Evaluation of the student life-stress inventory-revised.
At one time or another, everyone experiences some stress. Stress may be a different kind of and/or at different levels. Selye (1974) defined stress as the non-specific response of the body to demands made on it. He described stress as distress and eustress. The distress has negative effects but eustress has positive effects on humans. Some researchers refer to stressors as hassles (Lazarus & Folkman, (1984) or mild and severe (Gadzella, 1991). The mild stress would be equivalent to Selye's eustress and the severe stress to his distress.
The study of stress, its effects, and how to cope with it, is of concern to psychologists, counselors, educators, students, and common people in general. To combat stress, it is important to first recognize and admit that one is experiencing it, to understand what effects it has, and know how to cope and/or reduce the stressful experiences.
Theorists point out that the effects of stress are not entirely negative. Seligman and Csikszentmihalyi (2000), stated that researchers had devoted too much time to the weaknesses and harmful effects of stress and had neglected to explore the effects of stress which can make life worth living. Folkman and Mosknvitz (2000) also drew attention to the favorable outcomes of stressful experiences. Other researchers (e.g., Tedescki, Park, & Calhoun, 1998) felt that stress may promote personal growth, assist people in developing new skills, reevaluate priorities, and acquire new strengths. Sutherland (2000) summed it up indicating that most people would prefer some stimulation (caused by stress) rather than live a boring stress-free existence. Stated differently, stressful situations may lead to personal changes which might be beneficial to individuals. That is, it can improve one's coping skills and enable one to learn from one's mistakes (Calhoun & Tedescki, 2001). This type of stress may be referred to as mild or eustress as described by Selye (1974).
Over the years, researchers (Holmes & Rahe, 1967; Scheier & Carver, 1985) developed questionnaires to assist people in understanding their stressful experiences. Other researchers such as (Sarason, Johnson and Siegel (1978) studied stress and its relationships with various experiences. One inventory, Student-life Stress Inventory, SSI (Gadzella, 1991; Gadzella & Baloglu, 2001) assesses students' stress levels and assists students in understanding the different kind of stressors and reactions to stressors they might experience. Numerous studies have been conducted with the SSI (e.g., Gadzella, 1994; Gadzella & Baloglu, 2001; Gadzella & Guthrie, 1993; Gadzella & Fullwood, 1992; Gadzella, Ginther, & Fullwood, 1993; Misra & Castillo, 2004; Misra, MeKan, Russo, & West, 2000; Marzeth & Farileh, 2004) showing significant differences among students with different overall stress levels and their responses to the SSI. Other studies (e.g., Ming-Hui, 2005; Gadzella & Stephen, 2007; Gadzella & Marrs, 2007; Gadzella, Zascavage, Masten, Young, Stephens, & Pierce, 2007) showed differences among student stress level groups and academic performance. In a recent study (Gadzella & Masten, 2007), data showed that the mild stress level group performed better than the severe stress level group on processing and retaining information. Stated simply, this study showed that the mild stress can be beneficial to individuals.
The scores in the SSI categories were analyzed (Gadzella & Masten, 2005) and the data showed that some areas in the categories in the SSI did not measure effectively. So the SSI (Gadzella, 1991; Gadzella & Baloglu, 2001) was revised and is referred to here as the Student Life Stress Inventory-Revised (SSI-R; Gadzella, 2005). Data on the SSI-R were collected and analyzed. The purpose of the present study was to report the psychometric properties of the SSI-R and show its relationships with other inventories, such as, the Test Anxiety Inventory (Spielberger, 1980), State-Trait Anxiety Inventory (Spielberger, 1993), and Beck Depression Inventory (Beck, 1978).
There were 601 students, enrolled at a southwestern state university who voluntarily participated in the study, of whom 171 (28.5%) were men and 423 (70.4%) were women. Seven participants did not report their gender. In the group, 59 (9.8%) were freshmen, 97 (16.1%) sophomores, 142 (23.6%) juniors, 129 (21.5%) seniors, and 145 (23.6%) graduate students. Twenty-five students did not indicate their college status. Participants' ages ranged from 17 to 60 years (M= 20.03, SD = 8.31).Two hundred forty-two responded to the Test Anxiety Inventory, 238 responded to the State-Trait Anxiety Inventory, and 240 responded to the Beck Depression Inventory.
Participants were asked to indicate their perceived overall stress levels as mild, moderate, or severe. One hundred fifty-four (23.6%) indicated their overall stress levels as mild, 354 (55.6%) reported as moderate, and 115 (18.8%) as severe.
