تفاوت های فردی در تجربه خاطرات مزاحم: نقش توانایی مقاومت در برابر تداخل فعال
|کد مقاله||سال انتشار||مقاله انگلیسی||ترجمه فارسی||تعداد کلمات|
|39126||2009||13 صفحه PDF||سفارش دهید||محاسبه نشده|
Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Journal of Behavior Therapy and Experimental Psychiatry, Volume 40, Issue 2, June 2009, Pages 189–201
Abstract This study explored whether a relatively poor ability to resist or inhibit interference from irrelevant information in working memory is associated with experiencing undesirable intrusive memories. Non-selected participants (N = 91) completed a self-report measure of intrusive memories, and carried out experimental tasks intended to measure two different types of inhibition: resistance to proactive interference and response inhibition (i.e., the ability to prevent automatically triggered responses). The results showed a significant relationship between inhibition at the cognitive level (i.e., resistance to proactive interference) and the frequency of intrusive memories (especially in the group of female participants) whereas no such relationship with measures of response inhibition emerged. These findings are consistent with the idea that deficient inhibitory control reflects a vulnerability factor for experiencing intrusive memories. Implications for research investigating risk factors for the development of posttraumatic stress disorder (PTSD) are discussed.
Introduction There is evidence that most people will be exposed to at least one extremely threatening situation during the course of their lives (Ozer, Best, Lipsey, & Weiss, 2003). In a study among 900 US college students, the prevalence rate of having experienced a potentially traumatic event was found to be around 67% (Bernat, Ronfeldt, Calhoun, & Arias, 1998). There is, however, a great variety in how people deal with these highly aversive experiences. In the immediate aftermath of a traumatic event, most people report elevated levels of psychopathology, but only a minority of them will eventually develop chronic PTSD (McNally, Bryant, & Ehlers, 2003). The core symptoms of PTSD consist of persistent avoidance of stimuli associated with the trauma, increased arousal levels (e.g., hyper vigilance, exaggerated startle response) and intrusive re-experiencing, including recurring images, flashbacks, nightmares and distress when confronted with reminders of the traumatic event (American Psychiatric Association, 2000). Considering this, one of the intriguing puzzles surrounding research on PTSD is identifying the underlying cognitive mechanisms that could set people at risk for the maintenance of trauma-related symptoms. Knowledge of the underlying mechanisms could help explaining why and how well-known pre-trauma risk factors (see Brewin et al., 2000 and Ozer et al., 2003 for reviews) are involved in pathological responses such as intrusive memories. Cognitive theories of PTSD clearly describe the development of intrusive symptoms due to problems with encoding [e.g., perceptual processing ( Ehlers & Clark, 2000)], storage [Situational Accessible Memories (SAM, Brewin, Dalgleish, & Joseph, 1996)] and retrieval [Cue-driven retrieval due to strong associative learning ( Ehlers & Clark, 2000)] of the traumatic event. However, the question of how individual differences in posttraumatic psychopathology may be explained by pre-trauma information-processing properties that act as vulnerability factors remains largely unanswered. For example, there is convincing evidence that relatively low pre-morbid intelligence is an important predictor of chronic PTSD symptoms (e.g., Kaplan et al., 2002, Macklin et al., 1998 and McNally, 2003), but little is known about the underlying cognitive mechanisms relating intelligence to pathological responses to trauma. Interestingly, recent developments in the experimental memory literature suggest that specific cognitive deficits existing prior to the occurrence of a traumatic event may hamper natural recovery of intrusive re-experiencing that is part of the common posttraumatic response. For example, there is some evidence suggesting that individual differences in working memory capacity (WMC) might play a role in the maintenance of intrusive memories. It has been proposed that WMC reflects a domain-general capability to control attention, which is particularly important in situations involving proactive interference or conflict between competing response tendencies ( Engle, 2002). In two studies, Brewin et al. ( Brewin and Beaton, 2002 and Brewin and Smart, 2005) showed a positive relationship between WMC and the ability to block neutral or personally relevant thoughts from entering working memory. It has been suggested that individual differences on indices of WMC (e.g., Operation Span; Turner & Engle, 1989) reflect the capability to actively inhibit interference from events stored in long-term memory ( Kane and Engle, 2000, Lustig et al., 2001 and Rosen and Engle, 1998). In this light, the question arises whether deficient inhibitory control may function as a specific vulnerability factor for the persistence of intrusive memories in the aftermath of a traumatic event. Preliminary evidence for this idea comes from a study of Klein and Boals (2001). In this study employing healthy undergraduate students, the frequency of experiencing intrusive and avoidance symptoms related to a