Is Attentional Bias Towards Threat a Hallmark of Chronic Worry?

IS ATTENTIONAL BIAS TOWARDS THREAT A HALLMARK OF CHRONIC WORRY?

DISSERTATION

Presented in Partial Fulfillment of the Requirements for

the Degree Doctor of Philosophy in the Graduate

School of The Ohio State University

Jennifer Leigh Preston, M.A.

* * * * *

The Ohio State University 2006

Dissertation Committee: Approved by Dr. Michael Vasey, Adviser

Dr. Steven Beck ______Adviser Dr. Herbert Mirels Psychology Graduate Program

ABSTRACT

Research investigating adults with anxiety disorders has typically found that these disorders, including generalized anxiety disorder (GAD), are associated with an attentional bias toward threatening or negative information. However, some research has demonstrated that not all chronic worriers show an attentional bias toward threat.

It is currently unclear why a number of chronic worriers do not show this attentional threat bias, or how individuals who do not show the bias are different from those who do. The current study was designed to clarify why some chronic worriers do not show an attentional threat bias. Participants were undergraduate students recruited based on their level of worry. Recruitment focused on individuals with high levels of worry, but a subsample of individuals with lower worry levels was also included. Attentional threat bias was measured using one type of computerized dot probe paradigm called a probe discrimination task (PDT). Several psychological variables, including depression, social anxiety, and attentional control, were measured to investigate the nature of their relationship with attentional bias. Because minimal research has investigated the reliability of PDTs over time, the reliability of the PDT over a two- week period was examined. Results indicated that the attentional threat bias scores obtained from the PDT were unreliable over time and within each testing session. In

addition, no significant group differences in attentional bias scores were observed between individuals with or without GAD. However, chronic worriers displayed significantly greater attentional bias towards threat than individuals with lower levels of worry. None of the psychological variables measured in the study were consistently related to attentional bias scores. No significant predictors of the presence versus absence of attentional threat bias emerged. The absence of significant differences in attentional bias between individuals with and without GAD is inconsistent with most previous research, but the observed differences in attentional threat bias between groups based on worry level is consistent with previous findings.

The current study’s findings regarding the reliability of attentional bias scores are consistent with the one published study which found attentional bias scores to be unreliable over time.

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Dedicated to my parents for their unconditional love and support

ACKNOWLEDGMENTS

I wish to thank my adviser, Mike Vasey, for guidance and advice during all phases of the project.

I am grateful to Ted Robles for providing statistical assistance and helpful comments and suggestions on the manuscript.

I also wish to thank Laura Bills for her role in managing the data obtained in the study.

VITA

March 19, 1978 …………………… Born – Columbus, Ohio

2000 ……………………………….. B.A. Psychology, Dartmouth College

2000 – present …………………….. Doctoral Graduate student, Ohio State University

2003………………………………...M.A. Psychology, Ohio State University

2005 – present………………………Predoctoral Psychology Intern, VA Pittsburgh Healthcare System

PUBLICATIONS

Research Publications

Lambert, S.F., McCreary, B.T., Preston, J.L., Schmidt, N.B., Joiner, T.E., & Ialongo, N.S. (2004). Anxiety Sensitivity in African-American Adolescents: Evidence of Symptom Specificity of Anxiety Sensitivity Components. Journal of the American Academy of Child and Adolescent Psychiatry, 43(7), 887-895.

FIELDS OF STUDY

Major Field: Psychology

TABLE OF CONTENTS

Page Abstract………………………………………………………………………………...ii Dedication………………………………………………………………..……………iv Acknowledgments…………………………………………………………………..….v Vita……………………………………………………………………………..……...vi List of Tables……………………………………………………………………….…ix List of Figures………………………………………………………………………....xi

Chapters:

1. Introduction…………………………………………………………..……….…….1 Anxiety and Attention..……………………………………………………….. 1 Assessment of Attentional Bias…………………..……………………………2 Dichotic listening task …………………….………………………….. 2 Emotional Stroop task…………………….……….………..………….3 Dot probe task…………………………………….……………………6 Characteristics of Attentional Threat Bias in Generalized Anxiety.……….....11 Psychometrics of attentional bias measures…………..………………12 Clinical status…………………………………………………………18 Psychiatric symptom severity……………………………………….. 20 Attentional and effortful control………………..………………….....21 Current Study…………………………………………………………………23 Hypotheses……….…………………………………………………….……..24

2. Method………………………………………….……………………………...….26 Participants………………………………………..…………………………..26 Materials………………………………………………………………………27 Procedures………………………………………….…………………………31 Probe discrimination task (PDT)……………………………………...31 Measures……………………………………………………………………...32 Data Analysis…………………………………………………………………36 Participant characteristics…………………………………………….36 PDT word list order groups…………………………………………..37 PDT data……………………………………………………………...37 Reliability of RTs and attentional bias scores………………………..38 vii

Relationship of attentional bias to other constructs…………………..38 Self-report measure correlations……………………………………...39

3. Results……………………………………………………………………..…..…..40 Participant Characteristics…………………………………………………….40 DSM-IV diagnostic status…………………………………………….40 PSWQ scoring patterns……………………………………………….44 PDT Word List Order Groups………………………………………………...48 Probe Discrimination Task (PDT)……………………………………………50 Awareness check……………………………………………………...50 Preparation of reaction time (RT) data………………………………..52 RT means and correlations……………………………………………52 Attentional Bias for Negative Information…………………………………...55 Calculation of attentional bias scores…………………………………55 Means and ranges of attentional bias scores………………………….56 Reliability of attentional bias scores………………………………….67 Relationship of Attentional Bias to Other Constructs………………………...72 Correlational relationships with self-report measures………………...72 Moderation of relationship between worry and attentional bias……...72 Relationships Among Self-Report Measures…………………………………75 Ancillary Analyses……………………………………………………………75

4. Discussion……………………………………………………………………...... 83

Bibliography…………………………………………………………………………..95

Appendices: Appendix A: Telephone and Email Recruitment Script…………………….101 Appendix B: Word List used in Probe Discrimination Task (PDT)………...103 Appendix C: Self-Report Measures…………………………..……………..106

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LIST OF TABLES

Table Page

1 Participant demographics by GAD diagnostic status.………………………..28

2 Frequency of DSM-IV diagnoses as primary or non-primary diagnoses...... 41

3 Frequency of current DSM-IV diagnoses per participant.……………………41

4 Means and standard deviations of aggregate self-report measure scores of participants with GAD and participants in the Stable Low PSWQ group without GAD.………………………………………………………………....43

5 Frequency of current primary DSM-IV diagnoses across PSWQ scoring patterns.…….…………………………………………………………………46

6 Means and standard deviations of aggregate self-report measures by PSWQ scoring pattern.………………………………………………………………..47

7 Means and standard deviations of aggregate self-report measures for participants with and without GAD in the Stable High PSWQ group………..49

8 Means and standard deviations of aggregate self-report measures by PDT Word List Order………………………………………………………………51

9 Mean reaction times (ms) for threat-neutral word pairs of participants with GAD and participants in the Stable Low PSWQ group without GAD……….53

10 Mean reaction times (ms) for threat-neutral word pairs, by PSWQ scoring pattern…………………………………………………………………………54

11 Mean attentional bias scores (in ms) of participants with GAD and participants in the Stable Low PSWQ group without GAD……………………………….58

12 Mean attentional bias scores (in ms) of participants in the Stable High PSWQ and Stable Low PSWQ groups………………………………………………..59 ix

13 Correlations between attentional bias scores for each session in the total sample………………………………………………………………………...68

14 Correlations between upper and lower attentional bias scores for each session in the total sample…………………………………………………………….69

15 Correlations between attentional bias scores for each task and bias location across the two sessions………………………………………………………..70

16 Correlations between total attentional bias scores for each session in participants with GAD………………………………………………………..71

17 Correlations between attentional bias scores and the aggregate self-report measures………………………………………………………………………73

18 Correlations between self-report measures at Time 1 and Time 2……………76

19 Correlations between aggregate self-report measures………………………...77

20 Total facilitation and delayed disengagement scores (in ms) for participants with GAD and participants in the Stable Low PSWQ group without GAD….79

21 Total facilitation and delayed disengagement scores (in ms) for participants in the Stable High PSWQ and Stable Low PSWQ groups………………………79

22 Correlations between delayed disengagement scores and the aggregate self- report measures……………………………………………………………….81

LIST OF FIGURES

Figure Page

1 Participants’ PSWQ total score patterns from Prescreening to Time 1………45

2 Mean attentional bias scores (in ms) by Task and Word List Order…………60

3 Mean attentional bias scores (in ms) by Task and Presentation Duration……62

4 Mean attentional bias scores (in ms) by PSWQ Group………………………63

5 Mean attentional bias scores (in ms) by Task and Word List Order………….64

6 Mean attentional bias scores (in ms) of (a) Stable High PSWQ group and (b) Stable Low PSWQ group, by Bias Location, Task, and PSWQ Group………66

CHAPTER 1

INTRODUCTION

Anxiety and Attention

Research investigating anxiety disorders in adults has typically found that high levels of anxiety are associated with an attentional bias favoring threatening or negative information (Mogg & Bradley, 1998). This attentional bias is observed when threat-relevant stimuli compete with neutral stimuli for processing resources. In contrast, low anxious individuals usually show reduced attention to threat stimuli relative to neutral stimuli. Attentional bias toward threat-relevant stimuli has been observed in individuals with high trait anxiety (Bradley, Mogg, Falla, & Hamilton,

1998; Fox, Russo, & Dutton, 2002; MacLeod & Mathews, 1988) as well as those with anxiety disorders such as generalized anxiety disorder (GAD) (MacLeod, Mathews, &

Tata, 1986; Mogg, Bradley, & Williams, 1995), social phobia (Amir, Elias, Klumpp,

& Przeworski, 2003; Asmundson & Stein, 1994), panic disorder (McNally, Riemann,

& Kim, 1990), obsessive-compulsive disorder (OCD) (Tata, Leibowitz, Prunty,

Cameron, & Pickering, 1996), post-traumatic stress disorder (PTSD) (McNally, Kaspi,

Riemann, & Zeitlin, 1990), and specific phobia (Watts, McKenna, Sharrock, &

Trezise, 1986). Evidence supporting attentional biases towards threat has come from several assessment methods, including the dichotic listening task (Foa & McNally,

1986), the emotional (or “modified”) Stroop task (Williams, Mathews, & MacLeod,

1996), and the dot probe task (MacLeod, Mathews, & Tata, 1986).

Assessment of Attentional Bias

Dichotic listening task.

Dichotic listening tasks are intended to assess whether some individuals have a bias in processing information outside of their awareness. A dichotic listening task involves presenting two different channels of information simultaneously, one to each ear. The information presented may be lists of words or prose passages, and participants are asked to attend to the information on one channel. In some cases, participants are asked to respond by pressing a button whenever they detect a target word; in other cases, participants are asked to monitor a computer screen for a probe and press a button when it appears. Typically, participants are quick to detect target words when they are presented to the attended channel but are slower to detect targets in the unattended channel, unless the target words are emotionally salient. In research on attentional processes in anxiety, two types of target words are usually presented during this task: threatening and neutral. One study found that anxious participants, compared to controls, were quicker to respond to visual probes when listening to threatening words than neutral words when the words were presented on the unattended channel (Mathews & MacLeod, 1986). In a dichotic listening study of

obsessive-compulsive disorder patients, the results indicated that patients were faster in responding to unattended threatening words than neutral words before treatment, but they demonstrated equal detection of both types of words following treatment (Foa

& McNally, 1986). One interpretation of these findings is that anxious individuals selectively process threatening stimuli presented outside of awareness. However, a limitation of the dichotic listening task is that the researcher cannot determine whether participants are truly unaware of the information presented to the unattended channel.

Participants may switch attention between channels and thus the task may not accurately assess responses to information completely outside an individual’s awareness. Because of this limitation, other methodologies involving visual paradigms have been utilized more often in attentional processes research.

Emotional Stroop task.

The emotional Stroop task was developed before dot probe tasks and has been used more extensively in research. In the original Stroop task, participants are shown words printed in different colors. The emotional variant of the Stroop task usually employs two types of words: neutral words and threat-relevant words. Participants are asked to disregard the word meaning and name as quickly as possible the color in which each word is printed. Color-naming latency has been interpreted as being a function of the extent to which attention has been devoted to the content of the word

(i.e., the distractor; Kindt & Brosschot, 1998; McNally, Riemann, & Kim, 1990).

Therefore, the emotional Stroop task assesses how much the emotional content of the

words interferes with color naming. The interference effects provide a putative measure of attentional bias for threatening information. However, other explanations for such color-naming interference are possible and are discussed below.

Several versions of the emotional Stroop task have been utilized in published research. The emotional Stroop task words can be presented using a computer, tachistoscope, or on cardboard cards. When the words are presented using a computer, they are usually presented individually, but the card format presents words as a group (i.e., massed). In a review of the literature, Williams, Mathews, and

MacLeod (1996) found that massed presentation of words tended to result in larger interference effects; however, both massed and individual presentation versions of the emotional Stroop task produced replicable effects. Interference effects toward threat- relevant stimuli as measured by the emotional Stroop task have been observed in a wide range of anxiety disorders, including GAD (Mathews & MacLeod, 1985), social phobia (Mattia, Heimberg, & Hope, 1993), specific phobia (Watts, McKenna,

Sharrock, & Trezise, 1986), obsessive-compulsive disorder (Foa & McNally, 1986), panic disorder (McNally, Riemann, & Kim, 1990), and post-traumatic stress disorder

(McNally, Kaspi, Riemann, & Zeitlin, 1990).

In a review of the emotional Stroop task literature, Williams, Mathews, and

MacLeod (1996) discuss consistent evidence that people with anxiety and mood disorders show an increased latency to name the color in which an emotional word is printed. However, some researchers have raised questions about the validity of the typical interpretation of emotional Stroop task scores as directly reflecting a bias in

attention (de Ruiter & Brosschot, 1994; MacLeod, 1991; Mogg, Bradley et al., 2000).

The emotional Stroop task has been criticized because there are multiple interpretations of slowed color naming for threatening words. One alternative interpretation is that a person’s emotional response to threatening words may slow color naming (Watts, McKenna, Sharrock, & Trezise, 1986). De Ruiter and Brosschot

(1994) present another alternative interpretation of the emotional Stroop task: increased response latencies can result from trying to avoid cognitively processing threatening information. Therefore, the emotional Stroop interference effect may reflect cognitive avoidance, rather than attentional bias. No studies have clearly demonstrated why the emotional Stroop effect occurs or what the underlying mechanisms are (Williams, Watts, MacLeod, & Mathews, 1997). In an attempt to more directly measure attentional biases related to threat, the dot probe paradigm was created (MacLeod, Mathews, & Tata, 1986). Four published studies have compared attentional bias scores from an emotional Stroop task with those from a dot probe task, and found little support that the two tasks are measuring the same construct. Two studies found no correlation between the tasks (Dalgleish et al., 2003; Mogg, Bradley et al., 2000), one study found a weak relationship (Brosschot, de Ruiter, & Kindt,

1999), and another study found significant correlations across the different tasks but not between the subtypes of each task (Egloff & Hock, 2003). Given the confounding interpretations associated with the emotional Stroop task and its lack of correspondence with a more direct measure of attentional bias, the remainder of this discussion will focus solely on dot probe tasks.

Dot probe task.

Dot probe paradigms are becoming increasingly prevalent in research on attentional processes. Variations of the dot probe paradigm include the probe detection task and the probe discrimination task. In probe detection tasks, a participant is asked to indicate when a neutral symbol (i.e., probe) appears on the computer screen. First, two stimuli are presented on the computer screen. These stimuli are usually words or pictures. When words are used as stimuli, two words appear on the screen, either both neutral in valence or one neutral and one emotionally negative. The participant is then required to read the upper word aloud. On critical trials (i.e., all threat-neutral word pairs and a subset of neutral-neutral word pairs), a probe appears in the position of one of the two words. The participant is asked to provide a response (e.g., push a button on the computer keyboard) each time the probe appears. Latencies to detect probes following threatening stimuli are compared to latencies to detect probes following neutral stimuli.

