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Teacher burnout in pre-schools: A cross-cultural factorial validity, measurement invariance and latent mean comparison of the Maslach Burnout Inventory, Educators Survey (MBI-ES)
Accepted Manuscript Teacher burnout in pre-schools: A cross-cultural factorial validity, measurement invariance and latent mean comparison of the Maslach Burnout Inventory, Educators Survey (MBI-ES)
Michael Osei Aboagye, Qin Jinliang, Qayyum Abdul, Collins Opoku Antwi, Yasin Jababu, Emmanuel Affum-Osei PII: DOI: Reference:
S0190-7409(18)30508-5 doi:10.1016/j.childyouth.2018.09.041 CYSR 4012
To appear in:
Children and Youth Services Review
Received date: Revised date: Accepted date:
28 June 2018 28 September 2018 28 September 2018
Please cite this article as: Michael Osei Aboagye, Qin Jinliang, Qayyum Abdul, Collins Opoku Antwi, Yasin Jababu, Emmanuel Affum-Osei , Teacher burnout in pre-schools: A cross-cultural factorial validity, measurement invariance and latent mean comparison of the Maslach Burnout Inventory, Educators Survey (MBI-ES). Cysr (2018), doi:10.1016/ j.childyouth.2018.09.041
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ACCEPTED MANUSCRIPT Teacher burnout in pre-schools: a cross-cultural factorial validity, measurement invariance and latent mean comparison of the Maslach Burnout Inventory, Educators Survey (MBI-ES)
Michael Osei Aboagye, a, Qin Jinlianga, Qayyum, Abdula, Collins Opoku Antwi b, Yasin
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Jababuc [email protected], Emmanuel Affum-Oseid
a
c
University of Shanghai for Science and Technology
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b
North Carolina A&T State University The Chinese University of Hong Kong
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d
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Zhejiang Normal University, China
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Corresponding author at: 1601 East Market Street, Greensboro, NC, 27411, US
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ACCEPTED MANUSCRIPT
Recent development in research on teacher wellbeing has been associated with the interest in assessing teacher burnout with the widely used Maslach Burnout Inventory, Educators Survey (MBI-ES). The increasing application of the MBI-ES, in and out of the Western world, stresses the need to investigate the cross-cultural applicability and factorial
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validity of the scale. The present study investigated whether (a) the MBI-ES is applicable in a
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cross-cultural context (i.e., the three-factor model of the scale is equivalent across cultures) and (b) burnout syndrome differs significantly across these cultures and gender. Results of
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confirmatory factor analysis (CFA) did not support the 22-item MBI-ES. Subsequent
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exploratory factor analysis resulted in significant item reduction. The reduced-item (adjusted) three-factor model fitted the data, and invariant across cultures and gender.
Significant
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differences in teacher burnout symptoms were found across cultures and gender. The alterations made to the MBI-ES further reinforce cultural influences on the assessment of
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cross-cultural teacher burnout dimensions. Further implications for ECE teacher burnout
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management in cross-cultural contexts are discussed.
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Keywords: Teacher burnout; Preschool Education; Maslach Burnout Inventory, Educator Survey (MBI-ES); Cross-culture; structured means comparison
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1.0 Background of teacher burnout The prevalence of burnout, and specifically, teacher burnout is not a 21st -century development. In fact, the concept was duly acknowledged in the 20 th -century American society (McGeary & McGeary, 2012; Sarros & Sarros, 1990), where teachers’ emotional,
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mental and physical well-being were severely evaded (Affrunti, Mehta, Rusch, & Frazier,
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2018; Wilmar B. Schaufeli, 2017; Cunningham, 1983; Freudenberger, 1974), threatening job ; Kotova, Rozanov, Alexandrov, & Ivanovo,
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outcome (Medvedskaya & Sheryagina, 2017;
2017; Heydari & Abbasian, 2016; Lauermann & König, 2016; Salloum, Kondrat, Johnco, &
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Olson, 2015; Cunningham, 1983). Published inquiries and teachers’ participation in burnout workshops, soundly echoed burnout spread, severity and prevailing sentiments of the period
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(McGeary & McGeary, 2012; Cunningham, 1983), and perhaps, awareness of its debilitating
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consequences (Schaufeli, 2017; Freudenberger, 1974). The assessment of teacher burnout, then gained popularity in academia (Oh & Lee, 2009;
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Pines, 2002; Schwarzer et al., 2000; Sarros & Sarros, 1990), across distinct geographic contexts (Salmela-Aro & Read, 2017; Denton, Chaplin, & Wall, 2013; Maslach, Schaufeli,
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& Leiter, 2001). Empirical studies have revealed that burnout is a worldwide work-related phenomenon (Oh & Lee, 2009; Schwarzer et al., 2000), that closely influences the quality of teacher-work performance such as job efficacy (Lizano & Mor Barak, 2015; Pines, 2002), interpersonal relationships, and the overall teacher wellbeing (Griffiths, Royse, & Walker, 2018; Antonopoulou, Killian, & Forrester, 2017; Squires et al., 2014). Theoretical models for the assessment of cross-cultural teacher burnout studies then became significant determinants of the outcomes of these studies (Sarros & Sarros, 1990; Schwarzer et al., 2000). The Maslach Burnout Inventory (MBI) (Maslach & Jackson, 1981), has been adjudged as having strong psychometric properties (Worley et al., 2008), employed in over 90% of all empirical 3
ACCEPTED MANUSCRIPT burnout studies (Maslach, 2015), and recognized as a key model that facilitated burnout advancement in literature. In spite of the scale’s acceptability among scholars, Worley & Colleagues' (2008) metaanalysis of 24 exploratory and 13 confirmatory factor-analytic (EFA) (CFA) studies, in
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addition to 8 studies combining the two methods evinced the issue of inconsistent dimensionality of MBI scale where some research findings indicate internal structure of two
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(Galanakis, Moraitou, Garivaldis, & Stalikas, 2009; Walkey & Green, 1992), four (Firth,
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McIntee, McKweown, & Britton, 1985; Golembiewski, Munzenrider, & Carter, 1983; Palmira Faraci, 2018; Valente, Wang, & Menezes, 2018), and five factors (Densten, 2001), Kokkinos, 2006; Byrne, 1993) which is
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instead of three (Pérez-Mármol & Brown, 2018;
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consistent with the original factor-structure in Maslach & Jackson (1981). It is noteworthy that, recent studies have produced similar conflicting patterns evidenced in Worley & Colleagues' (2008) meta-analysis. Though Denton, Chaplin, & Wall's (2013) cross-cultural
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studies of New York City teachers (N=150) and Jamaica W.I. teachers (150) confirmed the
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three-factor structure of MBI scale, findings point to structural- and item-level differences between the two cultures. Mészáros, Ádám, Szabõ, Szigeti, & Urbán's (2013) study on 653
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Hungarian healthcare professionals using the Hungarian version of the MBI-HSS revealed a bifactor model as most appropriate for explaining considerable variance in observed scores after adopting CFA to test the proposed one-factor (Kanste, Miettunen, & Kyngäs, 2006), two-factor (Brookings, Bolton, Brown, & McEvoy, 1985), three-factor (Christina Maslach, Jackson, & Leiter, 1997), four-factor (Iwanicki & Schwab, 1981), and five-factor (Densten, 2001) models’ fit. Using a sample of 309 Italian high school teachers and a 20-item rather than the 22-item MBI-ES scale due to 2 items being problematic, Faraci (2018)replicated Firth, McIntee, McKweown, & Britton's (1985) four-factor structure where the emotional exhaustion component was broken into two (i.e., strain and frustration). Additionally, 4
ACCEPTED MANUSCRIPT Valente, Wang, & Menezes (2018) with two emotional exhaustion factor (i.e., Exhaustion & Strain), reported a four-factor structure as the most suitable in terms of fit on 1046 Brazilian bank employees’ sample even though the three-factor was fairly reasonable, as they observed. These studies, except Mészáros et al. (2013), employed both EFA and CFA techniques.
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Additionally, a good number of studies have investigated MBI scale’s cross-cultural measurement invariance (Denton et al., 2013; Xanthopoulou, Bakker, Kantas, & Demerouti,
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2012; Schutte, Toppinen, Kalimo, & Schaufeli, 2000; Horn, Schaufeli, Greenglass, & Burke,
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1997). The outcome of Schutte et al.'s (2000) three-nation comparison of MBI-GS on Finnish, Swedish and Dutch samples (N= 9055) established the scale’s non-invariance across
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the three contexts at item level – recording low factor loadings and item error correlations. Xanthopoulou & Associates (2012) structural and item level invariance test of the MBI-GS
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on Dutch and Greek samples with CFA resorted to some modifications – that, items 1, and 2 from exhaustion and 5 from cynicism as well as 6 from professional efficacy were not
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invariant. Again, results from Denton & Associates' (2013) comparative study between New
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York City (a cosmopolitan of a first world – U.S.) and Jamaica W.I. (a developing country on the Caribbean) displayed structural- and items- level differences. These findings are
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indicative of the perspective that, cross-cultural comparisons should not assume invariance in the constructs and items nomological network of the phenomenology of burnout (Squires et al., 2014; Denton et al., 2013). Particularly, little attention has been given to the applicability of the scale in economies with low socio-economic conditions as most of these studies have concentrated on teachers’ burnout in the North American or European geographic regions (Poghosyan, Aiken, & Sloane, 2009; Schutte et al., 2000). In this regard, the generalizability of the measurement properties of the scale in developing economies such as those in subSaharan Africa (i.e., Ghana), and South-eastern Asia (i.e., Pakistan and China) with
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ACCEPTED MANUSCRIPT challenging
socio-economic,
and
broadly
distinct
cultural conditions may be highly
challenged. In this respect, Worley et al., (2008) and Squires et al.'s (2014) conclusion that, the need to assess the cross-cultural fit of the most prominent burnout model (i.e., MBI-ES) in a
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distinct educational environment other than the original cultural context of the scale (U.S.), to evaluate the content, context, conceptual, semantic, and technical equivalence (Squires et al.,
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2014), is one of urgency. Also, Kristensen et al., (2005) declaring the MBI-ES conceptually
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flawed and unusable on Danish samples in its original state, further stressed on the untenable nature of the assumption that, the event of burnout or its antecedents stay unchanged across
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cultures and suggested structural- and item-level comparisons to clear such assumptions.
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These calls are in agreement with later scholars (Schimmenti, 2016; Craparo, Faraci, & Gori, 2015), that the test of factorial structure of popular socio-psychological research instruments across cultures for structural and item equivalence is a necessity. Therefore, the test of the
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MBI-ES scale’s cross-cultural (Ghana in West Africa, and China and Pakistan in Asia)
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applicability on the three low socio-economic contexts is imperative, and is expected to elicit unique insights that could inform burnout assessment. Given that the proper assessment of the
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burnout syndrome in these cultural settings requires culturally-adapted and theoreticallymeaningful measures, this study seeks to fill this gap. Accordingly, the first objective for undertaking this research is to assess whether or not the factor structure of the MBI-ES fits three cultural contexts (i.e., possesses factorial invariance across cultures). 1.1 Comparing teacher burnout across cultures and gender The international nature of burnout has necessitated considerable cross-cultural inquiries into the concept given its impact on employee well-being and organizational outcomes (Squires et al., 2014; Xanthopoulou et al., 2012; Poghosyan et al., 2009; Perrewé et al.,
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ACCEPTED MANUSCRIPT 2002). Findings from these investigations indicate cross-cultural differences in teacher burnout experience. First, North American samples exhibit higher mean levels of cynicism (depersonalization) and exhaustion as compared to that of Europe with Polish sample being the only deviation, whilst the highest burnout incidences are recorded in Taiwanese and Japanese samples (Denton et al., 2013; Maslach et al., 2001; Schwarzer et al., 2000). For
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instance, Schwarzer et al. (2000) identified significant differences between German and Hong
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Kong on the emotional exhaustion subscale of the MBI-ES, where the Germans exhibited less
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exhaustion than their counterparts in Hong Kong with a post hoc t test analysis. However, the difference between German and Hong Kong cultures were found to be minor when the two
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cultures were compared to the American cultural setting. The authors’ found the American side recording significantly higher burnout than found in Germany or Hong Kong. Also, (2002) discovered
American teachers,
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Pines
having less stressful work
conditions,
experienced higher burnout than Israeli teachers who work in more stressful conditions. The
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author’s finding was explained by the fact that cultural differences in work attitude and work
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significance to life explain the observed differences. Differences in burnout syndrome across cultures are not unique to the teaching
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profession, and there have been numerous studies in other human services professions such as health services with similar findings. For example, Schaufeli & Janczur's (1994) examination of burnout among practicing nurses in Poland (N=200) and The Netherlands (N=183), discovered that Poles experienced higher burnout than their Dutch counterparts, even when the differential work conditions’ potential confounding effects were accounted for. Again, Suñer-Soler et al. (2014) found Spanish healthcare professionals in Spain to be, fairly differently, burned out compared to their counterparts in Latin America. The authors implied differences in culture to be a potential explanation for their findings. However, Pienaar &
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ACCEPTED MANUSCRIPT Wyk (2006) and Kaur & Noman (2015) attributed cases of cultural variability to social support or the lack thereof, whilst Koki (2000) emphasizes the role of religion. Burnout researchers have indicated that the role of gender is a necessary consideration in teacher burnout syndrome (Droogenbroeck et al., 2014; Byrne, 1991; Russell et al., 1987). In
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most studies, female teachers have been found to experience higher levels of emotional exhaustion (Grayson & Alvarez, 2008; Lau et al., 2005), and lower levels of personal
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accomplishment than their male counterparts (Droogenbroeck et al., 2014; Grayson &
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Alvarez, 2008; Lau et al., 2005; Byrne, 1991), as a consequence of non-school environment responsibilities (for example, family duties that are deemed in certain cultures to be
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performed mainly by females) (Woodside et al., 2008). These societal female-oriented duties
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coupled with teacher job characteristics quicken the rate and magnitude of stress experience and the consequent burnout (Lau et al., 2005; Borthwick, Thornell, & F. Wilkinson, 1982). On another breadth, male teachers are known to keep their feelings to themselves, and as a
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result experience far greater depersonalization (Stoeber & Rennert, 2008; Lau et al., 2005;
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Byrne, 1991), and cynicism than female teachers (Woodside et al., 2008). These findings on burnout differences across cultures and gender have been discovered in
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the developed world, with little to no attention to low and middle income countries (i.e., Ghana, China and Pakistan), where children and youth education remain a major policy issue (Unesco, 2015; UNESCO, 2008). Therefore, comparing teacher burnout across LMICs will inform preventive and treatment intervention programs and policies through the pursuit, and discovery of distinct contextual resources and practices, and their adaptation in other contexts (Denton et al., 2013). In the light of this, the second objective of this study, therefore, was to examine whether or not burnout syndrome differs significantly across these cultures and gender.
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ACCEPTED MANUSCRIPT 2.0 Methods 2.1 Participants and Procedure The data used in this study was a baseline data on pre-school teachers’ wellbeing and teacher-child relationship quality in Ghana, Pakistan and China. The schools were randomly
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selected using two stratification selection criteria: administrative level (provinces/ regions and district/ division), and sources of funding (government/ public and non-government/
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private). Between 145 to 163 schools were selected from provincial/regional and district
Schools
were
sampled
with
respect
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capitals, one second-tier level town and two rural settlements of Ghana, China and Pakistan. to
socio-economic and
cultural compositions.
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Compositionally, the provincial/regional and district capitals serve as the microcosms of
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ethnic, cultural, technological, economic and administrative hubs of the countries, with schools enlisting pupils and staffs from diverse socio-cultural and economic backgrounds.
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The majority of the schools had two kindergarten (i.e., KG 1 for four years olds and KG 2 for 5 to 6 years old) teachers, though the range was from one to five in all three countries.
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No more than two teachers were sampled per school, and where teachers in the school were above two, two were randomly sampled for data collection (one each from KG 1 and KG 2).
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Additionally, in instances where two teachers managed a class, only the lead teacher was sampled. In the five, eight and three schools from Ghana, China and Pakistan, which had two teachers in a class, the lead teachers were sampled in all cases. The schools’ classroom compositions are of a typical inclusive character; composed of students with or without special developmental needs and teachers with different Sex and ages. A sample size of 869 was used for the study. Prior to data collection, research permit was obtained from the municipal directorate of education in the three countries. In line with the declaration of Helsinki, consent letters with information about the fundamental goals of
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ACCEPTED MANUSCRIPT the study were sent to the head teachers and principals of the schools and teacher consents were also obtained to ensure voluntary participation. The study protocol was approved by the Zhejiang Normal University Graduate Review Committee. Table 1 presents detailed description of the participants and schools’ characteristics. 2.2 Measures Burnout Scale
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2.2.1
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Teacher burnout was measured with the 22-item 3-factor Maslach Burnout Inventory, Educator’s Survey (MBI-ES), rated on a 7-point scale, ranging from (1= Never to 7=
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Everyday) (Maslach & Jackson, 1981). The emotional exhaustion sub-scale measures
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teachers’ feelings of being emotionally overextended and exhausted by their work (e.g., “I feel used up at the end of the workday”). Depersonalization sub-scale measures teacher’s
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perception of impersonal, and insensitive response to his/her students (e.g. “I feel I treat students as if they were impersonal objects”). Accomplishment on the other hand, assessed
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teachers’ feeling of competence in their work (e.g. “I have accomplished many worthwhile things in this job”). Reliability and validity of the MBI-ES have been established in previous
Teacher Stress
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2.2.2
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studies (Boles et al., 2000; Aluja et al., 2005).
