Teachers' occupation-specific work-family conflict.
Profound changes in the world of work in recent decades, such as rising numbers of women in career trajectories, have stimulated much research on work-family conflict (WFC) (Grzywacz & Marks, 2000). WFC is a form of interrole conflict comprising incompatible pressures from work and family roles (Greenhaus & Beutell, 1985). Results of this research have repeatedly demonstrated the negative effects of WFC on employees' behavior, emotions, and health (see Frone, 2003) and have underscored the importance of reducing the conflict.
Most research on WFC antecedents and outcomes use generic models to study managerial and demanding occupations (Cinamon & Rich, 2005). These models usually focus on the association between WFC and certain work stressors, assuming that such general stressors affect a wide variety of occupations similarly. However, these models often disregard distinctive aspects of particular occupations that may also affect WFC. Moreover, recent evidence demonstrates that certain occupations have unique role stressors that contribute to employees' stress (Bacharach & Bamberger, 1992; Narayanan, Menon, & Spector, 1999; Pousette & Hanse, 2002; Van Der Doef & Maes, 2002). Assessment of effects of unique stressors on WFC in specific occupations, in addition to effects of general occupational stressors, should provide a richer and more comprehensive picture of WFC antecedents. This approach may also enable developers of occupational health programs to focus on those elements proven effective in combating specific stressors in particular occupations.
Extending WFC research to specific occupations, this study investigated WFC among teachers, a profession largely overlooked by WFC researchers To illustrate the benefits of occupation-specific WFC research, we examined variables unique to teaching in addition to generic, universal variables often examined in WFC research. Although we were primarily interested in general and occupation-specific stressors' effects on WFC, the lack of research on teachers' work-family relations also stimulated analysis of two important outcomes of teachers' WFC: burnout and vigor.
Antecedents of WFC
Much research has explored antecedents of two types of WFC: when work is perceived as interfering with family (W [right arrow] F) and when family is perceived as interfering with work (F [right arrow] W). Most results indicate that stressors from work more heavily influence W [right arrow] F conflict, whereas family stressors more heavily influence F [right arrow] W conflict. Many researchers have investigated role characteristics that presumably produce role-related stress that diminishes one's capacity to meet demands of other roles (see Frone, 2003). Several studies found that W [right arrow] F conflict relates positively to number of hours employees devote to work (Grzywacz & Marks, 2000) and negatively to flexible schedules and managerial support (Bernas & Major, 2000).
Some stressors contributing to WFC may be common to most occupations, but the effects of stressors within different occupations will probably vary as a function of job and setting characteristics (Naraynan et al., 1999; Spark & Cooper, 1999). Researchers have also raised this claim for other work stress concepts, such as burnout (e.g., Byrne, 1999; Maslach, 1999). Accordingly, it is likely that commonly investigated generic variables, such as flexibility and number of work hours, will render varying effects on WFC in different occupations because of their unique characteristics. Examination of WFC in specific occupations may reveal that employees in different occupations establish distinct patterns of relationships between work and family roles. For example, flexibility of work hours may play a major role in moderating WFC in occupations that demand relatively fixed work schedules (e.g., factory workers), but its influence on WFC among employees who have more latitude to arrange their workday (e.g., artists) may be quite small. Likewise, number of work hours as a role stressor may have dissimilar effects on WFC for jobs that require individuals to spend their entire workday at the workplace, as opposed to occupations in which employees frequently apply ideas that were cultivated in their "free time" away from the work site. The latter typifies designers, teachers, and scientists, among others, who produce valuable work ideas away from the formal workplace.
Recent research has also established that unique stressors characterize particular occupations. For example, Simmons (2000) revealed that a patient's death was especially stressful for hospital nurses. Lloyd, King, and Chenoweth (2002) found that tension between social workers' professional philosophy and their work environment contributed to stress and burnout. Engineers reported that waste of time and interpersonal conflicts were especially stressful to them (Keenan & Newton, 1985). Van Der Doef and Maes (2002) showed that student aggression and professional education explained significant amounts of variance in teacher burnout. These studies support the value of conducting occupation-specific investigations to understand how specific work factors influence WFC in particular occupations instead of relying exclusively on generic models.
Another reason for advocating occupation-specific investigations is that global measures of stress that are removed from real work experiences provide inaccurate information that is relevant to only limited aspects of employee roles (Shirom, 1988). In contrast, occupation-specific stress measures that are sensitive to particular work situations are well understood by respondents from that occupation and provide more accurate and valid information.
