کارآزمایی تصادفی کنترل شده از اصلاح توجه برای اختلال اضطراب اجتماعی
|کد مقاله||سال انتشار||مقاله انگلیسی||ترجمه فارسی||تعداد کلمات|
|39235||2015||10 صفحه PDF||سفارش دهید||9000 کلمه|
Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Journal of Anxiety Disorders, Volume 33, June 2015, Pages 35–44
Abstract Social Anxiety Disorder (SAD) models implicate social threat cue vigilance (i.e., attentional biases) in symptom development and maintenance. A modified dot-probe protocol has been shown to reduce SAD symptoms, in some but not all studies, presumably by modifying an attentional bias. The current randomized controlled trial was designed to replicate and extend such research. Participants included treatment-seeking adults (n = 108; 58% women) who met diagnostic criteria for SAD. Participants were randomly assigned to a standard (i.e., control) or modified (i.e., active) dot-probe protocol condition and to participate in-lab or at home. The protocol involved twice-weekly 15-min sessions, for 4 weeks, with questionnaires completed at baseline, post-treatment, 4-month follow-up, and 8-month follow-up. Symptom reports were assessed with repeated measures mixed hierarchical modeling. There was a main effect of time from baseline to post-treatment wherein social anxiety symptoms declined significantly (p < .05) but depression and trait anxiety did not (p > .05). There were no significant interactions based on condition or participation location (ps > .05). Reductions were maintained at 8-month follow-up. Symptom reductions were not correlated with threat biases as indexed by the dot-probe task. The modified and standard protocol both produced significant sustained symptom reductions, whether administered in-lab or at home. There were no robust differences based on protocol type. As such, the mechanisms for benefits associated with modified dot-probe protocols warrant additional research.
Introduction Social Anxiety Disorder (SAD; American Psychiatric Association, 2013) has significant lifetime (12.1%) and 12-month (7.1%) prevalence rates (Ruscio et al., 2008), and comparable rates for men and women (American Psychiatric Association, 2013). The disorder is marked by nervousness or discomfort in social situations (Antony & Swinson, 2000), resulting from fears of being evaluated, embarrassed (Weeks et al., 2010a and Weeks et al., 2010b), or making a bad impression (Antony & Swinson, 2000). SAD typically lasts for 12 or more years (Grant et al., 2005), has low remission rates (Massion et al., 2002), and high depression comorbidity (Stein & Stein, 2008). The associated social isolation and high rates of comorbid depression may explain some of the increased suicide risk for patients with SAD relative to those without (Thibodeau, Welch, Sareen, & Asmundson, 2013), wherein 35% contemplate suicide regularly and 14% attempt suicide (Cougle, Keough, Riccardi, & Sachs-Ericsson, 2009). Models of SAD emphasize the central role of attentional processes and suggest that (1) heightened self-focused attention and (2) vigilance for external social threat cues influence the development and maintenance of SAD (e.g., Heimberg et al., 2010 and Hofmann, 2007). People with SAD more rapidly engage with and spend more time attending to external social threat cues and emotional faces in anxiety-provoking social situations (Asmundson and Stein, 1994, Chen et al., 2002 and Lee and Telch, 2008), and demonstrate biases in interpretation, attention, and imagery relative to non-anxious individuals (Hirsch & Clark, 2004). Together, these attentional processes may narrow attention, interfere with beneficial processing, and maintain SAD. Participants in a dot-probe protocol observe a screen on which randomly paired stimuli are presented (for ∼500 ms), one stimulus above the other. One stimulus is neutral (e.g., the word table) and the other is associated with threat (e.g., the word snake). After the stimuli presentation, a probe appears in a location (top/bottom) corresponding to where one of the stimuli appeared. Participants press a key as quickly as possible to indicate the probe location (top/bottom). People with clinically significant anxiety respond faster when probes appear in the location of threat stimuli related to their anxiety (i.e., congruent) versus the location of neutral stimuli (i.e., incongruent), regardless of location (top/bottom). In contrast, people without clinically significant anxiety (i.e., controls) respond comparably to threat and neutral words, producing no difference in response times across congruent, incongruent, and neutral trials (i.e., two neutral words presented). Modifying attentional biases using an adapted dot-probe protocol as a treatment for social anxiety has received increasing interest (Koster et al., 2009 and MacLeod et al., 2002). The adapted protocol involves two conditions: (1) the Attention Control Condition (ACC), in which neutral and threat stimuli are replaced by probes with equal frequency, and (2) the Attentional Modification Condition (AMC), in which the probe consistently replaces neutral stimuli. In the AMC participants implicitly learn to direct their attention away from the threat stimulus to detect and