Validation of an Australian Academic Stress Questionnaire

Australian Journal of Guidance & Counselling

Volume 19 Number 1 2009 ▲ pp. 56–70

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Address for correspondence: Natasha Lakaev, ‘Omaroo’ Hunter Street, Burringbar NSW 2483, Australia. E-mail:[email protected]

Validation of an Australian AcademicStress Questionnaire

Natasha LakaevBond University, Australia

The aim of the study was to establish the Lakaev Academic Stress Response Scale(LASRS; Lakaev, 2006) as a valid and reliable measure of stressresponses. The sample consisted of 375 Bond University studentsfrom several countries (142 Australia, 5 New Zealand, 68 UnitedStates, 8 Canada, 65 Asian, 66 Europe and 21 other) and fromvarious levels of tertiary education (266 undergraduate and 109 post-graduate). Participants completed six self-report questionnaires thatrelated to, acculturative stress, somatic stress symptoms, academicstress, stress responses, extraversion and general stress in order todetermine convergent and divergent validity. The LASRS was shownto have sound psychometric properties and was suggested to be asound way of measuring academic stress responses, particularly forAustralian students. The results are discussed in terms of past tertiaryacademic stress research and suggestions for future investigations.

■ KEYWORDS: cross-cultural academic stress, Australian academic stress,Stress Response Scale, cross-cultural

Tertiary students experience significantly greater than average levels of stress (Hall,Chipperfield, Perry, Ruthig, & Goetz, 2006; Moffat, McConnachie, Ross, &Morrisson, 2004). This stress comes from various aspects of life including develop-mental and social changes, financial and accommodation problems, work demands,and the specific demands of academia (Misra & McKean, 2000; Ross, Cleland, &Macleod, 2006). Often the demands of work, study and personal needs collide,tipping the balance and resulting in disequilibrium and excessive stress (Michie,Glachan, & Bray, 2001). Poor coping strategies and personality types may result inadditional stress in certain individuals, leading to negative patterns of behaviourand decreased academic performance (Abouserie, 1994; Tyssen, Dolatowski, Rovik,Thorkildsen, Ekeberg et al., 2007). When discussing student populations it is alsopertinent to consider the prefrontal cortex, which assists decision making, as oftenit does not complete its development until age 21 or later (Kagan & Baird, 2004).This variability in students’ maturity suggests even greater variability in individualsstress interpretation, responses and reactions to stressors.

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In Australia, there have been a small number of studies published regardinginternational student academic stress and acculturative psychological distress (e.g.,Ballard, 1987; Burns, 1991; Kennedy, 1995; Khawaja & Dempsey, 2007; Oei &Notowidjojo, 1990; Radford, Mann, Ohta, & Nakane, 1993); however, there hasnot been a great deal of investigation into domestic born Australian student aca-demic stress. Much of what exists is several decades old (e.g., McMichael &Hetzel, 1974) or is specific to physiological reactions to the transition from second-ary to tertiary education (e.g., Boyd & Chaseling, 1992; Farnill & Robertson,1990). For example, Farnill and Robertson assessed 261 first-year Australian stu-dents. The students completed the Brief Symptom Inventory (Derogatis, 1975),which assesses psychological symptoms, mid-year (low stress time) and at the endof the academic year (higher stress time). The results found that 42% of studentshad frequent sleep disturbances that aligned with stressful life experience at thehighest stress times of the university year. The sleep disturbances associated withacademic study may result in physical stress placed on the body and therefore theincreased stress students experience through the year may result from increasedphysical strain. Another study conducted by Winefield (1993) found thatAustralian undergraduate students suffered psychological distress, due to less sup-portive interactions with other students, teaching staff and financial hardship. It isintended that the current study be added to the Australian literature to helpdevelop a more precise picture of how Australian-born nationals react to academicstress along with stress mediators.

