Designing Assess Individual Differences Processing

29

Designing a Measure of Visual SelectiveAttention to Assess Individual Differencesin Information ProcessingBruce J. Avolio, Ralph A. Alexander,Gerald V. Barrett, and Harvey L. Sterns

The University of Akron

A new method for determining individual differ-ences in information processing was developed andillustrated. The measure, Visual Selective Attention,was constructed according to the parameters andspecifications of a standardized measure of auditoryselective attention. Emphasis was placed upon es-tablishing the relationship of this new measure withtraditional measures of information processing (i.e.,perceptual style and selective attention). The resultsprovided initial evidence for the reliability and val-idity of the new measure. Applications for VisualSelective Attention and interpretation of the find-ings are discussed in view of the current state of theinformation-processing literature. Implications foradditional research focus upon the practical appli-cations of the new measure.

The concern for individual differences in per-formance has grown dramatically in psychology.This growth is particularly evident with researchusing the Rod-and-Frame Test (RFT) developedby Witkin, Lewis, Hertzman, Machover, Meiss-ner, and Wapner (1954). As reported by Gold-berg (1979), the RFT was initially developedfrom the research focusing on spatial orienta-tion. In later analyses the RFT was applied as anobjective measure of personality. However, inthe context described here, the RFT will be con-sidered a measure of information processing(i.e., perceptual style).

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APPLIED PSYCHOLOGICAL MEASUREMENTVol. 5, No. 1, Winter 1981, pp. 29-42@ Copyright 1981 Applied Psychological Measurement Inc.

Considering the work with the RFT in the lastdecade, there have been few major efforts af-

forded to the investigation of information-pro-cessing ability and how different abilities relateto &dquo;real world&dquo; behavior. Some notable excep-tions to this generalization have been presentedin the area of automobile accident involvementand aircraft flight performance (Barrett, Mihal,Panek, Stems, & Alexander, 1977; Gopher &

Kahneman, 1971; Kahneman, Ben-Ishai, &

Lotan, 1973; Mihal & Barrett, 1976). Mihal andBarrett (1976) demonstrated the predictive va-lidity of selective attention ability and percep-tual style for determining those individuals in-volved in a higher proportion of accidents. Theseresults were supported by Barrett, Mihal, Pa-nek, Stems, and Alexander (1977). Gopher andKahneman (1971), who originally developed theAuditory Selective Attention Test (ASAT), dem-onstrated its utility in predicting aircraft flightperformance. The accumulation of this researchprovided substantial support for auditory selec-tive attention as a predictive tool in real worldsettings.

Recently, Barrett, Alexander, and Forbes

(1977) combined measures of information-pro-cessing ability into an integrated model to facili-tate the understanding of underlying processesassociated with task performance. The modelwas comprised of components of information-processing ability (e.g., selective attention, per-

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30

ceptual style, reaction time). The course in thedevelopment of this model has been to identifyor to construct measures of information process-ing that relate to other individual difference

measures, as well as to the task at hand. This

emphasis was demonstrated in the previous re-search of Mihal and Barrett (1976) and Barrett,Mihal, Panek, Stems, and Alexander (1977).Combining different measures of informationprocessing into a test battery, they demonstrateda moderate relationship between divergent in-formation-processing measures, in addition toestablishing a linkage between processing ca-pacity for separate sensory modalities (i.e., vi-sion versus hearing). As stated previously, bothmeasures separately were predictive of accidentinvolvement.One important result noted above concerns

the relationship in performance for different

sensory modalities. Researchers have focused

upon intersensory relationships in informationprocessing, specifically with vision and hearing.However, these research efforts have tended to

place a greater emphasis on measures of audi-tory versus visual selective attention. This trend

may be partially attributed to Broadbent (1958)and Von Wright (1968), who cautioned research-ers in conducting investigations with vision, dueto the confounding nature of eye movement pat-terns. Consequently, very few measures of visualattention were developed. The overemphasisplaced on auditory selective attention is evidentin the theoretical models of information process-ing, which specifically focus upon auditory per-ception (e.g., Broadbent, 1957; Kahneman,1973; Triesman, 1969).Ironically, the emphasis placed upon develop-

ing measures of auditory information processingtends to minimize the importance that the visualmodality demonstrates in influencing other sen-sory mechanisms (Colavita, 1971; Gibson & Yo-

nas, 1966; Kahneman, 1973; Pick, Warren, &

Hay, 1969; Rock & Victor, 1964). Kahneman(1973) emphasized this point by indicating thatthe mere position of the eye may determine thedirection of sensory attention.

