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RESULTS

 

 Psychology

 

Data Analysis

Table 1 presents descriptive statistics for each of the study variables. Scores for the scales on the CISS (TOC, EOC, andAOC) were converted to T-scores in order to standardize the results for both men and women. On the basis of information from the CISS manual (Endler & Parker, 1999), school counselors in this particular study scored at the 62nd percentile on the TOC (M = 53.01, SD = 7.71), the 27th percentile on the EOC (M - 43.91, SD = 8.88), and the 58th percentile on the AOC {M= 51.82, SD = 9.13). Regarding the organizational variables. Gray (1982) reported means for each subscale on the COSI (FS = 23.85, LDMA = 13.61, CTPR = 21.92, CPPR =7.79) with a national sample of school counselors (N= 361). For the present study, the mean for the FS subscale is comparable to Gray's previous results. However, means for each additional subscale indicate that counselors in the present study exhibited higher levels of stress regarding LDMA, CTPR, and CPPR. Also using a national sample of school counselors (N = 1,510), Coll and Freeman (1997) reported means on the RC (M= 15.5)andRI(M= 15.16) scales that were similar to findings in the present study. In their 1983 study of secondary school counselors (N= 487), Thompson and Powers reported an RA scale mean of 15.9, a score considerably lower than that of the population in the present study, indicating that school counselors in the present study more clearly understand their job duties and responsibilities.

For the outcome variables, an analysis of the studentized deleted residuals for the present study identified 1 extreme outlier in the EE subscale data and 3 in the DP subscale data. However, additional evaluation did not indicate that their removal from the data pool was warranted. Subsequently, a comparison of the means in this study with those of other outcome studies reported by Maslach et al. (1996) places this particular population of school counselors in the average range (middle third) on the EE subscale (M= 23.13, SD= 10.79) and the low range (lower third) on both the DP (M = 4.32, SD = 4.3) and the PA subscales (M= 41.39, SD = 5.02). These categorizations are similar when the population in the present study is compared with normed samples of K-12 teachers (N = 4,163) and social service workers (N= 1,538).

Hierarchical Regression Analysis Table 2 presents the zero-order correlations between the independent variables and each subscale score on the MBI-ES. All significant correlations were in the expected direction. A three-step hierarchical multiple regression model was used to analyze the individual and cumulative contributions made by the independent variables to each of the three dependent variables. Table 3 presents the variance accounted for by each step in the analysis as well as the beta weights associated with each independent variable in the final model.

For emotional exhaustion, Step 1 did not significantly predict EE scores, but accounted for 8% of the variation in this outcome. The two-step model contributed 33% to the overall variation in emotional exhaustion scores. The model at this stage was statistically significant overall, F(1, 70) = 4.96,p<.001,7^2=.33 (adjusted/;2 =.27). The Padded (.25) at this step was also significant. Step 3 contributed an additional .12 over and above the two-step model bringing the overall variation accounted for in this model to .45 (ad-justed R2 = .33). Although this third increase was not significant in and of itself (R2 add = .12, p <.08), the full model remained statistically significant, .F(14, 63) = 3.6&,p <>001. Among the individual variables, only emotion-oriented coping contributed significantly (p <.001) to the prediction of EE scores in the final model.

For depersonalization, the demographic variables in Step 1 contributed 7% to the overall variation in the model (ad¬justed R2 = .02) but did not significantly predict this outcome. Step 2 added an additional 8% (R2 add = .OS;p $11), bringing the total amount of variation accounted for by the model to 15% (adjusted R2 = .06). Although the combined effect of Steps 1 and 2 did not result in a statistically significant model, the next step did. Step 3 added an additional 15% to the model (/^add = .15, p $08), resulting in a statistically significant amount of variance (30%) accounted for by the full model, F(14, 63)= 1.91, p $05, adjusted/?2 =.14. As it did in the previous model, emotion-oriented coping again contributed significantly (p <.05) to the prediction of DP scores in the full model. Furthermore, one additional variable, FS, also made a statistically significant contribution to the outcome variable in the final model (p <.05).