In comparison to their domestic counterparts, foreign students are at higher riskof psychological problems due to stress (Huan, Yeo, Ang, & Chong, 2006; Lee &Bradley, 2005; Mortenson, 2006; Sandhu & Asrabadi, 1991). International stu-dents have a high risk of psychological problems due to the many adjustments theyare required to make in their social, academic and cultural lives when they enter anew society (Sandhu & Asrabadi). They suffer from loneliness due to homesick-ness, anxiety, depression and disorientation. Numerous studies have found this tobe the case in America (Brown & Lee, 2005), Britain (Greenland & Brown, 2005;Huan et al) and Australia (Sonderegger & Barrett, 2004). Chinese and East Asian,Malaysian, Korean, African, Turkish, Latin American, and European students whostudy internationally have all reported heightened academic stress and accultura-tive issues within their host country (Huan et al; Lin, 2007; Ninggal, 1998; Odera,2007; Shin, Han, & Kim, 2007; Tomas-Sabado, Qureshi, & Montserrat, 2007).

When looking at stress responses and reactions across cultures there are differ-ences in the expression of stress between cultures. It has been shown that Asian stu-dents react to academic failure with shame, embarrassment and loss of face withintheir social framework, especially in regards to their family (Matsumoto, 1991).Members of Asian cultures (e.g., Chinese and Japanese) view any outward displayof emotion in regards to personal distress as disruptive of the social atmosphere(Wellenkamp, 1995). When Americans experience stress it is viewed as an obstruc-tion to attaining goals, needs and desires (Mesquita, 2001). Mesquita found thatAmerican tertiary students view academic failures as missed opportunities and sub-sequently express the resulting stress as frustration. American students then tend togo into an action mode of expressing emotions (Frijda, Kuipers, & Schure, 1989)by analysing the issue and their persona extensively (Burleson & Mortenson,

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2003). Hence, American students actively seek social support (Matsumoto). Muchlike Americans, Europeans perceive stress as something to be overcome or con-quered which may build resilience and capacity to achieve (Mesquita). In a studylooking at Norwegian students’ personality traits that would surface under stress, itwas found that neuroticism was a trait that predicts vulnerability to stress (Tyssenet al., 2007). However, when this is combined with low extroversion and high con-scientiousness a brooding personality was detected in the European students.

The Current StudyThe current study seeks to validate a new instrument that measures students’ affec-tive, behavioural, physiological and cognitive responses to stress during theirattempts to maintain homeostasis. The Lakaev Academic Stress Response Scale(LASRS; Lakaev, 2006) will be assessed to establish the psychometric properties ofthe scale and its proficiency in measuring specific stress responses in university stu-dents. Specifically, the content, construct, criterion, convergent and divergent valid-ity of the LASRS will be examined along with reliability. The validation of theLASRS will provide a purpose-designed measure of the experience of stress reac-tions in response to tertiary studies. In light of a positive previous use (Lakaev,2006; Lakaev, 2008) the LASRS is expected to provide a reliable and valid measureof academic stress response, and will prove useful in predicting specific academicstress response problems in university students.

MethodParticipants

Participants were recruited from the Bond University student population. A total of375 consented to participate: 207 female, 168 male. The mean age of participantswas 24.50, and ages ranged from 17 to 57. The sample comprised 266 undergrad-uates, 67 postgraduates, 39 masters, 1 doctoral and 2 other students. Recruitmenttargeted a multicultural sample and 210 indicated that they were international stu-dents compared to 165 domestic students. Students’ country of origin comprised142 Australia, five New Zealand, 68 USA, eight Canada, 49 East Asia (Japan,Thailand, Malaysia, Korea, China, Philippines and Indonesia), 16 Other Asia(India), 66 Europe (France, Sweden, Norway, Germany, Poland, Turkey, Spain,Portugal, Britain, Finland, Malta, Denmark, Austria and Italy), and 21 other. Onehundred and eighty-eight students spoke English as their first language, 144 spokeEnglish as their second language, and 43 had a mixture of languages as theirsecond language and were consequently multi-lingual with English as one of theirspoken languages.

