Affective Interference: An Explanation for Negative Attention Biases in Dysphoria?

Transcription

1 Cognitive Therapy and Research, Vol. 26, No. 1, February 2002 ( C 2002), pp Affective Interference: An Explanation for Negative Attention Biases in Dysphoria? Greg J. Siegle, 1,4 Rick E. Ingram, 2,3 and Georg E. Matt 3 Research suggests that individuals with features of depression pay excessive attention to negative information. Yet, it is unclear what aspects of negative information are attended to by these individuals. Different answers to this question suggest different roles for attention in the onset and maintenance of depressive states. This study investigated aspects of emotional information to which college students with and without features of depression attend. Research participants completed an affective lexical decision task and an affective valence identification task. Dysphoric individuals were slow to identify the emotional valence of positive information and nonemotional aspects of negative information (the lexicality of negative words), but were not slow to identify the emotional valence of negative words. An affective-interference hypothesis is advanced to explain these results. Dysphoric individuals are proposed to attend to the emotional content of negative information at the expense of attending to other aspects of the information. Results are related to theories of ruminative coping with depression. KEY WORDS: depression; information processing; attention; rumination. Attention to emotional information is central to many theories of the onset and maintenance of depression (e.g., A. T. Beck, 1967, 1974; Ingram, 1984; Ingram, Miranda, & Segal, 1998). Support for these theories is found in literature suggesting that dysphoric and depressed individuals disproportionately attend to and remember negative information (Blaney, 1986; Matt, Vazquez, & Campbell, 1992; Matthews & Harley, 1996; Williams, Mathews, & MacLeod, 1996). Yet, it is unclear to which aspects of negative information dysphoric and depressed individuals attend. It is also unclear whether biased attention to negative information occurs in the early 1 University of Pittsburgh School of Medicine and VA Pittsburgh Healthcare System, Pittsburgh, PA. 2 Southern Methodist University. 3 San Diego State University, San Diego, California. 4 Correspondence should be directed to Greg Siegle, PhD, University of Pittsburgh School of Medicine, Western Psychiatric Institute and Clinic, 3811 O Hara St., Pittsburgh, PA 15213; gsiegle+@ pitt.edu /02/ /0 C 2002 Plenum Publishing Corporation

2 74 Siegle, Ingram, and Matt stages of attention, having to do with initial perceptions of information, or in late stages of attention, involving retrieval of associations from memory (Macleod & Mathews, 1991). Clearly specifying these aspects of the relationship between mood and attention to emotional information may lead to a better understanding of the role of information processing in affective psychopathology. This paper will focus specifically on attention biases in individuals who are dysphoric (have sad mood states thought to underlie depression) rather than individuals diagnosed with clinical depression to avoid confounding features associated with clinical diagnoses (Persons, 1986). Theories of emotional information processing from cognitive and physiological psychology may help to resolve ambiguities regarding the roles of cognitive and emotional information processing in dysphoric individuals. They suggest that emotional aspects of information (e.g., whether it is positive or negative; e.g., the notion that birthday is positive) and semantic (conceptual, nonemotional) aspects of the same information (e.g., the notion that birthday is the day on which one is born) can be processed in parallel by different highly interconnected physiological (LeDoux, 1996; Tucker & Derryberry, 1992) and cognitive (Bower, 1981; Ingram, 1984) systems. Attention can be differentially allocated to these aspects of information (Kitayama, 1990; Matthews & Harley, 1996). If emotional and nonemotional aspects of information are processed in parallel, then information-processing biases could occur as a function of attention to affective aspects of information, nonaffective aspects of information, or feedback between systems responsible for representing affective and nonaffective aspects of information. Depending on how much feedback occurs between the systems, attending to the affect associated with information could interfere with normal semantic associations (e.g., Siegle, 1999). This phenomenon will be referred to as affective interference. Affective interference might involve responding to the word death by immediately recognizing that the stimulus is negative and then thinking of other negative things unrelated to death such as one s low self-image. Attention to the emotional and nonemotional aspects of information can be examined separately by observing how quickly individuals respond to questions that direct their attention to relevant features of a stimulus. Reaction times have long been assumed to reflect the amount of effort an individual pays to information. Thus, longer reaction times are traditionally associated with paying less attention to a task (Massaro, 1988). By comparing individuals reaction times to questions regarding emotional and nonemotional aspects of a stimulus, relative attentional allocation to each of these components can be measured. Two reaction time tasks can thus be used to determine whether attending to emotional aspects of information impairs attention to nonemotional aspects of information. A valence identification task requires participants to identify the emotion associated with positive, negative, and neutral information. It thus directs participants attention towards the emotional aspects of stimuli. Participants reaction times are presumably related to how much attention they pay to emotional aspects of information. In contrast, an affective lexical decision task requires participants to judge whether a string of letters spells a word that may be positive, negative, or