The effects of vision on overall sensory perfor-mance seems to have been clearly demonstratedin past research. With this evidence accumu-lated, it seems questionable that an auditorymeasure of selective attention should be used to

predict tasks requiring visual processing.

Objectives

The purpose of the present investigation wasto develop a measure of visual selective attentionthat correlates with existing measures of in-

formation-processing ability. If moderate cor-relations are obtained between traditional mea-sures of information-processing ability (e.g., au-ditory selective attention and perceptual style)and a newly constructed measure of visual selec-tive attention, then initial evidence for the con-struct validity of this measure would be estab-lished. A moderate correlation would be desir-

able, since the ultimate goal was to use this newmeasure with other traditional measures to in-crease the predictive validity of the test batteryfor real world performance.An intermediate objective of this investigation

was to supplement the existing literature per-taining to a central processing mechanism thatcoordinates information-processing perfor-mance. For instance, Birch and Lefford (1967)indicated that the existence of a monitoring sys-tem that accumulates data across multiple sen-sory channels was highly probable. Evidence tosupport this contention was provided by Fisherand Rubenstein (1975a, 1975b). These research-ers demonstrated a significant relationship be-tween visual and auditory processing which in-creased with age. Support for a central mecha-nism has also come from additional research

(Forbes, Barrett, Alexander, & Phillips, 1976;Gopher, 1971; Kahneman, 1973; Webster &

Haselrud, 1964).To summarize, this investigation had two spe-

cific goals. The primary objective was the de-velopment of a reliable measure of visual selec-tive attention that can be used in future investi-

gations to predict individual differences in &dquo;real



31

world&dquo; performance. A secondary objective wasto provide additional evidence for the existenceof a central processing mechanism.

Method

Subjects

Sixty university student volunteers from a

large midwestem city participated in the study.The group was comprised of 30 males and 30 fe-males. The students’ ages ranged from 18 to 26.All students were selected from a universitypopulation and were in good health.

Experimental Tests

There were six relevant measures admin-istered to the group of students, although onlyfour will be analyzed in this report. The GroupEmbedded Figures Test (GEFT) developed byWitkin, Oltman, Raskin, & Karp (1971) was ad-ministered to all students. This test consists of

three parts in which the subject extracts a rele-vant stimulus amidst an irrelevant background.The first part was a practice section to help fa-miliarize the subject with the procedure. Thenext two sections were the test trials, which con-sisted of nine complex figures each. The subjectwas allowed 5 minutes to complete each test sec-tion. The subject’s score equals the total numberof figures correctly traced in both test sections.The RFT Model V-1260-M2, from the Poly-

metric Company, was also used as a measure ofperceptual style. The apparatus consists of aluminous rod surrounded by a luminous frame,which both rotate separately. This task was ad-ministered in a room that was specifically de-signed to decrease the effects of ambient light.The room was completely painted black with ablack carpet on the floor. The doors were sealedto eliminate light. Each subject was admin-istered the test as described by Witkin et al.

(1954), while seated in a stationary tilting chair(Model No. 18-20 Marietta Apparatus Com-pany). The chair was placed directly in front ofthe apparatus at a distance of 3 meters.