MeasuresSix instruments were administered to all participants to evaluate academic stressand to be used as comparison measures to the LASRS, along with a demographicquestionnaire.

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Acculturative Stress Scale for International Students. Sandhu and Asrabadi (1994)constructed the ASSIS to measure the psychological reactions of international stu-dents in the following areas: perceived deprivation, alienation, loneliness, home-sickness, hate, fear, stress due to change and guilt. The ASSIS is a self-report, paperand pencil questionnaire consisting of 36 items with seven subscales: PerceivedDiscrimination, Homesickness, Perceived Hate, Fear, Stress Due to Change/Cultural Shock, Guilt, and Nonspecific. Participants are asked to circle the numberthat best describes their response on a 5-point Likert scale with the anchorsStrongly disagree (1), Disagree (2), Not sure (3), Agree (4) and Strongly agree (5).The ASSIS has been found to have high internal consistency scores ranging from α= .87 to .95 for the total items measured by Cronbach’s alpha (Sandhu &Asrabadi, 1998). In the current study a Cronbach alpha of α = .97 was found forthe overall ASSIS scale. The subscales had the following Cronbach alphas:Perceived Discrimination α = .91, Homesickness α = .77, Perceived Hate α = .81,Fear α = .89, Stress Due to Change/Cultural Shock α = .78, Guilt α = .60 andNonspecific α = .93.

Chinese Stress Symptom Checklist. Cheng and Hamid (1996) constructed the CSSCto reflect that East Asians (Chinese) suffer greater somatisation symptoms whenstressed than do Western nationalities (primarily Caucasians). It is a self-report,paper and pencil questionnaire consisting of 40 items with two subscales: a 20 itemsubscale of Physical Symptoms, and a 20 item subscale of Psychological Symptoms.Participants are asked to indicate how frequently they have been affected by a stresssymptom in the past month on a 5-point frequency Likert scale (Cheng & Hamid)with the anchors of Never (0), Sometimes (1), Neutral (2), Often (3) and Frequently(4). The CSSC has excellent internal consistency with Cronbach’s alpha for thestudent sample of α = .94 for the total score, α = .88 for the Physical Symptomssubscale and α = .92 for the Psychological Symptoms subscale, and virtually identi-cal for the adult sample; overall alpha α = .94, Physical Symptoms subscale α = .87and Psychological Symptoms subscale α = .92 (Cheng & Hamid, 1996). Due to thehigh internal consistency the three measures allow the scale subgroups to be usedindependently or in combination to create the overall score (Cheng & Hamid,1996). In the current study a Cronbach’s alpha of α = .96 was found for the overallCSSC scale with the subscales producing Cronbach alphas for Physical Symptoms α= .94 and Psychological Symptoms α = .94. These Cronbach alphas were in align-ment with the excellent results produced by Cheng and Hamid (1996).

Depression Anxiety Stress Scale. The DASS-21 is a short version of the full scaleDASS, and consists of 21 statements that describe symptoms of depression, anxietyand stress (Antony, Bieling, Cox, Enns, & Swinson, 1998). The DASS-21 consistsof 21 items divided into three subscales, each containing seven items per subscale:Depression, Anxiety, and Stress. Participants are asked to indicate the extent towhich they have experienced symptoms of depression, anxiety and stress over thepast week. It is a self-report measure using a 4-point severity/frequency Likert scale(Lovibond & Lovibond, 1995) with the anchors of Did not apply to me at all (0),Applied to me to some degree, or some of the time (1), Applied to me to a consid-erable degree, or a good part of the time (2), and Applied to me very much, ormost of the time (3). Cronbach alphas for Depression α = .94, Anxiety α = .87, and


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Stress α = .91 have been found for the DASS-21 by Antony et al.. In the currentstudy Cronbach alphas were found for the subscales of the DASS-21, withDepression α = .87, Anxiety α = .87 and Stress α = .86.