Probe discrimination tasks (PDTs) involve the use of two different probes, and participants are asked to make a choice about which probe appeared on the screen. In a typical PDT task, a participant is shown two buttons and is asked to press one button when a certain event occurs on the screen, and to press the other button when a different event occurs. For example, participants may be asked to indicate which one of two probes appeared on the screen, or to indicate whether a probe appeared on the left or right side of the screen (MacLeod, Mathews, & Tata, 1986; MacLeod,

Rutherford, Campbell, Ebsworthy, & Holker, 2002). In probe discrimination studies, two stimuli are presented on the computer screen in different spatial locations (e.g., left or right, top or bottom) and a probe follows one of the stimuli. In this case, the participant is asked to respond to the probe, usually a small dot, by indicating the location of the probe (e.g., top or bottom of screen). On critical trials, an affectively neutral stimulus is presented with an emotionally negative stimulus. Probes may follow either negative or neutral stimuli. Average response latencies to detect probes in each of the two spatial locations are interpreted as an index of how much attention is allocated to each of the two locations. An attentional threat bias score can be calculated by comparing response latencies to probes following threat words and to probes following neutral words.

In current research, probe discrimination tasks are more commonly used than probe detection tasks. Probe discrimination tasks have several advantages over probe detection tasks. First, probe detection tasks contain many “filler” trials in which neutral stimuli are presented, and probes rarely follow these stimuli. Therefore only a small proportion of trials consist of threat stimuli, and these are the trials of interest.

As a result, probe detection tasks require many trials to gather a small amount of critical data. Second, the presentation of threat stimuli is confounded with the appearance of probes. Because most probe detection tasks involve probes following all threat-neutral trials and few neutral-neutral trials, individuals may learn that the presence of a threatening stimulus signals the likely presentation of a probe. However, individuals may vary in the degree to which they detect a relationship between threat

stimuli and probes, and this complicates the interpretation of probe detection task results. Therefore probe discrimination tasks are advantageous because useful data is collected on each trial and the covariation between the presentation of threat stimuli and probes is eliminated.

The stimuli presented prior to the probes can differ on several characteristics.

These characteristics can potentially affect the reliability of dot probe tasks. One variable is the type of stimulus. Some research using the dot probe paradigm has used pictures of faces or inanimate objects as the stimuli preceding the probes (Bradley,

Mogg, Falla, & Hamilton, 1998; Chen, Ehlers, Clark, & Mansell, 2002; Wilson &

MacLeod, 2003), and other research has used words (Amir, Elias, Klumpp, &

Przeworski, 2003; MacLeod, Mathews, & Tata, 1986; Mogg, Mathews, & Eysenck,

1992). A second variable is the length of time the stimulus is displayed. Stimuli can be presented for a very short duration (e.g., 15 ms), or for much longer (e.g., 1,250 ms). Stimuli that are displayed for a very short duration and are masked are interpreted as being subliminal or processed outside of the participant’s awareness.

Trials in which participants have sufficient time to become aware of the stimulus are called supraliminal. Supraliminal trials may have stimulus durations of 500 ms, 1,250 ms, or more. Another variable is whether the stimuli are masked after presentation.

When words are used as stimuli, a mask would be a string of random letters that is the same length as the word it follows. The onset and duration of mask presentation can also be controlled by the researcher. One more decision that must be made is how many trials the task will contain (e.g., 48, 128, 256, 1000). Because of the many

decisions researchers must make when creating a dot probe task, most programs used in attentional research differ from one another on one or more variables described above. These differences may affect the reliability of each measure. Given how different dot probe tasks can be from one another, the results of studies using dot probe tasks are not completely comparable and methodological differences and limitations must be taken into account when interpreting findings.

The first dot probe paradigm was employed by MacLeod, Mathews, and Tata

(1986) to compare attentional biases between participants with a diagnosis of generalized anxiety disorder (GAD) and non-anxious controls. The probe detection task used 24 physical threat-neutral word pairs, 24 social threat-neutral word pairs, and 240 neutral-neutral word pairs. The program presented each of the 288 word pairs for 500 ms, and dot probes followed a word pair on 96 of the 288 trials. Forty-eight of the 96 dot probes followed a threat-neutral pair, and the remainder of the probes followed neutral-neutral word pairs. Participants were asked read the top word aloud and to push a button when they saw the dot appear after a word pair. Probe detection latencies when probes followed threat words and neutral words were recorded and compared. Faster detection latencies for probes that followed threat words compared to probes that followed neutral words were interpreted as evidence for an attentional bias toward threat. Consistent with their predictions, MacLeod and colleagues found that clinically anxious participants showed a significant pattern of directing their

attention toward threat words. Moreover, they discovered that non-anxious controls displayed an opposite reaction: they tended to direct their attention away from threat words.

MacLeod and colleagues’ findings have been replicated in other samples of

GAD patients (Mogg, Bradley, & Williams, 1995; Mogg, Mathews, & Eysenck, 1992) and in samples of individuals with other anxiety disorders (Asmundson & Stein, 1994;

Tata, Leibowitz, Prunty, Cameron, & Pickering, 1996). Patients diagnosed with obsessive-compulsive disorder completed a probe detection task and demonstrated an attentional bias for contamination threat words, but not social threat words (Tata,

Leibowitz, Prunty, Cameron, & Pickering, 1996). In another study, individuals with social phobia completed a modified probe detection task and showed an attentional bias for social threat words (Amir, Elias, Klumpp, & Przeworski, 2003).

Similar biases in directing attention toward threat have been found when the stimuli preceding probes are faces, rather than words. For example, Bradley, Mogg,

Falla, and Hamilton (1998) used a probe discrimination task in which they presented non-clinical high and low trait anxious participants with pairs of faces. After the faces disappeared, a probe appeared in the same spatial location as one of the faces. Three types of facial expressions were used: neutral, threatening, and happy. The facial stimuli were displayed at both 500 and 1,250 ms durations. Group differences in attentional bias were found for the faces presented for 500 ms. Compared to low trait anxious group, high trait anxious participants showed greater vigilance for threatening faces and greater avoidance of happy faces. Another study presented angry, happy,

and neutral faces to controls and a clinical sample with social phobia, and found a similar pattern of group differences in attentional bias (Mogg, Philippot, & Bradley,

2004). These studies provide evidence that the attentional bias displayed by high anxious participants was specific to threat information and not a response to emotional material in general.

Characteristics of Attentional Threat Bias in Generalized Anxiety

As described above, many published studies report finding an attentional bias toward threat in high anxious and clinical samples. Studies using clinical samples

(e.g., individuals with GAD) typically have found an attentional bias towards threat more often than studies using non-clinical samples (e.g., high trait anxious individuals) (MacLeod, Mathews, & Tata, 1986; Mogg, Bradley, & Williams, 1995).

However, some research using largely clinical samples has found that not all clinically diagnosed participants show an attentional bias toward threatening information

(Mathews, Ridgeway, & Williamson, 1996; Mogg, Millar, & Bradley, 2000; Hazen,

Vasey, & Schmidt, 2001; MacLeod, personal communication, 2003).

It is currently unclear why a number of clinically anxious individuals do not show an attentional bias for threat, or how individuals who do not show the bias are different from those who do. The current study is intended to investigate whether an attentional bias toward threat is characteristic of a sample of chronic worriers, and what variables help predict the degree of attentional bias demonstrated, as measured

by a probe discrimination task. One variable of interest is the reliability of the probe discrimination task over time. Other variables to be explored include clinical status, severity of psychiatric symptomatology, and effortful control of attention.

Psychometrics of attentional bias measures.

Increasing numbers of studies are incorporating dot probe tasks as a measure of attentional bias; however, the reliability of these assessment tools has yet to be clearly established. Vasey, Dalgleish, and Silverman (2003) discuss the importance of establishing sound psychometric qualities of information processing assessment measures. Many studies have used dot probe tasks to assess attentional biases at one point in time and the obtained bias scores are interpreted as representing a stable and valid characteristic of the study participants. Additionally, several studies have employed a dot probe task as an outcome measure after implementing an intervention

(Hazen, et al., 2001; MacLeod, Rutherford, Campbell, Ebsworthy, & Holker, 2002).

In order to accurately understand the meaning of threat bias scores which change after an intervention, it must be established that the threat bias measure has adequate reliability. To date, no research has been published concerning the reliability of attentional threat bias scores in clinically anxious individuals. One published set of studies has investigated the reliability of dot probe threat bias scores in non-anxious individuals; however, there are a number of notable limitations to these studies.

In a series of two studies, Schmukle (2005) investigated internal consistency and retest reliability over a one-week period of attentional bias scores obtained from two versions of a dot probe task, one involving words as stimuli and one using pictures as stimuli. Both studies involved non-clinical samples within a university setting. In Study 1, 40 participants were presented with an original version of the dot probe task and then a modified version of the dot probe task, both using as stimuli threat-neutral and neutral-neutral word pairs. The modified task involved a standard

100ms word pair presentation duration, whereas in the original task the presentation duration varied with the number of syllables. Participants completed these dot probe tasks on two occasions, with a 1-week interval. To investigate internal consistency of his dot probe task, Schmukle computed split-half reliability and Cronbach’s α. Split- half reliability was computed by randomly splitting each dot probe task into two halves, and then attentional bias scores were calculated for each half and correlated to each other. However, one problem with this approach is that he did not appear to take into account the different types of trials when he randomly divided his tasks in half.

Computing bias scores requires reaction time values gathered from four different trial types, and using randomization to divide the task in half may not distribute trials of each type equally across the two halves of the task. This could result in skewed attentional bias scores if only one or two reaction times of one trial type contribute to the attentional bias score of half of the task. Schmukle’s approach to calculating

Cronbach’s α involved dividing the 64 critical trials (i.e., threat-neutral word pair) into

16 groups of 4 trials (quadruplets), with each quadruplet containing one of each of the

4 types of critical trials. An attentional bias score was calculated for each quadruplet, and Cronbach’s α was computed using those 16 attentional bias scores. One problem with this approach is that there is no theoretical reason to pair trials together into quadruplets. Each trial is fairly unique, and attentional bias scores--as they are typically computed--carry meaning because they involve multiple trials of each type averaged together, compared to another group of trials averaged together. Individual trials do not have meaning in and of themselves, and Schmukle’s approach to calculating Cronbach’s α did not appear to take this into account. As calculated by

Schmukle, both the original and modified dot probe task demonstrated poor internal consistency reliability and poor 1-week retest reliability. The author correlated the attentional bias scores with the trait version of the State-Trait Anxiety Inventory

(STAI-T), and only one significant result emerged, a positive correlation between the

STAI-T and the attentional bias score for the modified dot probe task at the second testing session (r = .26, p < .05).

In Study 2 of Schmukle’s (2005) investigation of dot probe task reliability, 40 participants completed a dot probe task using pairs of pictures (threat-neutral and neutral-neutral) as stimuli on two occasions with a 1-week interval. Schmukle found the same pattern of poor internal consistency and poor retest reliability for the pictorial dot probe task as he found in Study 1, and found nonsignificant correlations between the pictorial dot probe task attentional bias scores and the STAI-T.

Schmukle concluded that neither of the dot probe tasks using words as stimuli nor the pictorial dot probe task was internally consistent or stable (Schmukle, 2005).

The results of this study appear to provide preliminary evidence that the attentional bias scores obtained from dot probe tasks may be unreliable. However, aside from problems which exist with the author’s methods of calculating internal consistency, there are several other notable limitations of Schmukle’s studies. First, it is unclear how participants were recruited into the study, and what population the sample was intended to represent (e.g., high trait anxiety, low trait anxiety, a range of trait anxiety levels). Related to this first limitation, Schmukle did not report descriptive statistics for trait anxiety in the Study 2 sample. Second, Schmukle referred to this sample as

“nonclinical;” however, because he does not mention using a clinical interview or other diagnostic tool, it is possible that one or both of his samples did in fact contain individuals with anxiety disorders or other diagnoses. Third, the lack of information about his sample makes restriction of range a potentially serious data analytic problem. If his samples were highly homogenous on one or more variables, this could reduce the variance in his measures and result in inaccurate correlation coefficients.

Fourth, Schmukle referred to one of the dot probe tasks he used as the “original dot probe task” as modeled after MacLeod and colleagues’ (1986) task; however, the

“original dot probe task” used by Schmukle differs on many dimensions from

MacLeod and colleagues’ task (e.g., stimulus presentation duration, word list). In fact, the task as described in Schmukle’s studies differs from many other versions of dot probe tasks used in published studies. Thus Schmukle’s nomenclature of “original dot

probe task” is misleading and inaccurate. In his set of two studies, Schmukle has attempted to provide preliminary data regarding the reliability of dot probe tasks, but it is difficult to fully understand the meaning of his findings given the limitations described above.

If individuals’ threat bias scores vary over time, this variability may account for the lack of attentional threat bias found in some high anxious chronic worriers when they are assessed at only one point in time. However, there are several possible sources of variability in threat bias scores. One possible source is measurement error.

If a measure of attentional threat bias is unreliable at one assessment point in time, then finding no threat bias or a small degree of threat bias in some high anxious individuals may be expected. Another source of bias score variability is instability of the construct of attentional bias. Relatively little is known about the course of attentional bias over time. Perhaps attentional bias is unstable from day to day within individuals. If this were the case, one may not expect to obtain highly correlated bias scores from testing occasions two weeks apart.

Given that bias scores from a PDT rely upon contrasting threat and neutral probe reaction times, it is difficult to establish a PDT’s internal consistency, or reliability during one assessment session. Item-level analysis is impossible for a PDT.

Individual trials of the PDT are meaningless in isolation; trials derive meaning by comparing them with other trials. Average reaction times are calculated for each of the four types of trials: threat word in upper position + probe in upper position; threat word in upper position + probe in lower position; threat word in lower position +

probe in lower position; threat word in lower position + probe in upper position. The average reaction times for these trial types are compared using a difference score calculation which yields an attentional bias index score. Therefore, reaction times from individual trials are not compared to one another because there is no reason to match particular items together. In addition, a given individual is not expected to produce similar reaction times on each trial because of the unique characteristics of each trial type (e.g., locations of threat word and probe). Therefore calculating

Cronbach’s alpha is not a useful procedure because it is not expected that individuals will have similar reaction times on each trial. Unfortunately, the very structure of the

PDT as an assessment tool prevents using ideal methods of examining internal consistency.

Unfortunately, the structure of the PDT prevents a complete distinction between the different sources of variability in bias scores. However, if the results demonstrate that threat bias scores are stable over time and between each session’s two blocks of trials, this would provide some preliminary evidence supporting the reliability of the PDT. Even if the results do not follow this pattern, assessing attentional threat bias over time remains an important and necessary step in the process of establishing the psychometric properties of PDTs.

Clinical status.

Previous research indicates that in many cases having an anxiety disorder diagnosis affects the magnitude of attentional threat bias observed. It is also possible that clinical status affects the relationship between attentional threat bias and worry level. That is, participants’ clinical status may distinguish between those who show an attentional threat bias and those who do not. For example, all participants meeting criteria for generalized anxiety disorder (GAD) could show a strong threat bias, but the chronic worriers not meeting criteria for GAD may not show the same magnitude of bias.

Approximately half of the participants in the Hazen and colleagues (2001) attention retraining study met criteria for GAD, and these clinical participants displayed a wide range of attentional bias levels, including some individuals who showed no bias toward threat. Therefore in that study, clinical status was not a factor that allowed the authors to predict the degree of attentional threat bias observed.