Unique Characteristics of the Teaching Profession
Teaching occupies a special position regarding WFC. The fact that teachers' work extends beyond the work site and requires them to expend much effort at home raises questions regarding teachers' responses to generic WFC stressors, such as number and flexibility of work hours. Indeed, Cinamon and Rich (2005) found that many general variables established by research as antecedents of WFC among female managers and high-tech workers did not explain teachers' WFC. Their findings suggest that stressors related directly to teaching may better explain the variance in teachers' WFC.
Considerable research has reported specific factors in teachers' work that cause stress and reduced sense of efficacy. In general, frustration of goal attainment constitutes an important source of teacher stress. For example, student misbehavior and class management demands are major stressors for teachers (Hastings & Bham, 2003), as is parent intrusion in teachers' work (Dworkin, 1997). Other factors include large class size, many students with special needs in class, and low student achievement (Maslach & Leiter, 1999; Ross, 1998).
The present study examined three occupation-specific variables--class size, investment in student misbehavior, and investment in relations with parents--and five generic variables--flexibility of work hours, number of work hours, manager support, colleague support, and spousal support--as antecedents of teachers' WFC. We predicted that teachers' occupation-specific stressors would explain considerable variance in teachers' W [right arrow] F conflict in addition to that explained by generic stressors.
Outcomes of WFC
This study also examined outcomes of teachers' WFC. The dearth of research regarding WFC and teachers has yielded little evidence on its effects (Cinamon & Rich, 2005). To address this deficiency, we investigated teacher burnout and vigor, two outcomes linked to employees' health and work performance.
Scholars conceptualize burnout as a reaction of human service workers to stress that generates negative work outcomes, such as turnover, absenteeism, and low organizational commitment, as well as reduced psychological and physical well-being (Shirom, 2003). Definitions of burnout usually encompass three aspects: emotional exhaustion, depersonalization, and sense of reduced personal accomplishment. Emotional exhaustion refers to one's feelings of depletion of emotional resources. It is regarded as the fundamental component of burnout that leads to depersonalization (Maslach, Schaufeli, & Leiter, 2000). Research has shown that this dimension is most responsive to the nature and intensity of work-related stress (Lee & Ashforth, 1996; Schaufeli & Enzmann, 1998).
Ample evidence indicates that many teachers experience burnout and that it has both generic and specific antecedents (Burke & Greenglass, 1995). Maslach, Jackson, and Leiter (1996) concluded that general organizational stressors relating positively to educator burnout include role conflict and ambiguity, whereas participatory decision making, social support, and lack of autonomy relate negatively. Researchers have also examined specific stressors, discovering that disruptive and disrespectful student behavior predicted teacher burnout (Burke, Greenglass, & Schwarzer, 1996; Hastings & Bham, 2003; Van Der Doef & Maes, 2002), as did negative relations with students or staff (Dorman, 2003). Given the high incidence of teacher burnout and its negative effects, we examined whether W [right arrow] F conflict and F [right arrow] W conflict, in addition to other specific and generic stressors, contribute to teachers' emotional exhaustion, the primary component of burnout.
Recently, a few researchers investigating burnout have begun to study work engagement. Schaufeli and Bakker (2004) regarded engagement as different from burnout but not its polar opposite. An important component of work engagement is vigor, which Schaufeli, Bakker, and Salanova (2004) described as consisting of high levels of effort, energy, resilience, and persistence. Vigor represents a positive affective response to one's interactions with elements in the job and the job environment. Thus, it is likely that low levels of WFC are associated with high levels of employee vigor, whereas elevated levels of WFC are associated with reduced vigor. Accordingly, we were interested in examining the relationship between WFC and vigor. Furthermore, it is valuable to determine whether general and specific WFC variables affect burnout and vigor with similar strength but in opposite directions or whether the relationships follow unique patterns.
In sum, this study investigated the contribution of general and unique stressors to high school teachers' W [right arrow] F conflict and F [right arrow] W conflict as well as the relationships between these conflicts and burnout and vigor.
