Archives of Clinical Neuropsychology 23 (2008) 823–830

Brief report

The relation of depression and anxiety to measures of attention inyoung adults seeking psychoeducational evaluation

B.D. Hill a,b,∗, Todd A. Smitherman b, Russell D. Pella a,Judith R. O’Jile b, Wm. Drew Gouvier a

a Department of Psychology, Louisiana State University, Baton Rouge, LA 70803, USAb Department of Psychiatry and Human Behavior, University of Mississippi Medical Center/VA, Medical Center, Jackson, MS 39206, USA

Accepted 21 July 2008

Abstract

The relation between mood and attentional functioning in young adults seeking psychoeducational evaluation has not beenpreviously reported. This study examined the relation of self-reported depression and anxiety on attentional abilities among 161young adults referred for psychoeducational evaluation. Depression and anxiety were measured with the Beck Depression Inventory-II and the State-Trait Anxiety Inventory, respectively. Attentional functioning was assessed using the Trail Making Test, the d2 Testof Attention, the Conners’ Continuous Performance Test, and the WAIS-III Working Memory and Processing Speed Indices. Theunique variance accounted for by depression or anxiety was minimal (typically <1.5%); these null results were confirmed bydiagnostic subgroup analyses and also after examining the interaction between depression and anxiety. These results suggest thatperformance on measures of attention within samples of young adults seeking psychoeducational evaluation is minimally relatedto self-reported depression and anxiety.© 2008 National Academy of Neuropsychology. Published by Elsevier Ltd. All rights reserved.

Keywords: Attention; Anxiety; Depression; ADHD; Assessment

1. Introduction

The relation between mood symptoms and performance on neuropsychological tests has been the focus of consid-erable interest in recent years. While psychiatric populations tend to score below normative levels on a wide variety ofneuropsychological measures (Basso & Bornstein, 1999; Burt, Zembar, & Niederehe, 1995; Kindermann & Brown,1997; Sweet, Newman, & Bell, 1992; Tancer et al., 1990; Veiel, 1997), recent research has suggested that the rela-tion of affective variables to neuropsychological performance is quite variable (Kaufman, Grossman, & Kaufman,1994; Sherman, Strauss, Slick, & Spellacy, 2000; Rohling, Green, Allen, & Iverson, 2002; Tsushima, Johnson, Lee,Matsukawa, & Fast, 2005). Uncertainty regarding the specifics of this relation may also be due to the fact that few ofthese studies accounted for the effect of participant effort in their study methodology, with a few notable exceptions(Sherman et al., 2000; Rohling et al., 2002).

∗ Corresponding author at: Rhode Island Hospital, POB 110 Lockwood Street, Suite 430 Providence, RI 02903. Tel.: +1 401 444 4500;fax: +1 401 444 6643.

E-mail address: bhill@lifespan.org (B.D. Hill).

0887-6177/$ – see front matter © 2008 National Academy of Neuropsychology. Published by Elsevier Ltd. All rights reserved.doi:10.1016/j.acn.2008.07.003

824 B.D. Hill et al. / Archives of Clinical Neuropsychology 23 (2008) 823–830

In particular, the literature on depressive symptoms as they relate to measures of attention is relatively equivocal.Some researchers have noted a significant relation between depression and impaired attentional performance (Gass,1996; Ross, Putman, Gass, Baily, & Adams, 2003; Watari et al., 2006), while others have not (Miller, Faustman, Moses,& Csernansky, 1991; Reitan & Wolfson, 1997; Rohling et al., 2002). By comparison to depression, the contribution ofanxiety to cognitive impairment is understudied. Recent studies have suggested that self-reported anxiety symptomshave minimal effects on neuropsychological performance in both healthy (Waldstein, Ryan, Jennings, Muldoon, &Manuck, 1997) and assessment-seeking samples (Smitherman, Huerkamp, Miller, Houle, & O’Jile, 2007). However,there is some evidence suggesting that comorbid depressive and anxiety symptoms may exert a synergistic effecttogether (Kizilbash, Vanderploeg, & Curtiss, 2002).

Rarely has the relation between affective symptoms and attentional performance been examined in young adultsseeking psychoeducational evaluations, despite the fact that young adults constitute a growing population seeking suchservices (Gallagher, Gill, & Sysco, 2000). The one located study (Morasco, Gfeller, & Chibnall, 2006) did not obtainsignificant decrements in neuropsychological performance related to depression or anxiety; rather, they reported anon-significant trend toward anxiety being associated with improved performance among a sample of 70 participants.However, this study focused on intellectual and memory functioning and did not address attentional functioningin-depth.