Eysenck Personality Questionnaire — Revised (Extraversion). The EPQ-R(E),(Eysenck & Eysenck, 2006) is a tool based upon Eysenck’s (1967) biosocial per-sonality theory in which personality is the product of biological factors and theinteraction between temperance and environment and contains three temperamenttraits: psychotism or tough mindedness (P), extraversion-introversion (E) and neu-roticism or emotionality (N) which interact with the environment to produce per-sonality (Kemp & Center, 1998). Eysencks instrument also contains a Lie (L) scalethat has been shown to function as an index of socialisation or social conformity(Eysenck & Eysenck, 1975). The EPQ-R(E) is a self-report, paper and pencil ques-tionnaire consisting of 12 items and is a component of the 48 item EPQ-R ShortScale, designed specifically for survey use, providing quick measures of E, N, P andL. Participants are asked how much they agree with each statement and to put acircle around the ‘yes’ or ‘no’ (Eysenck & Eysenck, 2006) following the question.Alpha coefficients reported for all scales are, for P α = .78 (males) and α = .76(females), for E α = .90 (males) and α = .85 (females), for N α = .88 (males) and α= .85 (females), and for L α = .82 (males) and α = .79 (females) (Eysenk, Eysenk,& Barrett, 1985). In the current study a Cronbach’s alpha of α = .63 was found forthe overall EPQ-R(E) Short Scale.

Student-life Stress Inventory Scale. The SSI is a tool designed to measure tertiary stu-dents’ stressors and their reactions to these stressors. It is a self-report, paper andpencil questionnaire consisting of 51 items with nine subscales based upon a theo-retical model by Morris (1990). The model focuses upon five types of Stressors:Frustrations, Conflicts, Pressures, Changes, and Self-Imposed. Also four types ofReactions to Stressors are assessed: Physiological, Emotional, Behavioural, andCognitive Appraisal. Participants are asked to indicate the option that bestdescribes their experience of stress using a 5-point frequency Likert scale (Gadzella,1991) with the anchors of Never (0), Seldom (1), Occasionally (2), Often (3) andMost of the Time (4). Internal consistency has been supported for 381 students(males n = 120, females n = 258) and was α = .92 for the overall test scale. TotalStressors reported a Cronbach’s alpha of α = .92, Frustrations α = .70, Conflicts α= .68, Pressures α = .80, Changes α = .86, Self-imposed α = .63, Total Reactions toStressors α = .75, Physiological α = .86, Emotional α = .82, Behavioural α = .71,and Cognitive Appraisal α = .82 (Gadzella & Baloglu, 2001). In the current study aCronbach’s alpha of α = .95 was found for the overall SSI scale, with the subscalesof Frustrations α = .81, Conflicts α = .88, Pressure α = .81, Changes α = .88, Self-imposed α = .79, Total Stressors α = .92, Physiological α = .89, Emotional α = .86,Behavioural α = .83, Cognitive α = .87 and Total Reactions to Stressors α = .93

Lakaev Academic Stress Response Scale. The LASRS (Lakaev, 2006) was used withinthe current study for an exploratory factor analysis. It is a measure of stressresponse developed specifically for quantifying stress in university students in thestress response domains: Physiological, Behavioural, Cognitive, and Affective.Respondents rate how much of the time they experience symptoms on a 5-point

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Likert scale (Lakaev, 2006) with the anchors None of the Time (1), A Little of theTime (2), Some of the Time (3), Most of the Time (4), and All of the Time (5).Items are summed for subscale scores and subscales are summed for a total LASRSstress response score. Higher scores indicate a greater stress response. Items for theLASRS were generated from a review of the general stress and academic stress liter-ature. Twenty-seven items were selected and then tested in a pilot study; forty-fivestudent volunteers completed the 27 items as well as the Kessler-10, a measure ofnon-specific psychological distress. The 27 items were then submitted to a principalcomponents analysis, which confirmed the 4-factor component structure of thequestionnaire. Reliability analysis of the four factors using the leave-one-out proce-dure suggested that the scales would be improved by discarding six items. Theremaining 21 items yielded acceptable to excellent internal consistency rangingfrom .63 to .92. These 21 items became the LASRS as used in the present study tomeasure student responses to academic stress.