Throughout the presentation, the rod and framewere at the initial starting positions of 28° left orright.The procedure for setting the apparatus was

standard across trials. The experimenter movedthe rod in increments of 3° each time the subjectresponded. The subject stopped the experiment-er when the rod appeared vertical. After everyeighth trial the subject was placed upright for aduration of 1 minute with eyes closed before

continuing on to the next series. The subject’sscore was computed by the average number ofdegrees of error for the three series.The ASAT (Mihal & Barrett, 1976) presents

24 dichotic messages simultaneously to the sub-ject’s ears with volume adjusted for individualhearing levels. Each dichotic message was bro-ken down into two parts consisting of a series ofpairs of numbers and letters. The initial portionof the tape informed the subject of the nature ofthe test and his/her responsibilities. After com-pletion of the instructions, there were four prac-tice messages to help familiarize the subject withthe procedure. The practice and 24 test mes-sages were based on the following framework.Each message began with a verbal announce-

ment of the message number, which the subjectreported to the experimeter. After the voice onthe tape had indicated the message number,there was a 2.5-second interval before the rele-vant tone was initiated. The relevant tone was

presented for 200 milliseconds. A 2500 Hz toneindicated that the information on the right earchannel was relevant. A 250 Hz tone indicatedthat the left ear channel was relevant. It is im-

portant to note that both channels were present-ed simultaneously; therefore, the tones indicatedwhich channel to attend to and which to ignorefor each part of the message once the tone hadbeen presented. There was a 1.5-second gap be-fore 16 pairs of numbers and letters were pre-sented. These pairs were presented at a rate oftwo per second. Each pair consisted of eithersingle English letters and/or digits ranging from0 to 9 (e.g., B 8). After the 16 pairs were pre-sented (i.e., Part 1), there was a 1.5-second inter-



32

val before the relevant tone was presented forPart 2 of the message. The relevant tone (i.e.,2500 Hz or 250 Hz) was presented for 200 milli-seconds. After the tone was terminated, a 1.5-second interval followed before the presentationof pairs comprising Part 2 of the message.The second part of each message contained

three pairs of numbers, which were preceded byeither 0, 1, or 2 additional pairs of letters. Fol-lowing the presentation of the last pair in Part 2,there was a 5-second interval to allow the subjectto prepare for the presentation of the next mes-sage number.The subject’s task for both Parts 1 and 2 of

each message was to report aloud the digits ap-pearing on the channel that was indicated asbeing relevant. For Part 1 of all 24 messages, therelevant channel had either 2 or 4 relevant dig-its, while the irrelevant channels always had 6digits. For Part 2 of each message there were al-ways 3 relevant and 3 irrelevant digits presented.The scoring procedure for the ASAT consisted

of omission and intrusion errors. An omissionerror was scored when the subject failed to re-port a digit from the relevant channel. An intru-sion error was indicated when the subject report-ed a digit from the irrelevant channel. The re-porting of letters was very infrequent and there-fore not considered an intrusion error. The sub-

ject’s overall score was comprised of total omis-sion and intrusion errors across the 24 messages.The ASAT was presented on a Sony Solid

State Tape recorder, Model TC-353. The head-phones were Pickering stereo headphones Mod-el PH-4933. The presentation of the messageswas set at a level of amplification that was com-fortable for each subject.A Visual Selective Attention Test (VSAT) was

constructed to approximate a visual counterpartof the ASAT. The test was presented to subjectsthrough a Tektronix CRT screen Model No.4010 linked to a PDP 11E10 computer. Thecharacters appearing on the screen were num-bers and letters. The size of the characters was 3mm. (.58 visual angle subtended), which is in ac-cord with Purcell, Stanovich, and Spector (1978)

specifications. The pairs of numbers and letterswere presented in the center of the screen. Eachof the characters making up the pairs were pre-sented at 7.5 mm. on either side of the center

point of the screen. The major differences be-tween the auditory and visual measures of atten-tion were in the requirements of the subjects andthe pace of each test. With the auditory test,subjects attended to the left or right channel de-pending on the cue. Rather than split an indivi-dual’s field of vision, which does not representnormal visual processing, it was felt that havingsubjects respond to particular stimuli in boththe left and right channel would allow for a moreaccurate assessment of actual visual processing.This difference in methodology undeniablyplaces some constraints on the conclusions.Another difference was in the pace at which