potentially traumatic event was relatively high in people with relatively low WMC (Klein & Boals, 2001). In addition, an earlier study found that people who described themselves as highly distractible (which might be taken as an analogue to performance on WMC tasks) also reported a relatively high frequency of intrusive memories (Verwoerd & Wessel, 2007). The preceding studies have provided indirect evidence for the idea that relatively weak inhibitory control over the contents of working memory might be responsible for individual differences in the experience of unwanted intrusive memories. To further explore this issue, the present retrospective study focused on the relationship between deficient inhibitory control and the frequency of experiencing intrusive memories in an unselected student sample. It has been suggested that inhibition serves different functions (Hasher, Zacks, & May, 1999) and may even consist of two or more independent mechanisms (Friedman & Miyake, 2004). For example, one type of inhibition involves controlling automatically triggered prepotent responses in order to carry out an effortful primary and compatible response. A lack of such response inhibition seems to be involved in dysfunctional impulsive behavior (Nigg, 2000). Alternatively, inhibition may act on a more cognitive level and involve the ability to resist interference from information that was previously relevant to the task at hand, but has since become irrelevant because of a change in context (Friedman and Miyake, 2004 and Hasher et al., 1999). Intrusive memories may be seen as a profound example of experiencing unwanted interference in real life. Therefore, problems with this latter form of inhibition (i.e., resistance to proactive interference, PI) may be particularly relevant for explaining posttraumatic intrusive cognition. Interestingly, Friedman and Miyake (2004) found a relationship between a latent variable of resistance to PI and self-reports of general intrusive thoughts. However, it remains to be seen whether a similar pattern of associations will hold for the actual experience of intrusive memories related to a stressful event. The major aim of the present study was to examine whether there is indeed a general relationship between weakened inhibitory control at the cognitive level (i.e., resistance to PI) and the frequency of intrusive memories related to an earlier experienced stressful event. It was expected that a relatively weak ability to resist PI in working memory would be associated with a relatively high frequency of intrusive memories. In contrast, the ability to inhibit automatically triggered responses was not expected to show any relationship with individual differences in intrusive re-experiencing. A subsidiary aim of the current study was to explore the consequences of the process of cognitive inhibition. If a well-developed ability to resist PI prevents unwanted/irrelevant material to intrude into conscious awareness, does this mean that the resisted material has become less accessible for remembering at a later point in time? It has been suggested that keeping earlier studied but now irrelevant material out of working memory results in a reduced activation of the representation of that material in long-term memory ( Anderson and Spellman, 1995 and Rosen and Engle, 1998). Therefore, the present study looked at the ability to resist PI and its supposed consequence, using an AB–AC–AB list-learning paradigm. This paradigm renders two indices that are relevant to the present purpose: (a) the number of trials needed in order to learn new responses (AC) in the face of interference from earlier studied (old) material (AB) and (b) latencies to respond again with the old (AB) material after having learned these new responses (see Rosen & Engle, 1998). It was expected that showing more PI as reflected by a higher number of trials to learn new responses would predict relatively high scores on a self-report measure of intrusive memories. By contrast, if indeed the inhibition of unwanted responses has consequences for their later retrievability/accessibility, we expected to find a negative relationship between latencies and intrusive memories. That is, a relatively weak ability to resist PI would be reflected by faster reaction times (higher accessibility) for old (AB) responses. Thus, we predicted that shorter response latencies would be related to a higher frequency of intrusive memories. In addition, because the clinical literature consistently indicates that female gender increases the probability of developing PTSD following a traumatic experience (Ozer et al., 2003), we explored whether the hypothesized effect of low resistance to PI on the frequency of trauma-related intrusions might be especially pronounced in women. Finally, given the cross-sectional nature of the present study, it is important to rule out alternative explanations for the hypothesized relationship between resistance to PI and intrusive memories. For example, earlier research has shown that both deficient cognitive/inhibitory control and a high frequency of intrusive memories are related to elevated levels of depression (Ellis, 1990 and Ellis, 1991). Therefore, the present study investigated if the proposed relationship between relatively weak inhibitory control and intrusive memories might covary with elevated levels of depression.
