A Study to Examine the Impact of Stress Management Workshops on Nontraditional Students Academic Performance

1 Volume 5, Issue 1, 2012 A Study to Examine the Impact of Stress Management Workshops on Nontraditional Students Academic Performance Cindye T. Richburg, Assistant Professor, Claflin University, crichburg@claflin.edu Jonathan C. Mbah, Assistant Professor, Tuskegee University, mbahj@mytu.tuskegee.edu Nibaldo Galleguillos, Professor, McMaster University, gallegui@mcmaster.ca Abstract This study measured the effects of stress-management workshops on nontraditional students perceived stress levels and their academic performance. The study was conducted in an academic institution in southeastern part of the United States, which included 40 nontraditional undergraduate students. Students perceived stress levels and academic performance were assessed. Analyses of results from pretest and posttest show that nontraditional students academic performance as measured by GPA improved by 0.5 points on a scale of 1.5 to 4.0 with treatment showing a positive long-term effect. Introduction Many nontraditional students fail to complete their undergraduate degree due to poor academic performance (Taniguchi & Kaufman, 2005). Nontraditional students are at least 25 years old, are financially independent, work part-time or full-time, and/or are single parents or married. Study has shown that nontraditional undergraduates had delayed enrollment by at least one year after high school, were enrolled at least part-time, were single parents, were employed full-time, were financially independent from their parents, and/or had dependents (Walker, 2009; Gossett, Condoulis, Oaks, & Kendall, 2008; Jinkens, 2009). In this study the terms adult students, adult learners, and nontraditional students are used interchangeably. The multiple roles of nontraditional students can be a source of strain and conflict that results in their earning low grades (Giancola, Grawitch, & Borchert, 2009). Previous studies have shown a relationship between nontraditional students stress levels and their academic performance (Milam, 2008; Quimby & O Brien, 2006). The multiple roles of nontraditional students can be a source of strain and conflict. Some recent studies focusing on nontraditional students academic outcomes have suggested that colleges and universities should offer more resources (e.g., more staff, childcare assistance, financial aid, counseling services, and tutoring services) and have larger endowment assets per student in order to improve student outcomes (Milam, 2008; Quimby & O Brien, 2006). Offering more resources can strain a school s budget. However, some resources, such as counseling and tutoring services, can be achieved with only a modest commitment of college resources by reorganizing services currently available within the college (Ghosh, Javalgi, & Whipple, 2008). A growing number of nontraditional students are entering college; however, their academic performance and completion rates have remained low (Taniguchi & Kaufman, 2005). Among nontraditional undergraduates enrolled in U.S. colleges and universities between 1989 and 1990, only 31% earned their bachelor s degree by 1994, compared to 54% of traditional students (Taniguchi & Kaufman, 2005). Whereas 42.3% of traditional students complete their bachelor s degrees, only 9.9% of nontraditional students do (Milam, 2008). Also, the retention rate for nontraditional students is only 61.1%, compared to 81.8% for traditional students. The purpose of this study was to determine the effects of stress-management workshops on nontraditional students perceived stressors and their academic performance conducted within African Americans demography. Components of the treatment interventions comprised of 40 full-time nontraditional undergraduates enrolled in a business core course within the School of Business Administration of a private liberal arts college in the southeastern United States. Stress-management workshops focused on adaptive coping strategies were offered to nontraditional students in an effort to reduce their perceived stress and improve their academic performance. Student perceived stress levels and academic performance were assessed before and after the workshops to determine if the workshops impacted their outcomes. Giancola, Grawitch and Borchert (2009) found that nontraditional students reported their greatest stressors derived from the workplace. These students rated workplace stressors higher than personal stressors, t (148) =2.86, p<.001, and school stressors t (148) =13.76, p<.001, and personal life stressors higher than school

2 stressors, t (148) =11.57, p<.001. Nontraditional students reported the greatest inter-role conflict between school and family. Some studies show colleges and universities that provide more resources for nontraditional students are likely to have greater positive student outcomes (Ghosh, Javalgi, & Whipple, 2008; Milam, 2008). Conceptual framework This provides a lens that connects student perceived stressors with design aimed at alleviating such stressors. Focus was to determine (a) the effects of stress-management workshops on perceived stressors among nontraditional students and (b) the extent to which specific demographic characteristics (i.e., gender, age, and perceived stressors) of nontraditional students and the numbers of hours they work per week are related to their academic performances at the study site. Educators and administrators at the college investigated in this study can reduce the barriers faced by nontraditional students by giving such students access to stress-management counseling. By implementing stressmanagement workshops, we intend to accomplish the following: (a) reduce the perceived stress experienced by nontraditional students, (b) improve such students academic performance, and (c) identify concerns and recommend solutions regarding nontraditional students. The authors sought to