Participants were 230 teachers (48 men, 182 women) between the ages of 26 to 66 years (M = 43.3, SD = 9.64). Participants were recruited from five public high schools in one school district that served Jewish students of middle and low socioeconomic status. Sixty-seven percent of the participants (n = 154) had a BA or a BEd, 28% (n = 64) had a master's degree, and 1% (n = 2) had a doctorate. Four percent of the participants (n = 10) did not provide information on their degree. Years of teaching experience ranged from 1 to 39 (M = 15.7, SD = 9.6). Mean number of reported weekly work hours was 33 (SD = 12.3). Only married teachers were included in the sample. Years of marriage ranged from 1 to 39 (M = 16.43, SD = 9.55). The vast majority (96.5%) of the teachers had children (M = 2.76, SD = 1.4).
WFC. Cinamon and Rich's (2002a) adaptation of Gutek, Searle, and Klepa's (1991) Work-Family Conflict Scale measured teachers' perceptions of W [right arrow] F conflict and F [right arrow] W conflict on a 5-point Likert-type scale, ranging from 1 (strongly disagree) to 5 (strongly agree). Seven items assessed W [right arrow] F conflict (e.g., "My work takes up time I want to invest in my family"), and seven items assessed F [right arrow] W conflict (e.g., "My family demands and personal problems interfere with my work"). Factor analysis with varimax rotation on the present data validated Gutek et al.'s two-factor solution with the expected items. Cronbach's alphas of internal reliability were .78 for W [right arrow] F conflict and .81 for F [right arrow] W conflict.
Manager, colleague, and spousal support. Cinamon and Rich's (2002b) adaptation of Loerch, Russell, and Rush's (1989) manager support subscale assessed teachers' perceptions of manager, colleague, and spousal support. The adapted version included 14 items assessing perceptions of (a) manager support (n = 5; e.g., "My manager shows interest in my family life"), (b) colleague support (n = 4; e.g., "I get support from my colleagues"), and (c) spousal support (n = 5; e.g., "My spouse is interested in my work"). Participants responded to randomly presented items on a 5-point Likert-type scale, ranging from 1 (strongly disagree) to 5 (strongly agree). Factor analysis with varimax rotation of the expanded 14-item scale validated Loerch et al.'s three-factor solution with the expected items. Satisfactory internal reliability was achieved, with alphas of .77, .76, and .87 for the manager support, colleague support, and spouse support subscales, respectively.
Flexible work hours. Perception of flexible work hours was assessed using two items from Izraeli's (1993) research: "It is usually difficult to change my working hours" and "There is a lot of flexibility in my working hours." The correlation between these items was r = .52.
Emotional exhaustion. Participants responded to five items from the Maslach Burnout Inventory-General Survey (Schaufeli, Leiter, Maslach, & Jackson, 1996), describing work-related emotional exhaustion (e.g., "I feel tired when I wake up in the morning to a new work day") on a 7-point scale, ranging from 0 (never) to 6 (every day). Internal reliability of the scale was alpha = .84.
Feelings of vigor at work. Four items from the Utrecht Work Engagement Scale (Schaufeli et al., 2004; e.g., "At work, I feel strong and vigorous") assessed vigor on a 7-point scale, ranging from 0 (never) to 6 (every day). Internal reliability was alpha = .77.
Teachers' perceived investment in students' behavior problems. Two items with a common stem, "Students' behavior problems that you deal with demand from you ...," assessed teachers' time and emotional investment in students' behavioral problems. Teachers responded to the stem twice, once on a 10-point scale ranging from 1 (little time investment) to 10 (huge time investment) and the second time on a 10-point scale ranging from 1 (low emotional investment) to 10 (huge emotional investment).
Teachers' perceived investment in students' parents. Two items with a common stem, "Relations with your students' parents demand from you ...," assessed teachers' time and emotional investment in students' parents. Teachers responded to the stem twice, once on a 10-point scale ranging from 1 (low time investment) to 10 (huge time investment) and the second time on a 10-point scale ranging from 1 (low emotional investment) to 10 (huge emotional investment).
Professional and demographic variables. A questionnaire was also administered to collect information regarding teacher's gender, age, marital status and length of marriage, number and ages of children living at home, years of teaching experience, number of weekly work hours, number of weekly hours in housework, number of spouse's work hours, whether the respondent filled another role in school, number of students in the teacher's class, and number of students with special needs in the class.