3 Affective Interference in Dysphoria 75 neutral. This task directs participants attention towards nonemotional aspects of information. If dysphoric individuals attend to, and make associations with, emotional aspects of negative information at the expense of attending to its nonemotional aspects, they would be expected to respond especially quickly to negative information on a valence identification task. Because of affective interference they would be expected to react especially slowly to negative information on a lexical decision task. Feedback between structures responsible for processing affective and nonaffective features could exaggerate these biases. For example, a dysphoric individual who attends to negative aspects of information may respond to the typically positive stimulus birthday by associating it with the (semantic) belief I am getting old. This thought may trigger the person s recognition of negativity. The dysphoric individual may thus be especially slow to identify positive information as positive but, by the same token, be very quick to identify negative information as negative. Put another way, research has long suggested that the more meaningful information is to an individual, the more deeply it is processed (e.g., Craik & Lockhart, 1972). If dysphoric individuals are especially well-practiced at identifying negativity or find negative aspects of information to be particularly meaningful, they may process emotional aspects more deeply than semantic aspects. Such a strategy could allow affective aspects of information to interfere with perception of other (e.g., semantic) aspects of that information. Although the combination of these tasks is fairly novel, both tasks have been examined in the past. Valence identification tasks have been used with anxious individuals (Hill & Kemp-Wheeler, 1989; Mathews & Milroy, 1994) and with threat words with depressed populations (Hill & Kemp-Wheeler, 1989) but not with depressed or dysphoric individuals using positive, negative, and neutral words as stimuli. In contrast, a number of researchers have employed affective lexical decision tasks with nondysphoric, dysphoric, and depressed individuals. Most of these researchers predicted that depressed and dysphoric individuals would respond more quickly to negative words than to nonnegative words on this task (e.g., Challis & Krane, 1988; Macleod, Mathews, & Tata, 1986; Matthews & Southall, 1991; Ruiz Caballero & Bermudez Moreno, 1992). This hypothesis was not confirmed for any of these studies. Moreover, when the studies are looked at together, as summarized in Table I, a conclusion consistent with the notion of affective interference emerges (see Siegle, 1996, for a complete review of these data). A literature search revealed seven lexical decision task studies of nondepressed individuals and four studies involving depressed individuals, in which priming was not employed, 5 and in which reaction times to negative and neutral words were reported. No studies observed a significant difference in nondepressed individuals reactions to negative and neutral words. In contrast, all studies of depressed individuals suggested that they were slightly slower to respond to negative than to neutral words (meta-analytic CI = ms). 5 Priming studies were not included because evidence suggests that priming may statistically interact with affective recognition (Conway & Bekerian, 1987; Matthews & Southall, 1991).