Several published studies have also found inconsistent patterns of attentional threat bias in clinical samples with GAD. Mathews, Ridgeway, and Williamson

(1996) presented anxious (GAD and panic disorder), depressed, and control subjects with a dot probe task using threat-neutral pairs of words as stimuli. The dot probe task included trials of both long and short stimulus duration. The authors found an attentional threat bias in panic disorder patients for trials of both stimulus durations, but patients with GAD demonstrated an attentional bias towards threat only for long

exposure trials. For short exposure trials, the GAD group demonstrated an attentional bias away from threat. This finding of an inconsistent attentional bias towards threat was not consistent with the research literature to that point.

A more recent study also found an absence of attentional threat bias in individuals with GAD when they were presented with a probe detection task using paired pictures of threatening and neutral faces (Mogg, Millar, & Bradley, 2000). In this study, eye movement data and reaction time data were gathered from participants during a probe detection task with a stimulus presentation of 1000 ms. The eye movement data indicated that the individuals with GAD shifted their gaze quickly and frequently to threatening faces compared to neutral faces, which was interpreted by the authors as indicating an attentional bias to threat. However, the reaction time data showed an absence of attentional bias in participants with GAD.

Despite the fact that a majority of studies have found an attentional threat bias in clinical samples of GAD patients, the notable exceptions discussed above have demonstrated that not all individuals with GAD show a strong attentional bias toward threat. It is important not to discount these studies that found an absence of attentional bias because they raise important questions, such as whether the construct of attentional threat bias is unstable or whether the methods used to measure attentional threat bias (e.g., probe discrimination tasks) are unreliable. Alternatively, if some

GAD patients reliably show a bias toward threat but others reliably do not, it would have potentially important implications for understanding the disorder.

Psychiatric symptom severity.

It is possible that the magnitude of attentional threat bias is positively correlated with severity of psychiatric symptoms, such as trait anxiety, state anxiety, social anxiety, and depression. It is also possible that one or more of these types of psychiatric symptomatology affect the relationship between attentional threat bias and worry level. This kind of moderational relationship has not yet been established; therefore, measures of several different types of symptoms will be included in the present study in order to explore the relationships between attentional bias and anxious and depressive symptomatology.

At present, the research evidence is mixed regarding the relationship between depression and attentional threat bias. Despite the fact that clinical levels of anxiety and depression often co-occur, attentional threat bias is not consistently found in clinically depressed samples when dot probe tasks are used (MacLeod, Mathews, &

Tata, 1986; Mathews, Ridgeway, & Williamson, 1996; Mogg, Bradley, & Williams,

1995). A recent review of the literature concluded that attentional biases in depressed individuals are most often found when the stimuli are negative, self-relevant, and presented for longer periods of time to allow elaborative processing (Mogg & Bradley,

2005). Given that attentional bias in depressed individuals is most apparent at long stimulus durations, it seems plausible that level of depression would not influence subliminal trials of a probe discrimination task, as those trials are presented very

briefly. However, supraliminal trials would be more susceptible to being influenced by level of depression because they are presented long enough for individuals to be aware of the content of the stimuli.

As is the case with depression, the research evidence is mixed regarding the relationship of state anxiety and trait anxiety with attentional bias. In a variety of types of dot probe tasks, attentional threat bias has been associated with state anxiety

(Bradley, Mogg, & Millar, 2000; Mogg, Bradley, De Bono, & Painter, 1997), with trait anxiety (Koster, Verschuere, Crombez, & Van Damme, 2005), and with an interaction of state and trait anxiety (MacLeod & Mathews, 1988; Mogg, Bradley, &

Hallowell, 1994). Given these mixed results, it was unclear what would be found in the present study regarding the relationship of attentional bias with state anxiety and trait anxiety.

Attentional and effortful control.

Another variable that may relate to the presence or absence of an attentional threat bias is the ability to regulate attention and emotionality. Attentional control has been defined as the abilities to focus attention, shift attention, and flexibly control thought (Derryberry & Reed, 2002). Individual differences exist in level of attentional control, and possibly may explain the absence of attentional threat bias, as measured by a dot probe task. If individuals high in attentional control are given a long stimulus presentation or a long delay after being presented with threatening information, they may be able to shift attention away from the threatening stimulus. Therefore, these

individuals would appear to have a minimal or nonexistent bias toward threatening information. The probe discrimination task in the current study will include some trials with a very short stimulus presentation (subliminal trials) and some with a longer presentation (supraliminal trials). A short stimulus duration is included to attempt to measure a bias that may exist before an individual can control his or her attention and possibly direct it away from threatening content. A long stimulus duration is included so that bias scores may be compared between the two presentation conditions. The role of attentional control in attentional threat bias can be evaluated by comparing self- reported attentional control with bias scores obtained from supraliminal trials and subliminal trials.

Derryberry and Reed (2002) examined the relationship between attentional control and attentional bias using a spatial orienting task, which measures attentional bias but uses a different paradigm than dot probe tasks. In the spatial orienting task, high and low trait anxious participants engaged in a motivated game in which they lost or gained points based on their response speed to detecting targets. Participants were presented with a cue, and after a delay of either 250 or 500 ms, a target was presented to which participants responded by pressing a button. As predicted, the authors found that high anxious participants showed a stronger attentional bias in orienting to threat cues at the short delays, compared to the low anxious group. Additionally, attentional control was found to moderate the anxiety-related threat bias for stimuli presented for

500 ms. That is, participants low in attentional control maintained their bias toward threat at longer delays, but participants high in attentional control appeared better able

to shift attention away from the location of threatening information (Derryberry &

Reed, 2002). The current study seeks to replicate this finding using a probe discrimination task that includes both long and short stimulus durations.

Effortful control has been defined as the ability to self-regulate positive and negative emotionality. One way individuals may regulate emotionality is through attention to information in the environment. Effortful control is believed to develop during childhood, and children high in emotional control may be able to use attentional resources to restrict overly reactive emotional responses to stimuli

(Derryberry & Reed, 2002). In a study of children, effortful control was found to significantly moderate the relationship between anxiety and attentional bias (Vasey,

Dalgleish, & Silverman, 2003). Adult studies suggest that individuals low in effortful control react to threatening situations by narrowly focusing attention and being slow to shift attention away from threatening signals (Derryberry & Rothbart, 1997). Higher levels of effortful control appear to enable greater control of attention and less anxiety

(Derryberry & Rothbart, 1988, 1997).

Current Study

The present investigation was intended to investigate whether attentional threat bias is a hallmark (i.e., consistent indicator) of generalized anxiety disorder (GAD).

The current study identified college students who experience high levels of worry, and recruited those students as well as a smaller group of students who had lower levels of worry. At two experimental sessions spaced two weeks apart, participants completed

a probe discrimination task (PDT) and several questionnaires. They also completed a clinical interview at the first session. This study has attempted to fill several gaps in the research literature concerning attentional threat biases. One goal of this study was to replicate previous findings that not all chronic worriers show an attentional bias toward threat. The current study was intended to demonstrate the measurement of a reliable threat bias score that can be used in future studies of change. Once this reliable threat bias index has been established, we intended to use it to examine the correlates of the attentional bias. Possible correlates measured in this study were several psychological variables, including clinical status, worry, social anxiety, depression, and the ability to control one’s attention. If attentional threat bias is not found to be a hallmark of GAD, exploring the relationship of attentional bias with other constructs would allow us to better understand what factors may predict attentional bias towards threat.

Hypotheses

1. This study will replicate previous findings that individuals high in chronic worry will vary widely in attentional bias scores. This wide range of scores will include some scores of zero (indicating no bias), as well as bias towards threat and bias away from threat.

2. Individuals reporting higher levels of worry will show greater attentional bias scores.

2 4

3. Attentional control will moderate the relationship between worry and attentional bias scores for supraliminal trials.

4. Attentional control will be unrelated to attentional bias scores for subliminal trials.

5. Several psychological factors, such as clinical status, depression, and social anxiety, will moderate the relationship between worry and attentional bias.

6. The PDT attentional bias scores will demonstrate adequate reliability (e.g., r = 0.6) between sessions and between the two tasks within each session.

CHAPTER 2

METHOD

Participants

Undergraduate students enrolled in an introductory psychology course at a large midwestern university were screened for their level of worry using a prescreening questionnaire, the Penn State Worry Questionnaire (PSWQ).

Recruitment focused on students scoring at or above a cutoff score of 65. This cutoff score is 1.5 standard deviations above published mean scores for college students

(Meyer, Miller, Metzger, & Borkovec, 1990). A primary enrollment goal was to recruit 80 individuals who showed stable high scores on the PSWQ (i.e., score at or above 65 at prescreening and at Time 1), but I also planned to recruit 40 participants who showed lower scores on the PSWQ. This second group of participants was included in the study to enhance my statistical evaluation of the reliability of the PDT.

All students scoring above the cutoff score were contacted by phone or email by a researcher. The remaining students who were prescreened and who scored below the

cutoff score at prescreening were randomly selected and contacted by a researcher.

Individuals who had no serious and uncorrected visual impairments were invited to participate in the study.

No Axis I diagnosis was required to participate in the study, but after informed consent was obtained, the Structured Clinical Interview for DSM-IV (SCID-IV; First,

Spitzer, Gibbon, & Williams, 1994) was administered to establish DSM-IV diagnoses.

SCID interviews were conducted by a doctoral student in clinical psychology who has received extensive training in SCID administration and scoring.

One hundred thirty individuals, 39 men and 91 women, signed consent forms for this study. Three participants were excluded from the data analysis, one for noncompletion of the second experimental session, one for a malfunction of the computerized PDT, and one for large amounts of missing data on the self-report measures. A total of 127 participants’ data were included in the analyses. These participants’ ages ranged from 18 to 32 years (M = 19.6, SD = 2.4). Participants were primarily Caucasian (82%) and female (70%). Complete participant demographics are presented in Table 1.

Materials

The probe discrimination task (PDT) words were predominantly drawn from previous research into attentional biases in anxiety. Ninety-six pairs of threat and neutral words from a previous study were used (MacLeod, Rutherford, Campbell,

Ebsworthy, & Holker, 2002), and an additional 8 threat words and 56 neutral words

GAD Diagnostic Status

GAD No GAD Total Variable (N = 29) (N = 98) (N = 127) Age Mean 19.9 19.5 19.6 SD 2.9 2.2 2.4 Female Gender 24 (82.8%) 65 (66.3%) 89 (70.1%) Ethnicity White 25 (86.2%) 79 (80.6%) 104 (81.9%) Black 3 (10.3%) 10 (10.2%) 13 (10.2%) Hispanic 0 (0%) 2 (2.0%) 2 (1.6%) Asian 0 (0%) 7 (7.1%) 7 (5.5%) Information omitted 1 (3.5%) 0 (0%) 1 (0.8%) Marital Status Never married 27 (93.1%) 93 (94.9%) 120 (94.5%) Married 0 (0%) 3 (3.1%) 3 (2.4%) Divorced 1 (3.5%) 0 (0%) 1 (0.8%) Information omitted 1 (3.5%) 2 (2.0%) 3 (2.4%) Employment status Employed 4 (13.8%) 11 (11.2%) 15 (11.8%) Student 25 (86.2%) 87 (88.8%) 112 (88.2%)

Table 1. Participant demographics by GAD diagnostic status.

were selected from a set of words which had been rated for threat value in another study. The PDT words therefore consisted of a total of 104 threat words and 152 neutral words. These words were divided into 104 threat-neutral word pairs and 24 neutral-neutral word pairs, resulting in a total of 128 word pairs. Each pair of words was matched for word length and frequency (Kucera & Francis, 1967). The word pairs were presented either supraliminally (500 ms) or subliminally (14 ms, equal to one refresh cycle of the computer monitor). Word pairs presented subliminally were followed immediately by a mask of random letters (14 ms). On these trials, the probe followed the offset of the mask by 14 ms. In the supraliminal condition, the word pairs were not masked and the probe followed the offset of the word pair by 14 ms.

During the PDT session, each word pair was presented to participants twice, once in the subliminal condition and once in the supraliminal condition. A recent study investigated how repeated exposure to the same threatening pictorial stimuli affected attentional threat bias (Liu, Qian, Zhou, & Wang, 2006). The authors employed a probe discrimination task using pairs of threatening and neutral pictures, and they found that high trait anxious individuals displayed attentional bias towards threat for the first three out of the four times they were exposed to each block of stimuli. These results of Liu and colleagues (2006) provide preliminary evidence that repeating stimuli twice in a dot probe task is unlikely to attenuate attentional threat bias.

In the current study, each PDT session consisted of participants being presented with 256 word pairs, divided into two blocks of 128 trials. Each block contained 64 different word pairs, 52 threat-neutral word pairs and 12 neutral-neutral

word pairs; each word pair was presented twice. Within each block, the word pairs were presented in an individually randomized order. Thus the supraliminal and subliminal trials were interspersed.

The presentation of the two blocks of lists was counterbalanced across participants, and this created two presentation orders: List 1 followed by List 2 (Word

List Order 1), and List 2 followed by List 1 (Word List Order 2). Participants were randomly assigned to one of the two word list orders, and they received the same word list order at Time 1 and Time 2. For data analysis purposes, the word list a participant encounters first during the PDT will be considered Task 1, and the word list encountered second will be considered Task 2.

An awareness check followed the completion of Task 2 of the PDT.

Participants were presented with a pair of either words or strings of random letters; they were immediately masked by another string of random letters. Participants were asked to indicate whether they saw a word or random letters before the random letters appeared. If participants were unaware of the presence of the word stimuli, their performance should not exceed chance levels. Therefore, scores of approximately 50 percent correct on the awareness check are expected. According to a binomial distribution, the 95 percent confidence interval around 50 percent is 36-64 percent.

PDT subliminal trial data from participants who scored above 64 percent correct were excluded from analysis, because scores significantly above chance indicate that the subliminal trials were not truly outside of those individuals’ awareness.

Procedures

This study involved a total of two sessions. The first session lasted approximately 1.5 hours and the second session lasted approximately 1 hour. During the first session (Time 1), participants completed the PDT on the computer, followed by the awareness check. They then completed self-report questionnaires assessing their degree of anxiety, worry, depression, and attentional control. Finally, a structured interview was administered to assess the presence of current or past psychiatric diagnoses. The second session (Time 2) consisted of completing the PDT, awareness check, and the same self-report questionnaires. The two sessions were intended to be spaced 14 days apart, and the study was successful at achieving this time period between sessions (M = 14.0, SD = 0.9, range: 10-17).

Probe discrimination task (PDT).

In the supraliminal condition of the probe discrimination task, each trial began with the display of a fixation cross at the center of the screen for 500 ms. A word pair was then displayed in uppercase for 500 ms, with one word above the central fixation point and the other word below. The distance between the center of the words was 3 cm. Fourteen ms after the word pair disappeared from the screen, a dot probe appeared where one of the words had been. The probe remained on the screen until the participant responded by pushing one of two buttons to indicate whether the probe replaced the top or bottom word of the pair.

In the subliminal condition, the central fixation cross was followed by a word pair. The word pair was presented in uppercase for 14 ms. Fourteen ms after the word pair disappeared from the screen, a pair of random letter masks (e.g., GXIDNE) replaced the word pair. The masks were matched for length of the preceding words.

The masks were presented for 14 ms, and 14 ms after their removal a dot probe appeared in the position of one of the masks. The probe remained on the screen until the participant responded by pushing one of the buttons to indicate the location of the probe.

In both subliminal and supraliminal conditions, the threat stimulus words appeared in the upper and lower position with equal probability. The probe was also displayed in either position with equal probability. Participants were asked to focus on the cross at the center of the screen at the start of each trial and to press one of two buttons when they saw a small dot appear after the words. Participants completed several practice trials before beginning the main attentional task.

Measures

The assessment battery included the following measures of anxiety, depression, worry, attentional control, and effortful control. All measures except the

SCID-IV were administered at both assessment periods, and in an individually randomized order.

Penn State Worry Questionnaire (PSWQ; Meyer et al., 1990). The PSWQ consists of

16 items rated on a 5-point Likert scale, and yields a single score assessing a person’s tendency to worry. This measure has demonstrated good internal consistency (α =

0.93) and high test-retest reliability (r = 0.75) (Meyer, Miller, Metzger, & Borkovec,

1990). The PSWQ has been shown to have excellent psychometric properties in both clinical and nonclinical populations (for a review, see Molina & Borkovec, 1994).