Although previous studies of this genre have focused on general aspects of attention, few have focused on morespecific components of attentional functioning such as sustained attention and distractibility, which are highly relevantto ADHD (Barkley, Anastopoulos, Guevremont, & Fletcher, 1991). Prior studies have instead focused on variables moreconsistent with working memory, interference, and inhibition as well as other cognitive modalities such as memory andprocessing speed (Spreen & Strauss, 1991; Strauss, Sherman, & Spreen, 2006). Additionally, factor analytic studieshave confirmed that attention is not a unitary construct (Shum, McFarland, & Bain, 1990), and many specific tests ofattention (such as continuous performance tests, or CPTs) load on individual factors apart from more general tests thattap aspects of attentional functions (Kremen, Seidman, Faraone, Pepple, & Tsuang, 1992; Mirsky, Anthony, Duncan,Ahearn, & Kellam, 1991).

Clinical lore suggests that neurocognitive deficits should be interpreted cautiously when comorbid mood symptomsare present, and many clinicians thus are reluctant to interpret attentional impairments in the presence of depressive oranxiety symptoms (Groth-Marnat, 2000; Sweet et al., 1992). Empirical findings are needed to guide such decisions.The aim of this study was to evaluate the extent to which self-reported depressive and anxiety symptoms predictattentional performance in a young adult sample seeking psychoeducational evaluation after accounting for participanteffort. Consistent with negative findings from recent studies focusing on other cognitive domains (O’Jile, Schrimsher,& O’Bryant, 2005; Smitherman et al., 2007), we hypothesized that self-reported symptoms of depression and anxietywould be minimally associated with performance on common measures of attention in the present sample.

2. Method

2.1. Participants

The sample consisted of archival data extracted from adult patients referred for comprehensive psychoeducationalassessment to an outpatient mental health clinic located within a large southeastern university. Individuals having anIQ < 70 were excluded from data analysis, as were individuals scoring above 3.29 S.D. from the study sample as perTabachnick and Fidell (2001), so as to minimize the influence of extreme outliers. These exclusions yielded a finalsample size of 246 who had complete data for all variables of interest.

Three symptom validity tests (SVTs) were chosen to assess effort in this sample of 246 participants (see Bianchini,Mathias, & Greve, 2001 for a review of SVTs). Individuals giving insufficient effort during testing were identified andremoved from further analysis if they met any of the following criteria: (1) Wechsler Memory Scale-III (Wechsler,1997b) Auditory Recognition Delayed Index raw score <43 (Langeluddecke & Lucas, 2000), (2) Reliable Digits Score≤7 (Griffenstein, Baker, & Gola, 1994; Mathias, Greve, Bianchini, Houston, & Crouch 2002), or (3) Mittenberg’sformula (Mittenberg, Theroux-Fichera, Zielinski, & Heilbronner, 1995) discriminant function score >0.21 (Greve,Bianchini, Mathias, Houston, & Crouch, 2003). These criteria identified 85 individuals (35% of sample) as likely notgiving effort sufficient to consider their neuropsychological performance valid. These exclusions left a sample of 161individuals who had passed all measures of effort and response bias.

B.D. Hill et al. / Archives of Clinical Neuropsychology 23 (2008) 823–830 825

The mean age of the final sample of 161 was 22.58 years (S.D. = 5.45; range = 17–51); 52.80% of the participantswere male. One hundred forty-two were Caucasian, 12 were African-American, 5 were Hispanic, 1 was of Asiandescent, and 1 was of Middle Eastern descent. The mean IQ was 106.89 (S.D. = 12.42).

2.2. Psychiatric diagnoses

Axis 1 diagnoses were made according to DSM-IV criteria (American Psychiatric Association, 2000), determinedby the results of comprehensive psychoeducational assessment (including a thorough neuropsychological battery,clinical interview, and personality measures not described here), and confirmed by a licensed clinical neuropsychologist(WDG). The most common primary Axis I diagnoses of the sample were attention-deficit/hyperactivity disorders(n = 31), learning disorders (n = 24), depressive disorders (n = 19), anxiety disorders (n = 14), cognitive disorder NOS(n = 13), amnestic disorders (n = 5), bipolar disorders (n = 5), adjustment disorders (n = 4), and no diagnosis (n = 41);the remaining 5 participants had other primary Axis I diagnoses. Within the above diagnoses, there were 17 secondarydiagnoses of anxiety disorders and 9 secondary diagnoses of depressive disorders.