Teachers responded to a collection of widely-used and validated self-report measures developed by previous scholars to measure work-related stressors. Workload was assessed with 5 items (e.g. “My work requires too much from me”: a=.71) on 4-point scale (1=never to frequently) (Siegrist et al., 2004), emotional demands with 7 items (e.g. “My work demands a lot from me emotionally”: a=.86) on 4-point scale (1=never to 4=always) (Veldhoven & Meijman, 1994), work-family conflict with 5 items (e.g. “My work takes up time that I’d like to spend with my family/friend”: a=.81) on 5-point scale (1=never to 5=very often) (Frone, Russell, & Barnes, 1996), and role conflict with 8 items (e.g. “I work with groups who 10
ACCEPTED MANUSCRIPT operate quite differently”: a=.88) on 7-point scale (1=very false to 4=very true) (Rizzo et al., 1970). 2.3 Data preparation, descriptive statistics and analytic approach
2.3.1
Missing data and Descriptive statistics
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Cases with missing data (2.42%) were retained and treated as missing at random (MAR) by using full-information maximum likelihood estimators (FIML) (Allison, 2003). In line with
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Curran et al., (1996) and Allison, (2003), item descriptive statistics (mean and standard
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deviation), and normality (skewness and kurtosis) were examined. Two items (MBI 5, 15) appeared to be marginally skewed, with skewness values greater than the recommended
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threshold (±2.0). Logarithmic transformation was employed to produce a near-normal
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distributions (Field, 2005). Univariate normality assumptions were not violated, because maximum likelihood statistics are robust to mild violations of normality (Jackson et al.,
2.3.2
Data analytic approach
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2009). That notwithstanding, the items were carefully monitored in subsequent analyses.
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CFA, MGCFA and structured means analyses were performed in a structural equation modelling, using Amos 25 (Arbuckle, 2017). For the CFA, three competing models were
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compared: (1) proposed three-factor model, (2) an alternative two-factor model, and (3) another alternative one-factor model. Model fit was evaluated, using the Chi-Square (χ2 ) statistics (Cochran, 1952; Bentler & Bonett, 1980), the Standardized Root Mean Square Residual (SRMR), Comparative Fit Index (CFI), Tucker Lewise Index (TLI), the Root Mean Square Error of Approximation (RMSEA) (Bentler & Bonett, 1980; Bentler, 1990; Mueller & Hancock, 2008), and Akaike’s information criterion (AIC) (Akaike, 1987; Bryk & Raudenbush, 1992). CFI ratio ≥.90, SRMR≤.08 and RMSEA ≤.08 show acceptable fit, whereas good fit obtains CFI≥.95, SRMR≤.06 and RMSEA≤.06 (Maccallum et al., 1996; Hu,
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ACCEPTED MANUSCRIPT Bentler, & Hu, 1999), and the model with lower AIC value had a best fit (Akaike, 1987; Bryk & Raudenbush, 1992). Multi-group
confirmatory
factor
analyses
(MGCFAs)
were
performed
to
test
measurement invariance (MI) (Meredith, 1993), of the MBI-ES across gender, and cultures.
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Five invariance types of Byrne, Shavelson, & Muthen (1989), were tested: configural, metric, scalar, residual, and structural invariance (Mellenbergh, 1983; Meredith, 1993; Chen, 2007;
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Meredith & Teresi, 2006). Consistent with Cheung & Rensvold (2002), and Chen (2007),
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∆CFI, ∆RMSEA and ∆SRMR indices were examined for MI model fit. Considering the sample size (N>500), for testing metric invariance, a change of .010 in CFI, supplemented
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by changes of .015 in RMSEA and .030 in SRMR indicated equivalence. For test of scalar
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invariance and the other restricted models, ∆CFI.010, ∆RMSEA.015 and ∆SRMR.010 indicated equivalence (Cheung & Rensvold, 2002; Chen, 2007; Sass, 2011) (see Appendix B
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for summary of the MI tests steps).
Comparisons in the MBI-ES subscales were made using structured means analysis (Aiken
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et al., 1994; Hancock, 1997). One group was set as reference group, treating the others as comparison groups. The latent mean for the reference group was fixed at zero (0), and the
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latent group means for the comparison groups estimated as deviations from the reference group (Dimitrov, 2006). Differences in latent means are not influenced by the decision to fix reference groups’ mean at zero while freely estimating those of the comparison groups (Aiken et al., 1994; Hancock, 1997; Dimitrov, 2006). 3. Results 3.1 Assessing the factor structure of the MBI-ES across cultures Based on the hypothesised three-factor, alternative two-factor and one-factor structures of the MBI-ES, we performed CFAs on the whole sample. Factors, but not residual variances were allowed to be correlated. Factor loadings of all first indicator items were fixed to one.
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ACCEPTED MANUSCRIPT Results revealed that restricting the model from three to two dimensions (M3 to M2 ) and from two to one dimension (M2 to M1 ), significantly reduced the model fit (see Table1). Although the three-dimensional model (M3 ) fitted the data best, the fit was considered unacceptable. Item-level analysis
(Reise et al., 1993; Vandenberg & Lance, 2000; Sass, 2011), revealed
some items as potentially problematic: low factor loadings (<.40), R2 (<.20) (see Table2),
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and cross-loadings on other factors (Tabachnick & Fidell, 2007).
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3.2 Country-level and Cross-cultural exploration of the original MBI-ES factor structure
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Because the original 22-item three-factor MBI-ES model had psychometric problems, we
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restarted the evaluation process with an exploratory approach at both country-level and crosscultural level, as recommended by Squires et al. (2014). To examine the context-appropriate
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number of MBI-ES factors, we performed parallel analyses (J. L. Horn, 1965), and a graphical solution to scree test. Oblique rotation (Quartimax) was applied to examine item
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loadings on their respective factors, because the factors were found to be inter-correlated in the initial CFA and previous studies using the MBI-ES (Costello & Osborne, 2005). In line
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with Floyd & Widaman, (1995) and Costello & Osborne, (2005), three criteria were used to evalaute the items and their factors: a) items were required to extract on their theoritically
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meaningful underlying component, b) obtain a minimum loadings .40 or greater and, c) items with crossloadings to be droped as suggested by Costello & Osborne, (2005) and Tabachnick & Fidell, (2007).
Ghana: The parallel analysis and graphical solution to scree test produced three-factor solution. Factor1 was represented, in total, by 5 items (MBI-ES 1-3, 6, 8) that have described personal accomplishment subscale in the MBI-ES. Factor 2 was interpreted as emotional exhaustion as it was represented by seven substantive items: (MBI-ES 4, 7, 9, 12, 17, 19, & 21) belonging to the emotional exhaustion subscale of the MBI-ES. Factor 3 was represented
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extraction as they substantially cross-loaded on more than one factor. China: As a result of the EFA, three-factor structure was extracted. Factor 1 was interpreted
Factor2 was interpreted as emotional
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belonging to the personal accomplishment subscale.
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as personal accomplishment on the bases of 8 items (MBI-ES 4, 7, 9, 12, 17-19, 21)
exhaustion; represented by 5 items (MBI-ES 1-3, 6, 8), all being the original items described
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in the MBI-ES as emotional exhaustion subscale. Factor 3 was named depersonalization and was represented by 4 items (MBI-ES 10, 11, 15, 22), which originally formed the
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depersonalization subscale of the MBI-ES. Five items, four of them (MBI-ES 13, 14, 16, 20) from the emotional exhaustion scale, and one (MBI-ES 5) from the depersonalization scale
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were identified as having problematic loadings; had low loadings on their respective
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constructs, and cross-loaded on other factors. Pakistan: EFA results revealed three-factor structure. Factor 1 was represented by seven items (MBI-ES 4, 7, 9, 12, 17, 19, 21) belonging to the personal accomplishment scale of the
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MBI-ES. Factor2 was represented, in total, by 4 items (MBI-ES 1-3, 8); these were among the original items described in the MBI-ES as capturing emotional exhaustion. Factor 3 was represented by 5 items (MBI-ES 5, 10, 11, 15, 22) all belonging to the MBI-ES’ depersonalization subscale. Six items, five of them (MBI-ES 6, 13, 14, 16, 20) from the emotional exhaustion scale and one (MBI-ES 18) from the personal accomplishment scale had low loadings on their respective constructs and cross-loaded on other factors. Cross-cultural EFA:
Results revealed similar factor structure on the cross-cultural sample.
Factor1 was represented by seven items (MBI-ES 4, 7, 9, 12, 17, 19, 21) from the personal 14
ACCEPTED MANUSCRIPT accomplishment, factor2 by 5 items (MBI-ES 1-3, 6, 8) from the emotional exhaustion, and factor 3 by four items (MBI-ES 10, 11, 15, 22) belonging to depersonalization of the original MBI-ES subscales. Items (MBI-ES 5, 13, 14, 16, 18, 20), were verified as having problems in the extraction.
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3.3 Post hoc scale reduction Moving forward, the country-level and cross-cultural factor structures were compared.
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Problematic items found in two-third (2/3) or all of the countries and verified in the cross-
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cultural EFA were deleted. Results revealed that items (MBI-ES 13, 14, 16, 20) had problems in Ghana, China and Pakistan, (MBI-ES I5) China and Ghana, and (MBI-ES 18) Ghana and
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Pakistan samples (see Table3). However, item (MBI-ES I6) appeared to be problematic in only one out of the three countries. These measurement problems are not unique to this study;
Aluja
et
al.,
2005).
Thus
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some of these items have been characterized same in several other studies (Boles et al., 2000; considering
previous
empirical studies
and
conceptual
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considerations, we proceeded with reduced 16-items EFA without items (MBI-ES -ES 5, 13,
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14, 16, 18, & 20).
To obtain a statistically substantive and viable factor structure, having measurement items a) interpreted the same, and b) with similar meaning in the three cultures, we have first
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established that six items are unfit for this cross-cultural study. As a result of the EFAs, these items may be lacking the same meaning and interpretation across-cultures. Excluding them in the final extraction resulted in a clean factor-structure.
The adjusted factor-structure for the
cross-cultural study generated a consistent picture of the original MBI-ES factor-structure having three factors: emotional exhaustion (Factor1; 5 items), personal accomplishment (Factor 2; 7 items), and depersonalisation (Factor3; 4 items), sharing similar content, conceptual, semantic, and technical meaning with the original MBI-ES instrument (Maslach & Jackson, 1981). Oblique rotated EFA factor loadings and communalities (h2 ) for the 15
ACCEPTED MANUSCRIPT reduced 16-item three-factor MBI-ES are presented in Table3, whiles Appendix C presents the parallel analysis and graphical solution to scree test for the three samples 3.4 Confirmation of the reduce 16-item three-factor structure on cross-cultural sample To confirm the reduced 16-tems three-factor structure, CFAs were performed. Problems in single-sample post hoc modifications were resolved by applying the two-step strategy
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recommended by Arlot & Celisse, (2010) and Freire et al. (2017). Accordingly, taking
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advantage of the sample size, we split the sample into strictly random independent
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homogenous halves (Calibration sample: N=435 and Validation sample: N=434). This allowed for validation and modifications of the adjusted model in one half (Calibration
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sample) and cross-validation on the second half (Validation sample). Again, testing the three priori models in the calibration sample, we first established that
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the three-dimensional model fitted the data as compared to the two- and one-dimensional models. However, item-level analysis with the modification indices revealed some items
subscale)
as
having
measurement
error-covariance.
The
modification
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accomplishment
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(MBI-ES 1, 2 & 6 in the emotional exhaustion scale and all the items in the personal
allowed these errors to be correlated in order to improve the model fits, as done in previous studies (Boles et al., 2000; Aluja et al., 2005). The fit of the three-dimensional model
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substantially improved, whilst the two- and one-dimensional models remained misfit (see M1a Calibration sample;
Table 4). Cross-validation on the validation sample (M1b Validation
as well as the whole sample verified the initial results (M1
whole sample;
sample;
Table 4)
Table 4). All factor
loadings were significant. Inter-factor correlation patterns of the reduced 16-item latent scale scores did not reveal any appreciable change from the 22-item latent scale scores, and the coefficients were consistent with those reported in previous studies (Aluja et al., 2005; Worley et al., 2008). Emotional exhaustion correlated positively with depersonalisation (roriginal 16
MBI-ES=.36;
rreduced
ACCEPTED MANUSCRIPT MBI-ES
=.29, p<.01), and negatively with personal accomplishment (roriginal
MBI-ES=
-.17,
p<.01); whereas depersonalization correlated
MBI-ES=
-.20; rreduced
negatively with personal
accomplishment (roriginal MBI-ES=.-26; rreduced MBI-ES =-.23, p<.01). 3.5 Validity and reliability of the reduced 16-item MBI-ES
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To test for construct, convergent and discriminant validity and reliability, average variance explained, maximum shared variance, composite reliability and Cronbach's alpha for
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internal consistency ratios were computed and compared to their thresholds (Hair, Black,
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Babin, & Anderson, 2010; Fornell & Larcker, 1981). Results are comparable to those reported in previous studies (see Table 2). Further validity evidence based on the scale’s
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relation with other variables was achieved by performing separate structural equation models (SEM). The latent scores of the reduced 16-item MBI-ES subscales were regressed on work
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stressors. The regression weights were in the expected directions, and statistically significant: work stressors (workload, emotional demands, work-family conflict and role conflict) were
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positively associated with emotional exhaustion and depersonalization. On the other hand, the
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work stressors were negatively related to personal accomplishment, but only emotional demands and the total stress scores were statistically significant (see Table 5).
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3.6 Invariance test of the MBI-ES across cultures and gender Multigroup confirmatory factor analyses (MGFAs) were performed on the adjusted measurement model to test whether or not there are: 1) equality of factor structure, 2) equality of magnitude of factor loadings/ scaling units, 3) cross-group difference in the means of the observed items, 4) equality of error-variance, and 5) equality of factor variance across cultures and gender. 3.6.1
Invariance across cultures
17
ACCEPTED MANUSCRIPT We first established that the adjusted three-factor model fitted the groups for configural invariance test (see M1 Whole sample; M1a Calibration sample; M1b Validation sample; Table 6). Simultaneous analysis of least restricted solution revealed strong metric invariance (see M2 , M2a, M2b; Table 6). Moving forward, additional constraints were imposed to test for scalar invariance. The model fit indices showed poor fit (see M3 , M3a, M3b, Table 6), signalling non-invariant
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items in the model. Item-level analysis (Sass, 2011), revealed one item of the emotional
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exhaustion and depersonalization subscales (MBI-ES 2 “I feel emotionally drained from my work” and MBI-ES 11 “I worry that this job is hardening me emotionally) and three items of
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the personal accomplishment subscale (MBI-ES 7 “I feel very energetic”, 9 “In my work I
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deal with emotional problems very calmly” and 12 “I can easily understand how my students feel”) lacked invariance across cultures. This result was further cross-verified on the
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validation and calibration samples. Consequently, the intercepts for the
items were freely
estimated, and partial scalar invariance model tested (Vandenberg & Lance, 2000). Result
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showed acceptable fit for partial strong scalar invariance (see M4 , M4a, M4b; Table 6). Residual invariance and structural invariance were finally tested by imposing additional
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constraints. Results did not support the residual invariance model (see M5 , M5a, M5b; Table 6) and structural invariance (see M6 ; M6a, M6b; Table 6), because the additional constraints
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altered their model fits significantly, Taken together, the invariance tests supported partial strong factorial invariance across the three cultures (Meredith, 1993; Chen, 2007; Meredith & Teresi, 2006).
3.6.1.1 Structured means analyses of the modified MBI-ES across cultures Based on the MI test results, we performed structured means analysis to test latent mean differences across cultures. Ghana and China had higher latent mean scores than Pakistan on the emotional exhaustion subscale, accomplishment
and
depersonalization
and
lower latent mean score on the personal
subscales. 18
These differences in the emotional
ACCEPTED MANUSCRIPT exhaustion subscale were significant (z=3.617, p<.01) and (z=6.532, p<.01) for Ghana and China respectively. On the other hand, the difference in the personal accomplishment subscale was significant for China (z= -3.073, p<.01), but was not significant for Ghana (z= 1.503, p>.05). Similarly, the differences in the depersonalization subscale was significant for Ghana (z=-1.933, p<.05), but not significant for China (z= -.728, p>.05). These latent means
Invariance across gender
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3.6.2
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differences were further explored in simple graphs (Fig. 1).
sample;
M1a
calibration sample ;
M1b
validation sample ;
whole
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Results showed good model fit for configural invariance test across gender (see M1
Table 7). After imposing constraints on factor
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loadings, AIC decreased and CFI was lower than the threshold, indicating strong metric
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invariance (see M2 , M2a and M2b; Table 7). The model for scalar invariance (M3 , M3a, M3b; Table 7) was also supported, indicating strong factorial invariance. Residual invariance (M5, M5a, M5b, Table 7) and structural invariance (M6 , M6a, M6b;Table 7) were then tested and
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found to be fit, together supporting that the MBI-ES possesses strict factorial invariance
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across gender.
3.6.2.1 Structured means analyses of the MBI-ES across gender
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We then tested latent mean differences across gender. The comparison group (male teachers) scored lower on the emotional exhaustion subscale and higher on the personal accomplishment and depersonalization subscales compared to the reference group (female teachers). These differences were significant; emotional exhaustion (z=-3.399, p<.001), personal accomplishment (z=2.595, p<.01) and depersonalization (z=3.169, p<.001), and further plotted in simple graph (Fig. 2). 4.0 Discussion
19
ACCEPTED MANUSCRIPT The present study validated the three-dimensional structure; emotional exhaustion, depersonalization and personal accomplishment of the MBI-ES, using parallel analysis, CFA and MGCFA. We verified and extended the cross-cultural validity and measurement invariance evidence of the MBI-ES across LMICs (i.e., Chinese, Pakistani and Ghanaian). Our study adds to investigations on culturally-specific issues: cross-cultural meaning and and the conceptual equivalence of burnout
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interpretations of the MBI-ES’s items,
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dimensions, important to understanding burnout phenomenon to add to the scale’s global
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applicability. The study, employing statistically sophisticated methods, highlights insightful revelations of the factorial and structural validity as well as measurement equivalence of the
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hypothesized three-factor MBI-ES model.