Data on stress were collected from the responses to the Student-life Stress Inventory-Revered (Gadzella, 2005). The SSI-R has 53 items grouped under two sections: Stressors and Reactions to Stressors. In the Stressors section there are five categories: Frustrations, Conflicts, Pressures, Changes, and Self-imposed. In the Reactions to Stressors, there are four categories: Physiological, Emotional, Behavioral, and Cognitive Appraisal. The total stress score is the summation of the nine categories scores (values). The SSI-R is scored following the scoring instructions on scoring each item, category, section, and total. Students' course grades ranged from 36 to 100. (M= 84.27, SD = 10.11).
Participants were informed of the study; they signed the release forms indicating data may be used for research purposes. Instructors gave extra course credits for students who participated in the study. Students responded to the inventories during their class periods.
Two main software programs were used to analyze the data: Statistical Package for Social Sciences (SPSS) 10.0 (SPSS, Inc., 1998) and Equations 5.5 (EQS; Bentler, 1992; 1995; Bentler & Wu, 1993). Data were coded onto SPSS 10.0 database and arranged so that they could be transferred onto EQS. Several analyses were computed such as the reliability of the SSI-R (alphas and test-retest), current validity, confirmatory factor analyses, and correlations of its scores with the Test Anxiety Inventory, State-TraitAnxiety Inventory, and Beck Depression Inventory, respectively.
The internal consistencies for 594 participants by groups (men, women, and total SSI-R scores) are displayed in Table 1. The alpha for the total group on the total SSI-R was .93, for men .93, and for women .92.
Four hundred sixty participants responded to the SSI-R twice within 10 days. Correlations (test-retest) between the two scores for each category and total SSI-R are displayed in Table 2. The highest correlation (r = .765, p < .01) was for the Physiological category and the lowest (r = .424, p < .05) for Conflicts. The test-retest correlation for the Total SSI-R was r = .61 (p < .01).
Concurrent validity was computed for this group. Analysis of variances was used to determine differences among the stress level groups (i.e., mild, moderate, and severe) and responses to the items in the nine categories. The results (Table 3) showed significant differences among the groups in all categories and total stress score.
Tukey post hoc tests were computed for all categories and the Total SSI. The results showed that (a) in all categories (except the Cognitive Appraisal) and the Total SSI, the 'severe' stress level group scored significantly higher (p < .001) than the 'moderate' and 'mild' stress level groups, respectively, and (b) in all categories (except the Cognitive Appraisal and Behavioral), the 'moderate' group scored significantly higher (p < .001) than the 'mild' stress level group.
To perform the confirmatory factor analysis, intercorrelations for the nine categories, two sections (Stressors and Reactions to Stressors) and the Total SSI-R were computed. These correlations are summarized in Table 4 along with means and standard deviations for the nine categories. All correlations (Table 4) among categories, sections, and Total SSIR were significant (p < .001). The highest correlation (r = .57) was among scores in the Physiological and Emotional categories and the lowest (r =. 18) was with Cognitive Appraisal and Total SSI-R.
The hypothesized confirmatory factor analysis model included two latent variables: Stressors and Reactions to Stressors. All the parameters related to the dependent variables were set free to be estimated. The maximum likelihood (ML) estimation was used to estimate the free parameters of the model. The goodness-of-fit summary was obtained for the hypothesized model through the ML estimation method.
Results showed that the [chi square] associated with the model of independence (i.e., variables are uncorrelated) was rejected, [[chi square].sub.(36)] = 1664.45, p < .001. Adequate support was found for the hypothesized model in terms of fit statistics: Normed Fit Index (Bentler & Bonett, 1980); Bentler-Bonett Nonnormed Fit Index (Bentler & Bonett, 1980); Comparative Fit Index (Bentler, 1990); Incremental Fit Index (Bollen, 1989); Goodness of Fit Index (Joreskog & Sorbom, 1988); Adjusted Goodness of Fit Index (Joreskog & Sorbom); or Root Mean Square Error of Approximation (Steiger, 1990). Table 5 shows several fit indices for the model.
Because the fit indices supported the factor structure of the modified model, standardized coefficients were computed (see Figure 1). Figure 1 shows that nondiectional relationshop between Stressors and Reactions to Stressors was significant. Morever, measured variables loading ranged from .49 to .69 in the Stressors and from .10 to .81 in Reactions to Stressors. The largest amount of variance accounted forby stress generated by Changes was ([R.sup.2] = .48). The largest amount of variance accounted for by in the Reactions to Stressors ([R.sup.2] = .66).