State-Trait Anxiety Inventory (STAI; Spielberger, 1983). This measure includes state and trait anxiety forms (STAI-S and STAI-T), which assess the participant’s current state anxiety and stable tendency to react to life in anxious ways, respectively. Each scale consists of 20 items rated on a 4-point Likert scale. The STAI-T is a very widely used measure of trait anxiety and has demonstrated high test-retest reliabilities, ranging from 0.73-0.86. The STAI-T has high discriminant validity, and concurrent validity with other anxiety measures has ranged from 0.73-0.85 (Spielberger, 1983).

Beck Anxiety Inventory (BAI; Beck et al., 1988). The BAI consists of 21 items rated on a 4-point Likert scale, and is intended to assess the severity of anxiety in psychiatric populations. It has been widely used and demonstrates good psychometric properties. The BAI has demonstrated good internal consistency (α = 0.92) and high

1-week test-retest reliability (r = 0.75). In addition, evidence indicates the BAI has discriminant validity for distinguishing between anxious and nonanxious diagnostic groups (Beck, Epstein, Brown, & Steer, 1988).

Social Phobia Scale (SPS; Mattick & Clarke, 1998). The SPS consists of 20 items rated on a 5-point Likert scale, and it measures fears of being scrutinized or observed by others. Evidence has accumulated that the SPS is a reliable and valid instrument.

Internal consistency estimates with nonclinical and anxious individuals range from

0.87-0.94 (Heimberg, Mueller, Holt, Hope, & Liebowitz, 1992; Mattick & Clarke,

1998). Test-retest reliability coefficients of the SPS exceeded 0.90 for both 1 and 3 month intervals (Mattick & Clarke, 1998). The SPS was found to discriminate between clinical groups and between social phobic patients and normal samples

(Mattick & Clarke, 1998).

Beck Depression Inventory - II (BDI-II; Beck, Steer, & Brown, 1996). 21 items rated on a 4-point Likert scale. The BDI-II will evaluate level of depressive symptoms.

The BDI-II has demonstrated excellent internal consistency (α = 0.92) and 1-week test-retest reliability (r = 0.93). In addition, the BDI-II has been shown to have discriminant validity in distinguishing between depression and anxiety (Beck, Steer, &

Brown, 1996).

Attentional Control Scale (ACS; Derryberry & Reed, 2002). 20 items rated on a 4- point Likert scale. The ACS is a measure of attentional control, including the abilities

of focusing attention, shifting attention between tasks, and flexibly controlling thought. The ACS is a recently developed measure and its psychometric properties have not been published.

Effortful Control Scale (EC; Lonigan, Vasey, Phillips, & Hazen, 2004). 46 items rated on a 5-point Likert scale. The EC is a measure of self-regulation of positive and negative emotionality. In a factor analytic study conducted on data from children, the

EC was comprised of two subscales, “Distraction and Persistence” (EC-DP) and

“Impulsivity,” and several additional items not loading on these two scales (Lonigan,

Vasey, Phillips, & Hazen, 2004). The factor structure of the EC in adults is unknown, and the psychometric properties of the EC have not been established. Because the

Distraction and Persistence subscale (EC-DP) has been used in the research to date, this subscale was used in the present analyses.

Structured Clinical Interview for DSM-IV (SCID-IV; First et al., 1994). The SCID is a diagnostic instrument that assesses DSM-IV diagnostic criteria for Axis I disorders.

The SCID interview was conducted during the Time 1 session of the study to assess current psychiatric diagnoses.

Data Analysis

Participant characteristics.

Descriptive statistics were calculated for participants’ demographic variables and self-report measure scores. The frequency and type of DSM-IV psychiatric diagnoses were examined.

Participants were assigned to one of three groups based on their PSWQ score pattern from Prescreening to Time 1. The grouping focused on whether a participant’s scores were above or below the prescreening cutoff score of 65. Grouping participants based on their PSWQ score pattern resulted in the following groups: Group 1 (Stable

High PSWQ group; n = 54) had scores at or above prescreening cutoff at Prescreening and Time 1; Group 2 (Stable Low PSWQ group; n = 33) had scores below prescreening cutoff at Prescreening and Time 1; and Group 3 (Unstable PSWQ group; n = 40) had either (a) a Prescreening score at or above the cutoff and Time 1 score below the cutoff, or (b) a Prescreening score below the cutoff and Time 1 score at or above the cutoff. Groups 1 and 2 were considered “stable” scorers on the PSWQ, whereas Group 3 was considered “unstable” scorers. T-tests and chi-square analyses were conducted on participants’ demographic variables and self-report measure scores to examine any group differences based on DSM-IV diagnosis and PSWQ scoring pattern.

Based on DSM-IV diagnosis and worry pattern (PSWQ scores), comparisons between two sets of groups were made in further analyses. One set of comparisons was between individuals in the Stable High PSWQ group and Stable Low PSWQ

group. These comparisons were included because they focused on the variable by which participants were recruited into the study: the PSWQ. However, because the

Stable High PSWQ group included approximately equal numbers of individuals with and without GAD, another set of comparisons was made in an effort to isolate the effect of the clinical diagnosis of GAD. Therefore, another grouping compared participants with GAD (n = 29) to participants in the Stable Low PSWQ group who did not have GAD (n = 32). This comparison was intended to achieve the most contrasting groups possible within this dataset.

PDT word list order groups.

T-tests and chi-square analyses were conducted on participants’ demographic variables and self-report measure scores to examine any group differences based on random assignment to PDT word list presentation order.

PDT data.

Trials on which probe discrimination errors were made were excluded from analysis. To eliminate extreme outliers, all reaction times less than or equal to 150 ms, or greater than or equal to 1250 ms, were excluded from further analysis. Next, individual outliers were identified as RTs greater than 2 standard deviations from the individual’s mean RT for that trial type (e.g., Threat upper, Probe upper,

Supraliminal). These individual outliers were excluded from analysis. This approach

to eliminating outliers follows previous research in this area (Chen, Ehlers, Clark, &

Mansell, 2002; Mogg, Bradley, & Williams, 1995; Mogg, Millar, & Bradley, 2000).

Response latencies to the PDT trials were averaged within each trial type, and attentional threat bias scores were calculated from the RT data. The attentional bias scores were subjected to repeated measures ANOVAs. Group differences in reaction times (RTs) and attentional bias scores were investigated by examining the between subjects effects of DSM-IV diagnosis, PSWQ scoring pattern, and PDT word list order. When interactions involving two or three factors were found, I explored them further using simple main effects tests and reported these results in the text. Because interactions involving four or more factors are much more complex, I did not conduct simple main effects tests for those interactions.

Reliability of RTs and attentional bias scores.

Test-retest reliabilities of the reaction times from the PDT were calculated.

Test-retest reliabilities of the attentional threat bias scores were calculated.

Attentional bias scores obtained from each of the two tasks at Time 1 and Time 2 were compared to evaluate possible effects of time or fatigue within each assessment session.

Relationship of attentional bias to other constructs.

T-tests were used to compare attentional bias scores of participants with stable high versus stable low PSWQ scores. T-tests were also used to compare the GAD

group to the stable low PSWQ group without GAD. I calculated correlations between the self-report measures and the subliminal and supraliminal attentional bias scores obtained from the PDT.

Regression analyses were conducted to investigate whether clinical status, depression, attentional control, effortful control, or several types of anxiety, including state anxiety, trait anxiety, and social anxiety, acted as moderators of the relationship between worry and attentional bias. PSWQ score, representing the construct of worry, was entered on the first step in each moderation analysis. The potential moderator variable was entered on the second step, and on the third step the interaction between the PSWQ and moderator variable was entered.

Self-report measure correlations.

Correlations between the self-report measures at Time and Time 2 were calculated to examine test-retest reliability of each measure as well as the nature of each measure’s relationship with the other measures. Because the self-report measures were highly correlated at Time 1 and Time 2 (i.e., high test-rest reliability), the self-report measure scores were averaged across the two experimental sessions.

These aggregate self-report scores were utilized in most analyses involving these measures.

CHAPTER 3

RESULTS

Participant Characteristics

DSM-IV diagnostic status.

Fifty-four of the 127 participants met criteria for at least one current DSM-IV diagnosis. Of the 54 participants with a DSM-IV diagnosis, 51 participants met criteria for at least one anxiety disorder. Twenty-nine participants met criteria for generalized anxiety disorder (GAD). Of the 29 participants with GAD, 8 had comorbid diagnoses of other anxiety disorders (2 had social phobia, 2 had specific phobia, 2 had both social phobia and panic disorder, 1 had both social phobia and specific phobia, and 1 had specific phobia and obsessive-compulsive disorder), 2 had comorbid diagnoses of major depressive disorder and another anxiety disorder, and 2 had comorbid diagnoses of major depression only. The frequencies of current DSM-

IV diagnoses among the sample are presented in Tables 2 and 3.

Chi-square analyses revealed that participants with and without an anxiety disorder diagnosis did not differ significantly on any of the demographic variables measured in this study, including age, gender, ethnicity, marital status, and employment status. Of particular interest in this study is the GAD diagnosis, so

Frequency as Frequency as Total Current Axis I DSM-IV Primary Non-Primary Frequency Diagnosis Diagnosis Diagnosis of Diagnosis GAD 28 1 29 Panic Disorder 2 2 4 Social Phobia 11 6 17 Specific Phobia 7 5 12 Posttraumatic Stress Disorder 1 0 1 Obsessive-Compulsive Disorder 0 1 1 Major Depressive Disorder 2 3 5 Dysthymic Disorder 1 1 2 Alcohol Abuse 0 1 1 Alcohol Dependence 2 0 2

Table 2. Frequency of DSM-IV diagnoses as primary or non-primary diagnoses.

Number of Diagnoses Per Participant Frequency 0 73 1 41 2 8 3 4 4 0 5 1

Table 3. Frequency of current DSM-IV diagnoses per participant.

chi-square analyses were conducted on the demographic variables listed above to investigate group differences. These analyses indicated that participants with and without a diagnosis of GAD did not differ significantly on any of the demographic variables.

T-tests conducted on the aggregate self-report measures revealed a number of significant differences between participants with and without an anxiety disorder diagnosis. Compared to participants without an anxiety disorder, participants with an anxiety disorder scored significantly higher on the PSWQ, STAI-T, STAI-S, BAI,

BDI-II, and SPS (all p < .01). Higher scores on these measures indicate greater or more severe self-reported symptomatology. Compared to participants with an anxiety disorder, participants without an anxiety disorder scored significantly higher on the

ACS and EC-DP (both p < .01). Higher scores on these measures indicate greater levels of attentional or effortful control.

A similar pattern of results was found when t-tests were conducted on the aggregate self-report measures, comparing participants with GAD to participants in the Stable Low PSWQ group without GAD. The results of these t-tests are presented in Table 4. The observed power of these t-tests ranged from 0.97 to 1. Participants with GAD scored significantly higher on the self-report measures of symptomatology, while participants in the Stable Low PSWQ group without GAD scored significantly higher on self-report measures of attentional control and effortful control.

Stable Low PSWQ GAD + No GAD (N = 29) (N = 32) Measure Mean (SD) Mean (SD) PSWQ** 69.6 (5.6) 39.7 (11.0) STAI-T** 55.8 (7.5) 37.5 (8.0) STAI-S** 49.1 (11.0) 34.3 (10.1) BAI** 20.5 (9.9) 8.8 (8.2) BDI-II** 20.3 (10.9) 6.1 (5.3) SPS** 27.8 (16.7) 11.7 (9.5) ACS** 41.9 (8.0) 53.6 (7.6) EC-DP** 38.1 (7.8) 45.5 (7.2) Probability notes indicate significance of independent samples t-tests. ACS = Attentional Control Scale; BAI = Beck Anxiety Inventory; BDI-II = Beck Depression Inventory-II; EC-DP = Effortful Control Scale, Distraction & Persistence Subscale; PSWQ = Penn State Worry Questionnaire; SPS = Social Phobia Scale; STAI-S = State-Trait Anxiety Inventory, State version; STAI-T = State-Trait Anxiety Inventory, Trait version. ** p < .01.

Table 4. Means and standard deviations of aggregate self-report measure scores of participants with GAD and participants in the Stable Low PSWQ group without GAD.

PSWQ scoring patterns.

Participants were grouped into three groups based on their PSWQ score pattern from Prescreening to Time 1. The grouping focused on whether a participant’s scores were above or below the prescreening cutoff score of 65. Individual participants’

PSWQ scores from Prescreening to Time 1 are shown in Figure 1. Grouping participants based on their PSWQ score pattern resulted in the following groups:

Group 1 (Stable High PSWQ; n = 54) had scores at or above prescreening cutoff at

Prescreening and Time 1; Group 2 (Stable Low PSWQ; n = 33) had scores below prescreening cutoff at Prescreening and Time 1; and Group 3 (Unstable PSWQ; n =

40) had either (a) a Prescreening score at or above the cutoff and Time 1 score below the cutoff, or (b) a Prescreening score below the cutoff and Time 1 score at or above the cutoff. Groups 1 and 2 were considered “stable” scorers on the PSWQ, whereas

Group 3 was considered “unstable” scorers. Further analyses in which PSWQ scoring pattern was a factor focused primarily on Groups 1 and 2. The distribution of primary

DSM-IV diagnoses across the three PSWQ groups is shown in Table 5.

T-tests were conducted on the self-report measures to examine differences between participants in the two stable groups: Group 1 (Stable High PSWQ) and

Group 2 (Stable Low PSWQ). The results of these t-tests are presented in Table 6 and indicate many significant differences between the groups. The observed power of these t-tests ranged from 0.77 to 1. The results follow a similar pattern to the anxiety

40 PSWQTotal Scores

Prescreening Time 1 Assessment Point

Figure 1. Participants’ PSWQ total score patterns from Prescreening to Time 1. Each line represents one participant.

PSWQ scoring patterns Stable High Stable Low Unstable Current Axis I DSM-IV PSWQ PSWQ PSWQ Diagnosis (n = 54) (n = 33) (n = 40) GAD 24 1 4 Panic Disorder 2 0 0 Social Phobia 6 1 4 Specific Phobia 1 3 3 Posttraumatic Stress Disorder 0 0 1 Major Depressive Disorder 1 0 0 Dysthymic Disorder 0 0 1 Alcohol Dependence 0 2 0

Table 5. Frequency of current primary DSM-IV diagnoses across PSWQ scoring patterns.

Stable High PSWQ Stable Low PSWQ

(N = 54) (N = 33) Measure Mean (SD) Mean (SD) PSWQ** 70.1 (5.2) 40.2 (11.3) STAI-T** 53.5 (7.9) 38.0 (8.5) STAI-S** 47.8 (10.9) 35.0 (10.7) BAI** 19.6 (10.8) 9.3 (8.5) BDI-II** 16.4 (10.5) 6.9 (6.9) SPS** 28.3 (15.3) 12.7 (11.1) ACS** 42.7 (8.1) 53.1 (8.0) EC-DP** 40.6 (7.0) 45.0 (7.5) Probability notes indicate significance of independent samples t-tests. ACS = Attentional Control Scale; BAI = Beck Anxiety Inventory; BDI-II = Beck Depression Inventory-II; EC-DP = Effortful Control Scale, Distraction & Persistence Subscale; PSWQ = Penn State Worry Questionnaire; SPS = Social Phobia Scale; STAI-S = State-Trait Anxiety Inventory, State version; STAI-T = State-Trait Anxiety Inventory, Trait version. ** p < .01.

Table 6. Means and standard deviations of aggregate self-report measures by PSWQ scoring pattern.

disorder group differences, in that the Stable High PSWQ group scored higher on measures of psychiatric symptomatology, while the Stable Low PSWQ group scored higher on measures of attentional control and effortful control.