identify factors (such as age, gender, and perceived stressors) that predict the academic performance of nontraditional undergraduates at the college under study in order to (a) make recommendations regarding ways to improve the college s existing services and resources for nontraditional students and (b) encourage the college to offer stress-management workshops that reduce perceived stressors among nontraditional students. As in the current study, GPA is commonly used as an indicator of academic performance. Peggy, Sullivan, and Guerra (2007) found low academic performance and academic standing to be closely tied to student attrition. Retention among nontraditional students tends to be 9% lower than retention of traditional students (Harrell, 2008; Spellman, 2007) Research questions and hypotheses The researchers investigated the following research questions and hypotheses in order to examine the effectiveness of a stress-management intervention on students perceived stress levels and academic performance. The following research questions were identified: (a) does the implementation of the management workshops reduce the stressors that influence nontraditional undergraduates? (b) Does the implementation of the management workshops related to the nontraditional undergraduates academic performance? (c) Does gender predict academic performance of nontraditional undergraduate students? (d) Does age predict academic performance of nontraditional undergraduate students? (e) Does the number of hours worked per week predict academic performance of nontraditional undergraduate students? The study tested the following hypotheses: H1. Stress-management workshops reduce perceived stressors that influence nontraditional undergraduates; H2. Stress-management workshops increase academic performance (GPA) among nontraditional undergraduates; H3. Female nontraditional students have higher cumulative GPAs than male nontraditional students enrolled in the division; H4. Nontraditional students (aged 25 and older) have higher cumulative GPAs than traditional students (aged 24 and under) enrolled in the division; H5. Nontraditional students who work less than 20 hours per week have higher cumulative GPAs than nontraditional students who work 40 or more hours per week. The research methods and procedures used to examine the study s research questions and hypotheses are discussed next. It will explain the study s subject selection and recruitment, identify the instruments used, and discuss the study s design and data analysis. Research Methodology Components of the treatment interventions comprised of 40 full-time nontraditional undergraduates, all African- Americans in African American setting, enrolled in a business core course within the School of Business Administration of a private liberal arts college in the southeastern United States. Of the 40 students, 21 were enrolled in Section 1 of the business course (Group 1), and 19 were enrolled in Section 2 of the business course (Group 2). The study population comprised of nontraditional students aged 25 and older who were enrolled in a bachelor s degree program in an on-campus educational setting.

3 Switching replications group design was used to study two independent implementations of the program, which included two groups of nontraditional students and three waves of measurement, with a treatment group and a control group involving parallel pretests and posttests. A Perceived Stress Survey was administered to nontraditional students to measure their perceived stress levels before and after the workshops to determine if intervention impacted their stress levels and academic outcomes. Nontraditional students enrolled in the two business courses who agreed to participate in the study attended four stress-management workshops during the 2010 fall miniterm. The workshops were offered to nontraditional students over a 5-week period and were designed to enhance stress management and academic performance throughout the term. The assignments to groups were not random but were based on students registration and enrollment status in two sections of a business core course. Group 1 comprised students enrolled in the first section of the course; Group 2 comprised students enrolled in the second section of the course. The intervention consisted of four stressmanagement workshops during the fall mini-term. Each workshop took place from 6:00 p.m. to 8:00 p.m. and was conducted by a trained counselor from the college s counseling and testing center. The trained counselor rearranged her work schedule to conduct the stress-management workshops in the evenings at no cost to the researcher or the college. All study participants were required to attend all four workshops and sign in at each session. Each workshop offered advice as to how students can cope with particular stressors related to family issues, work concerns, and financial problems. The workshops were designed to offer effective coping strategies and techniques to help students better manage stress, concentrate on their studies, and enhance their academic performance. Data were assessed before and after the midterm period and at the end of the term. Instruments and perceived stress survey Three questionnaires were administered during the study; the first two were researchers developed. The first questionnaire, Perceived Stress Survey, was designed to assess nontraditional undergraduates perceived stress levels while the second, Stress Management Workshops Evaluation, was designed to measure the effectiveness of the stress-management workshops. The third questionnaire was the standardized 2007 National Study on Nontraditional Students Survey (NSS; Pusser et al., 2007). The NSS was designed to assess specific demographic characteristics, (i.e. age, gender, and perceived stressors) and number of hours worked per week in relation to students academic performance. The Perceived Stress Survey consisted of a 