4 76 Siegle, Ingram, and Matt Table I. Negative Reaction Times Neutral Reaction Times (D) for Nondepressed and Depressed Individuals, in Milliseconds for Published Affective Lexical Decision Tasks Study Nondepressed Depressed Bradley, Mogg, and Williams (1994) 5 3 Bray (1988) 10 Challis and Krane (1988) 62 Macleod, Tata, and Mathews (1987) Matthews and Southall (1991) SOA = 1500 ms: 18 SOA = 1500 ms: 76 SOA = 240 ms: 29 SOA = 240 ms: 50 Matthews, Pitcaithly, and Mann (1995) SOA = 1500 ms: 13 SOA = 240 ms: 14 Stip and Lecours (1992) and Stip, Lecours, 8 30 Chertkow, Elie, and O Cannor (1994) Williamson, Harpur, and Hare (1991) 46 Meta-analytically derived mean effect size a M D = 2.07, SD D = 4.21 M D = 17.49, SD D = 7.77 a Weighted average effect sizes were calculated using the inverse of the sampling difference variance for weights (Hedges & Olkin, 1985). This technique gives higher weights to studies with larger sample sizes and lower difference variances. Although this result is based on studies in which a variance was reported, results did not change appreciably when a sampling difference variance was estimated for studies in which none was provided. The two conditions from the Matthews and Southhall and Matthews et al. studies (1991, 1995) were counted as different experiments. Thus, these studies generally show the opposite pattern from what is usually predicted. Depressed individuals react more slowly to negative than to neutral words, whereas nondepressed individuals do not. This finding is consistent with the idea that the affect associated with negative information interferes with the recognition of nonaffective aspects of negative information. The affective lexical decision and valence identification tasks are probably not pure uncorrelated measures of affective and nonaffective processing. Rather, it is predicted that dysphoric individuals will be faster to name the valence of negative than positive or neutral information, but will be slower to name the lexicality of negative words because of feedback between systems involved in affective and semantic determination. To test these hypotheses, the current experiment contrasted the performance of dysphoric and nondysphoric individuals on a lexical decision and valence identification task. By analyzing the tasks separately, it can be determined whether the general patterns of interest are present in the data. By correlating performance on the tasks a determination of whether increasing reaction times on one task are associated with decreasing reaction times on the other can be made. METHOD Research Participants A multiple-gating procedure was used for selection of research participants to ensure that they had a stable mood over a number of weeks. Research participants were selected from a pool of over 3000 students in an introductory psychology course at San Diego State University. Dysphoric individuals were selected for having a Beck

5 Affective Interference in Dysphoria 77 Depression Inventory (BDI; A. T. Beck, 1967) score of over 15 (a score indicating moderate depressive symptomatology). Nondysphoric individuals were selected for having a BDI score under 6 at a mass screening at the beginning of the semester. Participants received class credit for their participation. In total, 138 students participated in the experiment, at least 2 weeks after the mass screening. In the dysphoric group, 30 participants had BDI scores over 16 when they came in for testing (M = 22.8, SD = 4.11) and were used in subsequent analyses. The increased cut-off was adopted to reflect the highest possible level of depressive severity upon testing that preserved an adequate sample size, derived through power analyses. Dysphoric participants included 10 men and 20 women of whom 7 identified as Asian, 14 as Caucasian, 7 as Hispanic, and 1 as having another ethnicity. In the nondysphoric group, 46 of the students who had BDI scores between 1 and 6 at the screening were still in this range at testing (M = 3.00, SD = 1.63) and were thus used in further analyses. They included 21 men and 25 women of whom 1 was identified as African American, 6 as Asian, 22 as Caucasian, 11 as Hispanic, and 1 as having another ethnicity. Distributions of ethnicity were not significantly different between the groups, χ 2 (4) = 2.85, p =.65. Measures The BDI was used to assess depressive symptomatology. The BDI is a 21-item self-report inventory. Individual items are worded so that responses reflect increasing degrees of severity and are given the values of 0 3. The total possible score ranges from 0 to 63. The inventory is frequently used to assess depressive symptoms in college populations. It has acceptable validity and reliability (A. T. Beck, 1967; A. Beck, Steer, & Garbin, 1988). The BDI was chosen rather than its successor, the BDI-II, as the study was begun before the BDI II was published. Stimuli for a lexical decision and valence identification task were displayed on an IBM PC compatible 486 computer with a 14-in. color monitor. Research participants sat approximately 28 in. from the bottom of the stimulus. Stimuli were drawn in lowercase letters approximately 5/8 in. high on the monitor, subtending approximately 1.21 of visual angle. For both computer administered tasks two sets of 10 positive, 10 negative, and 10 neutral words balanced for normed affect, word frequency, and word length were chosen from Siegle s corpus (Siegle, 1994). This corpus was compiled from published studies that employed normed word lists and pilot data collected for this experiment. Examples of positive words include happy and bliss. Examples of negative words include hopeless and ashamed. Examples of neutral words include library and slope. The positivity and negativity of word on the first word list were rated by 530 undergraduates. Analysis showed that the each of the word groups strongly and significantly differed from each other in both positivity and negativity ratings. Dysphoric and nondysphoric undergraduates did not tend to differ in their valence ratings (Williams, Conner, Siegle, Ingram, & Cole, 1998). In that sample negative words were rated farther from neutral words than neutral words were from positive words, on negativity. Likewise, positive words were rated farther from neutral words than neutral words were from negative, on positivity, suggesting