First, the three-factor pattern and item loadings of the MBI-ES were verified in a cross-
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cultural context. In line with previous studies (Denton et al., 2013; Schaufeli & Dierendonck, 1993; Schaufeli et al., 1994), our study did not support the 22-item three-factor structure; as potentially problematic in the cross-cultural context.
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some items were reported
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Specifically, these items had poor psychometric properties; low factor loadings and crossloadings on more than one factor. Similar results have been reported by previous studies that assessed teacher burnout with the MBI-ES in different geographic regions, testing the MBI-
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ES’s three-factor structure in Europe with samples from Catalonia (Aluja et al., 2005), Netherlands (Schaufeli & Dierendonck, 1993; Schaufeli et al., 1994), Norway (Richardsen & Martinussen, 2004), and also North America including the U.S. (Boles et al., 2000), and Canada (Byrne, 1991, 1993, 1994). This reveals the items’ inadequate predictive capacity for their latent constructs, and clear-cut interpretability of the 22-item MBI-ES three-factor solution (Destin, 2001). Maslach and Jackson (1981) advised burnout researchers to exclude some items (12 and 16) from the MBI-ES when assessing its measurement structure. Similarly, several scholars 20
ACCEPTED MANUSCRIPT of teacher burnout hinted of the need to exclude some of these same items, including (items 5, 13, 14, 16, 18, 20) in burnout assessment in different geographic regions that adopt the MBI-ES. A recent study on a cross-cultural adoption of the MBI-ES in eleven European countries with ten languages found several items, including (5, 14, 16, 20) problematic as they failed to possess similar interpretation across cultures (Squires et al., 2014). This
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magnitude of the 22-item MBI-ES measurement problems suggest the need for an adjusted
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model which is context- and culturally-relevant for the understanding of the underlying structure of burnout (Worley et al., 2008). The replicability of the MBI-ES structure and
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items’ validation across the three cultures, therefore verified the constructs’ cross-cultural
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meaning and usefulness.
The reduced 16-item three-dimensional factor model produced acceptable fit across the
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three cultures when some item error variances and the latent factors were correlated. This is consistently evidenced in previous studies that tested the MBI-ES’s three-factor model, and
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found it fit by allowing its factors to correlate, and permitting residual covariance (Worley et
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al., 2008; Denton et al., 2013). We found comparable relationship patterns between the burnout factors and those reported in previous studies (Worley et al., 2008). Support for the two subscales: emotional exhaustion and depersonalization as being the core of burnout was
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achieved (Hawrot & Koniewski, 2017), as they shared strong positive relation, and correlated negatively with personal accomplishment. These inter-factor correlations and the associations found between the burnout subscales and work stressors, together with validity and reliability evidence verified the scale’s psychometric strength, when adopted in cross-cultures (Boles et al., 2000; Aluja et al., 2005). Thus, we found the underlying factors in the reduced 16-item MBI-ES model substantially reliable and valid, fitting the Chinese, Pakistani and Ghanaian cultural contexts, allowing for cross-cultural invariance assessment and possible teacher burnout comparison. 21
ACCEPTED MANUSCRIPT The reduced 16-item MBI-ES in the cross-cultural context revealed partial strong factorial invariance across cultures and strong factorial invariance across gender (Reise et al., 1993; Cheung & Rensvold, 2002), serving as pre-requisites for multi-group comparison (Meredith & Teresi, 2006), for researchers to discern differences in teacher burnout in respect of the dimensions explored (Cheung & Rensvold, 2002; Meredith & Teresi, 2006; Chen,
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2007; Sass, 2011). That notwithstanding, our study found non-invariance items (MBI-ES 2,
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7, 9, 11, 12) across cultures. Thus, teachers’ perception of these items varied among those in
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Pakistan, Ghana and China. Possible reasons for this variations might be attributable to contextual elements of borderline distinctiveness in semantics, content, technicality and
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concepts of burnout as advised by (Squires et al., 2014).
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Significant differences in teacher burnout across countries and gender were revealed in our study. Ghanaian and Chinese preschool teachers reported higher experience of emotional exhaustion than their Pakistani counterparts. For personal accomplishment, the Pakistani
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preschool teachers recorded higher levels than their Ghanaian and Chinese counterparts. It
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was further revealed that, the Pakistani preschool teachers experienced higher levels of depersonalization than the Ghanaian and Chinese preschool teachers. Despite this variability
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in teacher burnout experience across these three low and middle income countries, classroom and school characteristics as presented in table 1 show fairly similar contextual conditions. Given the findings of empirical cultural analysis of burnout that assigned marked teacher burnout differences to cultural perspectives including the level of professional status of teaching in society (Denton et al., 2013), religious orientation (Koki, 2000), social support (Pienaar & Wyk, 2006), and existential significance of teaching profession in certain cultures (Pines, 2002), it is therefore indicative that, the results of this study may be due to the role of the broader cultural and systemic influence on teacher burnout reactions among pre-school teachers (Sarros & Sarros, 1990). This resonates with the theorisation by Bronfenbrenner & 22
ACCEPTED MANUSCRIPT Morris (1998), who highlighted not just the micro ecosystem (i.e., immediate contextual factors) of the school, but also, the macro level (i.e., broader cultural conditions) of economic, technological, legal, scientific and institutional ecosystem of people-environment relations.
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Gender differences where female teachers reported higher emotional exhaustion than their male counterparts, lower perceptions of personal accomplishment and depersonalization than
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male teachers have been found in most studies (Russell et al., 1987; Byrne, 1991; Lau et al.,
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2005; Grayson & Alvarez, 2008; Stoeber & Rennert, 2008; Droogenbroeck et al., 2014). The gender differences reported in our study might be explicable by the theses offered by
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Woodside et al. (2008) and Borthwick, Thornell, & Wilkinson, (1982), that extra societal gender roles such as excessive family-level responsibilities overburden females to be
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emotionally drained (Woodside et al., 2008), whilst men are expected to contain their emotions leading to alienation (Barbara M. Byrne, 1991; Lau et al., 2005b; Woodside et al.,
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(Woodside et al., 2008).
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2008), is distinctively gender roles socialization issues which is contextually defined
Altogether, our study results support the cross-cultural factorial validity of a shortened
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16-item MBI-ES, and its use plausible for cross-cultural teacher burnout evaluation. This possible cross-cultural evidence allows for discovery and understanding of key cross-country differences and similarities that may be important for teacher burnout management. Nevertheless, the interpretability of our study’s results should be made within the context of limitations. A number of limitations have been noted, and prominent amongst them is the generalizability of the results. The study samples are from Ghana, China, and Pakistan and by no means generalizable to the rest of Africa and Asia. The low correlations among some
23
ACCEPTED MANUSCRIPT items could relate to the complex nature of the constructs measured; emotional exhaustion, depersonalization and personal accomplishment (Squires et al., 2014). We recommend that futher tests in different African and Asian contexts are necessary. Regardless of these limitations, this study offers practical implications for ECE teacher burnout management.
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Our study’s results patterns indicate that, cross-cultural learning and sharing among preschool teachers through preschool teacher exchanges and continuous collaborations
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among ECE stakeholders can generate unique understanding of the best ways to fight against
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teacher burnout. For instance, Chinese and Ghanaian preschool teachers can adopt some unique and applicable Pakistani practices that make them less emotionally exhaustive,
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whereas higher depersonalization and personal accomplishment in the Pakistani contexts can be managed by looking into applicable practices in the Ghanaian and Chinese contexts. Our
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study has implication for a relook at the gender roles in Ghana, China and Pakistan that serve to facilitate and/ or deepen emotional exhaustion gap between men and women and that of
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depersonalization and personal accomplishment.
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On policy, the findings of our study can shape policy discussions and formulation in creating harmonious educational environment through close study of the differences in the
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three cultural settings and promote positive cultural learning and adaptions of relevant, and applicable ECE practices in other cultures. These investigations have become necessary in the light of the findings relating to differences in teacher burnout experience in different countries. Our findings also add to existing literature on the theoretical development and cross-cultural assessment of the teacher burnout with the MBI-ES. The results provoke discussions on pressing matters, including why emotional exhaustion is higher among Ghanaian and Chinese pre-school teachers than among the Pakistani preschool teachers in order to come up with sound explanation for these differences and ways to address them.
24
ACCEPTED MANUSCRIPT Reference Affrunti, N. W., Mehta, T., Rusch, D., & Frazier, S. (2018). Job demands, resources, and stress among staff in after school programs: Neighborhood characteristics influence associations in the job demands-resources model. Children and Youth Services Review,
PT
88, 366–374. https://doi.org/10.1016/j.childyouth.2018.03.031 Aiken, L. S., Stein, J. A., & Bentler, P. M. (1994). Structural equation analyses of clinical
RI
subpopulation differences and comparative treatment outcomes: Characterizing the daily
SC
lives of drug addicts,. Journal of Consulting and Clinical Psychology, 62, 488–499.
332. https://doi.org/10.1007/BF02294359
NU
AKAIKE, H. (1987). FACTOR ANALYSIS AND AIC. PSYCHOMETRIKA, 52(3), 317–
MA
Allison, P. D. (2003). Missing Data Techniques for Structural Equation Modeling. Journal of
ED
Abnormal Psychology, 112(4), 545–557. https://doi.org/10.1037/0021-843X.112.4.545 Aluja, A., Blanch, A., & Garcia, L. F. (2005). Dimensionality of the Maslach Burnout
EP T
Inventory in School Teachers : A Study of Several Proposals . European Journal of Psychological Assessment, (January). https://doi.org/10.1027/1015-5759.21.1.67
AC C
Antonopoulou, P., Killian, M., & Forrester, D. (2017). Levels of stress and anxiety in child and family social work: Workers’ perceptions of organizational structure, professional support and workplace opportunities in Children’s Services in the UK. Children and Youth Services Review. https://doi.org/10.1016/j.childyouth.2017.02.028 Arbuckle, J. L. (2017). Amos 25 User’s Guide. SPSS IBM. Arlot, S., & Celisse, A. (2010). A survey of cross-validation procedures for model selection. Statistics Surveys, 4, 40–79. https://doi.org/10.1214/09-SS054 Bentler, P. (1990). Comparative fit indices in structural models. Psychological Bulletin, 25
ACCEPTED MANUSCRIPT 107(2), 238–246. https://doi.org/0.1037/0033-2909.107.2.238 Bentler, P. M., & Bonett, D. G. (1980). Significance tests and goodness of fit in the analysis of covariance structures. Psychological Bulletin, 88(3), 588–606. https://doi.org/10.1037/0033-2909.88.3.588
PT
Boles, J. S., Dean, D. H., Ricks, J. M., Short, J. C., & Wang, G. (2000). The Dimensionality of the Maslach Burnout Inventory across Small Business Owners and Educators.
RI
Journal of Vocational Behavior, 56(1), 12–34. https://doi.org/10.1006/jvbe.1999.1689
SC
Borthwick, P., Thornell, J., & F. Wilkinson. (1982). Teacher burnout: A study of professional
NU
and personal variables. In Proceedings of the Annual Meeting of the American Association for Teacher Education. Houston, TX.
MA
Bronfenbrenner, U., & Morris, P. (1998). The ecology of de velopmental processes. In R. M. Lerner (Ed.), Handbook of child psychology: Vol. 1. Theoretical models of human devel-
ED
opment (pp. 993–1028). New York: Wiley. Brooks-Gunn, J., Berlin, L. J., Leve.
EP T
Brookings, J. B., Bolton, B., Brown, C. E., & McEvoy, A. (1985). Self-Reported Job Burnout Among Female Human Service Professionals. Journal of Occupational Behaviour, 6(2),
AC C
143–150.
Bryk, A. S., & Raudenbush, S. W. (1992). Hierarchical linear models in social and behavioral research: Applications and data analysis methods. Newbury Park, CA: Sage. Buys.
Byrne, B. M. (1991). Burnout: Investigating the impact of background variables for elementary, intermediate, secondary, and university educators. Teaching and Teacher Education, 7(2), 197–209. https://doi.org/10.1016/0742-051X(91)90027-M Byrne, B. M. (1993). The Maslach burnout inventory:Testing for factorial validity and 26
ACCEPTED MANUSCRIPT invariance across elementary, intermediate and secondary teachers. Journal of Occupational and Organizational Psychology, 66, 197–212. Byrne, B. M. (1994). Testing for the Factorial Validity, Replication, and Invariance of a Measuring Instrument: A Paradigmatic Application Based on the Maslach Burnout
PT
Inventory. Multivariate Behavioral Research, 29(3), 263288. https://doi.org/10.1207/s15327906mbr2903
RI
Byrne, M. B., Shavelson, R. J., & Muthen, B. O. (1989). Testing for the equivalence of factor
SC
covariance and mean structures: The issue of partial measurement invariance.
NU
Psychological Bulletin, 105, 456–466.
Chen, F. F. (2007). Sensitivity of goodness of fit indexes to lack of measurement invariance.
MA
Structural Equation Modeling, 14(3), 464–504. https://doi.org/10.1080/10705510701301834
ED
Cheung, G. W., & Rensvold, R. B. (2002). Evaluating Goodness-of- Fit Indexes for Testing
EP T
Measurement Invariance. Structural Equation Modeling: A Multidisciplinary Journal, 9(2), 233–255. https://doi.org/10.1207/S15328007SEM0902
AC C
Cochran, W. G. (1952). Test of Goodness of Fit. The Annals of Mathematical Statistics, 23(3), 315–345. https://doi.org/10.1214/aoms/1177729380 Costello, A. B., & Osborne, J. W. (2005). Best Practices in Exploratory Factor Analysis : Four Recommendations for Getting the Most From Your Analysis. Practical Assessment, Research & Evaluation, 10(7). Retrieved from http://pareonline.net/getvn.asp?v=10&n=7 Craparo, G., Faraci, P., & Gori, A. (2015). Psychometric properties of the 20-item toronto alexithymia scale in a group of Italian younger adolescents. Psychiatry Investigation,
27
ACCEPTED MANUSCRIPT 12(4), 500–507. https://doi.org/10.4306/pi.2015.12.4.500 Cunningham, W. G. (1983). Teacher burnout - solutions for the 1980’s: A review of the literature. The Urban Review, 15(1), 37–51. Curran, P. J., West, S. G., & Finch, J. F. (1996). The Robustness of Test Statistics to
PT
Nonnormality and Specification Error in Confirmatory Factor Analysis. Psychological
RI
Methods, 1(1), 16–29. https://doi.org/10.1037/1082-989X.1.1.16
Densten, I. L. (2001). Re-Thinking Burnout. Journal of Organizational Behavior, 22(8), 833–
SC
847. https://doi.org/10.1002/job.
NU
Denton, E. ge, Chaplin, W. F., & Wall, M. (2013). Teacher burnout: a comparison of two cultures using confirmatory factor and item response models. International Journal of
MA
Quantitative Research in Education, 1(2), 147.
ED
https://doi.org/10.1504/IJQRE.2013.056463
Dimitrov, D. M. (2006). Comparing groups on latent variables: A structural equation
EP T
modeling approach. Work, 26(2006), 429–436. Droogenbroeck, F. Van, Spruyt, B., & Vanroelen, C. (2014). Burnout among senior teachers :
AC C
Investigating the role of workload and interpersonal relationships at work. Teaching and Teacher Education, 43, 99–109. https://doi.org/10.1016/j.tate.2014.07.005 Field, A. (2005). Discovering Statistics Using IBM SPSS Statistics. 2nd Edition. London: Sage Publications. Firth, H., McIntee, J., McKweown, P., & Britton, P. G. (1985). Maslach Burnout Inventory: Factor Structure and Norms for British Nursing Staff. Psychological Reports, 57, 147– 150. Floyd, F. J., & Widaman, K. F. (1995). Factor Analysis in the Development and Refinement 28
ACCEPTED MANUSCRIPT of Clinical Assessment Instruments. Psychological Assessment, 7(3), 286–299. https://doi.org/10.1037/1040-3590.7.3.286 Fornell, & Larcker. (1981). structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 48(1), 39–50.
PT
Freire, C., Ferradás, M. del M., Núñez, J. C., & Valle, A. (2017). Estructura factorial de las
https://doi.org/10.1016/j.ejeps.2016.10.001
SC
Journal of Education and Psychology, (10), 1–8.
RI
Escalas de Bienestar Psicológico de Ryff en estudiantes universitarios. European
NU
Freudenberger, H. J. (1974). Staff Burn-Out. Journal of Social Issues, 30(1), 159–165. https://doi.org/10.1111/j.1540-4560.1974.tb00706.x
MA
from the SAGE Social Science Collections . All Rights Reserved . (n.d.).
ED
Frone, M. R., Russell, M., & Barnes, G. M. (1996). Work--family conflict, gender, and health-related outcomes: A study of employed parents in two community samples.
8998.1.1.57
EP T
Journal of Occupational Health Psychology, 1(1), 57–69. https://doi.org/10.1037/1076-
AC C
Galanakis, M., Moraitou, M., Garivaldis, F. J., & Stalikas, A. (2009). Factorial Structure and Psychometric Properties of the Maslach Burnout Inventory (MBI) in Greek Midwives. Europe’s Journal of Psychology, 5(4), 52–70. https://doi.org/10.5964/ejop.v5i4.240 Golembiewski, R. T., Munzenrider, R., & Carter, D. (1983). Phases of progressive burnout and their work site covariants: Critical issues in OD researcg and Praxis. The Journal of Applied Behavioral Science, 19(4), 461–481. Grayson, Ã. J. L., & Alvarez, H. K. (2008). School climate factors relating to teacher burnout : A mediator model. Teacher and Teaching Education, 24, 1349–1363. 29
ACCEPTED MANUSCRIPT https://doi.org/10.1016/j.tate.2007.06.005 Griffiths, A., Royse, D., & Walker, R. (2018). Stress among child protective service workers: Self-reported health consequences. Children and Youth Services Review, 90(May), 46– 53. https://doi.org/10.1016/j.childyouth.2018.05.011
RI
7th. ed. Prentice-Hall, Inc., Upper Saddle River, NJ, USA.