After receiving approval from the appropriate authorities, we distributed questionnaires to 400 teachers in five high schools. Each questionnaire set was in an open manila envelope that also contained a letter from the researchers (the authors of this article) on university stationery that solicited participation, ensured anonymity, and requested teachers to return the questionnaires in the sealed envelope to the school secretary within 2 weeks. Presentation sequence of the main instruments was counterbalanced. Participants had unlimited time to complete the questionnaires. We excluded from the 260 returned questionnaires those participants who did not respond to all items, individuals whom we suspected of random response, and unmarried teachers. A total of 230 complete questionnaire sets were analyzed (58%).
Table 1 presents means, standard deviations, and intercorrelations for the main variables examined in this study.
Antecedents of WFC
To examine generic and specific antecedents of high school teachers' WFC, we conducted two linear regression analyses for each of the two dependent variables: W [right arrow] F conflict and F [right arrow] W conflict. In the first regression, the first step comprised the following occupation-specific stressors: class size, number of students with special needs, investment in student misbehavior, and investment in relations with parents. The second step comprised generic stressor variables from the work domain: number of work hours, manager support, colleague support, and flexibility of work hours. The third step included generic stressor variables from the family domain: number of children, number of hours invested in housework, and spousal support. In the second regression, generic stressors were entered in the first step. The second step comprised the generic family stressors, and the occupation-specific stressors were entered in the third step. We determined the order of entry for the three groups of variables. Within each group, each variable was entered according to its contribution to explaining the variance in the dependent variable. The first regression shows the contribution of the generic stressors to the dependent variable above that of the occupation-specific stressors. The second regression reflects the contribution of occupation-specific stressors to the dependent variable that exceeded that of the generic stressors. Tables 2 and 3 present the contribution of occupation-specific stressors (the second regression).
Examination of the two regressions of W [right arrow] F conflict demonstrates that the specific stressors explained more variance of the W [right arrow] F conflict than did the generic stressors. The models of the two regressions explained 16% of the variance in the W [right arrow] F conflict. Table 2 indicates that the specific teacher variables explaining 11% of the variance were investment in student misbehavior and investment in relations with parents. Even when specific stressors were entered in the third step and not in the first step, they explained an additional 10% of the variance. Greater investment in student misbehavior raised W [right arrow] F conflict (r = .30, p < .01), as did greater investment in relations with parents (r = .27, p < .01). Perceptions of enhanced manager support explained another 4% of the variance and were related to teachers' lower levels of W [right arrow] F conflict.
Examination of the two regressions of F [right arrow] W conflict indicates that the two regression models explained 13% of the variance of the F [right arrow] W conflict. Table 3 demonstrates that unique teaching stressors explained 4% of the variance; only investment in student misbehavior made a significant contribution (r = .14, p < .05). Generic work stressors (Step 3) explained 6% of the variance, with flexibility of work hours (r = -.19, p < .01) and manager support (r = -.13, p < .05) reducing the F [right arrow] W conflict. Generic family stressors explained only 3% of the variance of F [right arrow] W conflict. Spousal support was the only significant predictor from the family domain of F [right arrow] W conflict (r = -.13, p < .05); it reduced F [right arrow] W conflict.
In sum, regression analysis indicated that the occupation-specific stressors, investment in student misbehavior, and investment in relations with parents significantly contributed to explain the variance in teachers' WFC. Two general stressors also significantly predicted WFC, but the specific stressors were considerably more powerful predictors than were the general stressors. These results support this study's argument regarding the advantages of examining both unique and generic stressors in specific occupations.
We also investigated whether teachers evidence the typical pattern found for other occupations whereby work stressors more heavily influence W [right arrow] F conflict and family stressors more heavily influence F [right arrow] W conflict.
Table 2 indicates that work but not family stressors explained significant amounts of variance in teachers' W [right arrow] F conflict. The outcome regarding F [right arrow] W conflict is less clear. Correlations between the four stressors that contributed significantly to the F [right arrow] W conflict were significant but low, and three of them--investment in student misbehavior, flexibility of work hours, and manager support--derived from the work domain. In the family domain, only spousal support correlated significantly with the F [right arrow] W conflict. These results suggest that work stressors explain more variance in WFC than do family stressors.
Antecedents of Burnout and Vigor
Another goal of this study aimed to assess teachers' burnout and vigor as a function of their WFC. We conducted linear regression analyses with emotional exhaustion (burnout) and vigor as the dependent variables. The first step of the regression included occupation-specific stressor variables. Generic work stressor variables composed the second step. We entered generic family stressors in the third step and W [right arrow] F conflict and F [right arrow] W conflict in the fourth step. Rules for order of entry of variables were the same as in the earlier analyses.