6 78 Siegle, Ingram, and Matt that valences differed in the expected direction and magnitude. 6 For the lexical decision task, 15 nonwords consisting of single letter perturbations of equal numbers of normed positive, negative, and neutral words, were also included (e.g., cousip, mendion ). For the lexical decision task, a row of 11 Xs was present on the screen at the beginning of the each presentation. After 2000 ms, the Xs in the middle of the string were replaced by letters spelling a word or nonword, with the Xs on either side remaining on the screen. After the stimulus duration, the letters were again masked by Xs. The question Is it a word? appeared on the screen. The same procedure was used for the valence identification task except that participants responded to the question What s the Valence? Determination of Stimulus Duration To increase the chances that internal feedback processes would be engaged during stimulus recognition, leading to affective interference, stimuli were slightly obscured by using a short stimulus duration. Just the same, shorter stimulus durations were assumed to add more noise (i.e., random variation) to reaction times because of incurred perceptual difficulties. To balance these concerns, pilot data was collected using a stimulus duration of 150 ms, which revealed relevant effects; this duration was thus chosen for the experiment. As a sensitivity check, two shorter durations (100 ms, 50 ms) were also included to make sure that there would be some duration short enough to allow cognitive effort sufficient to reveal biases. These conditions were only to be analyzed as a way of understanding whether stimulus duration contributed to null effects, if they were obtained. Procedure Potential research participants were invited by phone to participate in an experiment involving the perception of words. After obtaining informed consent, directions for the lexical decision task and valence identification tasks were shown to research participants on the computer. Research participants were then shown the directions again for the first task that they would complete. Participants were given a practice session consisting of three trials that were repeated until they were correctly performed. After querying for any questions, participants completed the first task. The identical procedure was used for the second task. In both tasks each stimulus (10 positive words, 10 neutral words, 10 negative words, 15 nonwords) was presented at stimulus durations of 50, 100, and 150 ms for a total of 135 trials. 6 The selection of words for the tasks was done using a computer program (Siegle, 1994) designed to create word lists of an arbitrary length balanced for normed affect, word frequency, and word length. To determine whether word valence covaried with other characteristics of the chosen stimulus words, two analyses were performed. A 3 (valence: positive, negative, neutral) 2 (word list: first, second) analysis of variance (ANOVA) with word frequency revealed no statistically significant main effects or interactions (F < 1.7 for all tests). Similarly, a 3 (valence: positive, negative, neutral) 2 (word list: first, second) ANOVA with word length revealed no statistically significant main effects or interactions (F < 1.5 for all tests). The list generating program and word sets that were used are available from the first author upon request.

7 Affective Interference in Dysphoria 79 The lexical decision task was conducted in the following manner. The research participant was asked to place his or her right palm below the keyboard with the index finger poised above the space bar, equidistant from the N and M keys. Each word and nonword was presented to the participant as described previously, at each stimulus duration. For each stimulus the research participant pushed a buttons for Yes or No, labels for which were placed over the N and M keys on the keyboard. The research participant s reaction time and response was recorded on the computer for each stimulus. The valence identification task was conducted in the following manner. The research participant was asked to place his or her right palm below the keyboard with the index finger poised above the space bar, equidistant from the Z, X, and C keys. Each word was presented at each stimulus duration to the participant as described previously. In response to each word the research participant pushed buttons labeled +,, or N (standing for Positive, Negative, or Neutral, respectively), which were placed over the Z, X, and C keys. Different keys were used for the different tasks so that all keys could be labeled at the beginning of the experiment. After the completion of both tasks, the BDI was administered on a computer, and participants were debriefed. The order in which tasks were completed, the order in which buttons for responses on the keyboard were labeled for the tasks, and the assignment of which word list was used for which task were counterbalanced using a strategy that ensured a balanced sampling of all possible combinations as the number of participants increased. The order of words within each task, and the order in which a given word was shown in a given stimulus duration were assigned pseudorandomly by computer (i.e., random to the extent possible using a computer-based random number generator) for each participant. RESULTS Mean reaction times to each valence and stimulus duration on each task were calculated. Reaction times below 150 ms were discarded as outliers because previous results suggest that reaction times in this range indicate that a response was made without regard for the stimulus (Matthews & Southall, 1991). Similarly, responses over 5000 ms were discarded as outliers under the assumption that such long response latencies indicated inattention to the trial. This relatively long cut-off was adopted because the magnitude of valid delays in reaction times because of interference effects was unclear a priori. Reaction times to stimuli that were incorrectly identified on the lexical decision task, and reaction times to stimuli whose valence was identified as incongruent with the normed valence on the valence identification task were not removed from the computation of means. Reaction times on the valence identification task were not significantly skewed, skew = 0.40, SE skew = Although reaction times on the lexical decision task were more skewed, skew = 1.90, SE skew = 0.277, no normalization transformation was applied to allow comparisons between effects on the tasks and with other relevant literature. One nondysphoric participant s valence identification task data were corrupted and therefore not included in analyses or