PT
Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2010). Multivariate Data Analysis,
Hancock, G. R. (1997). Structural equation modeling methods of hypothesis testing of latent
SC
variable means. Measurement and Evaluation in Counseling and Development, 30, 91–
NU
105.
Hawrot, A., & Koniewski, M. (2017). Factor Structure of the Maslach Burnout Inventory –
MA
Educators Survey in a Polish-Speaking Sample. Journal of Career Assessment, 1–16.
ED
https://doi.org/10.1177/1069072717714545
Hernández, T. J., & Sánchez, G. (2012). Prevalence of Burnout Syndrome in Employees,
EP T
(1996), 207–225.
Heydari, S., & Abbasian, G.-R. (2016). The relationship between Iranian EFL teachers’
AC C
professional development and their job burnout 1. Basic Research Journal of Education Research and Review Basic Research Journal of Education Research and Review ISSN, 4(2), 2315–6872.
Horn, J. E., Schaufeli, W. B., Greenglass, E. R., & Burke, R. J. (1997). A CANADIANDUTCH COMPARISON OF TEACHERS’ BURNOUT. Psychological Reports, 81, 371–382. Horn, J. L. (1965). FACTORS IN FACTOR ANALYSIS. PSYCHOMETRIKA, 30(2), 179– 185. 30
ACCEPTED MANUSCRIPT Hu, L. T., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis : Conventional criteria versus new alternatives Cutoff Criteria for Fit Indexes in Covariance Structure Analysis : Conventional Criteria Versus New Alternatives. A Multidisciplinary Journal, 6(1), 1–55. https://doi.org/10.1080/10705519909540118
PT
Iwanicki, E. F., & Schwab, R. L. (1981). A Cross Validation Study of the Maslach Burnout Inventory. Educational and Psychological Measurement, 41.
RI
https://doi.org/10.1177/001316448104100425
SC
Jackson, D. L., Gillaspy, J. A., & Purc-Stephenson, R. (2009). Reporting Practices in Confirmatory Factor Analysis: An Overview and Some Recommendations.
NU
Psychological Methods, 14(1), 6–23. https://doi.org/10.1037/a0014694
MA
Kanste, O., Miettunen, J., & Kyngäs, H. (2006). Factor structure of the Maslach Burnout Inventory among Finnish nursing staff. Nursing and Health Sciences, 8(4), 201–207.
ED
https://doi.org/10.1111/j.1442-2018.2006.00283.x
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Kaur, A., & Noman, M. (2015). Exploring Classroom Practices in Collectivist Cultures Through the Lens of Hofstede ’ s Model Exploring Classroom Practices in Collectivist
AC C
Cultures Through the Lens. The Qualitative Report, 20(11), 1794–1811. Koki, S. (2000). Prevention and Intervention for Effective Classroom Organization and Management in Pacific Classrooms, (808), 1–12. Kokkinos, C. M. (2006). Factor structure and psychometric properties of the Maslach Burnout Inventory-Educators Survey among elementary and secondary school teachers in Cyprus. Stress and Health, 22(1), 25–33. https://doi.org/10.1002/smi.1079 KotovA, M. B., Rozanov, K. B., Alexandrov, A. A., & Ivanovo, E. I. (2017). Professional burnout and quality of life in teachers. Voprosy Psikhologii, 2017–Janua(2), 67–79.
31
ACCEPTED MANUSCRIPT Kristensen, T. S., Borritz, M., Villadsen, E., & Christensen, B. (2005). The Copenhagen Burnout Inventory : A new tool for the assessment of burnout The Copenhagen Burnout Inventory : A new tool for the. Work & Stress: An International Journal of Work, Health & Organisations, 19(3), 192–207. https://doi.org/10.1080/02678370500297720
PT
Lau, P. S. Y., Yuen, M. A. N. T. A. K., & Chan, R. M. C. (2005a). Do demographic characteristics make a difference to burnout among hong kong secondary school
RI
teachers? Social Indicators Research, (71), 491–516. https://doi.org/10.1007/s11205-
SC
004-8033-z
Lau, P. S. Y., Yuen, M. A. N. T. A. K., & Chan, R. M. C. (2005b). Do demographic
NU
characteristics make a difference to burnout among hong kong secondary school
MA
teachers?, 491–516. https://doi.org/10.1007/s11205-004-8033-z Lauermann, F., & König, J. (2016). Teachers’ professional competence and wellbeing:
ED
Understanding the links between general pedagogical knowledge, self-efficacy and burnout. Learning and Instruction, 45, 9–19.
EP T
https://doi.org/10.1016/j.learninstruc.2016.06.006 Lizano, E. L., & Mor Barak, M. (2015). Job burnout and affective wellbeing: A longitudinal
AC C
study of burnout and job satisfaction among public child welfare workers. Children and Youth Services Review, 55, 18–28. https://doi.org/10.1016/j.childyouth.2015.05.005 Maccallum, R. C., Browne, M. W., & Sugawara, H. M. (1996). Power Analysis and Determination of Sample Size for Covariance Structure Modeling of fit involving a particular measure of model. Psychological Methods, 1(2), 130–149. Maslach, C. (2015). Burnout , Psychology of. International Encyclopedia of Social & Behavioral Sciences (Second Edi, Vol. 2). Elsevier. https://doi.org/10.1016/B978-0-08097086-8.26009-1 32
ACCEPTED MANUSCRIPT Maslach, C., & Jackson, S. E. (1981a). Maslach Burnout Inventory--ES Form. PsycTESTS. https://doi.org/10.1037/t05190-000 Maslach, C., & Jackson, S. E. (1981b). The measurement of experienced burnout. JOURNAL OF OCCUPATIONAL BEHAVIOUR, 2, 99–113.
Evaluating Stress: A Book of Resources (pp. 191–218).
RI
https://doi.org/10.1017/S0033291798257163
PT
Maslach, C., Jackson, S. E., & Leiter, M. P. (1997). Maslach Burnout Inventory. In
SC
Maslach, C., Schaufeli, W. B., & Leiter, M. P. (2001). Job burnout. Annual Review of
NU
Psychology, 52, 397–422.
McGeary, C. A., & McGeary, D. D. (2012). Occupational Burnout. In R. J. Gatchel & I. Z.
MA
Schultz (Eds.), Handbook of Occupational Health and Wellness (pp. 3–563).
ED
https://doi.org/10.1007/978-1-4614-4839-6
Medvedskaya, E. I., & Sheryagina, E. V. (2017). Empathy and professional burnout of
EP T
Russian and Belarusian teachers. Konsul’tativnaia Psikhologiia I Psikhoterapiia, 25(2), 59–74. https://doi.org/http://dx.doi.org/10.17759/cpp.2017250204
AC C
Mellenbergh, J. (1983). ITEM BIAS AND ITEM RESPONSE. International Journal of Educational Research, 13(2), 127–143. https://doi.org/https://doi.org/10.1016/08830355(89)90002-5
Meredith, W. (1993). MEASUREMENT INVARIANCE, FACTOR ANALYSIS AND FACTORIAL INVARIANCE. PSYCHOMETRIKA, 58(4), 525–543. https://doi.org/10.1007/BF02294825 Meredith, W., & Teresi, J. A. (2006). An essay on measurement and factorial invariance. Medical Care, 44(11), S69–S77. https://doi.org/10.1097/01.mlr.0000245438.73837.89 33
ACCEPTED MANUSCRIPT Mészáros, V., Ádám, S., Szabõ, M., Szigeti, R., & Urbán, R. (2013). The bifactor model of the maslach burnout inventory-human services survey (MBI-HSS) - An alternative measurement model of burnout. Stress and Health, 30(1), 82–88. https://doi.org/10.1002/smi.2481
PT
Mueller, R. O., & Hancock, G. R. (2008). Best practices in structural equation modeling. Best Practices in Quantitative Methods, 488–508. https://doi.org/10.4135/9781412995627
RI
Oh, S. H., & Lee, M. (2009). Examining the psychometric properties of the Maslach Burnout
Youth Services Review, 31(2), 206–210.
NU
https://doi.org/10.1016/j.childyouth.2008.07.012
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Inventory with a sample of child protective service workers in Korea. Children and
MA
Palmira Faraci. (2018). TESTING FOR THE DIMENSIONALITY OF THE MASLACH BURNOUT INVENTORY (MBI) ON A SAMPLE OF HIGH SCHOOL TEACHERS.
ED
Clinical Neuropsychiatry, 15(1), 50–59.
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Pérez-Mármol, J. M., & Brown, T. (2018). An Examination of the Structural Validity of the Maslach Burnout Inventory-Student Survey (MBI-SS) Using the Rasch Measurement
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Model. Health Professions Education. https://doi.org/10.1016/j.hpe.2018.05.004 Perrewé, P. L., Hochwarter, W. A., Rossi, A. M., Wallace, A., Maignan, I., Castro, S. L., Van Deusen, C. A. (2002). Are work stress relationships universal? A nine-region examination of role stressors, general self-efficacy, and burnout. Journal of International Management, 8(4), 423. https://doi.org/10.1016/S1075-4253(02)00107-2 Pienaar, J., & Wyk, D. Van. (2006). Teacher burnout : construct equivalence and the role of union membership. South African Journal of Education, 26(4), 541–551. Pines, A. M. (2002a). Teacher Burnout : A psychodynamic existential perspective. Teachers
34
ACCEPTED MANUSCRIPT and Teaching: Theory and Practice, 8(2), 37–41. https://doi.org/10.1080/13540600220127331 Pines, A. M. (2002b). Theory and Practice Teacher Burnout : A psychodynamic existential perspective. Teachers and Teaching: Theory and Practice, 8(2), 37–41.
PT
https://doi.org/10.1080/13540600220127331 Poghosyan, L., Aiken, L. H., & Sloane, D. M. (2009). Factor structure of the Maslach
RI
burnout inventory: An analysis of data from large scale cross-sectional surveys of nurses
NU
https://doi.org/10.1016/j.ijnurstu.2009.03.004
SC
from eight countries. International Journal of Nursing Studies, 46(7), 894–902.
Reise, S. P., Widaman, K. F., & Pugh, R. H. (1993). Confirmatory factor analysis and item
MA
response theory: two approaches for exploring measurement invariance. Psychological Bulletin, 114(3), 552–566. https://doi.org/10.1037/0033-2909.114.3.552
ED
Richardsen, A. M., & Martinussen, M. (2004). The Maslach Burnout Inventory : Factorial
EP T
validity and consistency across occupational groups in Norway. Journal of Occupational and Organizational Psychology, (77), 377–384.
AC C
https://doi.org/0.1348/0963179041752691 Rizzo, J. R., House, R. J., & Lirtzman, S. I. (1970). Role Conflict and Ambiguity in Complex Organizations. Administrative Science Quarterly, 15(2), 150–163. Russell, D. W., Altmaier, E., & Vanvelzen, D. (1987). Job-related stress, social support, and burnout among classroom teachers. Journal of Applied Psychology, 72(2), 269–274. Salloum, A., Kondrat, D. C., Johnco, C., & Olson, K. R. (2015). The role of self-care on compassion satisfaction, burnout and secondary trauma among child welfare workers. Children and Youth Services Review, 49, 54–61.
35
ACCEPTED MANUSCRIPT https://doi.org/10.1016/j.childyouth.2014.12.023 Salmela-Aro, K., & Read, S. (2017). Study engagement and burnout profiles among Finnish higher education students. Burnout Research, 7, 21–28. https://doi.org/10.1016/j.burn.2017.11.001
RI
Study. Australian Journal of Education, 34(2), 145–152.
PT
Sarros, A. M., & Sarros, J. (1990). How Burned out are our Teachers ? A Cross-cultural
SC
``, J. C. (1990). How Burned out are our Teachers ? A Cross-cultural Study, 34(2), 145–152. Sass, D. A. (2011). Testing measurement invariance and comparing latent factor means
NU
within a confirmatory factor analysis framework. Journal of Psychoeducational
MA
Assessment, 29(4), 347–363. https://doi.org/10.1177/0734282911406661 Schaufeli, W. B. (2017). Applying the Job Demands-Resources model: A “how to” guide to
ED
measuring and tackling work engagement and burnout. Organizational Dynamics, 46(2), 120–132. https://doi.org/10.1016/j.orgdyn.2017.04.008
EP T
Schaufeli, W. B., Daamen, J., & Mierlo, H. Van. (1994). Burnout among Dutch teachers: An MBI-Validity study. Educational and Psychological Measurement, 54(3), 803–812.
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https://doi.org/10.1177/0013164494054003027 Schaufeli, W. B., & Van Dierendonck, D. (1993). The construct validity of two emotional exhaustion measures. J Ournal of Organizational Behavior, 14(February 1991), 631– 647. https://doi.org/10.1002/job.4030140703 Schimmenti, A. (2016). Psychometric properties of the Adolescent Dissociative Experiences Scale in a sample of Italian adolescents. Journal of Trauma and Dissociation, 17(2), 244–257. https://doi.org/10.1080/15299732.2015.1064507 Schutte, N., Toppinen, S., Kalimo, R., & Schaufeli, W. B. (2000). The factorial validity of the 36
ACCEPTED MANUSCRIPT Maslach Burnout Inventory - General Survey (MBI-GS) across occupational groups and nations. Schwarzer, R., Schmitz, G. S., & Tang, C. (2000). Teacher Burnout in Hong Kong and Germany: A Cross-Cultural Validation of the Maslach Burnout Inventory. Anxiety,
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Stress & Coping, 13(3), 309–326. https://doi.org/10.1080/10615800008549268 Siegrist, J., Starke, D., Chandola, T., Godin, I., Marmot, M., Niedhammer, I., & Peter, R.
RI
(2004). The measurement of effort-reward imbalance at work: European comparisons.
SC
Social Science and Medicine, 58(8), 1483–1499. https://doi.org/10.1016/S0277-
NU
9536(03)00351-4
Squires, A., Finlayson, C., Gerchow, L., Cimiotti, J. P., Matthews, A., Schwendimann, R., …
MA
Sermeus, W. (2014). Methodological considerations when translating "burnout" Burnout Research, 1(2), 59–68.
ED
https://doi.org/10.1016/j.burn.2014.07.001
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Stoeber, J., & Rennert, D. (2008). Perfectionism in school teachers : Relations with stress appraisals , coping styles, and burnout. Anxiety, Stress & Coping: An International
AC C
Journal, 21(1), 37–53. https://doi.org/10.1080/10615800701742461 Suñer-Soler, R., Grau-Martín, A., Flichtentrei, D., Prats, M., Braga, F., Font-Mayolas, S., & Gras, M. E. (2014). The consequences of burnout syndrome among healthcare professionals in Spain and Spanish speaking Latin American countries. Burnout Research, 1(2), 82–89. https://doi.org/10.1016/j.burn.2014.07.004 Tabachnick, B. G., & Fidell, L. S. (2007). Using Multivariate Statistics, (5th ed.). Needham Heights, MA: Allyn and Bacon Publishers. Needham Heights, MA: Allyn and Bacon Publishers.
37
ACCEPTED MANUSCRIPT Unesco. (2015). Education for all 2015 National Review. Unesco, 1–67. UNESCO. (2008). Countries on the Move. UNESCO Education for All GlobalMonotoring Report. Retrieved from: http://www.unesco.org/education/gmr2008/press/chapter3.pdf. Valente, M. do S. da S., Wang, Y. P., & Menezes, P. R. (2018). Structural validity of the
PT
Maslach Burnout Inventory and influence of depressive symptoms in banking workplace: Unfastening the occupational conundrum. Psychiatry Research, 267(March),
RI
168–174. https://doi.org/10.1016/j.psychres.2018.05.069
SC
Vandenberg, R. J., & Lance, C. E. (2000). A Review and Synthesis of the Measurement
NU
Invariance Literature: Suggestions, Practices, and Recommendations for Organizational Research. Organizational Research Methods, 3(1), 4–70.
MA
https://doi.org/10.1177/109442810031002
Veldhoven, M., & Meijman, T. (1994). Het meten van psychosociale arbeidsbelasting met
ED
een vragenlijst: de vragenlijst beleving en beoordeling van de arbeid (VBBA).
EP T
Measuring psychosocial workload with a survey: the questionnaire on the experience and evaluation of work (QEEW). Amsterdam: NIA.
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Walkey, F. H., & Green, D. E. (1992). An Exhaustive Examination of the Replicable Factor Structure of the Maslach Burnout Inventory. Educational and Psychological Measurement, 52.
Woodside, J. R., Miller, M. N., Floyd, M. R., McGowen, K. R., & Pfortmiller, D. T. (2008). Observations on burnout in family medicine and psychiatry residents. Academic Psychiatry, 32(1), 13–19. https://doi.org/10.1176/appi.ap.32.1.13 Worley, J. A., Vassar, M., Wheeler, D. L., & Barnes, L. L. B. (2008). Factor Structure of Scores From the Maslach Burnout Inventory. Educational and Psychological
38
ACCEPTED MANUSCRIPT Measurement, 68(5), 797–823. https://doi.org/10.1177/0013164408315268 Xanthopoulou, D., Bakker, A. B., Kantas, A., & Demerouti, E. (2012). Measuring burnout and work engagement: Factor structure, invariance, and latent mean differences across Greece and the Netherlands. International Journal of Business Science and Applied
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Management, 7(2), 40–52. https://doi.org/10.1080/09585192.2012.751438
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ACCEPTED MANUSCRIPT Acknowledgement This study was funded by the Zhejiang Normal University (Graduate School PhD candidates’ sponsorship). We further extend our sincere thank you, to prof. Fan Chong Jun, Business School, the University of Shanghai for Science & Technology (USST) and prof. Yun-Fei Shao, University of Electronic Science and Technology of China for their statistical support and tutelage in the conduct of this study.