Correlations were computed between SSI-R scores and scores on the Test Anxiety State-Trait Anxiety and Beck Depression Inventory respectively, and course grades. These correlations are presented in Table 6.Test Anxiety scores are reported for worry (TA W),for emotional (TAE), and total (TAT).
In most cases, SSI-R scores correlated positively with scores in the other inventories. S cores in Cognitive Appraisal and Test Anxiety, (worry), Test Anxiety (Emotional) and Total Test Anxiety), respectively, did not correlate positively with scores in the Cognitive Appraisal. Data (Table 6) show the highest correlation (r = .55 p < .01) was between Physiological and Trait Anxiety scores and the lowest (r =. 15 p < .05) between Conflicts and Test Anxiety Emotional scores. Course grades correlated negatively with Test Anxiety (worry, r = -.20, State Anxiety (r = -.29 p < .01) and Beck Depression Inventories, (r = -.15 p < .05); respectively.
[FIGURE 1 OMITTED]
Conclusion and Discussion
The present study analyzed the psychometric properties of the SSI-R. Data showed the inventory is a reliable and valid instrument measuring students' stressors and reactions to stressors. The internal consistency for the Total SSI-R was .93 and test-retest correlations showed significant correlations on all categories ranging from .46 to .76. Confirmatory factor analysis showed the variables contributed to its respective latent variables. Significant positive correlations were found between SSI-R categories and Total Stress scores and the scores on the Test Anxiety, State and Trait Anxiety and Beck Depression Inventory, respectively.
To support the findings in the Gadzella and Masten's study (2007),it would be desirable to conduct other studies to determine if there are differences between participants who score mild versus severe stress on various activities and learning processes. In the present study, it was concluded that the SSI-R was a viable measure to study students' stressors and their reactions to stressors.
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Bernadette M. Gadzella, Ph.D., Professor Emeritus, Department of Psychology, Counseling, and Special Education, Texas A&M University-Commerce. Mustafa Baloglu, Ph.D., Professor & Dean, Faculty of Education, Gaziosmanpasa University, Tokat, Turkey. William G. Masten, Ph.D., Associate Professor, Department of Psychology, Counseling, and Special Education, Texas A&M University-Commerce. Qingwei Wang, Ph.D., Adjunct Professor, Department of Psychology, Counseling, and Special Education.
Correspondence concerning this article should be addressed to Dr. William G. Masten at william_masten@hotmail .com.
Table 1 Internal Consistencies (Alphas) for the Student-life Stress Inventory-Revised (SSI-R) by Subscales and the Total Scale Score for Gender and Total Groups Coefficient Alpha Group Men Women Total SSI-R Categories (n = 171) (n = 423) (n = 594) Stressors (Total) .86 .85 .85 Frustrations .75 .68 .70 Conflicts .78 .77 .77 Pressures .72 .65 .69 Changes .87 .84 .85 Self-imposed .63 .64 .63 Reactions to Stressors (Total) .90 .88 .89 Physiological .87 .85 .86 Emotional .85 .78 .81 Behavioral .71 .75 .74 Cognitive App. .82 .78 .79 Total Inventory .93 .92 .93 Table 2 Test-Retest Correlations for Two Responses to SSI-R (n = 460) Stressors Category r Frustrations .76 * Conflicts .42 * Pressures .64 ** Changes .65 ** Self-imposed .67 ** Physiological .77 * Emotional .71 * Behavioral .70 * Cognitive Appraisal .59 * Total .61 * * p < .05. ** p <. 