Finally, results from the personal accomplishment model closely mimic those from the emotional exhaustion model. Once again, Step 1 did not significantly predict the out-come variable, personal accomplishment, but the combination of Steps 1 and 2 resulted in a highly significant model overall, accounting for 40% of the variation in PA scores, F(7, 70) = 6.53, p 5..001, adjusted R2 = .34. Step 2 also resulted in a statistically significant R2 added (R2 add = .35, p ^.001). Although Step 3 did not contribute a statistically significant amount of variation in and of itself (2%), the final three-step model accounted for 42% of the overall variation in PA scores. This full three-step model still reflected statistical significance, F(14, 63) = 3.24, p S.OOl, adjusted R1 = .30. Once again, only EOC significantly contributed to the prediction of PA scores in the full model.

A post hoc power analysis was completed for each of the three models. For this study, power analyses for the three regression equations yielded the following results: EE = .97, DP = .83, PA = .95. This indicates a strong likelihood that the analyses were sufficiently sensitive to identify statistically significant variable relationships.

DISCUSSION

Overall, this sample of school counselors exhibited a fairly healthy profile on the MBI-ES when compared with norms provided in the MBI manual (Maslach et al., 1996). Thus, school counselors in this sample reported a strong sense of competence and successful achievement in their jobs (personal accomplishment) and an overall feeling that they were able to work with others on a regular basis in personal, caring ways (depersonalization). Only on the EE subscale did this group show any elevated levels of burnout. Although the mean score (M =23.13, SD= 10.79) was not so elevated as to be extreme, further examination of frequency counts revealed that 31 of the study's 78 respondents scored in the high range (S 27) or upper third of the EE subscale. This amounts to 40% of the sample reporting high levels of emotional exhaustion. Empirical evidence may help to explain this apparent disparity between higher scores on the EE subscale and the relatively low scores on the DP and PA subscales. Preliminary studies have provided support for the claim that burnout progresses sequentially from emotional exhaustion to depersonalization and subsequently on to reduced feelings of personal accomplishment (Lee & Ashforth, 1993; Leiter, 1989; Leiter & Maslach, 1988). If that is the case, it may be that this particular sample is reflective of a population of individuals, many of whom are experiencing the initial stages of burnout. A longitudinal study would be indicated to determine whether or not this population subsequently progresses to higher levels of depersonalization and reduced feelings of personal accomplishment.

A three-step hierarchical regression analysis was completed to determine both the unique and the cumulative contributions that each independent variable set contributed to the three outcome variables. In the end, each model accounted for a statistically significant amount of the variance in the three outcome measures (45%, 30%, and 42%, respectively). These findings indicate that demographic, intrapersonal, and organizational factors together account for a significant amount of the variation in burnout scores among this population. Furthermore, in two models, emotional exhaustion and personal accomplishment, the intrapersonal variables in Step 2 contributed statistically significant amounts to the model in and of themselves (25% and 35%, respectively).

Additionally, the single variable found to be statistically significant across all three models was the emotion-oriented coping variable. This result lends additional credence to Savicki and Cooley's (1982) argument that the intrapersonal dimension deserves more attention in the research on bum-out. Furthermore, these results suggest a strong emotional component to burnout. Those who deal with stressors and problems by focusing on the feelings associated with them run a higher risk of developing the symptoms of burnout. This would certainly justify increased attention to the ways that school counselors deal with stress. There is nothing in the literature to suggest that people who are highly emotional cannot continue to develop strengths in other areas. As such, the results of this study suggest that it might be useful for counselors to continually develop their coping skills. This might serve to buffer them from the lasting effects of burnout over time.

Although not reported in the Results section, a number of additional steps in the different models reflected data trends that were consistent with hypotheses but did not meet the .05 criterion for statistical significance. For example, in both the emotional exhaustion and depersonalization models, the organizational factors in Step 3 approached significance in each case (EE: R2add = .12, p $.08; DP: R2 add = .15, p $.08), thereby suggesting that this set of variables plays an important role in one's reported level of burnout. In addition, numerous variables were statistically significantly related to the outcomes when considered individually but did not add significant variation over and above the variance accounted for by the variables that were entered earlier in the model. We suspect that these steps and variables did not register as statistically significant largely due to the sample size. Because of this, readers should be cautioned about generalizing these finding to other samples.