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Declaration of Conflicting Interests The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
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Explored the factorial validity of the MBI-ES and burnout differences across three cultural contexts and gender. The MBI-ES fitted the three cultures after item-level modifications were made.
Significant differences in teacher burnout across countries and gender were found.
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ACCEPTED MANUSCRIPT Table 1: Sample demographics and work characteristics, stratified by country (N=869) Descriptive statistics: China(n=274)
Participants’ demographics & work characteristics
Frequency (%)
Demographic Profile of ECTs Gender M ale Female Age category <30 years 30 to 39 40
Descriptive statistics: Ghana(n=285) Frequency (%)
M ean±SD
101(%)
93(%) 181(%) 33.1 ±7.59
34.45±10.03
34(12%) 81(28%) 93(33%) 77(27%)
55(17.7%) 23(7.4%) 206(66.5%) 26(8.4%)
145(51%) 129(45%) 9(3%) 2(1%)
188(60.6%) 116(37.4%) 5(1.6%) 1(0.3%)
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250(81%) 52(17%) 7(2%) 0(0%)
8.7±6.84
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149(48%) 106(34%) 54(18%) 259(84%) 50(16%)
10.62±8.52
8.07±6.30
132(46%) 70(25%) 83(29%)
165(53.2%) 88(28.4%) 57(18.4%)
141(49.5%) 144(50.5%)
154(49.7%) 156(50.3%) 32.96±6.20
32.30±8.3
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33.33±8.40 29(10%) 58(21%) 92(32%) 106(37%)
17(5.5%) 23(7.4%) 115(37.1%) 155(50%)
2(1%) 95(31%) 212(68%)
51(18%) 192(67%) 42(15%)
40(12.9%) 259(83.5%) 11(3.5%)
3(1%) 21(7%) 157(51%) 128(41%)
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2.24±1.18
2.74±.99
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78(25%) 55(18%) 174(56%) 2(1%)
31.82±6.6
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1.94±.67
M ean±SD
140(45.2%) 122(39.4%) 48(15.5%)
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112(39%) 75(26%) 98(35%)
Educational level
Frequency (%)
97(%) 213(%)
184(%)
109(35%) 120(39%) 80(26%)
Junior High School High/Technical School College/Undergraduate/Diploma M asters + M arital Status M arried Single, Never M arried Single, Divorced Single, Widow (er) ECTs Work-related Characteristics Work experience 6 years or below 7 to 15 years >15 years School Type Public Private Class Size 15 16 to 25 26 to 35 >35 Job Task Child Caring Child Teaching Caring & Teaching Work hours/day 5 hours/day >5 hours/day Notes: ECTs= early childhood education range 18 to 59 (M age =33.27, SD=10.03)
M ean±SD
Descriptive statistics: Pakistan(n=310)
8.65±1.13 6.21±1.01 3(1%) 0(0%) 13(4.2%) 306(99%) 285(100) 297(95.8%) teachers. The final data comprised of male (n=291) and female (n=578) with age
6.28±2.27
Table 2: Fit of the original 22-item MBI-ES factor model across cultures: result of confirmatory factor analysis
Models M1 . 3-Factor proposed M2 . 2-Factor alternative M3 . 1-Factor alternative
χ2 [df] 1601.62[206] 1922.04[208] 2417.86[209]
X/df 7.78 9.24 11.57
CFI/TLI .67/.63 .60/.56 .48/.43
RMSEA .08 .09 .11
SRMR .09 .10 .11
Comparison M1 - M2 M1 - M3
Note: df= degree of freedom; TLI= Tucker Lewise Index; CFI= comparative fit index; RM SE= root mean squar approximation; SRM R=standardized root mean square residuals; AIC= Akaike’s information criterion. ***p<.001
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Dχ2[Dd
320.41[ 816.23
ACCEPTED MANUSCRIPT Table 3: Descriptive statistics, CFA factor loadings, validity and reliability of the original 22-item and reduced 16-item MBI-ES Overall item statistics Skewness Kurtosis MeanSD 3.382.02
.41 -.02 .12 .91 .39 .97 -.48 1.26 1.25
4.342.06 3.842.23
-1.11 -.56 -1.44 -.48 -1.17 -.26 .06 .66 .46
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2.731.96 3.442.04 2.711.93 5.082.14 2.421.74 2.381.83 5.911.54
-1.53 -1.17 -.55 -.45 -1.82 -.71 -.81 -.63
1.58 .17 -1.19 -1.05 2.55 -.99 -.38 -.87
2.16 2.01 1.60 2.65 1.39
5.53 3.95 1.51 6.32 1.24
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5.691.75 4.912.18 4.721.99
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6.091.50 4.942.22 5.351.69 5.071.88 2.953.35
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1. Emotional Exhaustion MBI 1. I feel used up MBI 2. Emotionally drained MBI 3. I’m working too hard MBI 6. frustrated MBI 8. Fatigued when I get up MBI 13. burned out MBI 14. Working with people MBI 16. At the end of my rope MBI 20. People puts too much stress on me Personal Accomplishment MBI 4. I feel exhilarated MBI 7. I feel energetic MBI 9. I deal with emotional problems MBI 12. I can understand my students MBI 17. I have accomplished many things MBI 18. I deal effectively with problems MBI 19. I’ m positively influencing MBI 21. I can create atmosphere 3. Depersonalization MBI 5. students blame me ♦ MBI 10. More callous towards people♦ MBI 11. Job is hardening me MBI 15. I don’ t really care ♦ MBI 22. Some students were impersonal object
1.911.59 2.051.64
Standardized CFA Load 22-Item MBI-ES 16-i .85 a .77(.60) .73 .72(.52) .71 .74(.55) .78 .58(.33) .60 .67(.45) .66 .21(.04) __ .04(.00) __ .36(.13) __ .45(.21) __ .71 a .51(.26) .45 .61(.37) .54 .59(.34) .65 .39(.15) .35 .49(.24) .64 -.11(.01) __ .41(.17) .38 .41(.17) .40 .77 a .17(.03) __ .75(.56) .74 .57(.33) .59 .49(.24) .49 .35(.12) .34
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Items: shortened items
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1.611.44 2.271.39 Note: CFA Standardized estimates and squared multiple correlations (R2) were recorded from the three-factor M BI-ES model in the cross-cultural sample. Items: 5, 13, 14, 16, 18, & 20 are excluded in the reduced M BI-ES due to low loadings and cross loadings. a= Cronbach’s alpha estimates for internal consistency ; b= square roots of average variance explained for discriminant validity; CR= Composite reliability, AVE= average variance explained, M SV= maximum shared variance; ♦Items with violations of normality (Log10 transformed). Item loadings are significant at ***p<.001 and **p<.01.
ms abbreviated
ional Exhaustion S 1 S 2 S 3 S 6 S 8 S 13 S 14 S 16 S 20 nalAccomplishment S 4 S 7 S 9 S 12
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Table 4: Country-level and Cross-cultural exploration of the MBI-ES factor structure: Results of exploratory factor analyses (EFA) Factor Loadings
1 .82 .80 .85 .63 .70 .31 .31 .38 .41
-.20 -.21
GHANA
2
3
.15
.12 .12
.56
.60 .71 .68 .36
.24 .32 .65 -.10 .64 .49
Factor Loadings
1
2
.81 .84 .82 .59 .70 .35 .26 .32 .58
.21 .16 .12
.19 .14
.52 .52 .48 .55
.25 -.24
.54 -.16
CHINA
3
.28 .24 .61 -.21 .57 .41
.21
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Factors Loadings
1 .74 .73 .65 .34 .68 .38 .28 .30 .26
-.15 -.17
2
-.13 -.10
-.19
.61 .50 .67 .52
P AKISTAN
Factor Loadings CROSS
3
1
.21
.80 .77 .82 .54 .63 .32 .30 .35 .33
.27 .57 .29 .38 .52 .55 .52
-.21 -.22 -.24
2 .10
.11
.60 .65 .64 .44
3 .16 .11 .11 .28 .27 .59 .61 .65 .55
.19
-CULTU
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S 17 S 18 S 19 S 21 rsonalization S 5 S 10 S 11 S 15 S 22
.39 -.14
.42
.57 .10 .47 .36
-.18 -.42 -.24 -.19
-.31 -.21 -.10 -.20 -.12
-.24 .51 .62 .43 .40
.14
.52 .67 .72 .60 .28
.14 -.15 .12
-.10
.18 -.24
-.14 .25 .74 .66 .54 .50
.17 .14
.52 .15 .45 .45
-.35 .27
.60 .48 .50 .48
.48 .73 .62 .69 .55
-.12
.30 -.10 -.19 -.14
-.22 -.31 -.18 -.13 -.25 .63 .68 .56 .44
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Note: M BI-ES= M aslach Burnout Inventory, Educators Survey; substantial loadings rounded .40 are bolded, crossloadings rounded30 are italicized. h2= item communalities (recorded from the cross-cultural sample).
Table 5: Fit of the reduced 16-item MBI-ES factor model: result of confirmatory factor analysis (χ2 [df])
CFI/TLI
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X/df
RMSEA SRMR
Comparison
(∆χ2 [df])
2.53 4.35 5.72
.91/.90 .79/.73 .70/.62
.06 .09 .10
.06 .09 M1a-M2a .11 M1a-M3a
176.37[2]** 310.89[3]**
244.02[92] 402.65[94] 635.24[95]
2.65 4.28 6.69
.90/.90 .80/.75 .65/.56
.06 .09 .11
.06 .09 M1b -M2b .11 M1b -M3b
158.63[2]** 391.22[3]**
335.69[92] 660.54[94] 1027.27[95]
3.65 7.03 10.81
.92/90 .81/.76 .69/.61
.06 .08 .11
.05 .09 M1 -M2 .11 M1 -M3
324.85[2]** 691.58[3]**
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232.77[92] 409.14[94] 543.66[95]
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Models Calibration sample M1a. 3-Factor proposed M2a. 2-Factor alternative M3a. 1-Factor alternative Validation sample M1b . 3-Factor proposed M2b . 2-Factor alternative M3b . 1-Factor alternative Cross-Validation Whole sample M1 . 3-Factor proposed M2 . 2-Factor alternative M3 . 1-Factor alternative
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Note: df= degree of freedom; TLI= Tucker Lewise Index; CFI= comparative fit index; RM SE= root mean squar approximation; SRM R=standardized root mean square residuals; AIC= Akaike’s information criterion. ***p<.001
Table 6: Validity of the reduced 16-item MBI-ES tested within several structural equation modelling Model
Cross-cultural model Workload Emotional demands Work family conflict Role conflict Total stress
Standardized Regression Coefficients Emotional Exhaustion Depersonalization Personal Accomplishment S.t Est (S.E)/R2 S.t Est (S.E)/R2 S.t Est (S.E)/R2 .18***(.11)/.03 .14***(.07)/.02 .29***(.07))/.09 .15***(.06)/.02 .27***(.03)/.07
.07+(.06)/.004 .07*(.04)/.01 .13***(.04)/.02 .11**(.03)/.01 .14***(.02)/.02
-.01(.08)/00 -.08*(.03)/.02 -.02(.06)/00 -.05(.04)/.002 -.12**(.03)/.06
Model fit RMSEA
.02 .03 .04 .02 .02
Note: St. Est.= Standardized Estimates, S.E=Standard Error, R=Explained variance of the M BI-ES latent factors due to the predictors (work stressors). Each row represent one SEM , Degree of freedom for all model =1, RM SEA= root mean squar approximation; CFI= comparative fit index; TLI = Tucker Lewise Index. + p<.10 *p<.05
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Statistic
CFI/TLI
.99/.97 .99/.97 .99/.96 .99/.99 .99/.99
ACCEPTED MANUSCRIPT **p<.01 ***p<.001
Table 7: Test of invariance of the reduced 16-item three-factor MBI-ES across cultures; result of MGCFA
χ2 [df]
Models (g: Pk., Cn., Gh.)
CFI
RMSEA
SRMR
Comparison
CFI
.030 .028 .034 .030 .033 .031
.0623 .0628 .0623 .0629 .0634 .0640
M 1a-M 2a M 2a-M 3a M 2a-M 4a M 4a-M 5a M 4a-M 6a
.00 .06 .01 .07 .01
1.76 1.68 2.02 1.79 1.97 1.81
.91 .91 .85 .90 .83 .89
663.40[368] 699.37[407] 888.25[455] 796.97[440] 1061.61[533] 817.84[458]
1.80 1.72 1.95 1.81 1.99 1.79
.91 .91 .86 .90 .83 .89
.030 .029 .033 .031 .034 .030
.0655 .066 .0661 .066 .0656 .0659
M 1b -M 2b M 2b -M 3b M 2b -M 4b M 4b -M 5b M 4b -M 6b
.00 .05 .01 .07 .01
.92 .92 .86 .91 .84 .89
.027 .026 .032 .028 .032 .029
.0585 .0589 .0587 .059 .0591 .0595
M 1 -M 2 M 2 -M 3 M 2 -M 4 M 4 -M 5 M 4 -M 6
.00 .06 .01 .07 .02
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830.99[368] 873.46[407] 1263.03[455] 1055.93[440] 1459.17[533] 1110.02[458]
2.26 2.15 2.78 2.40 2.74 2.42
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646.35[368] 683.59[407] 917.49[455] 786.01[440] 1049.53[533] 829.79[458]
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Calibration sample M 1a. Configural inv. M 2a. Metric inv. M 3a. Scalar inv. M 4a. Partial Scalar inv.a M 5a. Residual inv. M 6a. Structural inv. Cross-validating Validation sample M 1b . Configural inv. M 2b . Metric inv. M 3b . Scalar inv. M 4b . Partial inv.a M 5b . Residual inv. M 6b . Structural inv. Whole sample M 1 . Configural inv. M 2 . Metric inv. M 3 . Scalar inv. M 4 . Partial inv.a M 5 . Residual inv. M 6 . Structural inv.
χ2 /df
-
-
-
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Note: g = groups involved in the measurement invariance test, Pk.= Pakistan, Cn.=China, Gh.= Ghana, inv.= invariance, TLI= Tucker Lewise Index; CFI= comparative fit index; RM SEA= root mean square approximation; SRM R= standardize root mean square residuals; AIC= Akaike’s information criterion. a. Intercepts of the items “M BI-ES 2, 7, 9, 11, 12” were freely estimated across groups.
Table 8: Test of invariance of the reduced 16-item three-factor MBI-ES across gender; result of MGCFA Models (g: male & female) Calibration sample M 1a. Configural inv. M 2a. Metric inv. M 3a. Strong factorial inv. M 4a. Residual inv. M 5a. Structural inv. Cross-validation Validation sample M 1b . Configural inv. M 2b . Metric inv. M 3b . Strong factorial inv.
χ2 [df]
χ2 /df
CFI
RMSEA
SRMR
Comparison
CFI
RMSEA
568.37[276] 578.82[302] 637.03[334] 688.85[396] 651.85[346]
2.06 1.92 1.91 1.74 1.88
.90 .91 .90 .90 .90
.035 .033 .032 .029 .032
.0623 .0622 .0622 .0623 .0622
M 1a-M 2a M 2a-M 3a M 3a-M 4a M 3a-M 5a
-.01 .01 .00 .00
.0 .0 .0 .0
567.75[276] 604.10[302] 679.55[330]
2.06 2.00 2.04
.91 .90 .90
.035 .034 .035
.0655 .0655 .0657
M 1b -M 2b M 2b -M 3b
.01 .00
.0 -.0
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ACCEPTED MANUSCRIPT M 4b . Residual inv. M 5b . Structural inv. Whole sample M 1 . Configural inv. M 2 . Metric inv. M 3 . Strong factorial inv. M 4 . Residual inv. M 5 . Structural inv.
755.58[396] 686.68[346]
1.91 1.99
.88 .89
.032 .034
.0655 .0657
M 3b -M 4b M 3b -M 5b
.02 .01
.0 .0
762.59[276] 788.16[302] 911.47[334] 999.29[396] 932.73[346]
2.76 2.61 2.73 2.52 2.69
.92 .92 .91 .90 .90
.032 .030 .032 .030 .031
.0585 .0583 .0584 .0585 .0585
M 1 -M 2 M 2 -M 3 M 3 -M 4 M 3 -M 5
.00 .01 .00 .01
.0 -.0 .0 .0
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Note: g = groups involved in the measurement invariance test, inv.= invariance, TLI = Tucker Lewise Index; CFI= comparative fit index; RM SEA= root mean squar approximation; SRM R= standardized root mean square residuals; AIC= Akaike’s information criterion.
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Fig.1 Trend of burnout syndrome across cultures Fig.2 Trend of burnout syndrome across gender
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Figure 1
Figure 2
Michael Osei Aboagye, Qin Jinliang, Qayyum Abdul, Collins Opoku Antwi, Yasin Jababu, Emmanuel Affum-Osei PII: DOI: Reference:
S0190-7409(18)30508-5 doi:10.1016/j.childyouth.2018.09.041 CYSR 4012
To appear in:
Children and Youth Services Review
Received date: Revised date: Accepted date:
28 June 2018 28 September 2018 28 September 2018
Please cite this article as: Michael Osei Aboagye, Qin Jinliang, Qayyum Abdul, Collins Opoku Antwi, Yasin Jababu, Emmanuel Affum-Osei , Teacher burnout in pre-schools: A cross-cultural factorial validity, measurement invariance and latent mean comparison of the Maslach Burnout Inventory, Educators Survey (MBI-ES). Cysr (2018), doi:10.1016/ j.childyouth.2018.09.041
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ACCEPTED MANUSCRIPT Teacher burnout in pre-schools: a cross-cultural factorial validity, measurement invariance and latent mean comparison of the Maslach Burnout Inventory, Educators Survey (MBI-ES)
Michael Osei Aboagye, a, Qin Jinlianga, Qayyum, Abdula, Collins Opoku Antwi b, Yasin
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Jababuc [email protected], Emmanuel Affum-Oseid
a
c
University of Shanghai for Science and Technology
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b
North Carolina A&T State University The Chinese University of Hong Kong
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d
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Zhejiang Normal University, China
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Corresponding author at: 1601 East Market Street, Greensboro, NC, 27411, US
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ACCEPTED MANUSCRIPT
Recent development in research on teacher wellbeing has been associated with the interest in assessing teacher burnout with the widely used Maslach Burnout Inventory, Educators Survey (MBI-ES). The increasing application of the MBI-ES, in and out of the Western world, stresses the need to investigate the cross-cultural applicability and factorial
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validity of the scale. The present study investigated whether (a) the MBI-ES is applicable in a
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cross-cultural context (i.e., the three-factor model of the scale is equivalent across cultures) and (b) burnout syndrome differs significantly across these cultures and gender. Results of
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confirmatory factor analysis (CFA) did not support the 22-item MBI-ES. Subsequent
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exploratory factor analysis resulted in significant item reduction. The reduced-item (adjusted) three-factor model fitted the data, and invariant across cultures and gender.