Of the 54 participants in the Stable High PSWQ group, 24 participants met criteria for GAD and 30 participants did not. Additional t-tests were conducted on the self-report measures to examine differences between participants in this Stable High

PSWQ group with and without GAD. The results of these t-tests are presented in

Table 7 and revealed only one significant difference between the groups: participants in the Stable High PSWQ group with GAD scored significantly higher on the BDI-II than participants in the Stable High PSWQ group without GAD. However, the observed power of these t-tests was generally low, ranging from 0.05 to 0.42.

PDT Word List Order Groups.

Chi-square analyses revealed that participants receiving the two PDT word list orders did not differ significantly on GAD diagnostic status or any of the demographic variables measured in this study, including age, gender, ethnicity, marital status, employment status. Of the 29 participants with a diagnosis of GAD, 18 (62%) were assigned to Word List Order 1 on the PDT, and 11 (38%) were assigned to Word List

Order 2. Of the 98 participants without GAD, 50 (51%) were assigned to Word List

Order 1 on the PDT, and 48 (49%) were assigned to Word List Order 2. Of the 54 participants in the Stable High PSWQ group, 34 (63%) were assigned to Word List

Stable High PSWQ Stable High PSWQ + GAD + no GAD (N = 24) (N = 30) Measure Mean (SD) Mean (SD) PSWQ 70.5 (5.4) 69.8 (5.1) STAI-T 55.5 (8.1) 51.8 (7.4) STAI-S 48.8 (10.9) 46.9 (10.9) BAI 20.3 (10.6) 19.0 (11.1) BDI-II* 19.6 (11.7) 13.9 (8.9) SPS 26.6 (17.8) 29.7 (13.1) ACS 42.7 (7.8) 42.6 (8.4) EC-DP 39.2 (7.7) 41.7 (6.3) Probability notes indicate significance of independent samples t-tests. ACS = Attentional Control Scale; BAI = Beck Anxiety Inventory; BDI-II = Beck Depression Inventory-II; EC-DP = Effortful Control Scale, Distraction & Persistence Subscale; PSWQ = Penn State Worry Questionnaire; SPS = Social Phobia Scale; STAI-S = State-Trait Anxiety Inventory, State version; STAI-T = State-Trait Anxiety Inventory, Trait version. * p < .05.

Table 7. Means and standard deviations of aggregate self-report measures for participants with and without GAD in the Stable High PSWQ group.

Order 1 on the PDT, and 20 (37%) were assigned to Word List Order 2. Of the 33 participants in the Stable Low PSWQ group, 14 (42%) were assigned to Word List

Order 1 on the PDT, and 19 (58%) were assigned to Word List Order 2.

A series of t-tests conducted on the self-report measures revealed several significant differences between participants receiving the two PDT word list orders.

The results of these t-tests are presented in Table 8. The observed power of these t- tests was variable, ranging from 0.05 to 0.93. Compared to participants who received

Word List Order 2, participants who received Word List Order 1 scored significantly higher on the PSWQ, STAI-T, STAI-S, BAI, and BDI-II. There were no significant group differences on the other self-report meaures. Thus, random assignment to the two PDT word list orders resulted in two conditions of equivalent status on demographic variables, but not on the self-report measures.

Probe Discrimination Task (PDT)

Awareness check.

For the awareness check task following the PDT, the percentage of trials with correct responses was calculated for each participant at Time 1 and Time 2. Each participant’s percentage correct scores were evaluated to determine if their ability to detect the presence of words versus random letters was not significantly better than chance (i.e., 50 percent). No participants obtained scores at both time points that were significantly higher than 50 percent. The mean awareness check correct percentage at

Time 1 was 50.1 percent (SD = 7.7), and at Time 2 was 49.4 percent (SD = 7.8).

Order 1 Order 2

(N = 68) (N = 59) Measure Mean (SD) Mean (SD) PSWQ* 61.4 (13.3) 55.2 (15.7) STAI-T* 49.5 (9.6) 45.6 (10.2) STAI-S** 45.7 (11.3) 38.7 (11.7) BAI* 17.2 (11.0) 12.4 (9.8) BDI-II* 14.1 (10.4) 10.6 (8.3) SPS 24.7 (16.3) 21.4 (14.1) ACS 45.9 (7.8) 47.8 (10.5) EC-DP 42.1 (6.8) 42.3 (7.8) Probability notes indicate significance of independent samples t-tests. ACS = Attentional Control Scale; BAI = Beck Anxiety Inventory; BDI-II = Beck Depression Inventory-II; EC-DP = Effortful Control Scale, Distraction & Persistence Subscale; PSWQ = Penn State Worry Questionnaire; SPS = Social Phobia Scale; STAI-S = State-Trait Anxiety Inventory, State version; STAI-T = State-Trait Anxiety Inventory, Trait version. * p < .05. ** p < .01.

Table 8. Means and standard deviations of aggregate self-report measures by PDT Word List Order.

These values fell within the 95 percent confidence limits of chance level of performance (range 36-64 percent). No participant scored consistently and significantly better than chance; therefore, no data were excluded from further analyses as a result of the awareness check task.

Preparation of reaction time (RT) data.

Trials on which probe discrimination errors were made were excluded from analysis. First, to eliminate extreme outliers, all reaction times less than or equal to

150 ms, or greater than or equal to 1250 ms, were excluded from further analysis.

Next, individual outliers were identified as RTs greater than 2 standard deviations from the individual’s mean RT for that trial type (e.g., Threat upper, Probe upper,

Supraliminal). These individual outliers were then excluded from analysis. Errors and outliers accounted for 4.8% of the data.

RT means and correlations.

Mean RTs1 for each trial type are presented in Tables 9 and 10 and are grouped by GAD-Worry group (GAD vs. Stable Low PSWQ without GAD) and PSWQ scoring pattern (Stable High PSWQ group vs. Stable Low PSWQ group). Average

RTs for each task (1 vs. 2) at both of the sessions (1 vs. 2) and at both presentation durations (subliminal vs. supraliminal) were calculated, collapsed across trial

1 Some studies utilizing dot probe tasks have used median reaction times (RTs) instead of mean RTs because median scores are less influenced by outliers. Several analyses were conducted using median RTs to investigate whether the results differed from those obtained using mean RTs. The pattern of the results was not different using the median RTs; therefore, mean RTs were used in this study as planned. 52

Stable Lower GAD PSWQ + No GAD (N = 29) (N = 32) Threat Probe Mean (SD) Mean (SD) location location Supraliminal Time 1 Upper Upper 479 (62) 469 (58) Upper Lower 471 (62) 469 (62) Lower Upper 480 (68) 475 (59) Lower Lower 473 (64) 470 (57) Time 2 Upper Upper 451 (66) 451 (60) Upper Lower 443 (68) 441 (56) Lower Upper 455 (70) 451 (58) Lower Lower 443 (66) 446 (55)

Subliminal Time 1 Upper Upper 498 (59) 500 (57) Upper Lower 483 (56) 484 (54) Lower Upper 502 (56) 499 (54) Lower Lower 481 (52) 488 (58) Time 2 Upper Upper 471 (55) 472 (51) Upper Lower 453 (62) 457 (53) Lower Upper 474 (65) 470 (53) Lower Lower 457 (61) 454 (51)

Table 9. Mean reaction times (ms) for threat-neutral word pairs of participants with GAD and participants in the Stable Low PSWQ group without GAD.

High PSWQ Lower PSWQ (N = 54) (N = 33) Threat Probe Mean (SD) Mean (SD) location location Supraliminal Time 1 Upper Upper 481 (63) 467 (58) Upper Lower 473 (64) 466 (63) Lower Upper 486 (65) 472 (60) Lower Lower 474 (61) 468 (58) Time 2 Upper Upper 446 (62) 449 (61) Upper Lower 437 (60) 438 (57) Lower Upper 450 (62) 448 (59) Lower Lower 435 (60) 443 (56)

Subliminal Time 1 Upper Upper 499 (60) 497 (58) Upper Lower 481 (60) 482 (55) Lower Upper 500 (65) 498 (53) Lower Lower 482 (60) 485 (59) Time 2 Upper Upper 463 (54) 469 (53) Upper Lower 447 (61) 454 (56) Lower Upper 468 (60) 467 (55) Lower Lower 446 (58) 452 (53)

Table 10. Mean reaction times (ms) for threat-neutral word pairs, by PSWQ scoring pattern.

characteristics (i.e., threat location, probe location). This calculation resulted in 8 mean RTs (e.g., Supraliminal Task 1 Time 1; Supraliminal Task 2 Time 1; Subliminal

Task 1 Time 1; etc). Correlations between these 8 mean RTs were calculated to explore the reliability of the RTs within each session and across the two sessions.

These correlations ranged from 0.58 to 0.91, and they were all significant (all p < .01).

Correlations of the two tasks of same presentation duration within the same session were high (e.g., Subliminal Task 1 Time 1 and Subliminal Task 2 Time 1; range: 0.84 to 0.89), as were correlations of tasks of different presentation duration within the same session (e.g., Subliminal Task 1 Time 1 and Supraliminal Task 1 Time 1; range:

0.81 to 0.91). Correlations of tasks of different presentation durations across the two sessions were the lowest (e.g., Subliminal Task 1 Time 1 and Supraliminal Task 2

Time 2; range: 0.58 to 0.78). These results indicate that the test-retest reliabilities of the RTs from the PDT were very high.

Attentional Bias for Negative Information.

Calculation of attentional bias scores.

Attentional bias index scores were calculated from the RT data using a formula used in previous dot probe task studies (cf. MacLeod & Mathews, 1988; Mogg,

Mathews, & Eysenck, 1992): Attentional bias scores = ½ [(UpLt – UpUt) + (LpUt –

LpLt)], where U = upper position, L = lower position, p = probe, t = threat word.

Thus, UpLt is when the probe is in the upper position and the threat word is in the lower position, and so on. This equation calculates the mean latency of responses

when the threat word is in the same position as the probe, compared to when the threat word and probe are in different positions. The resulting value is considered to be an index of attentional bias for threatening information. A positive attentional bias score indicates attention directed toward the threatening word of the threat-neutral word pair. A negative attentional bias score indicates attention directed away from the threatening word (i.e., avoidance of threat). Attentional bias scores were calculated for each task at each presentation duration at each session. These calculations resulted in 8 bias scores. Further, attentional bias scores from each of the two tasks at each session were averaged to produce 4 average threat bias scores: Subliminal Time 1,

Subliminal Time 2, Supraliminal Time 1, and Supraliminal Time 2. Finally, attentional bias scores were averaged across the two sessions to create 2 overall threat bias scores: Supraliminal and Subliminal.

Means and ranges of attentional bias scores.

The participants demonstrated a wide range of attentional bias scores. Across the 8 averaged attentional bias scores (e.g., Supraliminal Task 1 Time 1, Subliminal

Task 1 Time 1), participants’ scores ranged from -72 to 109. Attentional bias scores ranged from -48 to 74 among participants with GAD, and ranged from -72 to 109 among participants without GAD. Mean attentional bias scores across the total sample were roughly centered around zero, indicating little consistent bias toward or away from threatening information. Our first hypothesis appears to be supported by this data, because many participants with GAD demonstrated weak attentional bias

towards threatening information, and in many cases they showed attentional bias away from threat. Attentional bias scores of participants with GAD and participants in the

Stable Low PSWQ group without GAD are presented in Table 11. T-tests revealed no significant differences between the groups. The observed power of these t-tests was low and no power estimate exceeded 0.34. Attentional bias scores of participants in the Stable High PSWQ group and Stable Low PSWQ group are presented in Table 12.

Again, t-tests revealed no significant differences between the groups. The observed power of these t-tests was low.

Mean attentional bias scores from trials with threat-neutral word pairs were entered into a 2 x 2 x 2 x 2 x 2 x 2 repeated measures analysis of variance (ANOVA) with four within-subjects variables: Bias Location (upper vs. lower), Presentation

Duration (subliminal vs. supraliminal), Task (1 vs. 2), and Session (Time 1 vs. Time

2); and two between-subjects variables: GAD-Worry group (GAD vs. Stable Low

PSWQ without GAD) and Word List Order (1 vs. 2). No significant main effects emerged from this analysis. Two significant two-way interactions emerged. The interaction of Task x Word List Order was significant, F(1,57) = 4.7, p < .05, observed power = 0.56. These data are presented in Figure 2. The attentional bias scores for the Word List Order 1 group decreased significantly from Task 1 to Task 2, F(1,57) =

8.8, p < .01, but the threat bias scores for the Word List Order 2 group did not change across the two tasks, F(1,57) = 0.02, p = .89. Also, the bias scores of the two word list order groups differed significantly at Task 2, F(1,57) = 5.1, p < .05, but not at Task 1,

F(1,57) = 0.6, p = .43. The involvement of PDT word list order in either a significant

Stable Low PSWQ GAD + No GAD

(N = 29) (N = 32) Mean (SD) Mean (SD) Supraliminal Task 1 1.2 (20.5) 5.8 (23.8) Time 1 Task 2 -1.3 (17.5) -1.9 (19.7) Overall -0.1 (13.5) 2.0 (13.1)

Task 1 8.1 (23.5) 0.2 (21.9) Time 2 Task 2 -3.7 (22.0) -5.5 (22.0) Overall 2.2 (17.3) -2.6 (15.2)

Subliminal Task 1 3.1 (19.7) -1.7 (17.2) Time 1 Task 2 3.1 (22.5) -2.5 (14.1) Overall 3.1 (15.0) -2.1 (11.7)

Task 1 -2.1 (15.0) 0.3 (14.8) Time 2 Task 2 2.2 (17.7) 0.5 (22.3) Overall 0.1 (11.1) 0.4 (14.2)

Table 11. Mean attentional bias scores (in ms) of participants with GAD and participants in the Stable Low PSWQ group without GAD.

Stable High PSWQ Stable Low PSWQ (N = 54) (N = 33) Mean (SD) Mean (SD) Supraliminal Task 1 3.9 (23.6) 5.7 (23.5) Time 1 Task 2 -0.3 (17.6) -2.0 (19.4) Overall 1.8 (13.0) 1.9 (12.9)

Task 1 4.6 (24.5) 0.4 (21.6) Time 2 Task 2 2.1 (24.7) -5.4 (21.6) Overall 3.4 (17.5) -2.5 (15.0)

Subliminal Task 1 1.5 (17.2) -1.3 (17.1) Time 1 Task 2 -0.7 (21.7) -1.5 (15.1) Overall 0.4 (13.8) -1.4 (12.2)

Task 1 3.5 (19.4) 0.3 (14.5) Time 2 Task 2 2.7 (16.3) -0.1 (22.2) Overall 3.1 (12.5) 0.1 (14.1)

Table 12. Mean attentional bias scores (in ms) of participants in the Stable High PSWQ and Stable Low PSWQ groups.

1 Order 1 0 Order 2 1 2 -1

Attentional Bias (ms) Attentional Bias -2

-3

-4 Task

Figure 2. Mean attentional bias scores (in ms) by Task and Word List Order.

main effect or interaction was unexpected. The interaction of Presentation Duration x

Task was also significant, F(1,57) = 5.0, p < .05, observed power = 0.60. This interaction is presented in Figure 3. Attentional bias scores on the supraliminal trials decreased significantly from Task 1 to Task 2, F(1,57) = 6.8, p < .05, but bias scores from subliminal trials did not change across the two tasks, F(1,57) = 0.2, p = .69.

There were no significant differences between the subliminal and supraliminal trials on either task.

To investigate the effects of PSWQ scoring pattern on attentional bias, another

2 x 2 x 2 x 2 x 2 x 2 repeated measures ANOVA was conducted on the mean attentional bias scores with four within-subjects variables: Bias Location (upper vs. lower), Presentation Duration (subliminal vs. supraliminal), Task (1 vs. 2), and

Session (Time 1 vs. Time 2); and two between-subjects variables of PSWQ Group

(Stable High PSWQ vs. Stable Low PSWQ) and Word List Order (1 vs. 2). There was a significant main effect of PSWQ Group, F(1,83) = 4.4, p < .05, observed power =

0.55, as the Stable High PSWQ group showed greater attentional threat bias scores than the Stable Low PSWQ group. This group difference is presented in Figure 4.