نتیجه گیری انگلیسی
. Results Data for three participants were excluded from analyses because of undue influence on the β values in the regression model. For two of these participants, data were unreliable due to many microphone errors or knowledge of the experimental manipulation on the interference task. One participant reported clinical levels of depression and intrusive memories. Furthermore, an additional four participants were excluded because they did not report about stressful events of moderate to strong intensity (past impact < 5), leaving 91 participants for further analyses. Descriptive statistics for the scales used in the present study are shown in Table 1. As shown in Table 2, the relatively low number of trials needed to reach three correct responses on the first list of the interference task resulted in a considerable kurtosis. Therefore, for this variable, rank correlations were calculated. None of the other variables used in the present study showed significant deviations in either skewness or kurtosis. Table 1. Mean, standard deviation (SD), minimum and maximum of the scales and experimental variables in this study N Mean SD Min Max IES total score 91 14.11 13.48 0 54 IES_Recency 91 58.95 51.45 0 235 CES-D 91 11.53 9.24 0 38 Past impact 91 8.43 1.25 6 10 Number of trials list 1 91 36.36 0.92 36 41 Number of trials list 2 91 39.62 3.45 36 50 Proportional increase in RT int. task 91 49.80 23.50 11 112 Proportional increase in RT (Stroop) 91 23.01 11.06 1.05 45.40 Prepotent associates (RNG) 91 −0.01 1.01 −1.78 3.38 Note. IES = Impact of Event Scale; IES_Recency = time in months since the event described on the IES took place; CES-D = Center for Epidemiologic Studies Depression Scale; past impact = distress experienced in relation to the event described on the IES; number of trials list 1 = number of trials needed to reach 3 correct answers on the interference task (list 1); number of trials list 2 = number of trials needed to reach 3 correct answers on the interference task (list 2); proportional increase in RT int. task = proportional increase in RT between the first- and the third-list (interference task); proportional increase in RT (Stroop) = proportional increase in RT between neutral trials and incongruent trials (Stroop); prepotent associates (RNG) = factor scores as an index of response inhibition on the random number generation task. Table options Table 2. Pearson and Spearman's rank correlations between the variables used in the present study Scales 1 2 3 4 5 6 7 8 1. IES – 2. IES_Recency −0.27* – 3. Past impact 0.40** −0.07 – 4. CES-D 0.36** 0.15 0.15 – 5. Number of trials 1 0.15a −0.01a −0.10a 0.05a – 6. Number of trials 2 0.32** −0.10 −0.04 0.15 0.06a – 7. Prop incr. (PI_task) 0.16 0.07 0.01 0.05 −0.02a 0.11 – 8. Prop incr. (Stroop) −0.08 −0.03 −0.08 0.06 −0.03a −0.09 −0.03 – 9. Prepot. ass. (RNG) 0.07 −0.16 0.05 0.01 0.03a 0.14 0.08 −0.17 Note. N = 91. IES = Impact of Events Scale; IES_Recency = time in months since the event described on the IES took place; CES-D = Center for Epidemiologic Studies Depression Scale; number of trials list 1 = number of trials needed to reach 3 correct answers on the first list of the interference task; number of trials list 2 = number of trials needed to reach 3 correct answers on the second list of the interference task; prop. incr. (PI_task) = proportional increase in RT between the first- and the third-list (PI_task); prop. incr. Stroop = proportional increase in RT between neutral trials and incongruent trials (Stroop); prepot. ass. (RNG) = factor scores as an index of response inhibition on the random number generation task. *p < 0.05. **p < 0.01. a Due to strong non-normality of the distribution, Spearman's rank correlations were calculated for the number of trials list 1 variable. Table options 3.1. Descriptive statistics and contents of reported intrusive memories Inspection of the mean impact ratings in Table 1 revealed that participants reported about events from their past that had a high impact on their lives at the time the event took place (i.e., M = 8.43 on a 10-point scale). The contents of the reported memories were compared with items used to measure life stress on the Life Experience Scale (LES; Johnson, Sarason, & Siegel, 1979). It appeared that 76% of the memories resembled LES categories of negative events (e.g., death of a close family member, serious illness of a close family member, death of a spouse, divorce of parents, broken relationship and trouble with study/employer). 