Significant
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differences in teacher burnout symptoms were found across cultures and gender. The alterations made to the MBI-ES further reinforce cultural influences on the assessment of
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cross-cultural teacher burnout dimensions. Further implications for ECE teacher burnout
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management in cross-cultural contexts are discussed.
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Keywords: Teacher burnout; Preschool Education; Maslach Burnout Inventory, Educator Survey (MBI-ES); Cross-culture; structured means comparison
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1.0 Background of teacher burnout The prevalence of burnout, and specifically, teacher burnout is not a 21st -century development. In fact, the concept was duly acknowledged in the 20 th -century American society (McGeary & McGeary, 2012; Sarros & Sarros, 1990), where teachers’ emotional,
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mental and physical well-being were severely evaded (Affrunti, Mehta, Rusch, & Frazier,
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2018; Wilmar B. Schaufeli, 2017; Cunningham, 1983; Freudenberger, 1974), threatening job ; Kotova, Rozanov, Alexandrov, & Ivanovo,
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outcome (Medvedskaya & Sheryagina, 2017;
2017; Heydari & Abbasian, 2016; Lauermann & König, 2016; Salloum, Kondrat, Johnco, &
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Olson, 2015; Cunningham, 1983). Published inquiries and teachers’ participation in burnout workshops, soundly echoed burnout spread, severity and prevailing sentiments of the period
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(McGeary & McGeary, 2012; Cunningham, 1983), and perhaps, awareness of its debilitating
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consequences (Schaufeli, 2017; Freudenberger, 1974). The assessment of teacher burnout, then gained popularity in academia (Oh & Lee, 2009;
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Pines, 2002; Schwarzer et al., 2000; Sarros & Sarros, 1990), across distinct geographic contexts (Salmela-Aro & Read, 2017; Denton, Chaplin, & Wall, 2013; Maslach, Schaufeli,
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& Leiter, 2001). Empirical studies have revealed that burnout is a worldwide work-related phenomenon (Oh & Lee, 2009; Schwarzer et al., 2000), that closely influences the quality of teacher-work performance such as job efficacy (Lizano & Mor Barak, 2015; Pines, 2002), interpersonal relationships, and the overall teacher wellbeing (Griffiths, Royse, & Walker, 2018; Antonopoulou, Killian, & Forrester, 2017; Squires et al., 2014). Theoretical models for the assessment of cross-cultural teacher burnout studies then became significant determinants of the outcomes of these studies (Sarros & Sarros, 1990; Schwarzer et al., 2000). The Maslach Burnout Inventory (MBI) (Maslach & Jackson, 1981), has been adjudged as having strong psychometric properties (Worley et al., 2008), employed in over 90% of all empirical 3
ACCEPTED MANUSCRIPT burnout studies (Maslach, 2015), and recognized as a key model that facilitated burnout advancement in literature. In spite of the scale’s acceptability among scholars, Worley & Colleagues' (2008) metaanalysis of 24 exploratory and 13 confirmatory factor-analytic (EFA) (CFA) studies, in
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addition to 8 studies combining the two methods evinced the issue of inconsistent dimensionality of MBI scale where some research findings indicate internal structure of two
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(Galanakis, Moraitou, Garivaldis, & Stalikas, 2009; Walkey & Green, 1992), four (Firth,
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McIntee, McKweown, & Britton, 1985; Golembiewski, Munzenrider, & Carter, 1983; Palmira Faraci, 2018; Valente, Wang, & Menezes, 2018), and five factors (Densten, 2001), Kokkinos, 2006; Byrne, 1993) which is
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instead of three (Pérez-Mármol & Brown, 2018;
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consistent with the original factor-structure in Maslach & Jackson (1981). It is noteworthy that, recent studies have produced similar conflicting patterns evidenced in Worley & Colleagues' (2008) meta-analysis. Though Denton, Chaplin, & Wall's (2013) cross-cultural
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studies of New York City teachers (N=150) and Jamaica W.I. teachers (150) confirmed the
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three-factor structure of MBI scale, findings point to structural- and item-level differences between the two cultures. Mészáros, Ádám, Szabõ, Szigeti, & Urbán's (2013) study on 653
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Hungarian healthcare professionals using the Hungarian version of the MBI-HSS revealed a bifactor model as most appropriate for explaining considerable variance in observed scores after adopting CFA to test the proposed one-factor (Kanste, Miettunen, & Kyngäs, 2006), two-factor (Brookings, Bolton, Brown, & McEvoy, 1985), three-factor (Christina Maslach, Jackson, & Leiter, 1997), four-factor (Iwanicki & Schwab, 1981), and five-factor (Densten, 2001) models’ fit. Using a sample of 309 Italian high school teachers and a 20-item rather than the 22-item MBI-ES scale due to 2 items being problematic, Faraci (2018)replicated Firth, McIntee, McKweown, & Britton's (1985) four-factor structure where the emotional exhaustion component was broken into two (i.e., strain and frustration). Additionally, 4
ACCEPTED MANUSCRIPT Valente, Wang, & Menezes (2018) with two emotional exhaustion factor (i.e., Exhaustion & Strain), reported a four-factor structure as the most suitable in terms of fit on 1046 Brazilian bank employees’ sample even though the three-factor was fairly reasonable, as they observed. These studies, except Mészáros et al. (2013), employed both EFA and CFA techniques.
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Additionally, a good number of studies have investigated MBI scale’s cross-cultural measurement invariance (Denton et al., 2013; Xanthopoulou, Bakker, Kantas, & Demerouti,
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2012; Schutte, Toppinen, Kalimo, & Schaufeli, 2000; Horn, Schaufeli, Greenglass, & Burke,
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1997). The outcome of Schutte et al.'s (2000) three-nation comparison of MBI-GS on Finnish, Swedish and Dutch samples (N= 9055) established the scale’s non-invariance across
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the three contexts at item level – recording low factor loadings and item error correlations. Xanthopoulou & Associates (2012) structural and item level invariance test of the MBI-GS
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on Dutch and Greek samples with CFA resorted to some modifications – that, items 1, and 2 from exhaustion and 5 from cynicism as well as 6 from professional efficacy were not
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invariant. Again, results from Denton & Associates' (2013) comparative study between New
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York City (a cosmopolitan of a first world – U.S.) and Jamaica W.I. (a developing country on the Caribbean) displayed structural- and items- level differences. These findings are
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indicative of the perspective that, cross-cultural comparisons should not assume invariance in the constructs and items nomological network of the phenomenology of burnout (Squires et al., 2014; Denton et al., 2013). Particularly, little attention has been given to the applicability of the scale in economies with low socio-economic conditions as most of these studies have concentrated on teachers’ burnout in the North American or European geographic regions (Poghosyan, Aiken, & Sloane, 2009; Schutte et al., 2000). In this regard, the generalizability of the measurement properties of the scale in developing economies such as those in subSaharan Africa (i.e., Ghana), and South-eastern Asia (i.e., Pakistan and China) with
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ACCEPTED MANUSCRIPT challenging
socio-economic,
and
broadly
distinct
cultural conditions may be highly
challenged. In this respect, Worley et al., (2008) and Squires et al.'s (2014) conclusion that, the need to assess the cross-cultural fit of the most prominent burnout model (i.e., MBI-ES) in a
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distinct educational environment other than the original cultural context of the scale (U.S.), to evaluate the content, context, conceptual, semantic, and technical equivalence (Squires et al.,
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2014), is one of urgency. Also, Kristensen et al., (2005) declaring the MBI-ES conceptually
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flawed and unusable on Danish samples in its original state, further stressed on the untenable nature of the assumption that, the event of burnout or its antecedents stay unchanged across
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cultures and suggested structural- and item-level comparisons to clear such assumptions.
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These calls are in agreement with later scholars (Schimmenti, 2016; Craparo, Faraci, & Gori, 2015), that the test of factorial structure of popular socio-psychological research instruments across cultures for structural and item equivalence is a necessity. Therefore, the test of the
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MBI-ES scale’s cross-cultural (Ghana in West Africa, and China and Pakistan in Asia)
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applicability on the three low socio-economic contexts is imperative, and is expected to elicit unique insights that could inform burnout assessment. Given that the proper assessment of the
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burnout syndrome in these cultural settings requires culturally-adapted and theoreticallymeaningful measures, this study seeks to fill this gap. Accordingly, the first objective for undertaking this research is to assess whether or not the factor structure of the MBI-ES fits three cultural contexts (i.e., possesses factorial invariance across cultures). 1.1 Comparing teacher burnout across cultures and gender The international nature of burnout has necessitated considerable cross-cultural inquiries into the concept given its impact on employee well-being and organizational outcomes (Squires et al., 2014; Xanthopoulou et al., 2012; Poghosyan et al., 2009; Perrewé et al.,
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ACCEPTED MANUSCRIPT 2002). Findings from these investigations indicate cross-cultural differences in teacher burnout experience. First, North American samples exhibit higher mean levels of cynicism (depersonalization) and exhaustion as compared to that of Europe with Polish sample being the only deviation, whilst the highest burnout incidences are recorded in Taiwanese and Japanese samples (Denton et al., 2013; Maslach et al., 2001; Schwarzer et al., 2000). For
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instance, Schwarzer et al. (2000) identified significant differences between German and Hong
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Kong on the emotional exhaustion subscale of the MBI-ES, where the Germans exhibited less
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exhaustion than their counterparts in Hong Kong with a post hoc t test analysis. However, the difference between German and Hong Kong cultures were found to be minor when the two
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cultures were compared to the American cultural setting. The authors’ found the American side recording significantly higher burnout than found in Germany or Hong Kong. Also, (2002) discovered
American teachers,
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Pines
having less stressful work
conditions,
experienced higher burnout than Israeli teachers who work in more stressful conditions. The
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author’s finding was explained by the fact that cultural differences in work attitude and work
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significance to life explain the observed differences. Differences in burnout syndrome across cultures are not unique to the teaching
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profession, and there have been numerous studies in other human services professions such as health services with similar findings. For example, Schaufeli & Janczur's (1994) examination of burnout among practicing nurses in Poland (N=200) and The Netherlands (N=183), discovered that Poles experienced higher burnout than their Dutch counterparts, even when the differential work conditions’ potential confounding effects were accounted for. Again, Suñer-Soler et al. (2014) found Spanish healthcare professionals in Spain to be, fairly differently, burned out compared to their counterparts in Latin America. The authors implied differences in culture to be a potential explanation for their findings. However, Pienaar &
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ACCEPTED MANUSCRIPT Wyk (2006) and Kaur & Noman (2015) attributed cases of cultural variability to social support or the lack thereof, whilst Koki (2000) emphasizes the role of religion. Burnout researchers have indicated that the role of gender is a necessary consideration in teacher burnout syndrome (Droogenbroeck et al., 2014; Byrne, 1991; Russell et al., 1987). In
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most studies, female teachers have been found to experience higher levels of emotional exhaustion (Grayson & Alvarez, 2008; Lau et al., 2005), and lower levels of personal
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accomplishment than their male counterparts (Droogenbroeck et al., 2014; Grayson &
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Alvarez, 2008; Lau et al., 2005; Byrne, 1991), as a consequence of non-school environment responsibilities (for example, family duties that are deemed in certain cultures to be
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performed mainly by females) (Woodside et al., 2008). These societal female-oriented duties
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coupled with teacher job characteristics quicken the rate and magnitude of stress experience and the consequent burnout (Lau et al., 2005; Borthwick, Thornell, & F. Wilkinson, 1982). On another breadth, male teachers are known to keep their feelings to themselves, and as a
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result experience far greater depersonalization (Stoeber & Rennert, 2008; Lau et al., 2005;
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Byrne, 1991), and cynicism than female teachers (Woodside et al., 2008). These findings on burnout differences across cultures and gender have been discovered in
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the developed world, with little to no attention to low and middle income countries (i.e., Ghana, China and Pakistan), where children and youth education remain a major policy issue (Unesco, 2015; UNESCO, 2008). Therefore, comparing teacher burnout across LMICs will inform preventive and treatment intervention programs and policies through the pursuit, and discovery of distinct contextual resources and practices, and their adaptation in other contexts (Denton et al., 2013). In the light of this, the second objective of this study, therefore, was to examine whether or not burnout syndrome differs significantly across these cultures and gender.
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ACCEPTED MANUSCRIPT 2.0 Methods 2.1 Participants and Procedure The data used in this study was a baseline data on pre-school teachers’ wellbeing and teacher-child relationship quality in Ghana, Pakistan and China. The schools were randomly
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selected using two stratification selection criteria: administrative level (provinces/ regions and district/ division), and sources of funding (government/ public and non-government/
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private). Between 145 to 163 schools were selected from provincial/regional and district
Schools
were
sampled
with
respect
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capitals, one second-tier level town and two rural settlements of Ghana, China and Pakistan. to
socio-economic and
cultural compositions.
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Compositionally, the provincial/regional and district capitals serve as the microcosms of
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ethnic, cultural, technological, economic and administrative hubs of the countries, with schools enlisting pupils and staffs from diverse socio-cultural and economic backgrounds.
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The majority of the schools had two kindergarten (i.e., KG 1 for four years olds and KG 2 for 5 to 6 years old) teachers, though the range was from one to five in all three countries.
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No more than two teachers were sampled per school, and where teachers in the school were above two, two were randomly sampled for data collection (one each from KG 1 and KG 2).
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Additionally, in instances where two teachers managed a class, only the lead teacher was sampled. In the five, eight and three schools from Ghana, China and Pakistan, which had two teachers in a class, the lead teachers were sampled in all cases. The schools’ classroom compositions are of a typical inclusive character; composed of students with or without special developmental needs and teachers with different Sex and ages. A sample size of 869 was used for the study. Prior to data collection, research permit was obtained from the municipal directorate of education in the three countries. In line with the declaration of Helsinki, consent letters with information about the fundamental goals of
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ACCEPTED MANUSCRIPT the study were sent to the head teachers and principals of the schools and teacher consents were also obtained to ensure voluntary participation. The study protocol was approved by the Zhejiang Normal University Graduate Review Committee. Table 1 presents detailed description of the participants and schools’ characteristics. 2.2 Measures Burnout Scale
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2.2.1
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Teacher burnout was measured with the 22-item 3-factor Maslach Burnout Inventory, Educator’s Survey (MBI-ES), rated on a 7-point scale, ranging from (1= Never to 7=
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Everyday) (Maslach & Jackson, 1981). The emotional exhaustion sub-scale measures
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teachers’ feelings of being emotionally overextended and exhausted by their work (e.g., “I feel used up at the end of the workday”). Depersonalization sub-scale measures teacher’s
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perception of impersonal, and insensitive response to his/her students (e.g. “I feel I treat students as if they were impersonal objects”). Accomplishment on the other hand, assessed
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teachers’ feeling of competence in their work (e.g. “I have accomplished many worthwhile things in this job”). Reliability and validity of the MBI-ES have been established in previous
Teacher Stress
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2.2.2
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studies (Boles et al., 2000; Aluja et al., 2005).
Teachers responded to a collection of widely-used and validated self-report measures developed by previous scholars to measure work-related stressors. Workload was assessed with 5 items (e.g. “My work requires too much from me”: a=.71) on 4-point scale (1=never to frequently) (Siegrist et al., 2004), emotional demands with 7 items (e.g. “My work demands a lot from me emotionally”: a=.86) on 4-point scale (1=never to 4=always) (Veldhoven & Meijman, 1994), work-family conflict with 5 items (e.g. “My work takes up time that I’d like to spend with my family/friend”: a=.81) on 5-point scale (1=never to 5=very often) (Frone, Russell, & Barnes, 1996), and role conflict with 8 items (e.g. “I work with groups who 10
ACCEPTED MANUSCRIPT operate quite differently”: a=.88) on 7-point scale (1=very false to 4=very true) (Rizzo et al., 1970). 2.3 Data preparation, descriptive statistics and analytic approach
2.3.1
Missing data and Descriptive statistics
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Cases with missing data (2.42%) were retained and treated as missing at random (MAR) by using full-information maximum likelihood estimators (FIML) (Allison, 2003). In line with
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Curran et al., (1996) and Allison, (2003), item descriptive statistics (mean and standard
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deviation), and normality (skewness and kurtosis) were examined. Two items (MBI 5, 15) appeared to be marginally skewed, with skewness values greater than the recommended
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threshold (±2.0). Logarithmic transformation was employed to produce a near-normal
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distributions (Field, 2005). Univariate normality assumptions were not violated, because maximum likelihood statistics are robust to mild violations of normality (Jackson et al.,
2.3.2
Data analytic approach
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2009). That notwithstanding, the items were carefully monitored in subsequent analyses.