One significant two-way interaction emerged: Task x Word List Order, F(1,83) = 6.0, p < .05, observed power = 0.68. This interaction is presented in Figure 5. The Word

List Order 1 group showed a significant decrease in bias scores from Task 1 to Task 2,

F(1,83) = 9.8, p < .01, while the bias scores of the Word List Order 2 group were stable from Task 1 to Task 2, F(1,83) = 0.12, p = .74. Bias scores at Task 1 did not

5 4 3 2 1 Subliminal 0 Supraliminal -1 1 2 -2

AttentionalBias (ms) -3 -4 -5 Task

Figure 3. Mean attentional bias scores (in ms) by Task and Presentation Duration.

3 2.5 2 1.5 1 0.5

0 Attentional Bias Attentional (ms) -0.5

-1 Stable High PSWQ Stable Low PSWQ PSWQ Group

Figure 4. Mean attentional bias scores (in ms) by PSWQ Group.

1 Order 1 0 Order 2 1 2 -1

Attentional Bias (ms) Attentional Bias -2

-3

-4 Task

Figure 5. Mean attentional bias scores (in ms) by Task and Word List Order.

differ between the two word list order groups, F(1,83) = 0.48, p = .49, but at Task 2 the Word List Order 2 group had significantly higher bias scores than the Word List

Order 1 group, F(1,83) = 8.0, p < .01. As with the previous ANOVA, the involvement of PDT word list order in either a significant main effect or interaction was unexpected. The main effect of PSWQ Group was subsumed under a significant three-way interaction: Bias Location x Task x PSWQ Group, F(1, 83) = 4.0, p < .05, observed power = 0.51. These data are presented in Figure 6. Within the Stable High

PSWQ group at Time 1, the upper threat bias scores were significantly higher than the lower threat bias scores, F(1, 83) = 5.4, p < .05, but at Time 2 the upper and lower bias scores for this group were not significantly different, F(1, 83) = 0.3, p = 58. In addition, the lower threat bias scores of participants in the Stable Low PSWQ group decreased significantly from Task 1 to Task 2, F(1, 83) = 6.3, p < .05, but this group’s upper threat bias scores remained stable from Task 1 to Task 2 F(1, 83) = 0.02, p =

.90. There was a significant four-way interaction of Task x Session x PSWQ Group x

Word List Order, F(1,83) = 4.3, p < .05, observed power = 0.53. There was also a significant six-way interaction of Bias Location x Duration x Task x Session x PSWQ

Group x Word List Order, F(1,83) = 6.1, p < .05, observed power = 0.69. These interactions will not be interpreted because of their complexity.

Upper Bias Lower Bias (a) Stable High PSWQ Group (b) Stable Low PSWQ Group

8 8 7 7 6 6 5 5 4 4 3 3 2 2 1 1 0 0 -1 1 2 -1 1 2 -2 -2

Attentional BiasAttentional (ms) Attentional Bias Attentional (ms)

6 -3 -3 -4 -4 -5 -5 -6 -6 Task Task

Figure 6. Mean attentional bias scores (in ms) of (a) Stable High PSWQ group and (b) Stable Low PSWQ group, by Bias Location, Task, and PSWQ Group.

Reliability of attentional bias scores.

Correlations between the attentional bias scores within the total sample were calculated. The overall threat bias scores for subliminal and supraliminal trials, when the bias scores were averaged across both tasks and both sessions, were not significantly correlated (r = -.04, p = .68). Correlations between subliminal and supraliminal attentional bias scores for each session are presented in Table 13.

Because the location of the attentional bias (upper versus lower) appeared to be influential in the one of the ANOVA analyses, correlations were calculated between bias scores from each location. These data are presented in Tables 14 and 15.

Contrary to our hypothesis, the test-reliability of the attentional bias scores was very poor. In addition, correlations between the two tasks at each session were very low.

Several significant correlations emerged among the upper and lower threat bias scores; however, these negative correlations was unexpected, given that the various threat bias scores are generally expected to be positively related to one another, even if only weakly.

Correlations of the attentional bias scores were also calculated within the group of participants with GAD. Compared to the reliabilities obtained from the total sample’s data, the test-retest reliability of attentional bias scores among the GAD group was equally poor. These correlations are presented in Table 16.

Supraliminal Subliminal Time 1 Time 2 Time 1 Time 2 Supraliminal Time 1 -- Time 2 .01 -- Subliminal Time 1 -.15 -.04 -- Time 2 .08 .02 .09 --

Table 13. Correlations between attentional bias scores for each session in the total sample.

Supraliminal Subliminal Time 1 Time 2 Time 1 Time 2 Bias Upper Lower Upper Lower Upper Lower Upper Lower Location Supraliminal Upper -- Time 1 Lower -.08 -- Upper .04 .03 -- Time 2 Lower -.16 .10 .10 -- Subliminal Upper -.10 -.07 -.03 .02 -- 6 Time 1

Lower -.12 .00 -.04 -.03 .02 -- Upper .03 -.03 .02 .06 .07 .09 -- Time 2 Lower .02 .12 -.12 .10 .06 -.05 -.02 --

Table 14. Correlations between upper and lower attentional bias scores for each session in the total sample.

Supraliminal Subliminal Time 1 Time 2 Time 1 Time 2 Bias Task 1 Task 2 Task 1 Task 2 Task 1 Task 2 Task 1 Task 2

Task Location U L U L U L U L U L U L U L U L Supraliminal Upper -- Time 1 1 Lower .04 -- Upper -.25** -.03 -- 2 Lower .05 -.06 -.19* -- Upper .01 .06 -.01 .16 -- Time 2 1 Lower -.02 .26** -.08 -.12 .02 -- Upper .05 -.06 .03 -.12 .06 .04 -- 2 Lower -.05 -.11 -.13 .15 .03 -.10 .10 --

Subliminal Upper -.12 -.12 -.03 -.06 -.17 -.13 -.12 -.04 -- Time 1 1 Lower -.10 .03 -.05 .11 -.10 .16 .00 -.04 .10 -- Upper .17 -.03 -.26** .05 .10 .04 .10 .14 .06 .06 -- 2 Lower -.12 -.10 .09 -.02 .04 .00 -.03 -.13 -.10 .00 -.01 -- Upper .12 .09 -.11 -.02 .12 .03 -.02 -.03 -.08 -.04 .04 -.04 -- Time 2 1 Lower -.02 -.14 -.08 .16 -.08 -.14 -.04 .09 .10 .05 .07 -.03 -.10 -- Upper .02 -.14 -.01 .04 .06 .08 -.13 .03 .12 .11 .05 .12 -.12 .07 -- 2 Lower .11 .10 .04 .10 -.01 .09 -.13 .15 -.04 .13 .01 -.21* .02 .17 -.05 -- Note: Test-retest reliabilities are in bold. U = Upper bias location, L = Lower bias location. *p < .05. **p < .01.

Table 15. Correlations between attentional bias scores for each task and bias location across the two sessions.

Supraliminal Subliminal Time 1 Time 2 Time 1 Time 2 Supraliminal Time 1 -- Time 2 .02 -- Subliminal Time 1 -.13 -.12 -- Time 2 .16 -.03 -.13 --

Table 16. Correlations between total attentional bias scores for each session in participants with GAD.

Relationship of Attentional Bias to Other Constructs

Correlational relationships with self-report measures.

Correlations were calculated between the subliminal and supraliminal attentional bias scores and scores on the self-report symptomatology measures and attentional control measures. These data are presented in Table 17. These correlations appeared to be centered around zero, indicating that the attentional bias scores and self-report measure scores were largely unrelated. No significant correlations emerged.

Moderation of relationship between worry and attentional bias.

Multiple linear regression analyses were conducted to investigate whether attentional control, effortful control, social anxiety, trait anxiety, state anxiety, depression, GAD diagnosis, or any anxiety disorder diagnosis acted as moderators of the relationship between worry and attentional bias. Two indices of attentional bias were used as dependent variables: Supraliminal and Supraliminal. Thus, for each moderator, two analyses were conducted, one for each of the dependent variables.

In each analysis, aggregate PSWQ score, representing the construct of worry, was entered on the first step. The potential moderator variable was entered on the second step of each analysis. For moderator variables collected at both time points

(e.g., BDI-II scores), the scores from each session were averaged and the aggregate score was entered. For variables measured only at Time 1 (e.g., anxiety disorder diagnosis), participants’ status on those variables at Time 1 was entered. Potential

Threat Bias Measure Supraliminal Subliminal PSWQ .10 .07 STAI-T .14 .02 STAI-S .16 .02 BAI .07 .02 BDI-II .13 .03 SPS .06 .09 ACS -.02 -.07 EC-DP -.08 -.04 ACS = Attentional Control Scale; BAI = Beck Anxiety Inventory; BDI-II = Beck Depression Inventory-II; EC-DP = Effortful Control Scale, Distraction & Persistence Subscale; PSWQ = Penn State Worry Questionnaire; SPS = Social Phobia Scale; STAI-S = State-Trait Anxiety Inventory, State version; STAI-T = State-Trait Anxiety Inventory, Trait version.

Table 17. Correlations between attentional bias scores and the aggregate self-report measures.

moderator variables in this study included attentional control (ACS), effortful control

(EC-DP), social anxiety (SPS), trait anxiety (STAI-T), state anxiety (STAI-S), general anxiety level (BAI), depression (BDI-II), GAD diagnosis, or any anxiety disorder diagnosis. On the third step the two-way interaction between the aggregate PSWQ score and moderator variable was entered. When the interaction terms involved continuous variables, each participant’s scores on those variables were centered in order to reduce multicollinearity of the independent variables.

Hypothesis five was not supported, as none of the potential moderator variables significantly influenced the relationship between worry and attentional bias for either supraliminal or subliminal bias scores. The hypotheses regarding the moderational effects of attentional control were partially supported by the data. The hypothesis that attentional control would not moderate the relationship between worry and attentional bias for subliminal trials was supported, but it is notable that this is a prediction of the null hypothesis. However, the hypothesis that attentional control would moderate the relationship between worry and attentional bias for supraliminal trials was not supported. Neither of the measures of attentional control or effortful control (i.e., ACS, EC-DP) moderated the relationships between worry and the two measures of supraliminal attentional bias.

Relationships Among Self-Report Measures

Correlations were calculated between the self-report measures at Time 1 and

Time 2 for the entire sample. These correlations are presented in Table 18. Test-retest

reliabilities of the self-report measures from Time 1 to Time 2 were very high, ranging from 0.64 to 0.89. Correlations between the aggregate self-report measures were calculated, and the results are presented in Table 19. As expected, the measures of symptomatology were strongly positively related to each other, and negatively related to the measures of attentional control and effortful control.

Ancillary Analyses

I conducted additional analyses using the attentional threat bias scores to investigate whether one of two processes was operating: facilitation to threat or delayed disengagement from threat. Facilitation to threat is demonstrated when individuals show speeding of detection of threatening information, as compared to neutral information. Delayed disengagement from threat is demonstrated when individuals have difficulty shifting attention away from threatening information, compared to neutral information. Several recent studies have investigated which of these processes best explains attentional threat bias (Fox, Russo, & Dutton, 2002;

Mogg, McNamara et al., 2000). Fox and colleagues (2002) found that difficulty disengaging from threat-related stimuli affected the magnitude of attentional threat bias.

The reaction time data from the PDT were analyzed to produce facilitation and delayed disengagement scores for each participant. Facilitation scores were calculated as follows: ½ [(UpN – UpUt) + (LpN – LpLt)], where U = upper position, L = lower position, p = probe, t = threat word, N = neutral-neutral word pair. Thus, UpLt is

Time 1 Time 2 Time 1 1. 2. 3. 4. 5. 6. 7. 8. 1. 2. 3. 4. 5. 6. 7. 8. 1. PSWQ -- 2. STAI-T .70** -- 3. STAI-S .55** .69** -- 4. BAI .55** .61** .63** -- 5. BDI-II .46** .75** .62** .70** -- 6. SPS .42** .57** .36** .57** .52** -- 7. ACS -.53** -.55** -.37** -.33** -.32** -.38** -- 8. EC-DP -.27** -.51** -.30** -.29** -.38** -.31** .61** -- Time 2 1. PSWQ .88** .67** .50** .53** .47** .47** -.58** -.36** -- 2. STAI-T .65** .81** .60** .58** .69** .59** -.56** -.50** .75** -- 3. STAI-S .43** .57** .64** .61** .62** .46** -.28** -.28** .46** .68** --

6 4. BAI .35** .42** .47** .71** .58** .52** -.19* -.26** .43** .55** .65** --

5. BDI-II .45** .66** .59** .68** .89** .53** -.35** -.37** .50** .74** .68** .65** -- 6. SPS .38** .45** .29** .47** .44** .83** -.31** -.28** .48** .57** .40** .63** .49** -- 7. ACS -.44** -.52** -.37** -.25** -.24** -.33** .77** .59** -.52** -.56** -.30** -.21* -.32** -.28** -- 8. EC-DP -.29** -.48** -.33** -.29** -.37** -.37** .58** .86** -.42** -.54** -.33** -.33** -.41** -.37** .57** -- Note: Test-retest reliabilities are in bold. ACS = Attentional Control Scale; BAI = Beck Anxiety Inventory; BDI-II = Beck Depression Inventory-II; EC = Effortful Control Scale; EC-DP = Effortful Control Scale, Distraction & Persistence Subscale; PSWQ = Penn State Worry Questionnaire; SPS = Social Phobia Scale; STAI-S = State-Trait Anxiety Inventory, State version; STAI-T = State-Trait Anxiety Inventory, Trait version. * p < .05. ** p < .01.

Table 18. Correlations between self-report measures at Time 1 and Time 2.

PSWQ STAI-T STAI-S BAI BDI-II SPS ACS EC-DP PSWQ -- STAI-T .75** -- STAI-S .55** .74** -- BAI .51** .61** .71** -- BDI-II .50** .77** .71** .72** -- SPS .48** .60** .43** .62** .53** -- ACS -.57** -.61** -.39** -.28** -.34** -.36** -- EC-DP -.36** -.55** -.36** .33** -.36** -.36** .64** -- ACS = Attentional Control Scale; BAI = Beck Anxiety Inventory; BDI-II = Beck Depression Inventory-II; EC = Effortful Control Scale; EC-DP = Effortful Control Scale, Distraction & Persistence Subscale; PSWQ = Penn State Worry Questionnaire; SPS = Social Phobia Scale; STAI-S = State-Trait Anxiety Inventory, State version; STAI-T = State-Trait Anxiety Inventory, Trait version. ** p < .01.

Table 19. Correlations between aggregate self-report measures.

when the probe is in the upper position and the threat word is in the lower position,

LpN is when the probe is in the lower position and follows a neutral-neutral word pair, and so on. Positive facilitation scores indicate that an individual is faster to respond to probe positions when they contain a threat word rather than when both words presented are neutral. Delayed disengagement scores were calculated as follows: ½

[(UpLt - UpN) + (LpUt – LpN)], where U = upper position, L = lower position, p = probe, t = threat word, N = neutral-neutral word pair. Positive delayed disengagement scores indicate that an individual is slower to respond to a probe position when a threat word is in the non-probed position than when both words presented are neutral. These facilitation and delayed disengagement scores were averaged across tasks and sessions, which resulted in four total scores: Supraliminal Facilitation, Subliminal

Facilitation, Supraliminal Delayed Disengagement, and Subliminal Delayed

Disengagement.