In the current study, the analysis was conducted on a sample of 375 mixednationality university students from Bond University. Assumptions of adequatesample size, missing values, normality, linearity, outliers, singularity and multi-collinearity were assessed prior to analysis to determine the data’s suitability forfactor analysis. Several multivariate outliers were detected and were subsequentlyremoved from the data set resulting in a total of 370 cases in the factor analysis.The majority of inter-item correlations were greater than .30 suggesting the use ofoblique rotation (Tabachnik & Fidell, 2007).

A Kaiser-Meyer-Olkin (KMO) analysis supported factorability, R = .92 andBartlett’s test indicated a breach of sphericity, χ2 = 4097.46, df = 210, p = < .01.However, factor analysis is robust to breaches of sphericity especially when thesample size is large (Tabachnik & Fidell, 2007). A Cattell scree plot and Kaiser’scriterion identified a 4-factor solution that explained 63% of variance in scores.Using Maximum Likelihood to obtain squared multiple correlations and goodness-of-fit tests, 4-factor solution was accepted as it allowed for a succinct structure ofitems and factors and accounted for 54% of the variance. The goodness-of-fit testshowed a significant likelihood ratio, χ2 = 271.36, df = 132, p = <.01 which indi-cates an inadequate fit of the model (Byrne, 2001). This test is however consideredto be a very stringent estimation of the goodness-of-fit and unrealistically seeks tofind a model that perfectly matches that of the population (Byrne). Furthermore, asthe sample size increases, the significant likelihood ratio test increases the χ2 value,resulting in an overinflated value (Byrne). Due to these shortcomings of the signifi-cant likelihood rotation, it was decided to use the alternative χ2 /df ratio (Byrne). Itwas found that the χ2 value was more than twice that of the degrees of freedom(271.36/132) which indicates an adequate goodness-of-fit.

This analysis generally supported the hypothesised 4-factor structure of theLASRS, with affective (factor 1), behavioural (factor 2), physiological (factor 3),and cognitive (factor 4) stress responses evident. All item loadings on the Cognitivefactor were negative, suggesting that this factor was identifying a process otherthan stress response as seen in the first three factors. Further analysis with consid-eration of the literature, suggested that this factor may be tapping worry. Worry isconsidered to be a distraction that provides short-term relief from stress andanxiety responses (Ginsberg, 2008; Szabo & Lovibond, 2006), and thus would be


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expected to show a pattern of negative loadings compared to stress responses. TheCognitive factor requires further study however it was decided to leave it in thecurrent study. There were four items that were split loaded (5, 6, 16 and 18). Ineach case the item was included in the factor on which it loaded highest. Item 18was evenly split loaded between the Affective and Cognitive factor; it was decidedto place it in the Cognitive factor as it was similar to the others that loaded in tothe Cognitive factor. The results of the analysis are presented in Table 1.

ProcedureApproval was gained by the Bond University Human Research Ethics Committeebefore beginning the testing. Participants were recruited from Bond University.Researchers approached students within the main campus library over a two-weekperiod. Participants were given an Explanatory Statement outlining the details of thestudy and were encouraged to read the statement. Those that agreed to participate