respond to the probe, which is thought to modify the attentional bias and reduce symptoms. In one of the original studies exploring the adapted dot-probe protocol as a treatment for SAD symptoms (Schmidt, Richey, Buckner, & Timpano, 2009), participants in the AMC (n = 18), but not in the ACC (n = 18), reported a significant reduction in SAD symptoms (i.e., p < .01; d > .50). Since then, several studies have provided additional support for AMC as a method to reduce SAD symptoms ( Amir et al., 2009b, Amir et al., 2011, Amir et al., 2008 and Schmidt et al., 2009). Training attention away from threat appears more effective for reducing social anxiety than training attention toward threat, neutral, or positive stimuli ( Heeren et al., 2011 and Heeren et al., 2012); however, studies have also found evidence that the AMC and ACC can both reduce symptoms, with no significant differences in those reductions between the conditions (e.g., Enock et al., 2014, Heeren et al., 2015 and Julian et al., 2012). Much of the attention training research with social anxiety has used a static set of pre-selected word stimuli to assess for the attentional biases, but then used pictures of faces as the stimuli for modifying any such biases (Amir et al., 2009b and Heeren et al., 2015). The intent was to avoid experimental conflation of repeated exposure to the stimuli with changes in attentional biases. That said, related research supporting the success of AMC relative to ACC for generalized anxiety disorder symptoms used words for both assessment and training (Amir, Beard, Cobb, & Bomyea, 2009), with those researchers recommending research exploring the use of only words for SAD as well (Amir et al., 2011). Furthermore, tailored stimuli, rather than a pre-selected static set, should be more salient and therein produce stronger effect sizes. Part of the appeal associated with the attention modification protocols involves the potential for wide spread cost-effective dissemination through the Internet. Indeed, such administration could be particularly suited to persons with social anxiety. At least four separate randomized controlled trials have administered the attention modification protocol remotely via the Internet to samples diagnosed with SAD found similar results (Boettcher et al., 2012, Carlbring et al., 2012, Neubauer et al., 2013 and Rapee et al., 2013); however, in all cases participants in both the AMC and ACC reported social anxiety symptom reductions of small to large effects sizes with no statistically significant differences between conditions. Furthermore, the studies did not report robust evidence of attentional biases before or after treatment, changes in an attentional bias over the course of treatment, or a relationship between attentional bias and symptom changes. A recent meta-analysis indicated that attentional biases were much smaller for studies administering the protocols through the Internet than for those administered in laboratories (Mogoase, David, & Koster, 2014). Nonetheless, the range of effect sizes for symptom changes was quite large for Internet studies (i.e., Hedges g = .05–.97) and for laboratory studies (i.e., Hedges g = .02–.82). The authors of the meta-analysis noted “the available evidence regarding ABM clinical utility [outside] the laboratory is currently limited” ( Mogoase et al., 2014, p. 18) and recommended additional research exploring Internet administrations that include extended follow-up assessments (e.g., 4+ months). The current randomized controlled study was designed to: (1) replicate and extend the initial findings presented by Schmidt et al. (2009) and Amir et al. (2008) by using word stimuli [in line with evidence from Heeren et al. (2015), Mogoase et al. (2014), and Rapee et al. (2013)] that were idiosyncratically selected; (2) evaluate the comparative impact of participation in a laboratory setting relative to remotely at home, adding to the currently limited literature; and (3) provide extended follow-up assessments evaluating the endurance of the AMC changes (i.e., at 4 and 8 months). There were five hypothesized outcomes. First, participants completing the AMC in the laboratory were expected to report significant reductions in SAD symptoms relative to participants completing the ACC in the laboratory. Second, participants completing the AMC remotely were expected to report significant reductions in SAD symptoms relative to participants completing the ACC remotely. Third, participants completing the AMC in the laboratory were expected to report greater SAD symptom reductions relative to those participating remotely. The additional symptom reduction was expected in the laboratory condition because it was thought of as an additive exposure to social situations. Fourth, participants in the AMC were expected to maintain symptom changes at 4 and 8 months after participation relative to participants in the ACC. Fifth, participants showing the greatest change in attentional biases in AMC were expected to show the greatest SAD symptom reduction, based on initial theory suggesting that AMC protocols lead to symptom improvement via change in attentional bias (Bar-Haim, 2010 and Clarke et al., 2014).