T-tests were conducted on the total facilitation and total delayed disengagement scores to examine differences between participants with GAD and participants in the Stable Low PSWQ group without GAD, as well as differences between the Stable High PSWQ and Stable Low PSWQ groups. These data are presented in Tables 20 and 21. Participants with GAD showed significantly greater delayed disengagement scores than participants in the Stable Low PSWQ group without GAD for subliminal trials, t(1,85) = 2.74, p < .01, suggesting that those with

GAD are slower to disengage from threatening information when it is presented outside of their awareness. This difference in subliminal delayed disengagement

Stable Low PSWQ + GAD no GAD (N = 29) (N = 32) Mean (SD) Mean (SD) Supraliminal Facilitation 0.50 (15.6) 1.87 (14.9) Delayed Disengagement 0.58 (14.5) -2.19 (13.3)

Subliminal Facilitation a -2.74 (12.9) 3.45 (12.0) Delayed Disengagement* 4.30 (11.6) -4.31 (12.9) Probability notes indicate significance of independent samples t-tests. a p = .07. * p < .01.

Table 20. Total facilitation and delayed disengagement scores (in ms) for participants with GAD and participants in the Stable Low PSWQ group without GAD.

Stable High PSWQ Stable Low PSWQ (N = 54) (N = 33) Mean (SD) Mean (SD) Supraliminal Facilitation -0.76 (16.0) 2.04 (14.7) Delayed Disengagement a 3.33 (16.3) -2.37 (13.2)

Subliminal Facilitation 0.16 (13.7) 3.46 (11.8) Delayed Disengagement b 1.58 (14.5) -4.09 (12.7) Probability notes indicate significance of independent samples t-tests. a p = .09. bp = .07.

Table 21. Total facilitation and delayed disengagement scores (in ms) for participants in the Stable High PSWQ and Stable Low PSWQ groups.

scores approached significance for the comparison of the Stable High PSWQ and

Stable Low PSWQ groups, t(1,85) = 1.85, p = .07. In addition, there was a trend toward a difference in supraliminal delayed disengagement scores between the Stable

High PSWQ and Stable Low PSWQ groups, t(1,85) = 1.85, p = .09. The facilitation scores were not significantly different between either set of groups.

Given the group differences found in delayed disengagement scores, correlations were calculated between the aggregate self-report measures and the average delayed disengagement scores for both supraliminal and subliminal trials.

These results are presented in Table 22. No significant correlations emerged from these analyses.

In addition, multiple linear regression analyses were conducted to investigate whether attentional control, effortful control, social anxiety, trait anxiety, state anxiety, depression, GAD diagnosis, or any anxiety disorder diagnosis acted as moderators of the relationship between worry and delayed disengagement scores. In each analysis, aggregate PSWQ score, representing the construct of worry, was entered on the first step. The potential moderator variable was entered on the second step of each analysis. The potential moderator variables were the same as in the previous moderational analyses predicting attentional bias scores. For moderator variables collected at both time points (e.g., BDI-II scores), the scores from each session were averaged and the aggregate score was entered. For variables measured only at Time 1

(e.g., anxiety disorder diagnosis), participants’ status on those variables at Time 1 was entered. On the third step the two-way interaction between the aggregate PSWQ score

Delayed Disengagement Measure Supraliminal Subliminal PSWQ .09 .09 STAI-T -.03 .08 STAI-S .-.10 .05 BAI -.16 -.03 BDI-II -.05 .11 SPS -.09 .11 ACS .02 -.05 EC-DP .09 .02 ACS = Attentional Control Scale; BAI = Beck Anxiety Inventory; BDI-II = Beck Depression Inventory-II; EC-DP = Effortful Control Scale, Distraction & Persistence Subscale; PSWQ = Penn State Worry Questionnaire; SPS = Social Phobia Scale; STAI-S = State-Trait Anxiety Inventory, State version; STAI-T = State-Trait Anxiety Inventory, Trait version.

Table 22. Correlations between delayed disengagement scores and the aggregate self- report measures.

and moderator variable was entered. When the interaction terms involved continuous variables, each participant’s scores on those variables were centered in order to reduce multicollinearity of the independent variables. None of the potential moderator variables significantly moderated the relationship between worry and delayed disengagement scores for either supraliminal or subliminal trials.

CHAPTER 4

DISCUSSION

The current study demonstrated that attentional bias towards threat, at least as measured by the probe discrimination task (PDT) used in this study, is not a hallmark of chronic worry. The results supported my first hypothesis that individuals who have high worry levels display a wide range of attentional bias scores. Participants meeting criteria for GAD displayed a wide range of attentional bias scores, ranging from strong bias toward threat to strong bias away from threat. Similar to the pattern found for the

GAD group, participants high in trait anxiety also showed a wide range of attentional bias scores. These results are consistent with several previous studies which found that either the entire sample or a subsample of participants with GAD did not show attentional bias towards threat (Mathews, Ridgeway, & Williamson, 1996; Mogg,

Millar, & Bradley, 2000; Hazen, Vasey, & Schmidt, 2001). However, the majority of the published attentional bias research has found attentional bias towards threat in

GAD samples.

My second hypothesis that individuals reporting higher levels of anxiety and worry will show greater attentional bias scores was partially supported. Participants

who demonstrated consistently high levels of worry across time produced, on average, significantly higher attentional bias scores than participants who demonstrated consistently lower levels of worry across time. However, contrary to expectations, attentional bias scores were uncorrelated with PSWQ scores. These conflicting results may have been due to the fact that the correlations were calculated using separate supraliminal and subliminal bias scores, whereas the group differences were found when all trials types were collapsed with one another (i.e., subliminal and supraliminal bias scores were combined). Another result that did not support my second hypothesis was the finding that participants with GAD did not show consistently higher attentional bias scores than participants who displayed stable low worry levels and did not have GAD.

My third hypothesis regarding the role of attentional control in supraliminal attentional bias scores was not supported by the data. I predicted that attentional control would moderate the relationship between worry and attentional bias scores for supraliminal trials because supraliminal trials involve words that the participants were consciously aware of and thus they could use conscious processes to override their automatic response to that information. Contrary to this prediction, neither of the measures of attentional control moderated the relationship between worry and attentional bias. One possible explanation for this finding is that our self-reported measures of attentional control may not accurately measure attentional control. As self-report measures, the ACS and EC-DP may be subject to participants’ biases about their attentional abilities. The ACS and EC-DP are relatively new measures and have

not been subjected to as much psychometric investigation as the self-report measures of symptomatology used in this study. It is possible that a behavioral task, such as a computer task, may be a more accurate measure of someone’s ability to control their attention. However, one published study (Derryberry & Reed, 2002) has shown that only high trait-anxious subjects who were also low in effortful control showed a bias in favor of threat. Although that study did not use a PDT, two unpublished studies conducted by Vasey and colleagues using PDTs found the same pattern of results

(Vasey, personal communication, June 22, 2006). Thus, the failure to find the expected pattern of results also raises questions about the validity of the PDT used in this particular study.

The fourth hypothesis regarding the role of attentional control in the relationship between worry and subliminal attentional bias scores was supported. I expected that on subliminal trials, which are by definition outside of an individual’s awareness, an individual’s ability to effortfully direct attention would not influence their bias scores for those trials. Consistent with my predictions, attentional bias scores for subliminal trials were unrelated to attentional control. None of the measures of attentional control (ACS) or effortful control (EC-DP) moderated the relationship between worry and attentional bias. However, it is important to note that this hypothesis amounts to predicting a null effect (i.e., no effect of attentional control), so the finding that the null hypothesis was supported in this case should be interpreted with caution.

My fifth hypothesis was unsupported, as none of the other psychological factors measured in the study, such as clinical status, depression, and social anxiety, moderated the relationship between worry and attentional bias. These analyses investigated whether other psychological variables influence the degree of attentional bias shown by an individual, given his or her level of worry. Contrary to predictions, the presence or absence of GAD did not significantly moderate the relationship between worry level and attentional bias scores within the total sample. In addition, the measures of symptomatology were largely uncorrelated with the attentional bias scores.

The sixth and final hypothesis that the attentional bias scores would be reliable between and within sessions was also unsupported by the data. The PDT attentional bias scores demonstrated poor reliability between sessions and between the two tasks within each session. One might expect to find higher reliabilities between two tasks closer in time (e.g., Task 1 and Task 2 at Time 1) than between two tasks father apart in time (e.g., Task 1 at Time 1 and Task 1 at Time 2); however, this was not the case in my data. Correlations were equally low between the two tasks of each session and across the two sessions. Further complicating the interpretation of these results was finding several significant, and even negative, correlations between the upper and lower threat bias scores. No negative correlations were predicted for any of the attentional bias scores.

The lack of reliability of attentional bias scores may explain the pattern of null findings in this study. Indeed, it is the most parsimonious explanation for this study’s

failure to find expected effects. To accurately measure the construct of attentional bias, attentional bias must first be measured reliably. The PDT program used in this study did not yield reliable attentional bias scores. Therefore, it was unlikely that my further analyses utilizing attentional bias scores, such as comparing the attentional bias scores of different groups of participants, would yield consistent and interpretable results.

As discussed previously, it is common for different groups of researchers to develop slightly – or greatly – different versions of the PDT. Therefore, the results of this study should be considered in light of the fact that the PDT used here does differ from those used in other studies, although the intent of the present study was to create a PDT that was similar to other PDTs in the literature. The findings regarding this

PDT’s reliability suggest that the reliability of PDTs may be dependent on some as-yet unknown variable, such as one of the features of the task (e.g., stimulus presentation time), the method of administering the task (e.g., using an apparatus to keep participants’ faces a standardized distance from the computer screen), or the environment in which the task is administered. Despite a lack of information about what factors influence the reliability of PDTs, most previous research has found group differences in attentional threat bias, suggesting that the PDT can be reliable enough to yield expected differences between individuals with and without anxiety disorder such as GAD. The present study found the expected differences between participants high and low in worry, but not between participants with GAD and participants without

GAD and also low in worry.

My finding that the PDT is unreliable is consistent with the only published set of studies to also investigate the reliability of dot probe tasks over time (Schmukle,

2005). However, the results of Schmukle (2005) should be interpreted with caution, as there are a number of methodological and data analytic problems with his two studies, which were mentioned previously. Schmukle (2005) used non-clinical samples for both studies, whereas the current study included individuals with and without clinical diagnoses. Schmukle proposed the possibility that attentional bias scores might be more reliable within a clinically anxious sample; however, this possibility was not supported by my results, which indicated that attentional bias scores were equally unreliable in individuals with and without GAD, as well as in individuals with and without any anxiety disorder, including GAD.

It is notable that the reaction times (RTs) from the PDT produced significant correlations with each other, even across the two-week interval, thus displaying high test-retest reliability. However, the attentional bias scores calculated from those RTs were largely uncorrelated with each other. The formula used to calculate attentional bias scores from RTs has been used in most published studies of dot probe tasks. One problem with this formula is that it relies upon two sets of difference scores to produce each attentional bias score. Difference scores are problematic in that they decrease consistency of measurement and reduce power. However, any alternative ways to calculate attentional bias scores without using difference scores have yet to be published or widely adopted.

The results of the present study are only partially consistent with previous research. While the majority of research on anxiety disorders has found an attentional threat bias in clinical samples, several studies found results similar to ours in which individuals with GAD did not demonstrate an attentional threat bias on a dot probe task. However, as was expected, participants with stable high worry levels demonstrated greater attentional threat bias towards threat compared to participants low in worry. In addition, my findings that chronic worriers and individuals with

GAD tended to display delayed disengagement from threat rather than facilitation towards threat is consistent with previous work in this area (e.g., Fox, Russo, &

Dutton, 2002).

It is difficult to explain why I did not find significant threat bias score differences between groups based on clinical anxiety diagnosis. One reason for this difficulty is the fact that the large majority of the word pairs used in the PDT came directly from previous research in this area which did find group differences in attentional threat bias (MacLeod, Rutherford, Campbell, Ebsworthy, & Holker, 2002).

It is possible that there was a systematic malfunction of the PDT program; however, I was present during each participant’s administration of the PDT and there was only one occurrence of an apparent problem with the PDT task, the result of which was elimination of that participant’s data from analysis. Another possibility is that attentional threat bias is more strongly demonstrated when an individual is primed in some way to feel anxious or worried, and no such priming task was involved in this

study. In fact, in an effort to avoid influencing attentional bias scores, at each session the PDT was completed first, followed by the self-report measures, followed by the structured clinical interview (at the first session only).

In addition, the threat words used in the PDT may not have been perceived as threatening to all participants. An alternative procedure is creating a threat word list for each participant based on the individual’s specific types of fears (e.g., physical, social). There is some evidence that using stimulus threat words which are relevant for an individual’s type of anxiety results in greater attentional bias towards those threat words. Tata and colleagues (1996) administered a dot probe task with both contamination threat and social threat words to high trait anxious individuals and patients with obsessive-compulsive disorder (OCD). The patients with OCD demonstrated an attentional bias only towards the contamination threat words and not the social threat words, while the high trait anxious participants showed an attentional bias only towards the social threat words. The disadvantages of using idiographic threat word lists include: (1) increased time and effort to alter the PDT computer program for each participant, and (2) increased difficulty in interpreting the meaning of differences in attentional bias scores across individuals, given that each person’s

PDT experience would be unique.

Strengths of the present study include the relatively large total sample size and the size of the subsample of participants with GAD. The overall sample size allowed for comparisons of different groups based on worry patterns over time. In addition,

the large sample size prevented the data analytic problem of restriction of range. The relatively large number of participants with GAD allowed for particular analyses to be conducted on that subsample.

Another strength of this study is the large number of trials included in the PDT.

Many dot probe task studies have used less than 100 trials to assess attentional threat bias (e.g., 72, 96). In this study, each PDT session consisted of 256 trials, administered in two blocks of 128 trials. In addition, the use of a probe discrimination task (as compared to a probe detection task) allowed me to collect data from each trial because all trials are probed, not just the critical trials (i.e., threat-neutral word pairs).

Increasing the number of data points collected should reduce the influence of error variance on the average reaction times and also on the attentional bias scores, which are derived from those reaction times.

One limitation of the current study is that the process of randomly assigning participants to PDT word list orders failed to result in groups which were equivalent on measures of anxious and depressive symptomatology. In addition, participants’ responses to the PDT appeared to differ based on which order of word lists they received. This finding was unexpected and may reflect the significant differences in symptomatology between the groups. However, this possibility is contradicted by the fact that the symptomatology measures were largely unrelated to the attentional threat bias scores.

Another limitation of the study is that the sample cannot be clearly defined as a clinical sample. A minority of participants met criteria for at least one DSM-IV

diagnosis. In addition, participants with anxiety disorders and other DSM-IV diagnoses were not necessarily seeking any kind of treatment when they entered the study. Thus, the current sample of predominantly female, Caucasian, college- educated, never married, non-treatment-seeking individuals may not be representative of chronic worriers or other GAD research samples. However, the goal of the study was not to recruit a clinical sample. The intention was to recruit chronic worriers as well as a smaller group of individuals who displayed a range of worry levels below the prescreening cutoff. This goal was achieved; however, the size of the chronic worrier subsample (i.e., participants in the Stable High PSWQ group) was smaller than intended.

Inadequate power for many analyses is another limitation of the study. Many of the t-tests examining group differences on the self-report measures had adequate power, but the t-tests examining group differences in attentional threat bias were underpowered. In addition, the repeated measures ANOVAs were also underpowered.

Increasing the number of participants in each group (e.g., Stable High PSWQ; GAD) would have increased power.

My finding that the PDT is unreliable raises concerns about how attentional bias scores are typically conceptualized and used. An implicit assumption in most attentional threat bias research is that an attentional bias score obtained at one point in time reflects a construct which is consistent over time. However, the results of the current study call this assumption into question and raise the broader question of what factors influence the reliability of dot probe tasks. It will be very important to identify

these factors as more researchers investigate attentional threat bias and test models which assume continuity of threat bias across time. Dot probe tasks have not been subjected to the same rigorous psychometric investigation as other psychological measures. The fact that only one published study has investigated the reliability of any kind of dot probe task is evidence for the extent of the problem (Schmukle, 2005).