2.3. Materials and procedures

All patients provided informed consent for testing and for the potential use of their data for subsequent researchstudies. The study was approved by the local institutional review board. Patients were administered the followingcommonly used measures of attentional functioning as part of a larger neuropsychological battery: the Conners’ CPT(Conners, 1994), the d2 Test of Attention (d2; Brickenkamp & Zillmer, 1998), and the Trail Making Test (TMT A andB; Reitan, 1955). Additionally, the Wechsler Adult Intelligence Scale, 3rd edition (WAIS-III; Wechsler, 1997a) wasgiven to acquire a full scale IQ score and obtain two index scores putatively germane to the attentional construct, theWorking Memory Index and the Processing Speed Index.

The Conners’ Continuous Performance Test (CPT) is a computer-administered measure of attentional abilities thatrequires the participant to respond to all stimuli except the infrequent target stimulus. The Conners’ CPT can beconsidered an internally driven attentional task as the patient is given few external cues to attend to the stimulus. TheConners’ CPT primarily measures sustained attention and distractibility. It is the CPT used most commonly by clinicalneuropsychologists (Rabin, Barr, & Burton, 2005) and reliably differentiates individuals with ADHD from those withmood disorders (Advokat, Martino, Hill, & Gouvier, 2007). Variables of interest were: standard error (S.E.) variability,hit reaction time (RT) block change (Block RT), hit RT SE block change (Block SE), hit RT interstimulus intervalchange (ISI RT), and hit RT SE interstimulus interval change (ISI SE). The last four variables, in particular, have beenfound to be sensitive to attentional impairment in ADHD (Aaron, Joshi, Palmer, Smith, & Kirby, 2002).

The d2 Test of Attention (d2; Brickenkamp & Zillmer, 1998) is a paper-and-pencil cancellation task that measuresdistractability, selective attention, and sustained attention. Although used less frequently than the Conners’ CPT, thed2 is a measure of specific attentional domains with strong psychometric properties (Spreen & Strauss, 1998). Therespondent is presented with rows comprised of the letters “d” and “p” with varying numbers of marks surroundingthe letters. The respondent is instructed to only mark the letter “d” that has two marks and to ignore all other stimuli.In comparison to the Conners’ CPT, the d2 can be considered an externally driven measure of attentional abilities asthe examiner regularly prompts the respondent during the task. The variables of interest were: total number of itemsprocessed (TN), omission errors (OE), commission errors (CE), concentration performance (CP), and fluctuation rateof performance (FR).

The Trail Making Test (TMT; Reitan, 1955) is a timed task of rapid visual scanning and sequencing. The TMTpart A is a task of rapid visual scanning and processing speed, in which the respondent connects randomly arrangednumbers in consecutive order. In Part B, the respondent connects randomly arrange letters and numbers in consecutiveorder, alternating between numbers and letters. Part B thus measures the ability to alternate rapidly between cognitivetasks and to divide attention (Strauss et al., 2006). Although the TMT has traditionally been viewed as a measure ofexecutive functioning, factor-analytic studies have demonstrated that it shares most of its variance with measures ofattention (O’Donnell, McGregor, Dabrowski, Oestreicher, & Romero, 1994). Variables of interest were the t-scores ofcompletion times for parts A and B.

The Full Scale IQ score and two index scores from the WAIS-III were also included in this study, the WorkingMemory Index (WMI) and the Processing Speed Index (PSI). While they do not primarily assess pure attentional

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ability (Tulsky, Ivnik, Price, & Wilkins, 2003), these indices do measure related constructs and are commonly utilizedin psychoeducational assessments, particularly adult ADHD evaluations, as indices of attention/concentration ability.Their inclusion in the present study was based on their indirect relation to the attentional construct and to determinewhether other common aspects of the psychoeducational evaluation process are influenced by depressive and anxietysymptoms.

Patients were also administered the Beck Depression Inventory-II (BDI-II; Beck, Steer, & Brown, 1996) and theState-Trait Anxiety Inventory (STAI; Spielberger, 1983) as part of the evaluation procedure. The BDI-II is a 21-itemself-report measure of depressive symptoms which asks respondents to rate the severity of symptoms for the past 2weeks. The STAI is a 40-item self-report measure of general affective, cognitive, and physiological manifestationsof anxiety; 20 items inquire about current symptoms (State subscale), and 20 assess more longstanding symptoms(Trait subscale). Though both of these inventories can be considered indices of negative affectivity, factor analytic datasupport the notion that these measures assess different constructs in young adults (Alzeghoul et al., 2001; Karagozoglu,Masten, & Baloglu, 2005).