The present study again indicated that when considered in the univariate context, numerous factors identified and confirmed by previous studies were significantly correlated with the outcome measures of burnout (see Table 2). For example, years of experience (YOE) was negatively correlated to outcome scores on both the EE (YOE = -.26) and DP (YOE = -.24) subscales, indicating that those with fewer years of experience in the profession were more likely to exhibit elevated scores on these subscales. This finding has been identified by other researchers also (Mills & Huebner, 1998). Of further note, three particular independent variables (emotion oriented coping, counselor teacher professional relationships, and role ambiguity) were significantly associated with each of the three outcome variables. Moreover, whereas six of the organizational variables were found to correlate with outcomes on the EE and DP subscales, only three were found to be directly associated with the PA subscale. This finding is consistent with the results of Lee and Ashforth's (1996) meta-analysis of 61 burnout studies, which revealed that organizational stressors correlated more frequently with emotional exhaustion and depersonalization than they did with personal accomplishment.

STRENGTHS AND LIMITATIONS

Three strengths of this study should be noted. First, by drawing extensively from the literature, the current study extends previous work in the field of school counseling in that the successive and cumulative contributions of demo¬graphics, intrapersonal factors, and organizational factors to burnout were evaluated. The resulting model represents both internal and external factors associated with burnout. As such, it offers a more complete picture of burnout than would simple correlational analyses. Furthermore, power analyses indicate that these findings have merit. The result is that consideration of the intrapersonal dimension when evaluating burnout appears to be strongly indicated. In addition, the sampling procedure that was used ensured that a representative sample of the school counselors involved in this particular statewide organization was included in this study.

There are also two limitations to this study as reported. First, survey research relies on self-report and voluntary par¬ticipation. This introduces the possibility that those counselors who are experiencing extremely high levels of bum-out might in fact have been too overextended to respond to this study. In any case, respondents still represented each of the 10 state regions from this sample in fairly proportional numbers. A second limitation of the study was the final sample size (n = 78). Related to this, the current research design used 14 variables in the final three-step model, thereby violating the traditionally recommended 10:1 sample size to variable ratio. However, in their discussion of power and sample size as it relates to multiple regression, Wampold and Freund (1987) encouraged caution regarding these traditional conventions. They urged applied researchers to calculate power when analyzing data and noted that regression analyses with considerably lower sample size to variable ratios have greater power to identify significant variable relationships than conventional guidelines would suggest.

IMPLICATIONS FOR FUTURE RESEARCH

Several recommendations for future research are indicated. First, replication of this model with a larger national sample would yield more generalizable results. Although research findings do not support further investigation of the zero-order correlations between certain independent variables and the MBI, additional analyses that would evaluate the overall contributions of these multiple variable sets to burnout are warranted. Furthermore, ongoing investigation of the impact of intrapersonal variables on burnout is indi¬cated. Lambie (2002) considered ego development among school counselors as one such intrapersonal variable influencing burnout. Other potentially relevant variables might include measures of personality, counselor self-efficacy, or resiliency. In fact, Maslach et al. (1996) recommended focusing in the future on an exploration of those factors that buffer individuals from the effects of burnout. They suggested that an increased understanding of the burnout construct would be greatly enhanced by evaluating the components that aid in the prevention and remediation of the symptoms related to burnout. Also, a relatively large number of this study's respondents reported high levels of emotional exhaustion. It is interesting that high scores were not observed on the DP and PA subscales for this sample. Longitudinal studies that examine the developmental sequence of burnout are thus indicated. Finally, existing research on burnout has brought researchers to the point at which they may begin to ask about the pathways that these variables follow to the different outcomes as measured by the MBI. Thus path-analytic studies may also be warranted.