Further, problems can arise from the use of dot probe tasks to measure changes in attentional threat bias over time. At least one published study has used attentional threat bias scores as indices of change after an experimental manipulation designed to alter the direction of attentional bias (MacLeod, Rutherford, Campbell, Ebsworthy, &

Holker, 2002). The authors’ interpretation of changes in attentional bias scores in this type of experiment would be significantly affected by the reliability of their measure of attentional bias. The findings of the current study and those of Schmukle (2005) regarding the unreliability of attentional bias scores from dot probe tasks may cast some doubt on MacLeod and colleagues’ conclusion that their manipulation causally affected changes in attentional threat bias scores.

Future research should examine the test-retest reliability of dot probe tasks over varying periods of time (e.g., 1 week, 1 month, 6 months, 1 year). Also, attentional threat bias can be assessed more than twice, and these additional assessments would provide even more information regarding the course of attentional threat bias over time. In addition, these studies need to be carried out in different samples (e.g., GAD patients, panic disorder patients, high trait anxious individuals), using different types of stimuli (e.g., threatening words, pictures of angry faces,

pictures of threatening objects), and using different stimulus durations (e.g., 14ms,

100ms, 500ms, 1250ms). Future research on dot probe tasks should demonstrate and report reliability of the particular version of the dot probe task used in each study.

Unfortunately, the comparability between different dot probe tasks has often been taking for granted in attentional bias research (Vasey, Dalgleish, & Silverman, 2003).

Given the number of ways in which dot probe tasks can vary, many basic psychometric studies will be required to achieve confidence in the reliability of these types of tasks. The reliability of attentional bias scores must be established before attentional bias scores can be validly used as indices of change following any type of intervention.

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Mogg, K., Bradley, B., De Bono, J., & Painter, M. (1997). Time course of attentional bias for threat information in non-clinical anxiety. Behaviour Research and Therapy, 35, 297-303.

Mogg, K., Bradley, B., Dixon, C., Fisher, S., Twelftree, H., & McWilliams, A. (2000). Trait anxiety, defensiveness and selective processing of threat: an investigation using two measures of attentional bias. Personality & Individual Differences, 28, 1063-1077.

Mogg, K., Bradley, B., & Hallowell, N. (1994). Attentional bias to threat: Roles of trait anxiety, stressful events, and awareness. Quarterly Journal of Experimental Psychology, 47A(4), 841-864.

Mogg, K., Bradley, B., & Williams, R. (1995). Attentional bias in anxiety and depression: The role of awareness. British Journal of Clinical Psychology, 34(1), 17-36. 98

Mogg, K., Mathews, A., & Eysenck, M. (1992). Attentional bias to threat in clinical anxiety states. Cognition & Emotion, 6(2), 149-159.

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Mogg, K., Philippot, P., & Bradley, B. (2004). Selective attention to angry faces in clinical social phobia. Journal of Abnormal Psychology, 113, 160-165.

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APPENDIX A

Telephone and Email Recruitment Script

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Recruitment Materials

Hello, My name is Jennifer Preston and I work in the psychology laboratory of Dr. Michael Vasey. Early in the quarter you completed a questionnaire for us in your Psych 100 class, and you qualify for our study based on that prescreening questionnaire. Our study is worth 2.5 hours of REP credit for approximately 2.5 hours of participation.

The study we're conducting is designed to investigate the relationship between anxiety, worry, and attention. We're interested in the consistency over time of a measure of attention. The first step in the study involves coming into the lab for approximately 1.5 hours. During this first session, you will have a brief interview with the experimenter. You will also fill out several questionnaires and complete a computer task. Again, this session will last approximately 1.5 hours and you will receive 1.5 hours of REP credit for it.

The second part of the study is a second session 2 weeks after the first part of the experiment. This second session will last approximately 1 hour and you will receive 1 hour of REP credit for participating. During this second session, you will complete several questionnaires and a computer task.

Anything you say during the entire study is completely confidential, and we would only break that confidentiality if we feel you are in danger of hurting yourself or someone else. Your participation in this study is completely voluntary, and you may withdraw from the experiment at any time without penalty.

Please email me back ([email protected]) if you have any questions about the experiment. If you are interested in participating, please see the available experiment times listed below.

(list of times)

These experiment times have been sent to several other students, so it's a "first come, first served" situation. If you would like to participate, please email me back with your first and second choice experiment times from those listed above. I will sign you up for the experiment online. The experiment will take place in 141 Townshend Hall.

Thank you, Jennifer Preston

Clinical Psychology Graduate Student 223 Townshend Hall 1885 Neil Ave Columbus, OH 43210 (614) 292-2345 [email protected] 102

APPENDIX B

Word List used in Probe Discrimination Task (PDT)

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104 Threat-Neutral Word Pairs: suffer parked nausea confer wound dried suffered recorded attacks physics destroyed furniture victims smelled damage campus tease aisle harm pond discouraged connections inferior shearing gloomy pastel sluggish textured tormented mythology grave filed panicky clarets cancer saddle insecure fetching desperate variables horror wagons danger league dead data defeat museum afraid detail shot cars bitter handle trauma enjoin evil hill kill shop fright sipped worried context disease remarks powerless multitude worthless batteries devastated stagecoach rejected quantity angry curve bomb crew threat varied worst owned severe recall catastrophe approximate sinister integral lethal racket assault bottles ignored lighted lost read tragic rector despised tomatoes terror pupils humiliated waterproof trap tent injury holder hazard ballot intimidated coefficient hopeless feathers awful tract inadequate transition mourn scans forlorn keyhole scared planet coffin edited conflict detailed strangled signature dull flew apprehension instrumental murder junior fear note agitation fireplace trouble evening incurable reclaimed worry inner stress cities enemy check hostile rolling distress creature pain laws

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tragedy request hatred fitted sad pat dismal midway grieving hallmark futile attire sickly tokens deathbed softener cry via unhappy bridges anxiety journal menacing panorama dying lists morgue tidbit hurt core shameful branched mutilated decanting explosive geometric suffocating constituent malicious bilateral lonely jersey hurricane dispersed pathetic cleaners misery fabric violent thereby corpse spiral

24 Neutral-Neutral Word Pairs:

nugget umpire honeybee bookcase loaded refund normally schedule oxen code encyclopedia intermission vacancy shelves conductor astronomy elm lab coming person doorway mileage instructor microscope spelling triangle wink rags librarian drugstore scene write pencil facing preparation description jar ate drink speed manage border ancient traffic transmit lipstick

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APPENDIX C

Self-Report Measures

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PSWQ

Instructions: Check the appropriate blank corresponding to the one phrase that best represents the extent to which you feel each item is typical of you.

SLIGHTLY SOMEWHAT MODERATELY VERY ALL AT NOT

1. If I do not have enough time to do everything, I do not worry about it. ______2. My worries overwhelm me. ______3. I do not tend to worry about things. ______4. Many situations make me worry. ______5. I know I should not worry about things, but I just cannot help it. ______6. When I am under pressure I worry a lot. ______7. I am always worrying about something. ______8. I find it easy to dismiss worrisome thoughts. ______9. As soon as I finish one task, I start to worry about everything else I have to do. ______10. I never worry about anything. ______11. When there is nothing more I can do about a concern, I do not worry about it any more. ______12. I have been a worrier all my life. ______13. I notice that I have been worrying about things. ______14. Once I start worrying, I cannot stop. ______15. I worry all the time. ______16. I worry about projects until they are done. ______

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STAI – T

INSTRUCTIONS: A number of statements which people have used to describe themselves are given below. Read each statement and then circle the appropriate number to the right of the statement to indicate how you generally feel. Do not spend too much time on any one statement but give the answer which seems to describe how

you generally feel.

Sometim Often always Almost never Almost

21. I feel pleasant……………………………………………… 1 2 3 4 22. I tire quickly …………………………………………..…… 1 2 3 4 23. I feel like crying …………………………………………… 1 2 3 4 24. I wish I could be as happy as others seem to be …….. 1 2 3 4 25. I am losing out on things because I can’t make up my mind soon enough ……………. ……………..……. 1 2 3 4 26. I feel rested …………………………………………….... 1 2 3 4 27. I am “calm, cool and collected”……………………...…. 1 2 3 4 28. I feel that difficulties are piling up so that I cannot overcome them …………………………………………… 1 2 3 4 29. I worry too much over something that really doesn’t matter …………………………………………………….. 1 2 3 4 30. I am happy ……………..…………………………..……. 1 2 3 4 31. I am inclined to take things hard………………………… 1 2 3 4 32. I lack self-confidence ………………………………..…… 1 2 3 4 33. I feel secure ………………………………………….….. 1 2 3 4 34. I try to avoid facing a crisis or difficulty ……………..…. 1 2 3 4 35. I feel blue..……………………………………………….. 1 2 3 4 36. I am content ……………………………………….…….. 1 2 3 4 37. Some unimportant thought runs through my mind and bothers me …………………..…………..…………….. 1 2 3 4 38. I take disappointments so keenly that I can’t put them out of my mind …………………………………….…….. 1 2 3 4 39. I am a steady person ……………….………………..… 1 2 3 4 40. I get in a state of tension or turmoil as I think over my recent concerns and interests………………………… 1 2 3 4

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STAI – S

INSTRUCTIONS: A number of statements which people have used to describe themselves are given below. Read each statement and then circle the appropriate number to indicate how you feel right now, that is, at this moment. Do not spend too much time on any one statement but give the answer which seems to describe your

present feelings best.

Somewhat soModerately Veryso much at all Not 1. I feel calm …………………………………………………...1 2 3 4 2. I feel secure …………………………………………..……..1 2 3 4 3. I am tense ……………………………………………..…….1 2 3 4 4. I feel strained …………………………………………..……1 2 3 4 5. I feel at ease …………………………………………..…….1 2 3 4 6. I feel upset ……………………………………………..……1 2 3 4 7. I am presently worrying over possible misfortunes .….…1 2 3 4 8. I feel satisfied ……………………………………………..…1 2 3 4 9. I feel frightened ………………………………………..……1 2 3 4 10. I feel comfortable ……………………………………..…….1 2 3 4 11. I feel self-confident …………………………………..……..1 2 3 4 12. I feel nervous …………………………………………..… 1 2 3 4 13. I am jittery ………………………………………………..… 1 2 3 4 14. I feel indecisive ………………………………………….. 1 2 3 4 15. I am relaxed .…………………………………………..… 1 2 3 4 16. I feel content …………………………………………..… 1 2 3 4 17. I am worried …………………………………………..…… 1 2 3 4 18. I feel confused ………………………………………..…… 1 2 3 4 19. I feel steady …………………………………………..……. 1 2 3 4 20. I feel pleasant …………………………………………..…. 1 2 3 4

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BAI

Instructions: Below is a list of common symptoms of anxiety. Please carefully read each item in the list. Indicate how much you have been bothered by each symptom during the PAST WEEK, INCLUDING TODAY, by checking the appropriate blank.

NOTALL AT MILDLY MODERATELY SEVERELY Itdid bother not me much Itwas very unpleasant, butI could stand it I couldbarely it stand

1. Numbness or tingling. ______2. Feeling hot. ______3. Wobbliness in legs. ______4. Unable to relax. ______5. Fear of the worst happening. ______6. Dizzy or lightheaded. ______7. Heart pounding or racing. ______8. Unsteady. ______9. Terrified. ______10. Nervous. ______11. Feelings of choking. ______12. Hands trembling. ______13. Shaky. ______14. Fear of losing control. ______15. Difficulty breathing. ______16. Fear of dying. ______17. Scared. ______18. Indigestion or discomfort in the abdomen. ______19. Faint. ______20. Face flushed. ______21. Sweating (not due to heat). ______

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SPS

Instructions: Check the appropriate blank corresponding to the one phrase that best represents the extent to which you feel each item is characteristic or true of you.

ALL

NOT AT NOT SLIGHTLY MODERATELY MUCH EXTREMELY

1. I become anxious if I have to write in front of other people. ______

2. I become self-conscious when using public toilets. ______

3. I can suddenly become aware of my own voice and of others listening to me. ______

4. I get nervous that people are staring at me as I walk down the street. ______

5. I fear I may blush when I am with others. ______

6. I feel self-conscious if I have to enter a room where others are already seated. ______

7. I worry about shaking or trembling when I’m watched by other people. ______

8. I would get tense if I had to sit facing other people on a bus or train. ______

9. I get panicky that others might see me to be faint, sick, or ill. ______

10. I would find it difficult to drink something if in a group of people. ______

11. It would make me feel self-conscious to eat in front of a stranger at a restaurant. ______

12. I am worried that people will think my behavior odd. ______

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SLIGHTLY MODERATELY MUCH EXTREMELY ALL AT NOT

13. I would get tense if I had to carry a tray across a crowded cafeteria. ______

14. I worry I’ll lose control of myself in front of other people. ______

15. I worry I might do something to attract the attention of others. ______

16. When in an elevator I am tense if people look at me. ______

17. I can feel conspicuous standing in a line. ______

18. I get tense when I speak in front of other people. ______

19. I worry my head will shake or nod in front of others. ______

20. I feel awkward and tense if I know other people are watching me. ______

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ACS

Please answer each item, indicating how often it is true for you on the following scale:

1 2 3 4 almost never sometimes often always

1. It's very hard for me to concentrate on a difficult task when there are noises around.

1 2 3 4

2. When I need to concentrate and solve a problem, I have trouble focusing my attention.

1 2 3 4

3. When I am working hard on something, I still get distracted by events around me.

1 2 3 4

4. My concentration is good even if there is music in the room around me.

1 2 3 4

5. When concentrating, I can focus my attention so that I become unaware of what's going on in the room around me.

1 2 3 4

6. When I am reading or studying, I am easily distracted if there are people talking in the same room.

1 2 3 4

7. When trying to focus my attention on something, I have difficulty blocking out distracting thoughts.

1 2 3 4

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1 2 3 4 almost never sometimes often always

8. I have a hard time concentrating when I'm excited about something.

1 2 3 4

9. When concentrating I ignore feelings of hunger or thirst.

1 2 3 4

10. I can quickly switch from one task to another.

1 2 3 4

11. It takes me a while to get really involved in a new task.

1 2 3 4

12. It is difficult for me to coordinate my attention between the listening and writing required when taking notes during lectures.

1 2 3 4

13. I can become interested in a new topic very quickly when I need to.

1 2 3 4

14. It is easy for me to read or write while I'm also talking on the phone.

1 2 3 4

15. I have trouble carrying on two conversations at once.

1 2 3 4

16. I have a hard time coming up with new ideas quickly.

1 2 3 4

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1 2 3 4 almost never sometimes often always

17. After being interrupted or distracted, I can easily shift my attention back to what I was doing before.

1 2 3 4

18. When a distracting thought comes to mind, it is easy for me to shift my attention away from it.

1 2 3 4

19. It is easy for me to alternate between two different tasks.

1 2 3 4

20. It is hard for me to break from one way of thinking about something and look at it from another point of view.

1 2 3 4

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Below are a number of sentences a person might use to describe themselves. Read each sentence; then circle the appropriate number next to each sentence to show how much this sentence describes you.

Indicate how much each sentence describes you: that is, how you are most of the time.

1 2 3 4 5 Very Much A Little Somewhat Not Very Much Not At All Like Me Like Me Like Me Like Me Like Me

Very A Little Somewhat Not Very Not Much Much At All 1. When an activity or task is difficult, I give up. 1 2 3 4 5 2. I have a hard time following instructions. 1 2 3 4 5 3. I often get lost in my work. 1 2 3 4 5 4. I do not complete my homework. 1 2 3 4 5 5. I start many things that I don’t finish. 1 2 3 4 5 6. When I get frustrated with projects or tasks, I 1 2 3 4 5 quit. 7. When I don’t get what I want, it’s hard to 1 2 3 4 5 enjoy something else. 8. I have a hard time concentrating on my work 1 2 3 4 5 because I’m always thinking about other things. 9. I have difficulty completing assignments on 1 2 3 4 5 time. 10. I will move from one task to another without 1 2 3 4 5 completing any of them. 11. Even little things distract me. 1 2 3 4 5 12. I leave my own projects or tasks unfinished. 1 2 3 4 5

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