TABLE 1

Factor Loadings for Maximum Likelihood Oblique Rotation of the LASRS

Factor

Item Affective Behavioural Physiological Cognitive

20. My work built up so much that I felt like crying .83

19. I felt emotional .82

6. My emotions stop me from studying .50 .35

12. I yelled at family or friends .43

18. I felt emotionally drained by university .37 .30 –.37

3. I felt I was lazy when it came to university work .74

11. I procrastinated on assignments .63

17. I was distracted in class .62

16. I was unable to study .53 .33

1. I had trouble concentrating in class .51

8. I avoided class .50

2. I used alcohol or drugs .47

7. I have trouble remembering my notes .35

9. I couldn’t breathe .80

21. I had difficulty eating .75

14. My hands were sweaty .71

15. I have had a lot of trouble sleeping .67

10. I had headaches .64

4. I felt overwhelmed by the demands of study –.71

13. I felt worried about coping with my studies –.53

5. There is so much going on that I can’t think straight .37 –.50

Total Items

Alpha Coefficents 4 8 5 4

Cronbach Alpha .82 .82 .85 .89

Note: Exploratory factor analysis with maximum likelihood extraction.



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were asked to sign the consent form. Participants then completed the demographicssheet and the ASSIS, CSSC, SSI, LASRS, EPQR-(E) and DASS questionnaires in thelibrary, either individually or in groups. The order of the questionnaires was coun-terbalanced to prevent fatigue effects. The researcher remained visible in the area forparticipants to ask questions, and then collected the questionnaires after 30 minutes.A Debriefing Letter, explaining the purpose of the study and how to access theresearch findings, was given to each participant upon return of the questionnaires.

ResultsThe analysis will assess the validity of the LASRS in comparison to other estab-lished stress and academic stress scales. A total N = 375 was used for the analysis.To ensure data quality descriptive analyses were conducted. Means, standard devi-ations and alpha coefficents for the ASSIS, CSSC, SSI, LASRS, DASS Stress scaleare presented in Table 2. As Table 2 shows, participants scored highest on the SSI.

Data was inspected for missing values and data entry errors; corrections weremade for errors found. Missing data was adjusted using the recommended medianreplacement as per Tabachnick and Fidell (2007). The data was then analysed fornormality, univariate and multivariate outliers, linearity and multicollinearity, andhomogeneity of variance–covariance matrices. Four cases were identified as multi-variate outliers using Mahalanobis distance at p < .001 and were excluded fromfurther analysis leaving n = 371. Bivariate scatter plots demonstrated that multi-variate assumptions of normality, homogeneity of variance and linearity were met.

Correlation AnalysisThe relationship between the scales utilised was determined via bivariate correla-tion analysis. Displayed in Table 3 are the Pearson product-moment correlationcoefficients for total scores on the ASSIS, CSSC, SSI, EPQ-R(E), LASRS and DASSStress. As Table 3 shows, all the stress scales used as dependent variables werestrongly significantly correlated. However, the ASSIS was not as strongly correlatedas the others, suggesting it is measuring a different type of stress. The EPQ-R(E)was only significantly correlated with the ASSIS. The EPQ-R(E) was negatively cor-related with all of the stress scales, demonstrating divergent validity with theLASRS. The LASRS correlated between .61 and .74 with other stress scales, indi-cating good to moderate convergent validity.

TABLE 2

Means and Standard Deviations (SD) for the ASSIS, CSSC, SSI, LASRS, and DASS Stress

Scale Mean SD

Total ASSIS (α = .97) .64 .77

Total CSSC (α = .96) .93 .77

Total SSI (α = .95) 2.20 .55

Total LASRS (α = .91) 1.17 .71

DASS Stress (α = .91) .94 .68

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The SSI was included in this study to assess the construct validity of the LASRSas they comprise similar subscales. Subscales of the LASRS (Affective, Behavioural,Physiological and Cognitive) and the SSI (Emotional, Behavioural, Physiologicaland Cognitive) were submitted to bivariate correlational analysis. As Table 4shows all subscales on the SSI and LASRS were significantly correlated. However,there were discrepancies in correlations of the same domain. For example, the SSIBehavioural scale was more highly correlated with the LASRS Affective scale thanthe LASRS Behavioural. The SSI Physiological and the LASRS Physiological scaleswere highly correlated, and the SSI Cognitive Appraisal and LASRS Cognitivescales were also significantly correlated. The SSI Emotional and LASRS Affectivescales were well correlated. This suggests that both scales are measuring the samegeneral construct but do not discriminate optimally between domains.