The model explained 40% of the variance in teachers' emotional exhaustion. Specific stressors explained 5% of the variance; investment in student misbehavior made the only significant contribution ([beta] = .21, p < .01). Another 8% of the variance was explained by manager support ([beta] = -.31, p < .01). None of the generic family stressor variables explained significant amounts of variance in teacher burnout. Twenty-seven percent of the variance was explained by W [right arrow] F conflict ([beta] = .42, p < .01) and F [right arrow] W conflict ([beta] = .24, p < .01), both of which increased teachers' emotional exhaustion.
The entire model explained 22% of the variance of vigor. Manager support explained 16% of the variance and was associated with increased vigor ([beta] = .35, p < .01). Whereas both W [right arrow] F conflict and F [right arrow] W conflict contributed to burnout and explained 27% of the variance, only F [right arrow] W conflict contributed an additional 6% of the variance ([beta] = -.28, p < .01). Increased F [right arrow] W conflict was associated with less vigor.
Consistent with the need for occupation-specific investigations to disclose how psychosocial factors at work influence stress (Pousette & Hanse, 2002; Van Der Doef & Maes, 2002), the current study examined the contribution of generic stressors from the work and family domains and of variables unique to teaching to high school teachers' WFC.
Results suggest some advantages of occupation-specific inquiry. Although correlations were only moderate to relatively low, generic stressors and variables unique to teaching provided significant contributions to explaining teachers' W [right arrow] F conflict. Specific variables included teacher investment in student behavior problems and in establishing and maintaining relations with the students' parents.
Contrary to typical results of WFC research, in this study, flexibility of teachers' work hours was positively correlated with WFC. This result can be explained by the possibility that, for teachers, flexibility of work hours means that one can leave the work site early and take occupational tasks home. Flexible work hours allow teachers to work less time at school and more at home. Clearly, the relationship between role stressors and WFC is not the same for all occupations.
Regarding the outcomes of WFC, both W [right arrow] F conflict and F [right arrow] W conflict predicted teacher burnout. Burke and Greenglass (2001) also found that both types of WFC were positively associated with high levels of burnout among nursing staff in hospitals. However, there is good reason to assume that a circular relationship exists. High levels of conflict lead to increased burnout, which reduces one's ability to handle stressors successfully, including demands from work and family. Indeed, in a recent longitudinal study, Westman, Etzion, and Gortler (2004) found that burnout preceded W [right arrow] F conflict. This finding accords with Schaufeli and Buunk's (2002) claim that individuals in an advanced phase of burnout report more negative work experiences, such as greater stress, more conflicts, and more role problems.
Whereas burnout was related to both kinds of WFC, vigor was predicted by F [right arrow] W conflict only. This is in line with Schaufeli and Buunk's (2002) theorizing that people with high levels of vigor may find that intrusions from home to work reduce their vigor at work; however, interference from work to home does not affect vigor at work.
Results here suggest that emotional exhaustion and vigor are distinct, albeit related, concepts. The correlation between them was negative but relatively low (r = -.25, p < .05), and they were predicted by different variables. Regarding the predictors of vigor, it should be mentioned that work engagement is the result of resources in the organization that have motivational potential because they make work meaningful. One such resource that received empirical support in the current study was social support. Receiving social support from one's manager and colleagues was linked to higher levels of vigor, indicating that social support is a resource that has an energizing function. In addition, number of work hours was positively related to vigor but unrelated to burnout. This may be due to teachers who have high levels of satisfaction and/or efficacy who work longer hours and display higher levels of vigor.
Inasmuch as the present study on teachers' WFC demonstrated the importance of occupation-specific aspects of teachers' work, further research should examine these aspects in a more detailed manner. For example, we were surprised that measures such as the total number of students and the number of students with special needs in the classroom, occupation-specific variables previously shown to contribute to teachers' stress (Ross, 1998), did not correlate with teachers' WFC. One explanation may be that participating teachers reported that there were fewer students in their classes, on average, than in the typical Israeli classroom (26 students vs. 30 students; Israel Central Bureau of Statistics, 2004); hence, these teachers may have felt that these factors were not especially stressful. It would also be valuable to ascertain the particular nature of students' special needs. Certain "special needs" make extraordinary demands on teachers' resources, whereas others may be satisfied more routinely by the classroom teacher or by means of pullout programs that reduce homeroom teachers' stress.
