IE component, reductions may not persist over time. Finally, based on the current study it is unclear whether AS reductions due to the CAST psychoeducation component would translate into the prevention of future psychopathological symptoms, or the amelioration of current symptoms, as has been seen in trials utilizing computer-based psychoeducation and IE (Norr et al., 2014; Schmidt et al., 2014, 2007b). Despite these limitations, the current study provides initial evidence that psychoeducation is sufficient to produce significant reductions in AS among an at-risk (i.e., high AS) group. This finding is promising as computerized psychoeducation can easily be delivered via the Internet, in the form of a web application, which would allow for large-scale dissemination of this type of prevention paradigm. For example, Muñoz and colleagues (2015) demonstrated the effectiveness of using Google Adwords to route individuals to an online smoking cessation intervention. Future work should determine if the CAST psychoeducation protocol utilized in the current study is equally efficacious in the amelioration of elevated AS when delivered remotely.

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Zvolensky, M.J., Goodie, J.L., Ruggiero, K.J., Black, A.L., Larkin, K.T., Taylor, B.K., 2002. Perceived stress and anxiety sensitivity in the prediction of anxiety-related responding: A multichallenge evaluation. Anxiety Stress Coping 15, 211-229. Zvolensky, M.J., Schmidt, N.B., Antony, M.M., McCabe, R.E., Forsyth, J.P., Feldner, M.T., Leen-Feldner, E., Karekla, M., Kahler, C.W., 2005. Evaluating the role of panic disorder in emotional sensitivity processes involved with smoking. J. Anxiety Disord. 19, 673686.

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Figure 1. CONSORT diagram.

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Figure 2. Mediation model examining the effects of intervention condition (1 = active, 2 = control) on post-challenge SUDs scores through changes in ASI-3 total scores. BL = baseline; PT = pos-treatment; Pre = pre-challenge; Post = post-challenge; STAI-T = State Trait Anxiety Inventory –Trait version; ASI-3 = Anxiety Sensitivity Index – 3; SUDs = Subjective Units of Distress. Parameter estimates are unstandardized. 95% confidence intervals are presented in parentheses. Nonsignificant pathways (p > .05) are represented by dashed lines.

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Figure 3. Mediation model examining the effects of intervention condition (1 = active, 2 = control) on post-challenge SUDs scores through changes in ASI-3 subscale scores. BL = baseline; PT = post-treatment; Pre = pre-challenge; Post = post-challenge; STAI-T = State Trait Anxiety Inventory –Trait version; ASI-3 = Anxiety Sensitivity Index – 3; Cog = cognitive concerns subscale; Phys = physical concerns subscale; Soc = social concerns subscale; SUDs = Subjective Units of Distress. Parameter estimates are unstandardized. 95% confidence intervals are presented in parentheses. Nonsignificant pathways (p > .05) are represented by dashed lines.

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Table 1 Means, Standard Deviations, and Intercorrelations for all Variables 1 2 3 4 5 6 7 8 9 10 11 12 13 1. BL -2. BL .53* -STAI* .48* -3. BL .34 * ASI-3 * * .44* -4. T BL .54 .33 * ASI-3 * * .73* .84 .77* -5. cogBL .59 * * ASI-3 * * * .63 .44 .75* -6. PT .37* .73 phys * * * ASI-3 * * * * * .40 .89 .34 .71 .63** -7. socPT .19 * * * * * ASI-3 * * * * * ** .50 .80 .72 .63 .48 -8. PT .48 .36 total * * * ASI-3 * * * * * ** .58 .79 .63 .86 .88 .83 .84* -9. cogPT .41 * * * * * ** ASI-3 * * .24 -.01 .04 .29 .15 .01 .03 .33 .15 -10. phys * * * * ** * ASI-3 * * .09 .05 .08 .29 .19 .12 .09 .19 .16 .49* -11. soc Pre * .45* .26 .13 .53* .39* .26 .08 .45* .32* .55 .27 -12. total * Pre * * * * * ** * * .45 .38 .41 .52 .53 .37 .39 .50 .18 .47* .39* -13. ADI- .40 * * * * * Post 12.3 8.13 12.8 33.3 7.77 4.7 9.63 22.1 13.8 9.33 32.7 22.6 Activ 41.5 SUDs * * * * * ** * * * * Post S 4.7 6.16 14.0 10.8 15.0 23.6 22.1 (n = 11.3 3.74 4.93 5.19 10.6 5.27 ADI3 7 3 0 0 9 8 7 e - 3 Contr SUDs 39.7 12.1 10.6 14.0 36.8 10.428. 8.5 12.7 31.7 20.4 17.3 40.1 38.2 7 6 6 9 9 7 9 2 30) S 6.5 5.85 14.3 17.2 18.1 23.9 21.0 M(n = 12.0 4.51 5.86 5.30 12.5 5.55 7 7 0 3 58 8 1 1 3 9 5 6 ol - 9 Note. SD BL = baseline; PT = post-treatment; Pre = pre-challenge; Post = post-challenge; STAI-T = 9 6 0 7 4 5 4 3 24) M State Trait Anxiety Inventory –Trait version; ASI-3 = Anxiety Sensitivity Index – 3; cog = SD cognitive concerns subscale; phys = physical concerns subscale; soc = social concerns subscale; SUDs = Subjective Units of Distress; ADI-S = Acute Dissociation Inventory – Short. *p < .05, **p < .01

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Table 2 Separate regression analyses examining the effects of condition on AS and fear reactivity to the dissociation challenge

PT ASI-3 total BL ASI-3 total Condition PT ASI-3 cog BL ASI-3 cog Condition PT ASI-3 phys BL ASI-3 phys Condition PT ASI-3 soc BL ASI-3 soc Condition

β

SE

p

.829 .198

.043 .068

<.001 .003

2

R .776

.594 .732

.064

<.001

.256

.088

.003 .799

.854 .133

.038 .064

<.001 .04 .665

.781 .165

.053 .080

<.001 .04

95% CI LL UL .667 .881 .743 .914 .065 .331 .428 .761 .606 .858 .085 .704 .779 .007

.428 .895 .928 .258

.520 .678 .008

.811 .885 .322

Note. Condition (1 = active, 2 = control); BL = baseline; PT = post-treatment; ASI-3 = Anxiety Sensitivity Index – 3; cog = cognitive concerns subscale; phys = physical concerns subscale; soc = social concerns subscale.

Highlights:  Investigated effects of computerized psychoeducation on anxiety sensitivity (AS)  Psychoeducation led to reductions in self-reported AS and its subfactors  Psychoeducation led to less fear reactivity to induced dissociative symptoms  Differences in fear reactivity were specific to changes in AS cognitive concerns  Findings suggest psychoeducation is sufficient for the reduction of elevated AS