the stimuli were presented. With the ASAT thepace of presentation was constant across mes-sages. With VSAT the speed of presentation wassystematically decreased across trials to evaluatethe upper range of individual ability. Neither ofthese differences was expected to have a majorimpact on the analysis of the relationship be-tween visual selective attention, auditory selec-tive attention, and perceptual style.The subjects were instructed on the nature of

the test and located approximately 30 cm. fromthe screen. After the instructions, the subjectsreceived four practice trials to help familiarizethem with the procedure. After the practice tri-als ended, the test messages began. There were24 test messages consisting of two parts each.The practice trials followed the same format asthe test messages; therefore, a description of thetest format will suffice.

At the beginning of each message, the messagenumber was presented and then erased. After a2.5 second interval, the relevant cue word was

presented for half a second. The cue words cof-fee and apple were chosen to correspond withthe relevant cues of an alternative measure of

auditory attention not reported here. The cueword coffee indicated for the subject to respondto all odd numbers in the left channel and even



33

numbers in the right. The word apple indicatedthat even numbers in the left channel and odd inthe right were to be reported. The instructionalset forced the subject to attend to both channels,therefore approximating normal visual process-ing. Memory factors were eliminated by suffi-cient practice of the instructional set.The cue words were presented on either side of

the midpoint of the screen to control for a posi-tion effect. Following the erasure of the cueword, there was a 2-second interval before Part1 of the message was presented. Part 1 consistedof 16 pairs, each pair consisting of either anEnglish letter and number, two English letters,or two numbers. The numbers ranged from 0 to9, with the exclusion of the number 8 due to itssimilarity with the letter B.Following the erasure of the last pair of Part 1,

there was a 2-second interval before the pre-sentation of the word for Part 2 of the message.After the cue word was erased, there was a2-second interval before the presentation of thesecond set of pairs. The second part of eachmessage always contained pairs of digits. Thesepairs were preceded by either 0, 1, or 2 addi-tional pairs of letters. Following the completionof Part 2, there was a 5-second interval beforethe presentation of Message Number 2, whichallowed the subjects to prepare for the nextmessage.The format of the test, summarized in Table 1,

called for a decrease of 50 milliseconds (msec) inthe presentation of each pair following everythird message. Consequently, each pair in thefirst three messages was displayed on the screenfor 400 msec; the next three messages presentedeach pair at a rate of 350 msec per pair. Follow-ing this pattern across the 24 messages, the lastthree messages presented each pair for a periodof 50 msec. All other specifications for theVSAT were set as close as possible to those usedby the ASAT. Scoring was also based upon thesame procedure used in the auditory test (i.e.,omission and intrusion errors).

Procedure

All subjects were tested individually under thesame conditions. At the beginning of the experi-ment, each subject had a detailed explanation ofthe purpose of the experiment. The total sampleof individuals was partitioned into subgroups.Subjects were assigned to groups randomly withequal numbers of males and females in eachgroup (e.g., five and five). The purpose of parti-tioning the subjects into groups was to counter-balance for order effects. To control order ef-

fects, the critical tests of the hypotheses (i.e.,ASAT and VSAT) were presented to each groupin several possible positions to counterbalancefor order. The critical tests were separated in theadministration of the battery by four other testmeasures (i.e., Competing Messages Test, RFT,Pace of Information Flow, and GEFT). One-wayanalyses of variance to test for order effects didnot yield any significant effects. There were novalues that were even marginally significant.The separation of critical tests in time also

helped to minimize fatigue effects. Additionalanalyses for differences due to the sex of the sub-ject did not reveal any significant trends; there-fore, correlational analyses and conclusions werebased on the overall sample and the four mea-sures of interest (i.e., VSAT, ASAT, GEFT,RFT).