All measures were administered in accordance with their standardized protocols. Prior to data analysis, raw scoreson the CPT and STAI were converted into norm-referenced t-scores as outlined in their respective manuals (CPT:Conners, 1994; STAI: Spielberger, 1983). Raw scores on the TMT were likewise converted into norm-referencedt-scores using the norms established by Heaton, Miller, Taylor, and Grant (2004). Raw scores on the d2 were convertedinto norm-referenced scores (M = 100; S.D. = 10) as outlined in the d2 manual (Brickenkamp & Zillmer, 1998), andstandard scores for the WAIS-III indices were calculated using the WAIS-III manual (The Psychological Corporation,2002). Higher scores on the TMT, d2, and WAIS indices are indicative of better attentional performance. Higher scoreson the Conners’ CPT are associated with poorer attentional performance; likewise, higher scores on the BDI and STAIare associated with increased depression and anxiety symptomatology, respectively. Additionally, as the BDI-II datawere positively skewed, a square-root transformation was applied to this variable to normalize it for all further analyses.

2.4. Statistical analyses

To examine relations between measures of attention and self-reported symptoms of depression and anxiety, multipleregression analyses were utilized to determine the amount of unique variance in each criterion measure that the BDI-IIand STAI scales individually predicted. Unique variance accounted for is expressed as point estimates of effect sizes(incremental change in R2 values).

3. Results

3.1. Aggregate regression analyses

Table 1 displays the mean scores for the predictor and criterion measures. Although BDI-II and STAI scoreswere highly correlated with one another (rs ranged from 0.55 to 0.71), multicollinearity among regression predictorvariables was not of concern because our analytic strategy evaluated the predictive utility of the BDI-II and STAIscores separately. Unique variance accounted for by self-reported depression or anxiety was typically very minimal,as depression or anxiety accounted for less than 1.5% of the variance in scores on almost every measure of attention.The two exceptions were that BDI-II scores accounted for 3.7% of the variance in WAIS-III Processing Speed andthat STAI-Trait scores accounted for 2.0% of the variance in d2 CP scores; only the former was statistically significant(p = .015) but was rendered non-significant after correcting for multiple comparisons. Unique variance predicted bythe BDI-II ranged from 0.000 to 0.037. Unique variance accounted for by the STAI-State ranged from 0.000 to 0.009,while that accounted for by the STAI-Trait ranged from 0.000 to 0.020.

3.2. Secondary analyses

To confirm the above results, we repeated all analyses after separating the sample into subgroups of those witha depressive disorder diagnosis (n = 23), those with an anxiety disorder diagnosis (n = 29), and those with neither adepression nor anxiety diagnosis (n = 118), allowing for overlap between groups in cases where both disorders werediagnosed. Using an interaction between effect-coded subgroup and each affective predictor (Subgroup × BDI-II,

B.D. Hill et al. / Archives of Clinical Neuropsychology 23 (2008) 823–830 827

Table 1Mean scores (and standard deviations) for the BDI-II, STAI, and attentional measures

Measure Mean (S.D.)

BDI-II 13.42 (9.96)STAI-State 56.28 (11.55)STAI-Trait 59.45 (11.82)WAIS working memory 104.96 (11.89)WAIS processing speed 96.99 (12.82)TMT A 43.86 (9.94)TMT B 46.13 (10.04)CPT SE variability 55.13 (11.58)CPT Block RT 48.25 (14.00)CPT Block SE 53.07 (9.76)CPT ISI RT 59.85 (14.33)CPT ISI SE 54.02 (10.81)d2 total number 87.70 (10.99)d2 omissions 103.00 (5.91)d2 commissions 105.20 (5.83)d2 CP 93.75 (7.68)d2 FR 100.88 (7.27)

Note: BDI-II, Beck Depression Inventory-II; STAI, State-Trait Anxiety Inventory; WAIS, Wechsler Adult Intelligence Scale, 3rd Edition; TMT,Trail Making Test parts A and B; CPT, Conners’ Continuous Performance Test; d2, d2 Test of Attention Scores from the STAI, TMT, and CPTrepresent norm-referenced t-scores as described in the text. Scores from the d2 represent standardized scores with a mean of 100 and a standarddeviation of 10.