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CFA, MGCFA and structured means analyses were performed in a structural equation modelling, using Amos 25 (Arbuckle, 2017). For the CFA, three competing models were
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compared: (1) proposed three-factor model, (2) an alternative two-factor model, and (3) another alternative one-factor model. Model fit was evaluated, using the Chi-Square (χ2 ) statistics (Cochran, 1952; Bentler & Bonett, 1980), the Standardized Root Mean Square Residual (SRMR), Comparative Fit Index (CFI), Tucker Lewise Index (TLI), the Root Mean Square Error of Approximation (RMSEA) (Bentler & Bonett, 1980; Bentler, 1990; Mueller & Hancock, 2008), and Akaike’s information criterion (AIC) (Akaike, 1987; Bryk & Raudenbush, 1992). CFI ratio ≥.90, SRMR≤.08 and RMSEA ≤.08 show acceptable fit, whereas good fit obtains CFI≥.95, SRMR≤.06 and RMSEA≤.06 (Maccallum et al., 1996; Hu,
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ACCEPTED MANUSCRIPT Bentler, & Hu, 1999), and the model with lower AIC value had a best fit (Akaike, 1987; Bryk & Raudenbush, 1992). Multi-group
confirmatory
factor
analyses
(MGCFAs)
were
performed
to
test
measurement invariance (MI) (Meredith, 1993), of the MBI-ES across gender, and cultures.
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Five invariance types of Byrne, Shavelson, & Muthen (1989), were tested: configural, metric, scalar, residual, and structural invariance (Mellenbergh, 1983; Meredith, 1993; Chen, 2007;
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Meredith & Teresi, 2006). Consistent with Cheung & Rensvold (2002), and Chen (2007),
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∆CFI, ∆RMSEA and ∆SRMR indices were examined for MI model fit. Considering the sample size (N>500), for testing metric invariance, a change of .010 in CFI, supplemented
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by changes of .015 in RMSEA and .030 in SRMR indicated equivalence. For test of scalar
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invariance and the other restricted models, ∆CFI.010, ∆RMSEA.015 and ∆SRMR.010 indicated equivalence (Cheung & Rensvold, 2002; Chen, 2007; Sass, 2011) (see Appendix B
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for summary of the MI tests steps).
Comparisons in the MBI-ES subscales were made using structured means analysis (Aiken
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et al., 1994; Hancock, 1997). One group was set as reference group, treating the others as comparison groups. The latent mean for the reference group was fixed at zero (0), and the
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latent group means for the comparison groups estimated as deviations from the reference group (Dimitrov, 2006). Differences in latent means are not influenced by the decision to fix reference groups’ mean at zero while freely estimating those of the comparison groups (Aiken et al., 1994; Hancock, 1997; Dimitrov, 2006). 3. Results 3.1 Assessing the factor structure of the MBI-ES across cultures Based on the hypothesised three-factor, alternative two-factor and one-factor structures of the MBI-ES, we performed CFAs on the whole sample. Factors, but not residual variances were allowed to be correlated. Factor loadings of all first indicator items were fixed to one.
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ACCEPTED MANUSCRIPT Results revealed that restricting the model from three to two dimensions (M3 to M2 ) and from two to one dimension (M2 to M1 ), significantly reduced the model fit (see Table1). Although the three-dimensional model (M3 ) fitted the data best, the fit was considered unacceptable. Item-level analysis
(Reise et al., 1993; Vandenberg & Lance, 2000; Sass, 2011), revealed
some items as potentially problematic: low factor loadings (<.40), R2 (<.20) (see Table2),
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and cross-loadings on other factors (Tabachnick & Fidell, 2007).
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3.2 Country-level and Cross-cultural exploration of the original MBI-ES factor structure
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Because the original 22-item three-factor MBI-ES model had psychometric problems, we
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restarted the evaluation process with an exploratory approach at both country-level and crosscultural level, as recommended by Squires et al. (2014). To examine the context-appropriate
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number of MBI-ES factors, we performed parallel analyses (J. L. Horn, 1965), and a graphical solution to scree test. Oblique rotation (Quartimax) was applied to examine item
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loadings on their respective factors, because the factors were found to be inter-correlated in the initial CFA and previous studies using the MBI-ES (Costello & Osborne, 2005). In line
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with Floyd & Widaman, (1995) and Costello & Osborne, (2005), three criteria were used to evalaute the items and their factors: a) items were required to extract on their theoritically
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meaningful underlying component, b) obtain a minimum loadings .40 or greater and, c) items with crossloadings to be droped as suggested by Costello & Osborne, (2005) and Tabachnick & Fidell, (2007).
Ghana: The parallel analysis and graphical solution to scree test produced three-factor solution. Factor1 was represented, in total, by 5 items (MBI-ES 1-3, 6, 8) that have described personal accomplishment subscale in the MBI-ES. Factor 2 was interpreted as emotional exhaustion as it was represented by seven substantive items: (MBI-ES 4, 7, 9, 12, 17, 19, & 21) belonging to the emotional exhaustion subscale of the MBI-ES. Factor 3 was represented
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ACCEPTED MANUSCRIPT by 4 items: (MBI-ES 10, I1, 15, 22), originally described as depersonalization subscale in the MBI-ES. Six items; four of them (MBI-ES 13, 14, 16, & 20) from the emotional exhaustion scale, one (MBI-ES 18) from the personal accomplishment subscale, and (MBI-ES 5) from the Depersonalization subscale were considered potentially problematic in the factor
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extraction as they substantially cross-loaded on more than one factor. China: As a result of the EFA, three-factor structure was extracted. Factor 1 was interpreted
Factor2 was interpreted as emotional
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belonging to the personal accomplishment subscale.
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as personal accomplishment on the bases of 8 items (MBI-ES 4, 7, 9, 12, 17-19, 21)
exhaustion; represented by 5 items (MBI-ES 1-3, 6, 8), all being the original items described
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in the MBI-ES as emotional exhaustion subscale. Factor 3 was named depersonalization and was represented by 4 items (MBI-ES 10, 11, 15, 22), which originally formed the
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depersonalization subscale of the MBI-ES. Five items, four of them (MBI-ES 13, 14, 16, 20) from the emotional exhaustion scale, and one (MBI-ES 5) from the depersonalization scale
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were identified as having problematic loadings; had low loadings on their respective
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constructs, and cross-loaded on other factors. Pakistan: EFA results revealed three-factor structure. Factor 1 was represented by seven items (MBI-ES 4, 7, 9, 12, 17, 19, 21) belonging to the personal accomplishment scale of the
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MBI-ES. Factor2 was represented, in total, by 4 items (MBI-ES 1-3, 8); these were among the original items described in the MBI-ES as capturing emotional exhaustion. Factor 3 was represented by 5 items (MBI-ES 5, 10, 11, 15, 22) all belonging to the MBI-ES’ depersonalization subscale. Six items, five of them (MBI-ES 6, 13, 14, 16, 20) from the emotional exhaustion scale and one (MBI-ES 18) from the personal accomplishment scale had low loadings on their respective constructs and cross-loaded on other factors. Cross-cultural EFA:
Results revealed similar factor structure on the cross-cultural sample.
Factor1 was represented by seven items (MBI-ES 4, 7, 9, 12, 17, 19, 21) from the personal 14
ACCEPTED MANUSCRIPT accomplishment, factor2 by 5 items (MBI-ES 1-3, 6, 8) from the emotional exhaustion, and factor 3 by four items (MBI-ES 10, 11, 15, 22) belonging to depersonalization of the original MBI-ES subscales. Items (MBI-ES 5, 13, 14, 16, 18, 20), were verified as having problems in the extraction.
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3.3 Post hoc scale reduction Moving forward, the country-level and cross-cultural factor structures were compared.
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Problematic items found in two-third (2/3) or all of the countries and verified in the cross-
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cultural EFA were deleted. Results revealed that items (MBI-ES 13, 14, 16, 20) had problems in Ghana, China and Pakistan, (MBI-ES I5) China and Ghana, and (MBI-ES 18) Ghana and
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Pakistan samples (see Table3). However, item (MBI-ES I6) appeared to be problematic in only one out of the three countries. These measurement problems are not unique to this study;
Aluja
et
al.,
2005).
Thus
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some of these items have been characterized same in several other studies (Boles et al., 2000; considering
previous
empirical studies
and
conceptual
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considerations, we proceeded with reduced 16-items EFA without items (MBI-ES -ES 5, 13,
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14, 16, 18, & 20).
To obtain a statistically substantive and viable factor structure, having measurement items a) interpreted the same, and b) with similar meaning in the three cultures, we have first
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established that six items are unfit for this cross-cultural study. As a result of the EFAs, these items may be lacking the same meaning and interpretation across-cultures. Excluding them in the final extraction resulted in a clean factor-structure.
The adjusted factor-structure for the
cross-cultural study generated a consistent picture of the original MBI-ES factor-structure having three factors: emotional exhaustion (Factor1; 5 items), personal accomplishment (Factor 2; 7 items), and depersonalisation (Factor3; 4 items), sharing similar content, conceptual, semantic, and technical meaning with the original MBI-ES instrument (Maslach & Jackson, 1981). Oblique rotated EFA factor loadings and communalities (h2 ) for the 15
ACCEPTED MANUSCRIPT reduced 16-item three-factor MBI-ES are presented in Table3, whiles Appendix C presents the parallel analysis and graphical solution to scree test for the three samples 3.4 Confirmation of the reduce 16-item three-factor structure on cross-cultural sample To confirm the reduced 16-tems three-factor structure, CFAs were performed. Problems in single-sample post hoc modifications were resolved by applying the two-step strategy
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recommended by Arlot & Celisse, (2010) and Freire et al. (2017). Accordingly, taking
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advantage of the sample size, we split the sample into strictly random independent
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homogenous halves (Calibration sample: N=435 and Validation sample: N=434). This allowed for validation and modifications of the adjusted model in one half (Calibration
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sample) and cross-validation on the second half (Validation sample). Again, testing the three priori models in the calibration sample, we first established that
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the three-dimensional model fitted the data as compared to the two- and one-dimensional models. However, item-level analysis with the modification indices revealed some items
subscale)
as
having
measurement
error-covariance.
The
modification
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accomplishment
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(MBI-ES 1, 2 & 6 in the emotional exhaustion scale and all the items in the personal
allowed these errors to be correlated in order to improve the model fits, as done in previous studies (Boles et al., 2000; Aluja et al., 2005). The fit of the three-dimensional model
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substantially improved, whilst the two- and one-dimensional models remained misfit (see M1a Calibration sample;
Table 4). Cross-validation on the validation sample (M1b Validation
as well as the whole sample verified the initial results (M1
whole sample;
sample;
Table 4)
Table 4). All factor
loadings were significant. Inter-factor correlation patterns of the reduced 16-item latent scale scores did not reveal any appreciable change from the 22-item latent scale scores, and the coefficients were consistent with those reported in previous studies (Aluja et al., 2005; Worley et al., 2008). Emotional exhaustion correlated positively with depersonalisation (roriginal 16
MBI-ES=.36;
rreduced
ACCEPTED MANUSCRIPT MBI-ES
=.29, p<.01), and negatively with personal accomplishment (roriginal
MBI-ES=
-.17,
p<.01); whereas depersonalization correlated
MBI-ES=
-.20; rreduced
negatively with personal
accomplishment (roriginal MBI-ES=.-26; rreduced MBI-ES =-.23, p<.01). 3.5 Validity and reliability of the reduced 16-item MBI-ES
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To test for construct, convergent and discriminant validity and reliability, average variance explained, maximum shared variance, composite reliability and Cronbach's alpha for
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internal consistency ratios were computed and compared to their thresholds (Hair, Black,
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Babin, & Anderson, 2010; Fornell & Larcker, 1981). Results are comparable to those reported in previous studies (see Table 2). Further validity evidence based on the scale’s
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relation with other variables was achieved by performing separate structural equation models (SEM). The latent scores of the reduced 16-item MBI-ES subscales were regressed on work
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stressors. The regression weights were in the expected directions, and statistically significant: work stressors (workload, emotional demands, work-family conflict and role conflict) were
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positively associated with emotional exhaustion and depersonalization. On the other hand, the
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work stressors were negatively related to personal accomplishment, but only emotional demands and the total stress scores were statistically significant (see Table 5).
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3.6 Invariance test of the MBI-ES across cultures and gender Multigroup confirmatory factor analyses (MGFAs) were performed on the adjusted measurement model to test whether or not there are: 1) equality of factor structure, 2) equality of magnitude of factor loadings/ scaling units, 3) cross-group difference in the means of the observed items, 4) equality of error-variance, and 5) equality of factor variance across cultures and gender. 3.6.1
Invariance across cultures
17
ACCEPTED MANUSCRIPT We first established that the adjusted three-factor model fitted the groups for configural invariance test (see M1 Whole sample; M1a Calibration sample; M1b Validation sample; Table 6). Simultaneous analysis of least restricted solution revealed strong metric invariance (see M2 , M2a, M2b; Table 6). Moving forward, additional constraints were imposed to test for scalar invariance. The model fit indices showed poor fit (see M3 , M3a, M3b, Table 6), signalling non-invariant
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items in the model. Item-level analysis (Sass, 2011), revealed one item of the emotional
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exhaustion and depersonalization subscales (MBI-ES 2 “I feel emotionally drained from my work” and MBI-ES 11 “I worry that this job is hardening me emotionally) and three items of
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the personal accomplishment subscale (MBI-ES 7 “I feel very energetic”, 9 “In my work I
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deal with emotional problems very calmly” and 12 “I can easily understand how my students feel”) lacked invariance across cultures. This result was further cross-verified on the
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validation and calibration samples. Consequently, the intercepts for the
items were freely
estimated, and partial scalar invariance model tested (Vandenberg & Lance, 2000). Result
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showed acceptable fit for partial strong scalar invariance (see M4 , M4a, M4b; Table 6). Residual invariance and structural invariance were finally tested by imposing additional
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constraints. Results did not support the residual invariance model (see M5 , M5a, M5b; Table 6) and structural invariance (see M6 ; M6a, M6b; Table 6), because the additional constraints
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altered their model fits significantly, Taken together, the invariance tests supported partial strong factorial invariance across the three cultures (Meredith, 1993; Chen, 2007; Meredith & Teresi, 2006).
3.6.1.1 Structured means analyses of the modified MBI-ES across cultures Based on the MI test results, we performed structured means analysis to test latent mean differences across cultures. Ghana and China had higher latent mean scores than Pakistan on the emotional exhaustion subscale, accomplishment
and
depersonalization
and
lower latent mean score on the personal
subscales. 18
These differences in the emotional
ACCEPTED MANUSCRIPT exhaustion subscale were significant (z=3.617, p<.01) and (z=6.532, p<.01) for Ghana and China respectively. On the other hand, the difference in the personal accomplishment subscale was significant for China (z= -3.073, p<.01), but was not significant for Ghana (z= 1.503, p>.05). Similarly, the differences in the depersonalization subscale was significant for Ghana (z=-1.933, p<.05), but not significant for China (z= -.728, p>.05). These latent means
Invariance across gender
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3.6.2
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differences were further explored in simple graphs (Fig. 1).
sample;
M1a
calibration sample ;
M1b
validation sample ;
whole
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Results showed good model fit for configural invariance test across gender (see M1
Table 7). After imposing constraints on factor
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loadings, AIC decreased and CFI was lower than the threshold, indicating strong metric
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invariance (see M2 , M2a and M2b; Table 7). The model for scalar invariance (M3 , M3a, M3b; Table 7) was also supported, indicating strong factorial invariance. Residual invariance (M5, M5a, M5b, Table 7) and structural invariance (M6 , M6a, M6b;Table 7) were then tested and
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found to be fit, together supporting that the MBI-ES possesses strict factorial invariance
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across gender.
3.6.2.1 Structured means analyses of the MBI-ES across gender
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We then tested latent mean differences across gender. The comparison group (male teachers) scored lower on the emotional exhaustion subscale and higher on the personal accomplishment and depersonalization subscales compared to the reference group (female teachers). These differences were significant; emotional exhaustion (z=-3.399, p<.001), personal accomplishment (z=2.595, p<.01) and depersonalization (z=3.169, p<.001), and further plotted in simple graph (Fig. 2). 4.0 Discussion
19
ACCEPTED MANUSCRIPT The present study validated the three-dimensional structure; emotional exhaustion, depersonalization and personal accomplishment of the MBI-ES, using parallel analysis, CFA and MGCFA. We verified and extended the cross-cultural validity and measurement invariance evidence of the MBI-ES across LMICs (i.e., Chinese, Pakistani and Ghanaian). Our study adds to investigations on culturally-specific issues: cross-cultural meaning and and the conceptual equivalence of burnout
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interpretations of the MBI-ES’s items,
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dimensions, important to understanding burnout phenomenon to add to the scale’s global
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applicability. The study, employing statistically sophisticated methods, highlights insightful revelations of the factorial and structural validity as well as measurement equivalence of the
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hypothesized three-factor MBI-ES model.
First, the three-factor pattern and item loadings of the MBI-ES were verified in a cross-
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cultural context. In line with previous studies (Denton et al., 2013; Schaufeli & Dierendonck, 1993; Schaufeli et al., 1994), our study did not support the 22-item three-factor structure; as potentially problematic in the cross-cultural context.
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some items were reported
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Specifically, these items had poor psychometric properties; low factor loadings and crossloadings on more than one factor. Similar results have been reported by previous studies that assessed teacher burnout with the MBI-ES in different geographic regions, testing the MBI-
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ES’s three-factor structure in Europe with samples from Catalonia (Aluja et al., 2005), Netherlands (Schaufeli & Dierendonck, 1993; Schaufeli et al., 1994), Norway (Richardsen & Martinussen, 2004), and also North America including the U.S. (Boles et al., 2000), and Canada (Byrne, 1991, 1993, 1994). This reveals the items’ inadequate predictive capacity for their latent constructs, and clear-cut interpretability of the 22-item MBI-ES three-factor solution (Destin, 2001). Maslach and Jackson (1981) advised burnout researchers to exclude some items (12 and 16) from the MBI-ES when assessing its measurement structure. Similarly, several scholars 20
ACCEPTED MANUSCRIPT of teacher burnout hinted of the need to exclude some of these same items, including (items 5, 13, 14, 16, 18, 20) in burnout assessment in different geographic regions that adopt the MBI-ES. A recent study on a cross-cultural adoption of the MBI-ES in eleven European countries with ten languages found several items, including (5, 14, 16, 20) problematic as they failed to possess similar interpretation across cultures (Squires et al., 2014). This
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magnitude of the 22-item MBI-ES measurement problems suggest the need for an adjusted
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model which is context- and culturally-relevant for the understanding of the underlying structure of burnout (Worley et al., 2008). The replicability of the MBI-ES structure and
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items’ validation across the three cultures, therefore verified the constructs’ cross-cultural
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meaning and usefulness.