5-item section pertaining to respondents demographic characteristics and a 10-item section that addressed perceived stressors related to academic, institutional, personal, work, family, and emotional issues. The NSS was developed by researchers at the Curry School of Education of the University of Virginia with funding from the Lumina Foundation for Education (Pusser et al., 2007). Procedures By using switching replications group design, the study examined two independent implementations of the program (stress-management workshops intervention) involving two groups of nontraditional students (Groups 1 and 2) and three waves of measurement (perceived stress levels and academic performance operationalized as GPA), with a treatment group and a control group involving parallel pretests and posttests. The goal was to determine what changes in student outcomes could be attributed to the treatment. Before and after the workshops, the perceived stress survey was administered to nontraditional students to measure perceived stressors and relationship to students GPA. For the first implementation, only Group 1 attended the stress-management workshops. For the second implementation, only Group 2 did, as shown in Table 1 1. However, participants were not randomly assigned to groups. This design allowed assessing the effects of the treatment on Group 1 while withholding the treatment from Group 2 which served as a wait-list control group. Results The results reported addressed the following: (a) main effects of treatment, that is, extent of relationship between stress-management workshops and nontraditional undergraduates academic performance, (b) gender prediction of academic performance, (c) age prediction of academic performance, and (d) effect of weekly hours work on academic performance of nontraditional undergraduates.

4 Workshop implementation Students were asked to rate the program s value by responding to questions on the workshops evaluation form about the overall effectiveness of the stress management intervention. Responses were analyzed by appropriate statistics to assess the program s effectiveness. Pretest and posttest results indicated that the program was effective with highly significant results as depicted by the statistics, F (1, 40) = 5.21, p < 0.0001. In addition, post-hoc analysis of the group means was conducted. In the case of all intervention outcomes (participants responses to the workshops evaluation questions), the means of the two groups differed by less than a unit, with a minimum difference of 0 and a maximum difference of 0.7. For each of these differences, the standard error was 2.8. Thus, one group did not significantly differ from the other. The mean difference was fewer times the standard error, so it could be asserted with high confidence that the population means of the first group did not significantly differ from the population means of the second group. The workshops evaluation items I will be better able to cope with stress based on what I learned in the workshops and The workshops were very informative correlated most strongly with workshop outcomes (r 2 = 0.8). The items The workshops provided useful study tips to aid in my academic progression, I am better equipped to handle stress as a result of the workshops, and The workshops lived up to my expectations also strongly correlated with workshop outcomes. Two of these correlations were negative. The number of cases used for each correlation was determined on a pairwise comparison basis. For example, there were 40 valid pairs of data for I will be better able to cope with stress based on what I learned in the workshops and The workshops were very informative, so that correlation of 0.8 was based on 40 observations. Overall, the results indicated that stress-management workshops benefited both groups of students. The outcome of the intervention suggested a statistically significant relationship between the workshops and students perceived stress levels. There was also a significant relationship between the intervention and students academic performance. Responses to the workshops evaluation survey indicated that the following items correlated most strongly with academic performance: (a) the workshops provided useful study tips, (b) the workshops were very informative, (c) the workshops provided useful coping strategies, (d) the workshop activities stimulated my stress management skills, and (e) the workshops lived up to my expectations. Over 95% of stressors were statistically significant with respect to nontraditional students. Although there is a negative relationship between age and maintaining employment, the results indicated that maintaining employment might be related to lower academic performance. Also, there was a statistically significant negative correlation between availability of childcare (F = -.628, p < 0.0001) and academic performance, because non-availability of childcare was highly related to absenteeism from class. As expected, there was a significant positive correlation between educational financing and academic performance (F = 0.24, p =.0007). Gender prediction of academic performance Table 1 listed the predictor variables used for both genders in the first and second implementations of the workshop intervention. There were some similarities between the sets of data obtained. Fourteen stressors were analyzed. Eight of them significantly correlated with reduced academic performance. Six of them did not significantly correlate with academic performance. However, stressors such as stressed about the quality of counseling services (F = 2.24, p =.06) and stressed about your academic performance involving examinations and quizzes (F = 2.15, p =.06) both approached statistical significance and therefore may have somewhat influenced academic performance. The results were unexpected in that all of the examined stressor variables are generally considered to influence academic performance.