8 80 Siegle, Ingram, and Matt Table II. Mean Reaction Times (in Milliseconds) for the 150-ms Condition for NonDysphoric (N lexical decision = 46, N valence identification = 45) and Dysphoric (N = 30) Individuals Nondysphoric Dysphoric Task Valence M SD M SD Lexical decision Positive Negative Neutral Nonword Valence identification Positive Negative Neutral the table. The performance of dysphoric and nondysphoric individuals on the lexical decision and valence identification tasks are shown in Table II. Planned contrasts were performed to test the following hypotheses: (1) that dysphoric people would respond faster to negative words than to nonnegative words on the valence identification task, (2) that dysphoric people would respond slower to negative than to nonnegative words on the lexical decision task, and (3) that differences in reaction times to negative and nonnegative words would be greater for dysphoric than for nondysphoric people. Based on pilot studies, the 150-ms condition was hypothesized to be fast enough to necessitate cognitive effort in identifying its valence, but slow enough to be reliably recognized. The 150-ms condition was therefore used for all contrasts. Familywise alpha was controlled at.05 using a Bonferroni adjustment for each family of contrasts. Contrasts for each task were analyzed as representing different families of tests. Exact p values are reported to allow interpretation of significance with the use of the applied or other significance thresholds. On the lexical decision task although dysphoric individuals reacted approximately 30 ms slower to negative than to neutral words, this difference was not statistically significant, t(29) = 1.6, p =.12. Nondysphoric individuals reacted approximately 40 ms faster to negative than to neutral stimuli. The difference between the dysphoric and nondysphoric participants differences in means (D) was 70 ms, which was significant, F(1, 74) = 7.37, p =.008, η 2 =.09, supporting the affective interference hypothesis. Differences were smaller but in the same direction when reactions to positive words were compared to negative words, F(1, 74) = 1.99, p =.162, η 2 =.03. On the valence identification task, dysphoric individuals reaction times were 200 ms faster to negative than to neutral stimuli, t(29) = 5.6, p <.001. Because nondysphoric individuals also reacted 180 ms faster to negative than to neutral stimuli, the 20-ms difference in biases between dysphoric and nondysphoric individuals was not significant. The greatest difference between the reactions times of dysphoric and nondysphoric individuals was with regard to positive stimuli on the valence identification task. Dysphoric individuals were significantly slower to react to positive than to negative words, D = 166 ms, in comparison to nondysphoric individuals, D = 20 ms, F(1, 73) = 6.45, p =.013, η 2 =.08, supporting the notion that depressed individuals attend more quickly to negative than to positive information.