With regard to methodological issues, as in many previous studies on WFC and occupational stress among teachers, all measures here were based on self-report. Exclusive dependence on self-report measures may limit the validity of the findings. Validity of results could be enhanced by gathering information from school administrators, colleagues, and spouses, as well as from self-reports. In addition, researchers and practitioners outside of Israel are cautioned about the generalizability of the findings because of possible cultural differences in work-family relations among teachers that could affect the issues investigated in this study.
Results of the present study highlight practical implications concerning the importance of using occupation-specific models of WFC when developing occupational health programs. Instead of trying to reduce teachers' WFC by designing more flexible work hours, as would stem from generic models, it might be more effective to assist teachers to cope effectively with student behavior problems. Alternatively, helping teachers to interact constructively with students' parents may offer a more useful strategy than reducing teachers' work hours. Indeed, Berridge, Cooper, and Highley (1997) mentioned specific components as the first level of essential elements of an integrated and systematic approach to employee assistance programs. Results of the present study support a strategy that blends generic and occupation-specific factors in seeking to enhance work-family relations and to minimize their negative effects.
Bacharach, S., & Bamberger, P. (1992). Causal models of role stressor antecedents and consequences: The importance of occupational differences. Journal of Vocational Behavior, 41, 13-34.
Bernas, K. H., & Major, D. A. (2000). Contributors to stress resistance: Testing a model of woman's work-family conflict. Psychology of Women Quarterly, 24, 170-178.
Berridge, J., Cooper, C., & Highley, C. (1997). Employee assistance programmes and workplace counseling. Chichester, England: Wiley.
Burke, R. J., & Greenglass, E. R. (1995). A longitudinal study of psychological burnout in teachers. Human Relations, 48, 187-202.
Burke, R. J., & Greenglass, E. (2001). Hospital restructuring, work-family conflict and psychological burnout among nursing staff. Psychology and Health, 16, 583-594.
Burke, R. J., Greenglass, E. R., & Schwarzer, R. (1996). Predicting teacher burnout over time: Effects of work stress, social support, and self-doubts on burnout and its consequences. Anxiety, Stress and Coping: An International Journal, 9, 261-275.
Byrne, B. M. (1999). The nomological network of teacher burnout: A literature review and empirically validated model. In A. Huberman & R. Vandenberghe (Eds.), Understanding and preventing teacher burnout: A sourcebook of international research and practice (pp. 15-37). New York: Cambridge University Press.
Cinamon, R. G., & Rich, Y. (2002a). Gender differences in attribution of importance to life roles. Sex Roles, 47, 531-541.
Cinamon, R. G., & Rich, Y. (2002b). Profiles of attribution of importance to life roles and their implications for the work-family conflict. Journal of Counseling Psychology, 49, 212-220.
Cinamon, R. G., & Rich, Y. (2005). Work-family conflict among female teachers. Teaching and Teacher Education, 21, 365-378.
Dorman, J. P. (2003). Relationship between school and classroom environment and teacher burnout: A LISREL analysis. Social Psychology of Education, 6, 107-127.
Dworkin, A. G. (1997). Coping with reform: The intermix of teacher morale, teacher burnout, and teacher accountability. In B. J. Biddle, T. L. Good, & I. F. Goodson (Eds.), International handbook of teachers and teaching (pp. 459-498). London: Kluwer Academic.
Frone, M. R. (2003). Work-family balance. In J. C. Quick & L. E. Tetrick (Eds.), Handbook of occupational health psychology (pp. 143-162). Washington, DC: American Psychological Association.
Greenhaus, J. H., & Beutell, N. J. (1985). Source of conflict between work and family roles. Academy of Management Review, 10, 76-88.
Grzywacz, J. G., & Marks, N. F. (2000). Family, work, work-family spillover, and problem drinking during midlife. Journal of Marriage and the Family, 62, 336-348.
Gutek, B. A., Searle, S., & Klepa, L. (1991). Rational versus gender role explanations for work-family conflict. Journal of Applied Psychology, 76, 566-568.
Hastings, R. P., & Bham, M. S. (2003). The relationship between student behaviour patterns and teacher burnout. School Psychology International, 24, 115-127.
Israel Central Bureau of Statistics. (2004). Statistical yearbook (No. 55). Jerusalem: Government Printing Office.