5 Table 1. Gender in Relation to Other Variables Variables Group 1(n =21 Group 2 (n = 19) F p F P Marital status 2.64.03 2.45.04 Employment status 2.51.04 0.88.54 Feeling unable to cope with juggling school and family 2.81.02 1.70.13 Stressed about lack of access to counseling 1.58.19 1.05.40 Stressed about grades (academic performance) 3.47.01 3.12.01 Multiple-roles conflict (student, employee, spouse, etc.) 2.55.03 1.65.14 Stressed about personal finances 1.75.13 1.05.41 Student overwhelmed with stressors 1.72.14 1.64.16 Stressed about quality of financial aid 1.84.11 1.37.25 In light of this development, the effects of the stressor variables were further examined. T- tests showed that the following variables remained statistically significant: unable to control anger (b = -0.05, p <.40), with b notations, as used in the contexts, denoting the parameter estimate of group mean for each variable output; overwhelmed (b = - 0.02, p <.85); and stressed about lack of access to counseling services (b = -0.27, p <.14). The Pearson productmoment correlation (r 2 ) was 0.67; therefore, the variables in the model accounted for approximately 67% of the predictors variability. The results indicated that gender significantly predicted the academic performance of nontraditional undergraduates enrolled in an on-campus program as shown in Table 1. It was hypothesized that female nontraditional students would have higher cumulative GPAs than male nontraditional students. The results obtained for gender were aggregated and were not specific to females or males. However, analysis of the stressor variables showed that gender did predict Age prediction of academic performance Table 2 listed the predictor variables used for age in the first and second implementations of the workshop intervention. As study showed, age did not significantly influence academic performance. For the first implementation, the variables marital status, feeling unable to cope with juggling school and family responsibilities, and multipleroles conflict did not significantly correlate with age. Table 2. Age in Relation to Other Variables Variables Group 1 (n = 21) Group 2 (n = 19) F p F p Marital status 0.76.62 0.50.83 Employment status 2.59.05 1.21.32 Feeling unable to cope with juggling school and family 1.34.25 1.85.12 Stressed about lack of access to counseling 2.56.04 0.95.46 Stressed about grades (academic performance) 3.75.00 1.85.12 Multiple-roles conflict (student, employee, parent, spouse, etc.) 1.39.23 1.30.27 Stressed about personal finances 3.04.01 1.20.32 Student overwhelmed with stressors 0.86.56 1.63.15 Stressed about quality of financial aid 1.08.40 1.29.28 For both genders, these variables were generally considered the main predictors of academic performance. However, for the first implementation, age significantly interacted with these variables, race/ethnicity, stress about exams and quizzes, stress about grades, stress about personal finances, stress about lack of access to counseling services, and stress about quality of counseling services. For the second implementation, the relationships between age and the stressor variables were not statistically significant. It was therefore concluded that gender was the primary predictor of academic performance. The deviations observed for age in both implementations were not apparent, might have resulted from sampling error, and hence are considered outliers. The results indicated that age was not a predictor. As shown in Table 2, most of the stressor variables did not significantly correlate with academic performance. Therefore, the results did not support the hypothesis that nontraditional students would have higher cumulative GPAs than traditional students. In fact, the traditional students

6 tended to perform better than the nontraditional students. Effect of weekly hours work on academic performance The NSS was used to assess participants demographic characteristics (age, gender, and perceived stressors) and number of hours worked per week in relation to the participants academic performance. With respect to nontraditional students, 14 of the 15 stressor variables significantly correlated with academic performance. However, as related to traditional academic performance among nontraditional students, only 3 of the 15 stressor variables significantly correlated with academic performance. The results indicated that traditional students tend to experience fewer stressors than nontraditional students and that the stressors affect academic performance among nontraditional students as shown in Table 3. Table 3. Results of the 2007 National Study on Nontraditional Students Survey Nontraditional students (n = 40) Traditional students (n = 43) Stressors F p F p What challenges did you face upon returning to school? Availability of childcare 4.83.01 1.38.24 Maintaining employment 7.80.00 0.58.62 Cost of childcare/dependent care 5.13.01 1.87.16 Having family financial obligations 3.46.02 1.46.24 What are your biggest stressors since returning to school? Conflicts with job commitments, including travel and emergencies 3.73.02 0.93.40 Financial cost associated with schooling as a family