نتیجه گیری انگلیسی
. Results 3.1. Sample characteristics Descriptive statistics of the dependent variables for each group are presented in Table 1. There were no statistically significant differences between participants who discontinued after baseline, discontinued after post-treatment, discontinued after 4-month follow-up, and those who completed the 8-month follow-up on age, F(3, 104) = 2.08, p = .11, η2 = .06, years with significant SAD symptoms, F(3, 104) = 1.41, p = .25, η2 = .04, the SIPS total score, F(3, 104) = .97, p = .41, η2 = .03, the CES-D, F(3, 104) = 2.29, p = .08, η2 = .06, or the trait scale of the STAI, F(3, 103) = 1.41, p = .24, η2 = .04. There were no significant differences between men and women, at baseline or at the 8-month follow-up, on age, years with significant SAD symptoms, the SIPS total score, the CES-D, or the trait scale of the STAI (all ps > .05, all r2s < .03). There were also no differences in attrition rates between men and women, χ2(3) = 1.15, p = .77, V = .10, between active and control groups, χ2(3) = 2.42, p = .49, V = .15, or between the in lab and remote location groups, χ2(3) = 1.24, p = .74, V = .11; as such, no further attrition or intent-to-treat analyses were conducted. Table 1. Dependent variable scores for each group for each time period. Time Treatment condition in lab (AMC) Effect sizes (d) differences 1 (n = 26) 2 (n = 23) 3 (n = 19) 4 (n = 16) 2v1 3v1 4v1 SIPS 36.77 (7.98) 29.39 (9.51) 31.26 (8.60) 32.56 (9.68) 1.03 0.73 0.57 STAI-T 57.81 (9.78) 54.70 (10.84) 57.37 (9.96) 56.40 (8.41) 0.34 0.00 0.09 CES-D 26.38 (11.38) 21.35 (9.71) 25.58 (13.74) 24.19 (11.37) 0.50 0.10 0.22 Time Control condition in lab (ACC) Effect sizes (d) differences 1 (n = 31) 2 (n = 20) 3 (n = 16) 4 (n = 15) 2v1 3v1 4v1 SIPS 37.19 (8.13) 28.75 (11.17) 30.13 (8.64) 29.27 (11.54) 1.04 0.87 0.97 STAI-T 57.26 (10.84) 53.65 (11.61) 53.12 (12.63) 50.13 (11.53) 0.33 0.38 0.66 CES-D 21.68 (13.22) 19.85 (10.04) 19.81 (10.76) 20.00 (13.03) 0.14 0.14 0.13 Time Treatment condition at remote location (AMC) Effect sizes (d) differences 1 (n = 25) 2 (n = 19) 3 (n = 17) 4 (n = 12) 2v1 3v1 4v1 SIPS 34.76 (11.37) 27.53 (12.82) 27.76 (13.65) 26.50 (12.19) 0.69 0.58 0.69 STAI-T 50.76 (12.17) 47.79 (8.14) 47.94 (10.05) 46.33 (11.11) 0.22 0.19 0.33 CES-D 20.84 (10.64) 17.26 (8.06) 20.82 (11.32) 15.58 (10.23) 0.33 0.02 0.47 Time Control condition in remote location (ACC) Effect sizes (d) differences 1 (n = 26) 2 (n = 20) 3 (n = 17) 4 (n = 14) 2v1 3v1 4v1 SIPS 37.77 (11.64) 29.50 (11.17) 30.47 (10.94) 28.93 (8.75) 0.71 0.63 0.76 STAI-T 56.16 (7.81) 50.15 (13.63) 51.53 (10.06) 51.86 (12.90) 0.77 0.59 0.55 CES-D 23.65 (11.81) 22.40 (10.94) 20.35 (9.95) 23.07 (12.72) 0.11 0.28 0.05 Notes: AMC, Attentional Modification Condition; ACC, Attention Control Condition; SIPS, Social Interaction Phobia Scale; STAI-T, State-Trait Anxiety Index, Trait Form; CES-D, Centre for Epidemiological Studies Depression Scale; d, Cohen's d; 1, baseline; 2, post-treatment; 3, 4-month follow-up; 4, 8-month follow-up. Table options 3.2. Idiosyncratic word ratings There were no differences in the baseline average ratings of threat words between participants who completed baseline but discontinued after baseline and participants who continued to participate in the treatment, t(105) = .65, p = .49, r2 < .01. Among participants who completed baseline and post-treatment, the average concordance rates of words selected for presentation (based on ratings of emotional intensity) at both baseline and end of treatment were as follows: ACC in Lab 46%; ACC Remote 45%; AMC in Lab 44%; AMC Remote 50%. The proportions were not statistically significantly different across the four groups, χ2(1) = 0.26, p = .61, V = .04. Furthermore, there were no statistically significant differences in the average baseline ratings of words presented