Izraeli, D. N. (1993). Work/family conflict among women and men managers in dual-career couples in Israel. Journal of Social Behavior and Personality, 8, 371-385.
Keenan, A., & Newton, T. (1985). Stressful events, stressors and psychological strains in young professional engineers. Journal of Occupational Behavior, 6, 151-156.
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.
Lloyd, C., King, R., & Chenoweth, L. (2002). Social work, stress and burnout: A review. Journal of Mental Health, 11, 255-266.
Loerch, K. J., Russell, E. A., & Rush, C. M. (1989). The relationships among family domain variables and work-family conflict for men and women. Journal of Vocational Behavior, 35, 288-309.
Maslach, C. (1999). Progress in understanding teacher burnout. In H. Amichael & V. Roland (Eds.), Understanding and preventing teacher burnout: A sourcebook of international research and practice (pp. 211-222). New York: Cambridge University Press.
Maslach, C., Jackson, S. E., & Leiter, M. P. (1996). Maslach Burnout Inventory: Third edition. In R. J. Wood & C. P. Zalaquett (Eds.), Evaluating stress: A book of resources (pp. 191-218). Lanham, MD: Scarecrow Press.
Maslach, C., & Leiter, M. P. (1999). Teacher burnout: A research agenda. In H. Amichael & V. Roland (Eds.), Understanding and preventing teacher burnout: A sourcebook of international research and practice (pp. 295-303). New York: Cambridge University Press.
Maslach, C., Schaufeli, W. B., & Leiter, M. P. (2000). Job burnout. Annual Review of Psychology, 52, 397-422.
Narayanan, L., Menon, S., & Spector, P. E. (1999). Stress in the workplace: A comparison of gender and occupations. Journal of Organizational Behavior, 20, 63-73.
Pousette, A., & Hanse, J. J. (2002). Job characteristics as predictors of ill-health and sickness absenteeism in different occupational types--A multigroup structural equation modelling approach. Work and Stress, 16, 229-250.
Ross, J. A. (1998). The antecedents and consequences of teacher efficacy. Research on Teaching, 7, 49-74.
Schaufeli, W. B., & Bakker, A. B. (2004). Job demands, job resources, and their relationship with burnout and engagement: A multi-sample study. Journal of Organizational Behavior, 25, 293-315.
Schaufeli, W. B., Bakker, A. B., & Salanova, M. (2004). The measurement of work engagement with a brief questionnaire: A cross-national study. Educational and Psychological Measurement, 28, 21-35.
Schaufeli, W. B., & Buunk, B. P. (2002). Burnout: An overview of 25 years of research and theorizing. In M. J. Schabracq, J. A. M. Winnubst, & C. L. Cooper (Eds.), Handbook of work and health psychology (pp. 383-425). Chichester, England: Wiley.
Schaufeli, W. B., & Enzmann, D. (1998). The burnout companion to study and practice: A critical analysis. Washington, DC: Taylor & Francis.
Schaufeli, W. B., Leiter, M. P., Maslach, C., & Jackson, S. E. (1996). The MBI-General Survey. In C. Maslach, S. E. Jackson, & M. P Leiter (Eds.), Maslach Burnout Inventory manual (3rd ed., pp. 19-26). Palo Alto, CA: Consulting Psychologists Press.
Shirom, A. (1988). Situationally anchored stress scales for the measurement of work-related stress. In J. R. Hurrell Jr., L. R. Murphy, S. L. Sauter, & C. L. Cooper (Eds.), Occupational stress: Issues in development and research (pp. 66-75). London: Taylor & Francis.
Shirom, A. (2003). Job-related burnout. In J. C. Quick & L. E. Tetrick (Eds.), Handbook of occupational health psychology (pp. 245-265). Washington, DC: American Psychological Association.
Simmons, B. L. (2000). Eustress at work: Accentuating the positive. Unpublished doctoral dissertation, Oklahoma State University, Stillwater.
Spark, K., & Cooper, C. L. (1999). Occupational differences in the work-strain relationship: Toward the use of situation-specific models. Journal of Occupation and Organizational Psychology, 72, 219-229.
Van Der Doef, M., & Maes, S. (2002). Teacher-specific quality of work versus general quality of work assessment: A comparison of their validity regarding burnout, (psycho)somatic well-being and job satisfaction. Anxiety, Stress and Coping: An International Journal, 15, 327-344.