budget priority 3.93.02 0.92.44 Inability to give 100% to job when school requirements intervene 8.14.00 2.47.08 Managing course load 7.42.00 1.76.17 It was hypothesized that nontraditional students who worked less than 20 hours per week would have higher cumulative GPAs than nontraditional students who worked 40 or more hours per week. As shown in Table 3, the results of nontraditional students response to maintaining employment was F = 7.80; p =.00 compared to the response of traditional students, F = 0.58; p =.62). This is supported by authors earlier findings that nontraditional students reported their greatest stressors derived from the workplace (Giancola, Grawitch and Borchert, 2009). However, in some cases, research questions and hypotheses were addressed using more than one data output. Data outputs from the workshop implementation, the workshops evaluations, and the NSS were used throughout the study. Significance was determined based on critical F values and p values. Most of the study s independent variables significantly correlated with students academic performance. Overall, the results indicated that the stressmanagement intervention reduced perceived stressors and improved academic performance among nontraditional students in the School of Business Administration. Although most of the stressor variables interacted with gender influenced academic performance, age was not a statistically significant influence. The implications of the results are discussed in section 5. Discussion The authors found a causal relationship between stress-management workshop implementation and student academic performance. Several findings held true across all studies. The stress-management intervention workshops were successful: they reduced perceived stressors and boosted students GPAs. In the workshops, students learned how to prudently manage their finances and not be wasteful. The intervention program identified and minimized key stressors associated with poor academic performance. This finding is supported by the authors earlier statement in section 1 that a correlation exists between nontraditional students stress levels and their academic performance (Milam, 2008; Quimby & O Brien, 2006). Overall, the analyses indicated that the workshops can help nontraditional students who experience perceived stressors such as financial problems.

7 Workshops evaluations The core factors that determined the benefit of the workshop intervention for both gender and age were the measures of the outcome of program implementation. The outcome was analyzed using switching replications group design implemented in the course of the program and compared to F- statistics of the variables introduced during the course of the implementation. Wilks lambda criteria F-statistics were used to determine which relationships were statistically significant at an alpha level of 0.05. The applied variables were previously mentioned as part of the psychometric properties of the Perceived Stress Survey. Main effects of treatment Switching replication group design was used in the study to show that the main effect was statistically significant, demonstrating that students who had the stress-management workshop intervention performed better than control students. Both the analyses of the switching replications design from the data acquired during workshop implementation and the workshops evaluations showed that the program intervention significantly reduced stressors among nontraditional undergraduates. As shown in Tables 1 and 2, F tests indicated that most of the investigated stressors significantly correlated with academic performance. Wilks lambda criteria F-statistics were used to determine which relationships were statistically significant at an alpha level of 0.05. Figures 1 and 2 were the pre-post bivariate distributions of the first and second implementations, respectively. As shown in Figures 1 and 2, analyses of the switching replications design indicated that individuals who participated in the stress-management workshops had improved GPAs. Treatment group tended to score higher on the posttest than on the pretest, indicating a program effect. Figures 1 and 2 were fitted with regression lines to show the pre-post relationship for each group and the treatment effect. The line for the treatment group showed a gain of about (0.5) points on a scale of (1.5 to 4.0) when compared to the control group at any pretest value. Therefore, the results showed that stress-management workshops reduced perceived stressors that influence nontraditional undergraduates and improved their academic performance (GPA). Figure 1. Effect of program intervention with Group 1 as the treatment group