9 Affective Interference in Dysphoria 81 Sensitivity Analyses Omnibus ANOVAs To be sure that results of relevant planned contrasts were not qualified by unexpected interactions omnibus group (dysphoric, nondysphoric) valence (positive, negative, neutral) multivariate split-plot ANOVAs, controlled using a Bonferroni correction at each level, were performed on the 150-ms stimulus duration condition. On the lexical decision task, a significant Valence Group interaction, F(2, 72) = 3.65, p <.05, η 2 =.09, was observed. Simple effects analysis (Maxwell & Delaney, 1990) yielded no significant effect of valence within the depressed group, F(2, 28) = 1.25, p >.05, η 2 =.082, or within the control group, F(2, 43) = 2.75, p >.05, η 2 =.11, suggesting the interaction was motivated by the previously reported complex contrast. On the valence identification task, a significant Valence Group interaction, F(2, 72) = 3.39, p <.05, η 2 =.09, was observed. There was a significant effect of valence within the depressed group, F(2, 28) = 15.04, p <.001, η 2 =.52, which was driven by the previously reported faster responses to negative than to positive or neutral words. Similarly, in the control group the effect of valence was also significant, F(2, 43) = 9.23, p <.001, η 2 =.30, and was driven by faster responses to positive and negative words than to neutral words. Robustness of Results to Gender and Stimulus Duration To examine robustness of the results to the extra noise introduced by decreasing stimulus duration, a 2 (dysphoric, nondysphoric) 3 (positive, negative, neutral valence) 3 (50, 100, 150 ms stimulus duration) mixed ANOVA on reaction time was performed for each task. No significant interactions with stimulus duration were observed for either task. The analysis revealed significant main effects of stimulus duration on the lexical decision task, F(2, 73) = 103.8, p <.001, and valence identification task, F(2, 72) = 84.1, p <.001, explained by longer reaction times in the shorter stimulus duration condition. On the valence identification task, a significant Valence Group interaction was also observed, F(2, 72) = 4.6, p <.01. Simple effects analyses, controlled using a Bonferroni correction at each level, revealed that the planned contrasts, reported previously, largely accounted for the Dysphoria Valence interaction. When gender was included in the same ANOVAs as a factor, no significant main effects or interactions with gender were observed. The only significant effects were those present when gender was not included. Thus, the reported effects do not appear to be qualified by gender differences or differences in stimulus duration. Robustness to Outliers The following strategy was adopted to be sure that the current results were robust to outliers. Relevant effects were determined to be captured by a significant Dysphoria Task Valence interaction that accounted for approximately 11.5% of the variation in reaction times, Hotelling s F(2, 69) = 4.48, p <.05. The Dysphoria Task Valence interaction was examined using a number of data aggregation

10 82 Siegle, Ingram, and Matt methods suggested by Ratcliff (1993). These included examination of a range of temporal thresholds for outlier removal other than the 5000-ms threshold used in other analyses. Examined values ranged from 2000 ms to no rejection. Similarly, measures of central tendency for reaction times that have been shown to correct for violations of normality in individual participants data including medians and harmonic means were explored. In each case the Dysphoria Task Valence interaction was significant, and the effect size was comparable to that for the analyses reported above. Results were also qualitatively similar when incorrect responses were removed from the computation of means. In fact, effect sizes for all contrasts increased under this restriction; in most cases signal detection rates were high for both dysphoric and nondysphoric individuals on both tasks. Mixed ANOVAs entering counterbalanced conditions (button order, task order, word list), stimulus duration, and dysphoria as independent variables yielded no main effects or interactions with the counterbalanced variables on reaction times in separate analyses for each task. Reliability of Reaction Times To examine whether apparent differential response latencies were tempered by low reliability of reaction times, the internal consistency of reaction times for each valence, for each word set, on both tasks was calculated. In the reported sample, Cronbach s alpha was >.7 for positive and negative words on each word set, on both tasks, and for neutral words on the valence identification task. Alpha was.68 for one word set, and.61 for the other, for neutral words on the lexical decision task. Does Attending to Emotional Features Disrupt Attention to Aspects of Stimuli? Results presented thus far suggest that dysphoria may be associated with attention to emotional aspects of stimuli, at the expense of attention to nonemotional aspects of stimuli. If true, a large portion of variation in reaction times on the lexical decision task should be accounted for by reaction times on the valence identification task, at least for dysphoric individuals. A first analysis of this relationship involved examining correlations between relevant effects on the tasks. Differences in reaction times to negative and neutral words on the lexical decision task were significantly correlated with differences in reaction times to positive and negative words on the valence identification task, r =.23, p <.05. To investigate this relationship in a more sophisticated fashion, hierarchical multiple regressions were performed on the differences in reaction times to each of the valences. Variables representing differences in reaction times to negative and neutral words, positive and neutral words, and positive and negative words on the valence identification task were entered on the first step of the regression. Dysphoria, scored dichotomously as in previous analyses, was entered on the second step. Terms representing the interaction of dysphoria and valence identification biases were entered on the third step. This technique allowed examination of the unique contribution of valence-mediated reaction-time biases above and beyond dysphoria, as well as the role of dysphoria in moderating affective interference.