In order to determine criterion validity, correlations between the DASS subscalesand the LASRS subscales were assessed. As Table 5 shows, there were significantcorrelations between all of the LASRS subscales and the DASS subscales. ThePearson coefficients ranged from low (.29) to moderate (.74) indicating the LASRSstress scales shared a fair relationship with depression and anxiety.

TABLE 3

Correlation Coefficients for ASSIS, CSSC, SSI, LASRS, EPQ-R(E) and DASS Stress Scores

Total ASSIS Total CSSC Total SSI Total LASRS Total EPQ-R(E) DASS Stress

Total ASSIS 1 .32** .25** .24** –.14** .21**

Total CSSC 1 .72** .74** –.08 .67**

Total SSI 1 .68** –.03 .62**

Total LASRS 1 –.03 .61**

Total EPQ-R(E) 1 –.05

DASS Stress 1

Note: * p < .05, ** p < .01.

TABLE 4

Correlation Coefficients for SSI Subscales and LASRS Subscales

SSI LASRS

Physiological Emotional Behavioural Cognitive Cognitive Physiological Behavioural Affective

SSIPhysiological 1 .58** .57** .33** .54** .67** .31** .57**Emotional 1 .74** .49** .51** .29** .34** .60**Behavioural 1 .45** .44** .32** .38** .57**Cognitive 1 .26** .15* .12* .28**

LASRSCognitive 1 .55** .56** .74**Physiological 1 .32** .56**Behavioural 1 .56**Affective 1

Note: * p < .05, ** p < .01.



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DiscussionThe study conducted a factor analysis and investigation of validity on the LASRS, anewly developed academic stress response scale. It was predicted that the LASRSwould be a reliable and valid measure of tertiary academic stress response and thatit would show to have construct validity in a factor analysis. Furthermore, theLASRS was expected to have respectable psychometric properties of content, crite-rion, convergent and divergent validity.

The LASRS produced excellent reliability using Cronbach’s alpha for the overallLASRS scale and the LASRS subscales. The internal consistency of the LASRS’stotal and subscale scores was good and all alphas were above .80. This indicatesthat the LASRS is a reliable measure of academic stress responses. The results con-firmed the predicted 4-factor structure of the LASRS and that it was generally com-parable to the alike subscales of the SSI. Affective, Behavioural, Physiological andCognitive factors were extracted and accounted for a significant proportion ofvariance with adequate goodness-of-fit of the model obtained. The Cognitive factorcomprised of negative loaded items indicating that items on the Cognitive factorgenerally decrease as items on the other factor scores increase. Further investiga-tion of the Cognitive items and the literature suggested the most plausible explana-tion is that the Cognitive items were tapping the construct of worry (e.g., ‘I feltworried about coping with my studies’). Worry is generally accepted as the cogni-tive process whereby repetitive thoughts give the illusion of improving perform-ance, while providing brief relief from stress (Ginsberg, 2008; Szabo & Lovibond,2006). Primarily the factor analysis helped to correct the organisation of itemsacross domains, showing that the pilot study’s organisation of items was not suc-cinct. These adjustments suggest that the LASRS has good construct validity whenused in a context similar to this study.