Results

Means and standard deviations are presentedin Table 2 for the computed scores for each in-formation-processing measure. The data indi-cated some restriction in range with the scores

acquired. These findings may be attributed tothe ages of the subjects, that is, younger indivi-duals often perform better on measures of in-formation processing (Panek, Barrett, Stems, &

Alexander, 1978).The major intention was to investigate the es-

tablishment of a new measure of selective atten-

tion. Nunnally (1978) has suggested that all new



34

Table 1Message Format Summary for Visual

and Auditory Selective Attention

measures should be tested for their reliability;therefore, tests for internal consistency wereconducted using coefficient alpha. This statisticwas the most appropriate indication of reli-

ability based on the design of the selective atten-tion measures. The reliability estimates are pre-sented in Table 3. The reliability estimates forthe VSAT indicated that this measure obtainedconsistent responses to the stimulus presenta-tions throughout the task. The consistency in re-sponding provided some evidence for the reli-ability of this measure.

Pearson product-moment correlations were

computed between total scores on all of the testsin the battery. Table 4 presents the results ofthese analyses. The relationship between themeasures of selective attention yielded a signifi-cant positive correlation. VSAT also related sig-nificantly to the GEFT. The relationship withthe RFT was not significant. A significant neg-ative relationship between the VSAT and theGEFT was obtained, since the attention mea-sures were based on total incorrect, whereas theGEFT was total correct.



35

Table 2Means and Standard Deviations for

Computed Information-processing Scores(n=60)

To further analyze the relationship betweenauditory and visual attention measures, the

component scores from each were computed andcorrelated (see Table 5). Partitioning the totalscores resulted in patterns of correlations thataided in clarifying the relationship of these twomeasures. Comparing the intercorrelations be-tween the two measures for Parts 1 and 2, therelationships among intrusion errors were con-sistently low and nonsignificant, whereas omis-sion errors demonstrated a higher frequency ofsignificant relationships with each other. Thispattern may result from the subjects’ reluctanceto generate responses they were unsure of (i.e.,

intrusion errors) versus having responses go bythat they were unprepared to initiate (i.e., omis-sion errors), therefore decreasing the amount ofvariance in intrusion error scores that could at-tenuate the correlations.Another interesting pattern of correlations

arose from the relationships between Parts 1 and2 across the two measures of attention. For Part2 of the auditory measure, the omission and to-tal error scores correlated significantly with cor-responding scores of the visual attention mea-sure more frequently and higher than Part 1

component scores. This pattern was true forboth parts of the VSAT. Overall, Part 2 omis-



36

Table 3Tests for Internal Consistency on the

Selective Attention Measures Using Coefficient Alpha(N=60)

sion scores exhibited higher correlations, for

both measures, than those of Part 1. An ex-

planation for this finding is given below.The intercorrelations of subscores within each

test demonstrated consistently high significantrelationships. Relationships involving intrusionerror scores were often somewhat lower thanthose demonstrated between omission error

scores, although still significant in most cases.Again, the lower correlations demonstrated byintrusion error scores may be partially attri-buted to the nature of the score and the ra-tionale previously discussed. Overall, the inter-correlations within the specific measures wereconsistently strong and in the positive direction.

To determine whether the relationships be-tween component scores for the attention mea-sures would correlate significantly with scoresfrom the perceptual style measures, additionalanalyses were conducted. The results from theseanalyses, summarized in Table 6, did not varysubstantially from those displayed with totaloverall scores for the attention measures. Again,omission errors for the ASAT did provide highercorrelations with the measure of interest; how-ever, this pattern was not evident in the first partof the VSAT. Also of interest is the lack of signif-icance demonstrated with Series 3 of the RFTversus Series 1 and 2. In Series 3 the individualremained erect while the apparatus was manip-