11 Affective Interference in Dysphoria 83 Biases on the valence identification task accounted for 5.7% of the variation in the difference in lexical decision reaction times to negative and neutral words, which was marginally significant, F(2, 72) = 2.19, p =.12. Dysphoria accounted for an additional 6.3% of the variation, F(1, 71) = 5.09, p <.05. Interactions of dysphoria and valence identification biases were not statististically significant, R 2 =.016, F(2, 69) =.64, p >.05. In contrast, 10.1% of the variation in the difference in reaction times to negative and positive words on the lexical decision task was accounted for by biases on the valence-identification task, F(2, 72) = 4.04, p <.05. Quicker reaction times to negative versus neutral words on the valence identification task were associated with slower reaction times to negative versus positive words on the lexical decision task. Neither dysphoria nor interactions of dysphoria with valence identification biases explained significantly more variation, R 2 =.04, p >.05. This behavior is consistent with the notion that interference on the lexical decision task is due to preoccuption with negative aspects of the stimuli. DISCUSSION The main findings from this experiment suggest that compared to nondysphoric participants, dysphoric research participants were slower to name the valence of positive than of negative or neutral words, and were slightly, though significantly, slower to identify the lexicality of negative than of neutral words. Being quick to name the negativity of words was associated with being slow to name their lexicality. In general, these findings are consistent with the idea the idea of affective interference, that is, that dysphoric individuals attend to the emotional aspects of stimuli at the expense of attending to the nonemotional aspects of stimuli. Additionally, in support of the idea of affective interference, responding slowly to the lexicality of positive, compared to negative words, was associated with quick identification of the emotionality of negative words. Together, these findings suggest that depressed individuals may more easily recognize emotional qualities of negative than other information, and that such biases could be associated with difficulty responding to any other aspects of negative information. An explanation for the obtained data that is consistent with the affective interference hypothesis suggests dysphoric individuals often ruminate or think repeatedly about information that is salient to their depression. Nolen-Hoeksema has suggested that individuals possessing a ruminative cognitive style tend to focus on their symptoms of depression at the expense of other tasks they are given to do (e.g., Nolen-Hoeksema & Morrow, 1993; Nolen-Hoeksema, Parker, & Larson, 1994). Using a broader definition of rumination (e.g., Ingram s notion that rumination involves feedback between the mental representations of nonemotional and emotional associations with information [Ingram, 1984]) ruminating individuals might be hypothesized to reveal biases on tasks assessing both emotional and nonemotional information processing, when they are dysphoric. Specifically, ruminative coping might lead dysphoric individuals to quickly recognize and ruminate upon negative information, yielding to quick judgments of that information as negative. In contrast, positive information would provide the least possible grounds for either quick recognition or