Westman, M., Etzion, D., & Gortler, E. (2004). The work-family interface and burnout. International Journal of Stress Management, 11, 413-442.
Rachel Gali Cinamon, School of Education, Tel Aviv University, Ramat Aviv, Israel; Yisrael Rich, School of Education, Bar Ilan University, Ramat Gan, Israel; Mina Westman, Department of Organizational Behavior, Tel Aviv University, Ramat Aviv, Israel. The authors would like to express their appreciation to Dee B. Ankonina for her editorial contribution. Correspondence concerning this article should be addressed to Rachel Gali Cinamon, School of Education, Tel Aviv University, Ramat Aviv 69978, Israel (e-mail: email@example.com).
TABLE 1 Means, Standard Deviations, and Intercorrelations Between the Research Variables Variable M SD 1 2 3 4 5 1. W [right arrow] 3.30 0.90 -- F conflict 2. F [right arrow] 2.05 0.73 .47** -- W conflict 3. Manager 3.29 0.94 -.09 -.12 -- support 4. Spousal 3.94 0.90 -.13* -.17* .16* -- support 5. Colleague 3.83 0.76 .01 .01 .59** .15* -- support 6. Burnout 3.20 1.4 .55** .46** -.23** -.08 -.06 7. Vigor 4.64 1.0 -.06 -.27** .38** .06 .27** 8. Investment in 5.62 2.3 .28** .05 .04 -.06 .07 parents 9. Investment in 6.78 2.3 .30** .17* .06 .01 .03 student misbehavior 10. Number of 8.78 7.0 .06 .08 .07 -.12 -.00 special need students 11. Flexible hours 2.87 0.66 .12 .19** .05 .01 .14* 12. Class size 26.60 7.7 .05 .07 .05 -.05 -.04 13. Number of 32.05 8.4 .04 -.04 .16* .05 .19** work hours Variable 6 7 8 9 10 11 12 13 1. W [right arrow] F conflict 2. F [right arrow] W conflict 3. Manager support 4. Spousal support 5. Colleague support 6. Burnout -- 7. Vigor -.25** -- 8. Investment in .10 .08 -- parents 9. Investment in .20** .06 .57** -- student misbehavior 10. Number of .07 -.06 .06 .07 -- special need students 11. Flexible hours .09 .01 .05 .14* -.05 -- 12. Class size -.02 -.07 .09 .00 .16* -.02 -- 13. Number of -.08 .14* .07 -.05 .08 -.06 -.03 -- work hours Note. W [right arrow] F conflict = work-interfering-with-family conflict; F [right arrow] W conflict = family-interfering-with-work conflict. *p< .05. **p < .01. TABLE 2 Significant Variables in the Linear Regression Predicting Work [right arrow] Family Conflict (N = 230) Step and Variable B SE B [beta] Step 1: Occupation-specific stressors Investment in student misbehavior .086 .033 .22*** Investment in relations with parents .055 .032 .05* Step 2: Generic work stressors Investment in student misbehavior .008 .032 .20*** Manager support -.186 .082 -.19*** Step 3: Generic family stressors Note. [R.sup.2] = .11 for Step 1; [DELTA][R.sup.2] = .04 for Step 2; [DELTA][R.sup.2] = .01 for Step 3. *p < .05. ***p < .001. TABLE 3 Significant Variables in the Linear Regression Predicting Family [right arrow] Work Conflict (N = 230) Step and Variable B SE B [beta] Step 1: Occupation-specific stressors Investment in student misbehavior .07 .03 .20*** Step 2: Generic family stressors Investment in student misbehavior .07 .03 .22*** Spousal support -.14 .06 -.17* Step 3: Generic work stressors Investment in student misbehavior .06 .03 .20* Spousal support -.14 .06 -.16* Manager support .14 .07 .18* Flexibility of work hours .18 .08 .16* Note. [R.sup.2] = .04 for Step 1; [DELTA][R.sup.2] = .03 for Step 2; [DELTA][R.sup.2] = .06 for Step 3. *p < .05. ***p < .001.
|Printer friendly Cite/link Email Feedback|
|Publication:||Career Development Quarterly|
|Date:||Mar 1, 2007|
|Previous Article:||Relationships between parental attachment, work and family roles, and life satisfaction.|
|Next Article:||A Holland perspective on the U.S. workforce from 1960 to 2000.|