CONCLUSION

A clearer understanding of burnout and its correlates has implications for professional job satisfaction as well as professional training. If indeed professional school counselors' abilities to deliver comprehensive services are compromised as levels of stress and burnout increase, then it is important to study this phenomenon and develop strategies for coping with its symptoms. For this study, evidence was presented supporting the hypothesis that one's intrapersonal coping style has a direct, associative relationship with each of the dimensions of burnout as measured by the MBI-ES. As a result, professional development programs and school districts would be wise to promote school counselor awareness of the potential impact that dealing with stress, primarily on an emotional level, can have. This may mean engaging future and current professionals in the time-honored tasks of skill development in the areas of time management and skill prioritization. The results also seem to indicate that working relationships with teachers and administrators matter, as do clear delineations and definitions of job expectations. Although some of the responsibility for creating positive work environments rests with administrators and school leadership personnel, school counselors (as leadership personnel themselves) can also do much to influence these factors. In fact, with their specialized training in group dynamics and interpersonal relationships, who are better poised than school counselors to contribute this expertise to their schools? In the end, the goal is to better serve those populations of students, parents, and teachers with whom school coun¬selors work. It can be argued that healthy people are better able to undertake this daily task than are those who are experiencing increased levels of burnout. The results of this study suggest, then, that these dimensions warrant additional consideration.