at both baseline and at the end of treatment, F(3, 79) = .33, p = .80, η2 = .01, nor in the average baseline ratings of words presented at the end of treatment but not at baseline, F(3, 79) = .38, p = .77, η2 = .01. Among words presented at both baseline and at the end of treatment, the average ratings were higher (i.e., less distressing) at post-treatment than at baseline, F(1, 79) = 31.86, p < .001, partial η2 = .29; however, there was no interaction across the four groups, F(3, 79) = .06, p = .98, partial η2 < .01. Among words presented only at baseline, the average ratings were higher (i.e., less distressing) at post-treatment than at baseline, F(1, 79) = 26.34, p < .001, partial η2 = .25; however, there was no interaction across the four groups, F(3, 79) = .97, p = .41, partial η2 = .04. The results indicate all participants reported the words at baseline as less distressing at post-treatment, irrespective of treatment condition or location. 3.3. Dot probe task RT data RTs on the attentional bias task were screened for outliers by excluding trials with RTs that were greater than two standard deviations from the mean RT for each individual participant on each day. The outlier analysis was scaled to each individual's mean response time, rather than implementing a general cut-off (e.g., 2000 ms), which could eliminate legitimate observations from slower participants. This resulted in exclusion of data from 2.37% of trials. Trials with errors (4.42%) were also excluded from analyses. Data were available from both baseline and post-treatment for 82 participant completers. Response times post-treatment were overall faster (M = 618 ms; SE = 25.7) than baseline (M = 720 ms; SE = 32.9), leading to a significant main effect of time, F(1, 78) = 20.6, MSE = 40151, p < .001, View the MathML sourceηp2=.21. No other significant main effects or significant interactions were observed, all Fs < 2.41, all ps > .12. Across the entire sample of 82 participant completers, responses were 3 ms faster on congruent probe trials than on incongruent probe trials baseline, an effect that did not differ across the ACC and AMC groups and was not statistically greater than zero, t(81) = .76, p > .45. Based on initial theory suggesting that the AMC leads to symptom reduction by modifying an initial bias toward threat stimuli (Clarke et al., 2014), the magnitude of the change in bias from pre- to post-treatment should be correlated with the magnitude of reduction in SAD symptoms. For each participant, the change in bias toward threat words was determined by computing the average difference in response times on incongruent and congruent trials from pre- to post-treatment. The change in total SIPS scores over time was also computed, and Pearson's correlations were computed among these three change scores, stratified by treatment type (ACC vs. AMC). Negative correlations (i.e., smaller post-treatment biases accompanied by larger symptom reductions) were expected in the AMC condition if attentional modification was associated with symptom reduction; no correlation should have been observed in the ACC condition. Contrasting expectations, the observed correlations were near zero in the AMC group (i.e., SIPS, r < .01, p = .97) and negative, but non-significant, in the ACC group (i.e., SIPS, r = −.26, p = .10). 