3.2. Relationship between intrusive memories (IES) and resistance to PI As shown in Table 3, the HMR analysis with the IES as the dependent variable resulted in a significant 21% of explained variance for the four control variables, F (4, 86) = 5,301, p < 0.001. Significant predictors were depressive symptoms (CES-D) and recency of the distressing event described on the IES (depression, semi-partial r2 = 13%, p < 0.001; recency of event, semi-partial r2 = 9%, p < 0.05). The number of trials needed to learn the first-list responses (e.g., baseline for learning paired-associates on the interfering second list) showed no significant relationship with the frequency of intrusive memories, β = 0.06, p = 0.56. Table 3. Summary of hierarchical regression analysis with IES scores as dependent variable and the control variables and PI (number of trials) as predictors (N = 91) Model 1: number of list 2 trials as predictor Step Predictors ΔR2 (%) DF F-Change B SE β 1 21 4,86 5.72** CES-D 0.08 0.02 0.39** IES_Recency −0.01 0.01 −0.31** Gender 0.11 0.46 0.02 Number of trials list 1 0.13 0.23 0.06 2 5 1,85 5.81** CES-D 0.08 0.02 0.36** IES_Recency −0.01 0.01 −0.29** Gender 0.10 0.44 0.02 Number of trials list 1 0.16 0.22 0.07 Number of trials list 2 0.13 0.05 0.23* 3 5 1,84 5.66* CES-D 0.08 0.02 0.34 IES_Recency −0.01 0.01 −0.31** Gender −0.08 0.44 −0.02 Number of trials list 1 0.22 0.22 0.09 Number of trials list 2 0.12 0.05 0.21* Gender × trials list 2 −0.52 0.22 −0.22* Note. CES-D = Center for Epidemiologic Studies Depression Scale; IES_Recency = time in months since the event described on the IES took place; number of trials list 1 = number of trials needed to reach 3 correct answers on the first list of the interference task; number of trials list 2 = number of trials needed to reach 3 correct answers on the second list of the interference task. *p < 0.05. **p < 0.01. Table options In the first HMR analysis the number of trials needed to reach a criterion of three correct responses on the second list was included in the second step of the model. The results showed that the number of trials needed added another 5% of explained variance to the regression model, β = 0.23, p < 0.05. These findings indicate that people with a reduced ability of suppressing first-list intrusions during second-list learning also reported a relatively high frequency of intrusive memories. 1 With the inclusion of the interaction term between number of 2-list trials and gender in the third step, a small but significant 5% of explained variance was added to the model, β = −0.22, p < 0.05. Further exploration of this interaction term revealed that the relationship between number of 2-list trials and intrusive memories was especially pronounced in the female group (10% of unique variance in IES scores, β = 0.33, p < 0.01, n = 70). The second HMR analysis used proportional delay in RT between the first- and the third list as predictor in the second step. This step added no significant amount of variance to the model, ΔR2 = 0.02, F (1, 87) = 2.62, p = 0.11. Furthermore, no additional variance was explained by including the interaction term between the inhibition index and gender in the third step of the model, F (1, 86) = 0.3, p = 0.58. Thus the present results provide no convincing evidence to sustain the idea that a relatively reduced accessibility of memory representations for earlier interfering material is related to a relatively low frequency of intrusive memories. 3.3. Relationship between intrusive memories and indices of response inhibition The results of the HMR analysis with the IES as dependent variable and the two measures of response inhibition (Stroop, RNG prepotent associates)2 included in the second step showed that no extra variance could be explained by the model, ΔR2 = 0.00, F-change (2, 85) = 0.20, p = 0.95. Again, no additional variance was explained by including the two interaction terms with gender in the third step, F (1, 83) = 0.30, p = 0.76. Thus, individual differences on measures of response inhibition did not show any relationship with the frequency of experiencing intrusive memories.