01 Table 3 Means, Standard Deviations, and F-ratios for Groups (Mild n = 154, Moderate n = 334, and Severe n = 113) on the Ratings of Their Stressors and Reactions to Stressors Group M SD F(2,598) I. Stressors (Total) Mild 66.66 10.85 97.86 * Moderate 75.61 10.20 Severe 84.67 10.67 Frustrations Mild 15.89 4.03 40.56 * Moderate 18.26 3.88 Severe 20.42 4.82 Conflicts Mild 9.71 2.86 26.33 * Moderate 11.04 2.67 Severe 12.23 3.21 Pressures Mild 13.96 3.07 58.71 * Moderate 15.69 2.66 Severe 17.51 1.98 Changes Mild 6.98 2.36 77.14 * Moderate 8.57 2.46 Severe 10.84 2.85 Self-imposed Mild 20.11 4.02 28.49 * Moderate 22.02 3.86 Severe 23.66 3.58 II. Reactions to Mild 60.30 13.70 127.45 * Stressors (Total) Moderate 74.38 13.48 Severe 88.18 16.76 Physiological Mild 27.30 7.86 83.52 * Moderate 34.72 8.78 Severe 41.44 10.60 Emotional Mild 9.99 3.60 100.13 * Moderate 12.91 3.25 Severe 15.97 3.68 Behavioral Mild 15.05 4.07 70.15 * Moderate 18.18 4.63 Severe 22.07 6.00 2.65 Cognitive App. Mild 7.95 3.63 ** Moderate 8.56 2.47 Severe 8.69 2.90 III. Total Inventory Mild 126.96 21.63 148.00 * Moderate 149.99 20.87 Severe 172.85 24.04 * p < .0001; ** p < .05 Table 4 Means, Standard Deviations, and Interrelationships among the Total and Subscale Scores of the SSI-R 1 2 3 4 5 Stressors .77 * .66 * .72 * .71 * .56 * 1. Frustrations 2. Conflicts .46 * 3. Pressure .37 * .38 * 4. Changes .52 * .33 * .44 * 5.Self-imposed .25 * .23 * .44 * .28 * Reactions to .50 * .37 * .51 * .54 * .66 * Stressors 6. Physiological .41 * .31 * .47 * .46 * .38 * 7. Emotional .46 * .37 * .46 * .51 * .41 * 8. Behavioral .45 * .35 * .39 * .44 * .27 * 9. Cognitive .04 * -.05 -.01 .09 ** .04 Total .67 * .54 * .65 * .67 * .63 * Mean 18.0 10.92 15.59 8.59 21.84 Standard Deviation 4.36 2.95 2.91 2.82 4.02 6 7 8 9 Stressors .57 * .63 * .54 * 0.03 1. Frustrations 2. Conflicts 3. Pressure 4. Changes 5.Self-imposed Reactions to .90 * .78 * .77 * .25 * Stressors 6. Physiological 7. Emotional .57 * 8. Behavioral .51 * .61 * 9. Cognitive .09 ** .10 ** -.15 * Total .84 * .78 * .74 * .18 * Mean 34.08 12.74 18.11 8.43 Standard Deviation 10.09 3.95 5.31 2.62 * p < .01; ** p < .05 Table 5 Goodness-of-Fit Summaries for the Confirmatory Factor Analysis Model Model Fit Indices (n = 559) ML (a) Independence Model [c.sup.2] * 1664.45 Confirmatory Model [c.sup.2] (36) * 114.56 Normed Fit Index .93 Nonnormed Fit Index (26) .93 Comparative Fit Index .95 Incremental Fit Index .95 Goodness-of-Fit Index (GFI) .96 Adjusted GFI .93 (a) ML = Maximum Likelihood. * p < .001. GFI = Goodness-of-Fit Index greater than .90 indicates adequate fit (Bentler & Bonett, 1980) AGFI = Adjusted Goodness-of-Fit Index greater than .90 indicates adequate fit (Bentler & Bonett, 1980) RMSEA = Root Mean Square Error Approximation less than .10 indicates adequate fit (Bentler & Bonett, 1980). Table 6 Correlations between SSI-R and other Inventory Scores Category TAW TAE TAT STA (n = 242) (n = 238) Frustration .37 ** .30 ** .35 ** .43 ** Conflicts .19 ** .15 ** .18 ** .28 ** Pressures .18 ** .24 ** .24 ** .23 ** Changes .27 ** .24 ** .27 ** .39 ** Self-imposed .23 ** .29 ** .29 ** .24 ** Physiological .46 ** .47 ** .49 * .47 ** Emotional .26 ** .27 ** .29 ** .37 ** Behavioral .18 ** .16 ** .18 ** .35 ** Cognitive Appraisal .07 .08 .09 .18 ** Total .42 ** .42 ** .45 ** .52 ** Course grade -.20 ** -.08 -.14 -.29 ** Category TR BDI (n = 240) Frustration .57 ** .50 ** Conflicts .36 ** .35 ** Pressures .26 ** .26 ** Changes .51 ** .48 ** Self-imposed .29 ** .19 ** Physiological .55 ** .51 ** Emotional .44 ** .46 ** Behavioral .41 ** .45 ** Cognitive Appraisal .26 ** .22 ** Total .64 ** .59 ** Course grade -.21 ** -.15 * * p < .05. ** p < .01 Note: TAW = Test Anxiety (Worry), TAE = Test Anxiety Emotional, TAT = Total Test Anxiety STA = State Anxiety, TR = Trait Anxiety, BDI = Beck Depression Inventory
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|Author:||Gadzella, Bernadette M.; Baloglu, Mustafa; Masten, William G.; Wang, Qingwei|
|Publication:||Journal of Instructional Psychology|
|Date:||Jun 1, 2012|
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