The LASRS demonstrated good convergent and divergent validity when assessedagainst the ASSIS, CSSC, SSI, DASS Stress and the EPQ-R(E). The LASRS showedto be highly correlated with CSSC, SSI and DASS Stress indicating that the LASRS’measurement of stress is in alignment with that of reputable scales. The LASRS,

TABLE 5

Correlation Coefficients for the DASS Subscales and LASRS Subscales

DASS LASRS

Depression Anxiety Stress Physiological Behavioural Affective Cognitive

DASSDepression 1 .57** .69** .31** .42** .56** .38**Anxiety 1 .70** .69** .26** .50** .44**Stress .1 .52** .32** .64** .54**

LASRSPhysiological 1 .32** .56** .55**Behavioural .1 .56** .56**Affective 1 .74**Cognitive 1

Note: ** p < .01.

along with the other stress scales, showed a low correlation with the ASSIS, indicat-ing that the ASSIS is measuring a different type of stress (i.e., the ASSIS focusesupon acculturative stress). The EPQ-R(E) was used for divergent validity analysisand had a negative correlation as expected. This direction was expected as extrover-sion has a negative relationship with stress in that those who are stressed, are morelikely to behave more introvertedly, as proposed by Eysenck and Eysenck (2006).

The SSI and LASRS subscales were assessed to determine if the LASRS subscales(Affective, Behavioural, Physiological and Cognitive) had validity against anothermeasure of these stress responses. The results showed that the scales significantlypositively correlated, with only the correlation between Cognitive factors beinglow. Criterion validity was predicted to be shown between the LASRS measures ofstress and the related constructs of depression and anxiety. Lovibond (1998) statesthat the independent constructs of stress, depression and anxiety consistently showa moderate to strong correlation and that the DASS can be used to determine theunique effect of each. Correlations between the subscales of the LASRS and theDASS Anxiety and Depression scales showed a moderate relationship between theconstructs. This supports that the LASRS is a valid measure of stress in that it canbe used to predict scores on a separate but related construct.

LimitationsWhile there were many strengths to this study some limitations were apparent. It

was conducted in an uncontrolled manner and environment within the BondUniversity Library across a 2-week period. This means that the participants did notcomplete the questionnaire in a controlled environment and that not all partici-pants completed the questionnaire in the same context. Further to this, consideringthe diverse range of cultures tested and the large age range of students, differencesmay have been present in regards to stress exposure, resilience and coping strate-gies of students. Further assessment of the LASRS scale using other comparisonmeasures would assist in verifying the scales validity. The LASRS was initiallybased on responses from Australian university students and therefore may haveimpacted upon results for the international students. However, their results on theLASRS were in line with those from the other scales. The stability of the LASRS isunclear as no test–retest analysis was performed. Language may have also been abarrier as many of the students who participated in the study did not have Englishas their first language.

StrengthsThe study had numerous strengths however the most notable is the sample size (N= 375). The Affective, Behavioural and Physiological factors of the LASRS shouldprove useful in quantifying ineffective responses to academic stress both in domes-tic tertiary students and across various groups of international students. TheCognitive factor of the LASRS requires additional verification before it can be con-sidered as psychometrically sound as the other subscales.

Future ResearchFurther research would be beneficial in the area of tertiary academic stress forAustralian born domestic students as very little is available on this subject, espe-cially as this study suggested that Australian students had high responses to stress.

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Another area of concern is the lack of recent data in regards to international stu-dents academic stress experiences within the Australian tertiary context. It isstrongly suggested that more research be conducted in this area to gain a more com-prehensive understanding of the psychological processes in relation to stress of uni-versity students. Furthermore, there is also a lack of notable data on our domesticstudents and how they respond to stress and its associated stressors. Investigationsin this area would go a long way to developing appropriate support and counsellingservices for both domestic and international students suffering academic stress. TheLASRS could be used in other Australian universities to compare different interna-tional student populations to Australian born tertiary students, as well as in othercountries for domestic and international comparison. In addition other studies mayfocus upon Australian born domestic students, utilising the LASRS to develop aneducated view of stress levels within our tertiary structures.

In summary, the LASRS has shown to be a psychometrically sound academicstress scale and should be submitted to further statistical analysis in order to estab-lish it as a stable measure of academic stress responses.

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Documents

Validation of an Australian Academic Stress Questionnaire