12 84 Siegle, Ingram, and Matt ruminative association of the information with relevant memories, leading to quick recognition of its lexicality but slow recognition of its emotional features. Appeals to rumination might also predict that people who ruminate on their own dysphoria (or negative information that is relevant to them) would be most delayed in identifying negative information not specifically relevant to their dysphoria; when presented with negative information that is not personally relevant, a dysphoric individual might think about negative information that is personally relevant (e.g., a loss event), and thus respond slowly to the presented nonpersonally relevant negative information. This hypothesis may explain why the difference in response times to negative and neutral words was larger for dysphoric individuals than for nondysphoric individuals on the lexical decision task. It also may suggest a need to assess the personal relevance of experimental stimuli. Yet, relationships between differential lexical decision reaction times to negative and neutral words and valence identification biases were weak and not replicated under different types of analysis. If failure to detect this effect is not due to low power, it could reflect the presence of two groups of dysphoric individuals. One group was slow to respond to negative words on the lexical decision task; these individuals may also have been slow to respond to negative words on the valence-identification task. Such individuals might be said to have a generalized bias away from negative information, perhaps as a result of heightened perceptual defense to negative information (Powell & Helmsley, 1984). A second group of dysphoric individuals were primarily slow to respond to positive words on the valence identification task, a phenomenon that was very weakly associated with being slower to respond to negative than to neutral words on the lexical decision task. This group of individuals might experience affective interference. An alternate explanation for discrepancies between performance on the tasks is that the lexical decision and valence identification tasks might require different levels of processing resources. In this case, the lexical decision task stimuli might not have been processed to the same extent as the valence identification stimuli and thus, biases were not as large. To examine the extent to which each task involved recruitment of processing resources, Siegle, Granholm, Ingram, and Matt (2000) measured pupil dilation, a correlate of cognitive load (e.g., Beatty, 1982), while depressed and never-depressed individuals completed the valence identification and lexical decision tasks. Patterns of pupil dilation on both tasks were similar in shape (i.e., same factor structure) and magnitude (similar peak levels of dilation) suggesting that the tasks required similar processing resources. A final potential explanation for the differential effect sizes concerns variability in the reliability of reaction time estimates on the tasks. Internal consistency was slightly lower for neutral words on the lexical decision task in comparison to neutral words on the valence identification task, and in comparison to positive and negative words on both tasks. As the primary comparison on the lexical decision task was between reaction times to negative and neutral words, the reliability of this difference could have appeared small because of decreased consistency in response times to neutral words. Several limitations of the current study must be acknowledged. Foremost, the idea of affective interference suggests a difference in the way dysphoric individuals will respond to negative stimuli that are and are not personally relevant; the study

13 Affective Interference in Dysphoria 85 did not assess the personal relevance of presented stimuli. Similarly, obtained results could have been a function of the word sets that were chosen, for example, positive and negative words could be more semantically related than chosen neutral words, leading to confounding of word sets with observed biases. Additionally, the power to detect a strong interaction of dysphoria with valence-identification on lexical decision reaction times may be low because no explicit effort was made to obtain a group of ruminating individuals with low BDI scores. Thus, the weak interaction in performed regressions may not reflect a true absence of an Information Processing Bias Dysphoria Interaction. Differences between task demands (e.g., the lexical decision task required a binary choice, and the valence identification task required choosing between three alternatives) could also have decreased power to detect relationships between measurements of emotional and semantic identification. The lack of observable gender differences may have been due to low power; there were relatively few dysphoric males in the sample (10/30). Other research suggests that potential correlates of affective interference, such as rumination, are subject to gender differences (e.g., Nolen-Hoeksema, Larson, & Grayson, 1999). A final limitation involves the interpretation of BDI scores as representing dysphoria. Because other aspects of psychological distress (e.g., anxiety) were not controlled for, it is possible that elevations on the BDI represented diffuse psychological distress rather than pure dysphoria. These limitations aside, the present results suggest some possibly important directions for future research. Because the extent to which evidence for affective interference in dysphoric undergraduates can be used to inform an understanding of clinical depression is unclear, exploring the generalizability of the current findings to clinical depression may also be useful. Previous research has shown that many cognitive aspects of dysphoria mirror those found in clinically depressed samples. Evidence for affective interference in depressed samples might provide a great deal of insight into the role of cognition in depression. To further assess the role of affective interference in emotional information processing, experiments that explicitly identify stimuli that are and that are not personally relevant for dysphoric individuals may be useful. Additionally, it may be useful to investigate whether there is physiological support for the idea that mental structures involved in the identification of the affective content of a stimulus could interfere with those involved in the identification of the nonemotional content of a stimulus. Based on the performance of computational neural network models of relevant brain circuits on simulated lexical decision and valence identification tasks (Siegle, 1999; Siegle & Ingram, 1997), it is expected that individuals who are slow to react to negative information on the lexical decision task may have excessive activation of brain structures responsible for the identification of positive and negative aspects of information both before and after their reaction to the presented stimulus. Another useful future direction will be to examine correspondences between affective interference and other types of information processing biases commonly observed in depressed individuals. Affective interference specifically regards changes in processing because of unusual patterns of attentional allocation. Research has shown that both depression and dysphoria were characterized by better memory for negative than for positive information (e.g., Matt, et al., 1992). Moreover, theorists

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