REFERENCES

Buchner, A., Faul, F., & Erdfelder, E. (1997). G*Power for Macintosh, Version 2.1.2. [Computer software]. Retrieved June 15, 2006, http://www.psycho.uni-duesseldorf.de/aap/projects/gpower
Butcke, P., Moracco, J. C., & McEwen, M. K. (1984). Measuring occupational stress among counselors: A multidimensional concept. Measurement and Evaluation in Guidance, 17, 24-31.
Coll, K. M., & Freeman, B. (1997). Role conflict among elementary school counselors: A national comparison with middle and sec¬ondary school counselors. Elementary School Guidance & Coun¬seling, 31,251-26\.
Cosway, R., Endler, N. S., Sadler, A. J., & Dreary, I. J. (2000). The Coping Inventory for Stressful Situations: Factorial struc¬ture and association with personality traits and psychologi¬cal health. Journal of Applied Biobehavioral Research, 5, 121-143.
Cummings, 0. W., & Nail, R. L. (1983). Relationships of leadership style and burnout to counselors' perceptions of their jobs, them¬selves, and their clients. Counselor Education and Supervision, 22, 227-234.
Dahir, C. A. (2001). The national standards for school counseling programs: Development and implementation. Professional School Counseling, 4, 320-327.
Endler, N. S., & Parker, J. D. A. (1999). Coping Inventory for Stressful Situations (C1SS): Manual (2nd ed.). Toronto, Ontario, Canada: Multi-Health Systems.
Freeman, B., & Coll, K. M. (1997). Factor structure of the Role Ques¬tionnaire (RQ): A study of high school counselors. Measurement and Evaluation in Counseling and Development, 30, 32-39.
Gold.Y. (1984). The factorial validity of the Maslach Burnout In¬ventory in a sample of California elementary and junior high school classroom teachers. Educational and Psychological Mea¬surement, 44, 1009-1016.
Gray, P. (1982). Development of a counselor occupational stress in-ventory. Dissertation Abstracts International, 43, 06A. (UMINo. 8225469)
Handy, J. A. (1988). Theoretical and methodological problems with occupational stress and burnout. Human Relations, 41, 351-369.
Hansen, J. C. (1967). Job satisfactions and job activities of school counselors. The Personnel and Guidance Journal, 45, 790-794.
Hargrove, D. S. (1989). Review of the Maslach Burnout Inventory, second edition. In J. C. Conoley & J. J. Kramer (Eds.), The tenth mental measurements yearbook (pp. 473-475). Lincoln: The University of Nebraska Press.
Huberty, T. J., & Huebner, E. S. (1988). A national survey of burnout among school psychologists. Psychology in the Schools, 25, 54-61.
Huebner, E. S., & Huberty, T. J. (1984). Burnout among rural school psychologists. Research in Rural Education, 2, 95-99.
Iwanicki, E. F., & Schwab, R. L. (1981). A cross-validational study of the Maslach Burnout Inventory. Educational and Psychologi¬cal Measurement, 41, 1167-1174.
Keegan, A. R. (1986, September 4). Time: A precious commodity for counselors. Guidepost, 4, 1.
Kendrick, R., Chandler, J., & Hatcher, W. (1994). Job demands, stressors, and the school counselor. The School Counselor, 41, 365-369.
Lambie, G. (2002). The contribution of ego development level to degree of burnout in school counselors. Dissertation Abstracts International, 63, 02A. (UMINo. 3041698)
Lee, R. T, &Ashforth, B. E, (1993). A longitudinal study ofbumout among supervisors and managers: Comparisons between Leiter and Maslach (1988) and Golembiewski et al. (1986) models. Organizational Behavior and Human Decision Processes, 54, 369-398.
Lee, R. T, & Ashforth, B, E. (1996). A meta-analytic examination of the correlates of the three dimensions of job burnout. Journal of Applied Psychology, 81, 123-133.
Leiter, M. P. (1989). Conceptual implications of two models of burnout: A response to Golembiewski. Group and Organization Studies, 14, 15-22.
Leiter, M. P., & Maslach, C. (1988). The impact of interpersonal environment on burnout and organizational commitment. Jour¬nal of Organizational Behavior, 9, 297-308.
Licht, M. H. (2000). Multiple regression and correlation. In L. G. Grimm & P. R. Yarnold (Eds.), Reading and understanding mul-tivariate statistics (pp. 19-64). Washington, DC: American Psy¬chological Association.
Maslach, C. M. (1993). Burnout: A multidimensional perspec¬tive. In W. B. Schaufeli, C. M. Maslach, & T. Marek (Eds.), Professional burnout; Recent developments in theory and re¬search (pp. 19-32). Washington, DC: Taylor and Francis.
Maslach, C. M., & Jackson, S. E. (1981). The measurement of experienced burnout. Journal of Occupational Behavior, 2, 99-113.
Maslach, C. M., Jackson, S. E., & Leiter, M. P. (1996). Maslach Burnout Inventory (3rd ed.). Palo Alto, CA: Consulting Psy¬chologists Press.
Mills, L. B., & Huebner, E. S. (1998). A prospective study of per¬sonality characteristics, occupational stressors, and burnout among school psychology practitioners. Journal of School Psy¬chology, 36, 103-120.
Moracco, J. C., Butcke, P. G., & McEwen, M. K. (1984). Measuring stress in school counselors: Some research findings and implica¬tions. The School Counselor, 32, 110-117.
Parker, B. A. (1982). Stress and the school counselor. Journal of Non-White Concerns, 11, 3-10.
Patrick, P. K. S. (1979). Burnout: Job hazard for health workers. Hospitals, 53, 87-90.
Pierson-Hubeny, D., & Archambault, F. (1987). Role stress and perceived intensity of burnout among school psychologists. Psy¬chology in the Schools, 24, 244-253.
Reiner, H. D., & Hartshorne, T. (1982). Job burnout and the school psychologist. Psychology in the Schools, 19, 508-512.
Rizzo, J. R., House, R. J., & Lirtzman, S. I. (1970). Role conflict and ambiguity in complex organizations. Administrative Science Quar¬terly, 15, 150-163.
Sandoval, J. (1989). Review of the Maslach Burnout Inventory, second edition. In J. C. Conoley & J. J. Kramer (Eds.), The tenth mental measurements yearbook (pp. 475-476). Lincoln: The University of Nebraska Press.
Sandoval, J. (1993). Personality and burnout among school psy¬chologists. Psychology in the Schools, 30, 321-326.
Savicki, V, & Cooley, E. J. (1982). Implications of burnout research and theory for counselor educators. The Personnel and Guidance Journal, 60, 415-419.
Schwab, R. L., Iwanicki, E, F, & Pierson, D. A. (1983). Assessing role conflict and role ambiguity: A cross validation study. Educational and Psychological Measurement, 43, 587-593.
Sears, S. J., & Navin, S. L. (1983). Stressors in school counseling. Education, 103, 333-337.
Stickel, S. A. (1991, February). A study of burnout and job satisfac¬tion among rural school counselors. Paper presented at the an¬nual conference of the Eastern Educational Research Association, Boston.
Thompson, D., & Powers, S. (1983). Correlates of role conflict and role ambiguity among secondary school counselors. Psychologi¬cal Reports, 52, 239-242.

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