3.4. Self-reported symptom changes 3.4.1. SAD symptoms The time factor was statistically significant in the random-effects model (p < .0001) predicting SIPS scores over time. Paired contrasts demonstrated that SIPS scores at post-treatment were significantly lower than SIPS scores at baseline (ΔMD = −7.12, SE = 1.82, p < .001), that SIPS scores at the 4-month follow-up were significantly lower than SIPS scores at baseline (ΔMD = −6.50, SE = 1.94, p < .001), and that SIPS scores at the 8-month follow-up were significantly lower than SIPS scores at baseline (ΔMD = −7.03, SE = 2.08, p < .001). Without taking into account condition status, the current findings suggest that participants experienced reductions in SIPS scores, and that these reductions were maintained after 8 months. The interaction of treatment condition and time was not statistically significant (p > .50), suggesting that changes over time in SIPS scores did not differ between the treatment conditions. The interaction of treatment location and time was not statistically significant (p > .90), suggesting that changes over time in SIPS scores did not differ between individuals who participated in the lab and those who participated in a remote location. Moreover, the three-way interaction of treatment location, treatment condition, and time was not statistically significant (p > .80). None of the other fixed factors (i.e., ethnicity, education, marital status, gender, years with SAD, age) were statistically significant predictors of SIPS scores (ps > 30). SIPS total scores for each of the conditions at each time period are reported in Table 1. Changes in scores over time across the conditions and time periods were medium to large (Cohen's d ranging from 0.57 to 1.04). Effect sizes of change at the 8-month follow-up (0.57 to 0.97) were comparable to those demonstrated immediately after treatment (0.69 to 1.04). 3.4.2. Trait anxiety (STAI-T scores) The time factor was statistically significant in the random-effects model (p < .01) predicting STAI-T scores over time. Paired contrasts demonstrated that STAI-T scores at post-treatment were significantly lower than STAI-T scores at baseline (ΔMD = −4.43, SE = 1.96, p < .05). STAI-T scores at the 4-month follow-up were not statistically significantly lower than STAI-T scores at baseline (ΔMD = −3.07, SE = 2.06, p > .10), and scores at the 8-month follow-up were not statistically significantly lower than STAI-T scores at baseline (ΔMD = −2.61, SE = 2.21, p > .20). The results suggest that participants experienced reductions during treatment that were not sustained over the 4- and 8-month follow-ups, irrespective of condition. The interaction of treatment condition and time was not statistically significant (p > .30), the interaction of treatment location and time was not statistically significant (p > .90), and the three-way interaction of treatment location, treatment condition, and time was not statistically significant (p > .10). No other fixed-effect factors (i.e., ethnicity, education, marital status, gender, years with SAD, age) were statistically significant predictors of STAI-T scores over time (ps > .30). 3.4.3. Depression symptoms (CES-D scores) The time factor was not statistically significant in the random-effects model (p > .20) predicting CES-D scores over time, suggesting participants did not experience reductions in depression symptoms during the study. The interaction of treatment condition and time was not statistically significant (p > .10), the interaction of treatment location and time was not statistically significant (p > .80), and the three-way interaction of treatment location, treatment condition, and time was not statistically significant (p > .80). The level of education factor was a statistically significant predictor of CES-D scores (p < .05). The paired contrasts indicated that participants who did not complete high school reported greater CES-D scores (10.91, SE = 4.03, p < .01) than participants who completed education greater than high school. Participants who completed high school did not report different CES-D scores relative to those who received education greater than high-school (ΔMD = −2.20, SE = 2.60, p > .30). No other fixed-effect factors (i.e., ethnicity, marital status, gender, years with SAD, age) were statistically significant predictors of CES-D scores (ps > .30).