Table 4Correlations Among Total Scores

(N=60) _



37

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ulated. Varying the individual’s bodily orienta-tion (i.e., Series 1 and Series 2) showed a demon-strable effect on the relationship between per-ceptual style and selective attention. Perhaps theincreased difficulty in performing Series 1 and 2contributed to the relationships in componentscores between selective attention and percep-tual style.These data show that the VSAT correlated

with measures of auditory selective attentionand perceptual style. These results provide someevidence for the construct validity of this newmeasure in assessing individual differences ininformation processing.A power analysis was conducted to determine

the number of subjects necessary to achieve sig-nificance for testing differences between depen-dent correlation coefficients (i.e., Hotellings Ttest analyzing r12 versus r13, given r23), given apotentially moderate effect size (i.e., 30). Withthis effect size a sample of 57 subjects was re-quired to obtain a two-thirds probability of re-jecting the null hypothesis, given that the al-ternative was true for a one-tailed test of signifi-cance at a .05 level (Cohen, 1969, Table 4.4.1, p.130). Consider the null hypothesis as stating nodifference in correlations between the selectiveattention measures (i.e., Variables 1 and 2) ver-sus their relationship with measures of percep-tual style (i.e., Variable 3). The alternative hypoth-esis indicated that measures of selective atten-tion had significantly higher relationships witheach other than their corresponding relation-ships with perceptual style. The results of thetests for dependent correlation coefficients arepresented in Table 7.Since the attention measures were supposedly

tapping the same construct, it was expected thatthese measures would relate significantly higherwith each other than their corresponding rela-tionships with the remaining tests in the battery.The results partially supported this contention.The VSAT did correlate highly with the auditorymeasure; however, this correlation was not sig-nificantly higher than the one obtained betweenVSAT and the GEFT. With the RFT the al-ternative hypothesis was supported.Downloaded from the Digital Conservancy at the University of Minnesota, http://purl.umn.edu/93227.

May be reproduced with no cost by students and faculty for academic use. Non-academic reproduction requires payment of royalties through the Copyright Clearance Center, http://www.copyright.com/

38

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39

Table 7T-tests for Dependent Correlation Coefficients

Comparing the Relationships Between TotalScore for Selective Attention and Perceptual Style

Thus, the VSAT did correlate significantlyhigher with a similar measure of attention versusits relationship with one measure of perceptualstyle. Since the VSAT did relate to all measures,it might be concluded that it was samplingabilities across several domains (e.g., visual at-tention, auditory attention, perceptual style).

Discussion

The results obtained confirmed the relation-

ship between visual and auditory selective atten-tion and emphasized the reaffirmation of pastliterature concerning the existence of individualdifferences in information processing (i.e., Bar-rett, Alexander, & Forbes, 1977; Barrett, Cabe,& Thornton, 1968; Barrett, Mihal, Panek,Sterns, & Alexander, 1977; Forbes & Barrett,1978; Gopher & Kahneman, 1971; Kahnemanet al., 1973; Mihal & Barrett, 1976). The resultsreconfirmed individual differences in informa-

tion-processing ability.As previously indicated, there were differences

between Part 1 and Part 2 errors for both atten-tion tests and between their respective relation-ships with perceptual style. An explanation forthese findings comes from Gopher and Kahne-man (1971), where Part 2 omission and intrusionerrors were represented as being more reliableand valid predictors of performance. In explain-ing this finding the authors attributed the differ-ences to a reconsideration of selective orienta-

tion from the first half of each message to thesecond.

Through these changes in selective orienta-tion, the second portion of each message pro-vided a more valid estimate of selective attention

ability. Gopher (1971) provided additional evi-dence for the change in selective orientation,which corresponds in shifts from Part 1 of eachmessage to Part 2. The importance of Gopher’sresults arises from the modality which was ex-plored (i.e., vision); the results provided evidencefor variations in selective orientation being asso-ciated with changes in visual focal attention. Go-pher’s findings generalized the concept of shiftsin selective orientation across sensory mo-

dalities. Based on those results, the use of theVSAT in a real world setting could contribute topredictive capacity in determining one’s abilityto rapidly shift selective orientation.The results indicated that significant relation-

ships existed between various information-pro-cessing measures, supporting the existence of acentral processing mechanism. However, the twoselective attention tests did not relate signifi-cantly higher with each other than their relation-ships with the GEFT. This finding can be ex-plained by the earlier comments of Witkin,Goodenough, and Oltman (1977). In their initialconception both the RFT and GEFT were con-sidered similar measures of the same construct

(i.e., individual differences in disembeddingability in perception or field dependence-inde-



40

pendence). The ability to disembed perceptuallywas shown to be related with intellectual activi-

ties, cognitive functioning, and overall structur-ing competence. Research further incorporateda wide array of spatial-visual cognitive factorsinto the dimension of field dependence-indepen-dence. The result of this consistent line of re-search indicated that the processes involved inthe RFT and GEFT may not be isomorphic, re-sulting in differing relationships between theseand other information-processing measures.