Subgroup × STAI-State, Subgroup × STAI-Trait), the amounts of variance accounted for were similar to those found inthe aggregate sample: Subgroup × BDI-II mean = 0.6%, Subgroup × STAI-State mean = 1.1%, and Subgroup × STAI-Trait mean = 1.4%. These small amounts of unique variance suggest that the previous regression analyses were notdifferentially influenced by diagnostic status. We also analyzed the aggregate data using an interaction analysis betweenBDI-II scores and STAI-State scores to assess possible synergistic effects of depression and anxiety. The interactionbetween BDI-II and STAI-State scores accounted for a mean of 0.8% of variance on the measures of attention.

4. Discussion

Relations between self-reported depressive and anxiety symptoms and specific measures of attentional functioningwere examined in a young adult sample seeking psychoeducational assessment. This study improved upon existingliterature by utilizing a large sample, taking into account both anxiety and depressive symptoms, excluding participantssuspected of giving insufficient effort, and incorporating a variety of attentional measures. Our results suggest that self-reported depressive or anxiety symptoms minimally affect attentional performance in this population. Three lines ofevidence support this conclusion: (a) R2 point estimates indicating that self-reported depression and anxiety accountedfor less than 1.5% of unique variance on almost every measure of attention; (b) confirmation of these results withdiagnostic subgroup analyses; and (c) observation that depression and anxiety exerted minimal synergistic influence.These findings suggest that attentional deficits in this population, when they are observed, are most likely indicativeof actual attention problems rather than epiphenoma associated with self-reported symptoms of depression or anxiety.

Previous research using different samples has indicated that self-reported mood symptoms exert minimal influenceon tasks of verbal learning (O’Jile et al., 2005) and executive functioning (Smitherman et al., 2007). The present studyextends those findings to tasks of attention within a younger sample referred for assessment of educational/learningdifficulties. Our results coincide with those of Morasco et al. (2006), who examined the effect of mood on memoryand intellectual functioning in a similarly aged assessment-seeking sample. However, our study did not confirm theirreport of a non-significant trend toward anxiety actually improving neuropsychological performance, perhaps becausethey did not focus specifically on attention and used a smaller sample.

It is plausible that psychopathology severity, versus the mere presence of symptoms, may account for disruptionsin cognitive functioning. While the participants in this study included those who met criteria for an Axis I depressiveor anxiety disorder, the sample also included individuals reporting subthreshold symptoms. However, attentional

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functioning was unrelated to both symptom severity and diagnostic status in both the aggregate sample and diagnosticsubgroups. We also failed to find evidence of any synergistic effect of self-reported depressive and anxiety symptoms.In conjunction with the extant literature (Grossman, Kaufman, Mednitsky, Scharff, & Dennis, 1994; Kaufman et al.,1994; Rohling et al., 2002), the present results challenge the conventional notion that symptoms of depression andanxiety detrimentally impact performance on attention-related measures.

Two limitations of our study are worth noting. First, our sample was comprised primarily of young college studentswho are likely to be higher-functioning than samples used by other studies of this genre. The present results thus shouldnot be generalized to groups of individuals that differ greatly from the current population of interest, such as olderadults or individuals with more severe psychopathology (e.g., inpatients or those with severe depressive or anxietydisorders). Secondly, the attentional measures used here may not be sensitive enough to detect extremely minor changesin cognitive performance that could result from symptoms of depression or anxiety. However, such possible minorchanges are unlikely to be clinically significant. Ultimately, neither of these potential limitations greatly weakens thegeneralizability of our results to the sample of interest—young adults seeking psychoeducational evaluation.

Our incorporation of imbedded SVTs indicated that 35% of our sample was suspected of poor effort. This highpercentage is likely a function of our conservative decision to exclude participants who failed any of three SVTindices, but the sheer prevalence of suboptimal effort underscores the need to assess effort in this population. Thoughour statistical results were similar whether including or excluding individuals giving suboptimal effort, SVTs likelyconstitute good clinical practice and may clarify the diagnostic picture in cases complicated by the presence of severemood symptoms.

In summary, the current study has direct relevance to those who field referrals for evaluation of suspect ADHDand learning disorders in young adults. Within this context and population, the present findings indicate that whenattentional deficits are observed, they are likely not accounted for by self-reported symptoms of depression or anxiety.Our results suggest that mood-related explanations for attentional impairments observed during psychoeducationalevaluations should be entertained with great caution, particularly if such explanations are informed solely by patientself-report.

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