8 Figure 2. Effect of program intervention with Group 2 as the treatment group Switching replications group design Figure 3 is the switching replications design for the workshop implementation. As shown in Figure 3, participants GPAs continued to improve after the treatments ended. The results suggest that the workshops had a long-term effect. This is supported by the results for Group 1 with respect to specific items on the workshops evaluation form. For all items on the evaluation, F values were and p values were <.0001. Similarly, the results for Group 2 proved that both the F and p values were and <.0001 respectively. Figure 3. Long-term treatment effect for both treatment groups Such a design was feasible because students could be pretested at the beginning of the term, Group 1 could receive the treatment during the first half of the fall mini-term, and Group 2 could receive the treatment during the second half of the fall mini-term. When some of the variability in the pretest was removed while preserving the differences between the groups by subtracting the residual values, the range between them was minimized. In other words, the

9 posttest was adjusted for pretest variability. In effect, the pretest was subtracted out. The use of switching replications and nonequivalent groups design depicted enhancement of organizational efficiency in resource allocation. Institutions need allocate only enough resources to offer the program to half of their students at any given time. Treatment outcomes could be short-term or long-term. During the first phase, the treatment group improved, whereas the control did not as shown in Figure 3. During the second phase, the original control group (now the treatment group) improved as much as the first treatment group had. However, during the second phase, the original treatment group continued to improve, even though they no longer were participating in the program. Thus, the program had long-term effects, presumably because the students continued to apply and develop learning and coping skills acquired in the program. The switching replications design addressed the potential for social threats such as compensatory rivalry, compensatory equalization, and resentful demoralization, all of which are likely to be present in educational contexts in which programs are offered to some students but not others. The switching replications design mitigated these threats because everyone eventually received the treatment. The nonequivalent groups design lacked randomization, but the switching replications design balanced this because it is independent of who received the treatment first and it produced the fairest way of allocating the assignment. Consequently, the workshops reduced perceived stressors and improved students academic performance. For both treatment groups, performance linearly improved with each subsequent workshop. Analysis performed showed that the treatment-group average significantly differed from the control-group average for first and second implementations, F (6, 33) = 2.64, p =.03. However, the second control group and second treatment group did not significantly differ, F (8, 31) = 1.41, p =.23. This result was expected because during the second phase, the original control group (now the treatment group) improved as much as the first treatment group. Conclusion Switching replications design was used to evaluate nontraditional students academic performance based on stressmanagement workshop implementation study. The materials were developed via design research methods and had not previously been evaluated in classroom settings. The primary objective was to enhance students academic performance by identifying and ameliorating perceived stressors that affect that performance. As evidenced in the results obtained and analyses performed, workshops identified and minimized perceived stressors. Also, it was observed that the treatment could have long-term positive effects. For most perceived stressors, gender had more effect on academic performance than age. It was concluded that the program developed in this study resulted in improved academic performance of nontraditional students. Based on the findings, it is recommended that stress-management workshops for nontraditional students be implemented and continued each semester. The methodology and procedures utilized in this study suggest that traditional students could benefit from stress management workshop as well. In addition, studies should be extended to larger sample sizes and demography to address the major limitations of the study. Students should be encouraged to participate in the program and continue with the treatment long enough to substantially reduce the stressors that impede academic performance given the trend observed in the study. References Ghosh, A.K., Javalgi, R. & Whipple, T.W. (2008). Service strategies for higher educational institutions based on student segmentation. Journal of Marketing for Higher Education, 17 (2), 238-255. Giancola, J. K., Grawitch, M.J., & Borchert, D. (2009). Dealing with the stress of college: A model for adult students. Adult Education Quarterly: A Journal of Research and Theory, 59 (3), 246-263. Gossett, B., Condoulis, A., Oaks, M., Kendall, J.R. (2008). Building communities within a diverse adult population. Continuing Higher Education Review, 72, 120-128. Harrell, I. L. (2008). Increasing the success of online students. Inquiry, 13 (1), 36-44. Jinkens, R. C. (2009). Nontraditional students: Who are they? College Student Journal, 43 (4), 979-987.

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