This pattern may also indicate differential com-

ponents existing within cognitive structures thatare related but that allow for the processing ofinput from divergent channels (i.e., visual andauditory).Another possible reason for the VSAT not

being correlated significantly higher with the au-ditory attention measure may be attributed to vi-sual dominance on task performance. In review-ing the literature, research concerning the effectof vision on sensory performance indicated thatthe visual modality can affect perception inother sensory modalities (e.g., Kahneman, 1973;Pick et al., 1969; Rock & Victor, 1964). If visioncontributed a dominating effect to performance,then obtaining differences between tasks depen-dent on the visual modality (i.e., RFT andVSAT) seems highly unlikely. Additional sup-port for this contention comes from the low rela-tionship between auditory attention and percep-tual style.The other area of concern relates to the format

for the VSAT, which was based upon an audi-

tory measure used by Mihal and Barrett (1976).Using this measure (which has been shown to bepredictive of selective attention ability) as a

model, the results displayed the potential for

using VSAT as an alternative measure of selec-tive attention ability. Several inferences can bemade based on these results. Since auditory se-lective attention has been shown to be related toaccident involvement and pilot competency(Barrett, Alexander, & Forbes, 1977; Barrett,Mihal, Panek, Stems, & Alexander, 1977; Go-

pher & Kahneman, 1971; Mihal & Barrett,1976; Kahneman et al., 1973; Thomton et al.,1968; Trankell, 1959), and the VSAT was re-lated to a measure of auditory attention, the useof both measures in a diagnostic battery may re-sult in an increment in predictive validity.Further evidence for the use of the VSAT in

real world settings comes from its relationshipwith perceptual style. Abilities indicative of per-ceptual style also have been shown to be relatedto accident involvement and monitoring perfor-mance (Barrett, Alexander, & Forbes, 1977;Barrett, Mihal, Panek, Stems, & Alexander,1977; Barrett & Thomton, 1968; Barrett,Thomton, & Cabe, 1969; Forbes & Barrett,1978; Harano, 1970; Mihal & Barrett, 1976),therefore providing additional evidence for theuse of VSAT combined in a diagnostic batterywith other information-processing tests to pre-dict real world behavior.Based on previous literature, McDonnell and

Perusse (1974) have been the only other authorsto attempt construction of a visual analog of anauditory attention measure. An important dif-ference in their design and the design in thepresent study involves the process of validation.The present study modeled the visual test afteran accepted auditory measure of attentionshown to be predictive of performance in realworld settings, whereas McDonnell and Perussechose to construct both tasks based upon theirown parameters rather than comparing them toan alternative measure of information process-ing (i.e., ASAT).To summarize, a reliable test of Visual Selec-

tive Attention was developed based upon thespecifications presented by Mihal and Barrett(1976). Based on these results, the next logicalphase for use of this new measure would be todetermine its applicability for predicting realworld performance (e.g., driving performance).If this new measure provides increments in ac-countable variance over existing information-processing tests, further use of the measure inmore diverse settings could be warranted.



41

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Acknowledgments

This paper was supported in part by the AndrusFoundation, Contract No. 223-822-0375, and Per-sonnel and Training Research Programs, Psycholog-ical Sciences Division, Office of Naval Research, un-der Contract No. N00014-75-C-0985, NR 151-377.This paper is based in part upon an unpublishedmastPr’s thesis conducted by thefirst author.

Author’s Address

Send requests for reprints or further information toBruce J. Avolio, Psychology Department, The Univer-sity of Akron, Akron, OH 44325.



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