The reduced 16-item three-dimensional factor model produced acceptable fit across the
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three cultures when some item error variances and the latent factors were correlated. This is consistently evidenced in previous studies that tested the MBI-ES’s three-factor model, and
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found it fit by allowing its factors to correlate, and permitting residual covariance (Worley et
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al., 2008; Denton et al., 2013). We found comparable relationship patterns between the burnout factors and those reported in previous studies (Worley et al., 2008). Support for the two subscales: emotional exhaustion and depersonalization as being the core of burnout was
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achieved (Hawrot & Koniewski, 2017), as they shared strong positive relation, and correlated negatively with personal accomplishment. These inter-factor correlations and the associations found between the burnout subscales and work stressors, together with validity and reliability evidence verified the scale’s psychometric strength, when adopted in cross-cultures (Boles et al., 2000; Aluja et al., 2005). Thus, we found the underlying factors in the reduced 16-item MBI-ES model substantially reliable and valid, fitting the Chinese, Pakistani and Ghanaian cultural contexts, allowing for cross-cultural invariance assessment and possible teacher burnout comparison. 21
ACCEPTED MANUSCRIPT The reduced 16-item MBI-ES in the cross-cultural context revealed partial strong factorial invariance across cultures and strong factorial invariance across gender (Reise et al., 1993; Cheung & Rensvold, 2002), serving as pre-requisites for multi-group comparison (Meredith & Teresi, 2006), for researchers to discern differences in teacher burnout in respect of the dimensions explored (Cheung & Rensvold, 2002; Meredith & Teresi, 2006; Chen,
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2007; Sass, 2011). That notwithstanding, our study found non-invariance items (MBI-ES 2,
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7, 9, 11, 12) across cultures. Thus, teachers’ perception of these items varied among those in
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Pakistan, Ghana and China. Possible reasons for this variations might be attributable to contextual elements of borderline distinctiveness in semantics, content, technicality and
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concepts of burnout as advised by (Squires et al., 2014).
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Significant differences in teacher burnout across countries and gender were revealed in our study. Ghanaian and Chinese preschool teachers reported higher experience of emotional exhaustion than their Pakistani counterparts. For personal accomplishment, the Pakistani
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preschool teachers recorded higher levels than their Ghanaian and Chinese counterparts. It
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was further revealed that, the Pakistani preschool teachers experienced higher levels of depersonalization than the Ghanaian and Chinese preschool teachers. Despite this variability
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in teacher burnout experience across these three low and middle income countries, classroom and school characteristics as presented in table 1 show fairly similar contextual conditions. Given the findings of empirical cultural analysis of burnout that assigned marked teacher burnout differences to cultural perspectives including the level of professional status of teaching in society (Denton et al., 2013), religious orientation (Koki, 2000), social support (Pienaar & Wyk, 2006), and existential significance of teaching profession in certain cultures (Pines, 2002), it is therefore indicative that, the results of this study may be due to the role of the broader cultural and systemic influence on teacher burnout reactions among pre-school teachers (Sarros & Sarros, 1990). This resonates with the theorisation by Bronfenbrenner & 22
ACCEPTED MANUSCRIPT Morris (1998), who highlighted not just the micro ecosystem (i.e., immediate contextual factors) of the school, but also, the macro level (i.e., broader cultural conditions) of economic, technological, legal, scientific and institutional ecosystem of people-environment relations.
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Gender differences where female teachers reported higher emotional exhaustion than their male counterparts, lower perceptions of personal accomplishment and depersonalization than
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male teachers have been found in most studies (Russell et al., 1987; Byrne, 1991; Lau et al.,
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2005; Grayson & Alvarez, 2008; Stoeber & Rennert, 2008; Droogenbroeck et al., 2014). The gender differences reported in our study might be explicable by the theses offered by
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Woodside et al. (2008) and Borthwick, Thornell, & Wilkinson, (1982), that extra societal gender roles such as excessive family-level responsibilities overburden females to be
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emotionally drained (Woodside et al., 2008), whilst men are expected to contain their emotions leading to alienation (Barbara M. Byrne, 1991; Lau et al., 2005b; Woodside et al.,
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(Woodside et al., 2008).
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2008), is distinctively gender roles socialization issues which is contextually defined
Altogether, our study results support the cross-cultural factorial validity of a shortened
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16-item MBI-ES, and its use plausible for cross-cultural teacher burnout evaluation. This possible cross-cultural evidence allows for discovery and understanding of key cross-country differences and similarities that may be important for teacher burnout management. Nevertheless, the interpretability of our study’s results should be made within the context of limitations. A number of limitations have been noted, and prominent amongst them is the generalizability of the results. The study samples are from Ghana, China, and Pakistan and by no means generalizable to the rest of Africa and Asia. The low correlations among some
23
ACCEPTED MANUSCRIPT items could relate to the complex nature of the constructs measured; emotional exhaustion, depersonalization and personal accomplishment (Squires et al., 2014). We recommend that futher tests in different African and Asian contexts are necessary. Regardless of these limitations, this study offers practical implications for ECE teacher burnout management.
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Our study’s results patterns indicate that, cross-cultural learning and sharing among preschool teachers through preschool teacher exchanges and continuous collaborations
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among ECE stakeholders can generate unique understanding of the best ways to fight against
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teacher burnout. For instance, Chinese and Ghanaian preschool teachers can adopt some unique and applicable Pakistani practices that make them less emotionally exhaustive,
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whereas higher depersonalization and personal accomplishment in the Pakistani contexts can be managed by looking into applicable practices in the Ghanaian and Chinese contexts. Our
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study has implication for a relook at the gender roles in Ghana, China and Pakistan that serve to facilitate and/ or deepen emotional exhaustion gap between men and women and that of
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depersonalization and personal accomplishment.
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On policy, the findings of our study can shape policy discussions and formulation in creating harmonious educational environment through close study of the differences in the
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three cultural settings and promote positive cultural learning and adaptions of relevant, and applicable ECE practices in other cultures. These investigations have become necessary in the light of the findings relating to differences in teacher burnout experience in different countries. Our findings also add to existing literature on the theoretical development and cross-cultural assessment of the teacher burnout with the MBI-ES. The results provoke discussions on pressing matters, including why emotional exhaustion is higher among Ghanaian and Chinese pre-school teachers than among the Pakistani preschool teachers in order to come up with sound explanation for these differences and ways to address them.
24
ACCEPTED MANUSCRIPT Reference Affrunti, N. W., Mehta, T., Rusch, D., & Frazier, S. (2018). Job demands, resources, and stress among staff in after school programs: Neighborhood characteristics influence associations in the job demands-resources model. Children and Youth Services Review,
PT
88, 366–374. https://doi.org/10.1016/j.childyouth.2018.03.031 Aiken, L. S., Stein, J. A., & Bentler, P. M. (1994). Structural equation analyses of clinical
RI
subpopulation differences and comparative treatment outcomes: Characterizing the daily
SC
lives of drug addicts,. Journal of Consulting and Clinical Psychology, 62, 488–499.
332. https://doi.org/10.1007/BF02294359
NU
AKAIKE, H. (1987). FACTOR ANALYSIS AND AIC. PSYCHOMETRIKA, 52(3), 317–
MA
Allison, P. D. (2003). Missing Data Techniques for Structural Equation Modeling. Journal of
ED
Abnormal Psychology, 112(4), 545–557. https://doi.org/10.1037/0021-843X.112.4.545 Aluja, A., Blanch, A., & Garcia, L. F. (2005). Dimensionality of the Maslach Burnout
EP T
Inventory in School Teachers : A Study of Several Proposals . European Journal of Psychological Assessment, (January). https://doi.org/10.1027/1015-5759.21.1.67
AC C
Antonopoulou, P., Killian, M., & Forrester, D. (2017). Levels of stress and anxiety in child and family social work: Workers’ perceptions of organizational structure, professional support and workplace opportunities in Children’s Services in the UK. Children and Youth Services Review. https://doi.org/10.1016/j.childyouth.2017.02.028 Arbuckle, J. L. (2017). Amos 25 User’s Guide. SPSS IBM. Arlot, S., & Celisse, A. (2010). A survey of cross-validation procedures for model selection. Statistics Surveys, 4, 40–79. https://doi.org/10.1214/09-SS054 Bentler, P. (1990). Comparative fit indices in structural models. Psychological Bulletin, 25
ACCEPTED MANUSCRIPT 107(2), 238–246. https://doi.org/0.1037/0033-2909.107.2.238 Bentler, P. M., & Bonett, D. G. (1980). Significance tests and goodness of fit in the analysis of covariance structures. Psychological Bulletin, 88(3), 588–606. https://doi.org/10.1037/0033-2909.88.3.588
PT
Boles, J. S., Dean, D. H., Ricks, J. M., Short, J. C., & Wang, G. (2000). The Dimensionality of the Maslach Burnout Inventory across Small Business Owners and Educators.
RI
Journal of Vocational Behavior, 56(1), 12–34. https://doi.org/10.1006/jvbe.1999.1689
SC
Borthwick, P., Thornell, J., & F. Wilkinson. (1982). Teacher burnout: A study of professional
NU
and personal variables. In Proceedings of the Annual Meeting of the American Association for Teacher Education. Houston, TX.
MA
Bronfenbrenner, U., & Morris, P. (1998). The ecology of de velopmental processes. In R. M. Lerner (Ed.), Handbook of child psychology: Vol. 1. Theoretical models of human devel-
ED
opment (pp. 993–1028). New York: Wiley. Brooks-Gunn, J., Berlin, L. J., Leve.
EP T
Brookings, J. B., Bolton, B., Brown, C. E., & McEvoy, A. (1985). Self-Reported Job Burnout Among Female Human Service Professionals. Journal of Occupational Behaviour, 6(2),
AC C
143–150.
Bryk, A. S., & Raudenbush, S. W. (1992). Hierarchical linear models in social and behavioral research: Applications and data analysis methods. Newbury Park, CA: Sage. Buys.
Byrne, B. M. (1991). Burnout: Investigating the impact of background variables for elementary, intermediate, secondary, and university educators. Teaching and Teacher Education, 7(2), 197–209. https://doi.org/10.1016/0742-051X(91)90027-M Byrne, B. M. (1993). The Maslach burnout inventory:Testing for factorial validity and 26
ACCEPTED MANUSCRIPT invariance across elementary, intermediate and secondary teachers. Journal of Occupational and Organizational Psychology, 66, 197–212. Byrne, B. M. (1994). Testing for the Factorial Validity, Replication, and Invariance of a Measuring Instrument: A Paradigmatic Application Based on the Maslach Burnout
PT
Inventory. Multivariate Behavioral Research, 29(3), 263288. https://doi.org/10.1207/s15327906mbr2903
RI
Byrne, M. B., Shavelson, R. J., & Muthen, B. O. (1989). Testing for the equivalence of factor
SC
covariance and mean structures: The issue of partial measurement invariance.
NU
Psychological Bulletin, 105, 456–466.
Chen, F. F. (2007). Sensitivity of goodness of fit indexes to lack of measurement invariance.
MA
Structural Equation Modeling, 14(3), 464–504. https://doi.org/10.1080/10705510701301834
ED
Cheung, G. W., & Rensvold, R. B. (2002). Evaluating Goodness-of- Fit Indexes for Testing
EP T
Measurement Invariance. Structural Equation Modeling: A Multidisciplinary Journal, 9(2), 233–255. https://doi.org/10.1207/S15328007SEM0902
AC C
Cochran, W. G. (1952). Test of Goodness of Fit. The Annals of Mathematical Statistics, 23(3), 315–345. https://doi.org/10.1214/aoms/1177729380 Costello, A. B., & Osborne, J. W. (2005). Best Practices in Exploratory Factor Analysis : Four Recommendations for Getting the Most From Your Analysis. Practical Assessment, Research & Evaluation, 10(7). Retrieved from http://pareonline.net/getvn.asp?v=10&n=7 Craparo, G., Faraci, P., & Gori, A. (2015). Psychometric properties of the 20-item toronto alexithymia scale in a group of Italian younger adolescents. Psychiatry Investigation,
27
ACCEPTED MANUSCRIPT 12(4), 500–507. https://doi.org/10.4306/pi.2015.12.4.500 Cunningham, W. G. (1983). Teacher burnout - solutions for the 1980’s: A review of the literature. The Urban Review, 15(1), 37–51. Curran, P. J., West, S. G., & Finch, J. F. (1996). The Robustness of Test Statistics to
PT
Nonnormality and Specification Error in Confirmatory Factor Analysis. Psychological
RI
Methods, 1(1), 16–29. https://doi.org/10.1037/1082-989X.1.1.16
Densten, I. L. (2001). Re-Thinking Burnout. Journal of Organizational Behavior, 22(8), 833–
SC
847. https://doi.org/10.1002/job.
NU
Denton, E. ge, Chaplin, W. F., & Wall, M. (2013). Teacher burnout: a comparison of two cultures using confirmatory factor and item response models. International Journal of
MA
Quantitative Research in Education, 1(2), 147.
ED
https://doi.org/10.1504/IJQRE.2013.056463
Dimitrov, D. M. (2006). Comparing groups on latent variables: A structural equation
EP T
modeling approach. Work, 26(2006), 429–436. Droogenbroeck, F. Van, Spruyt, B., & Vanroelen, C. (2014). Burnout among senior teachers :
AC C
Investigating the role of workload and interpersonal relationships at work. Teaching and Teacher Education, 43, 99–109. https://doi.org/10.1016/j.tate.2014.07.005 Field, A. (2005). Discovering Statistics Using IBM SPSS Statistics. 2nd Edition. London: Sage Publications. Firth, H., McIntee, J., McKweown, P., & Britton, P. G. (1985). Maslach Burnout Inventory: Factor Structure and Norms for British Nursing Staff. Psychological Reports, 57, 147– 150. Floyd, F. J., & Widaman, K. F. (1995). Factor Analysis in the Development and Refinement 28
ACCEPTED MANUSCRIPT of Clinical Assessment Instruments. Psychological Assessment, 7(3), 286–299. https://doi.org/10.1037/1040-3590.7.3.286 Fornell, & Larcker. (1981). structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 48(1), 39–50.
PT
Freire, C., Ferradás, M. del M., Núñez, J. C., & Valle, A. (2017). Estructura factorial de las
https://doi.org/10.1016/j.ejeps.2016.10.001
SC
Journal of Education and Psychology, (10), 1–8.
RI
Escalas de Bienestar Psicológico de Ryff en estudiantes universitarios. European
NU
Freudenberger, H. J. (1974). Staff Burn-Out. Journal of Social Issues, 30(1), 159–165. https://doi.org/10.1111/j.1540-4560.1974.tb00706.x
MA
from the SAGE Social Science Collections . All Rights Reserved . (n.d.).
ED
Frone, M. R., Russell, M., & Barnes, G. M. (1996). Work--family conflict, gender, and health-related outcomes: A study of employed parents in two community samples.
8998.1.1.57
EP T
Journal of Occupational Health Psychology, 1(1), 57–69. https://doi.org/10.1037/1076-
AC C
Galanakis, M., Moraitou, M., Garivaldis, F. J., & Stalikas, A. (2009). Factorial Structure and Psychometric Properties of the Maslach Burnout Inventory (MBI) in Greek Midwives. Europe’s Journal of Psychology, 5(4), 52–70. https://doi.org/10.5964/ejop.v5i4.240 Golembiewski, R. T., Munzenrider, R., & Carter, D. (1983). Phases of progressive burnout and their work site covariants: Critical issues in OD researcg and Praxis. The Journal of Applied Behavioral Science, 19(4), 461–481. Grayson, Ã. J. L., & Alvarez, H. K. (2008). School climate factors relating to teacher burnout : A mediator model. Teacher and Teaching Education, 24, 1349–1363. 29
ACCEPTED MANUSCRIPT https://doi.org/10.1016/j.tate.2007.06.005 Griffiths, A., Royse, D., & Walker, R. (2018). Stress among child protective service workers: Self-reported health consequences. Children and Youth Services Review, 90(May), 46– 53. https://doi.org/10.1016/j.childyouth.2018.05.011
RI
7th. ed. Prentice-Hall, Inc., Upper Saddle River, NJ, USA.
PT
Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2010). Multivariate Data Analysis,
Hancock, G. R. (1997). Structural equation modeling methods of hypothesis testing of latent
SC
variable means. Measurement and Evaluation in Counseling and Development, 30, 91–
NU
105.
Hawrot, A., & Koniewski, M. (2017). Factor Structure of the Maslach Burnout Inventory –
MA
Educators Survey in a Polish-Speaking Sample. Journal of Career Assessment, 1–16.
ED
https://doi.org/10.1177/1069072717714545
Hernández, T. J., & Sánchez, G. (2012). Prevalence of Burnout Syndrome in Employees,
EP T
(1996), 207–225.
Heydari, S., & Abbasian, G.-R. (2016). The relationship between Iranian EFL teachers’
AC C
professional development and their job burnout 1. Basic Research Journal of Education Research and Review Basic Research Journal of Education Research and Review ISSN, 4(2), 2315–6872.
Horn, J. E., Schaufeli, W. B., Greenglass, E. R., & Burke, R. J. (1997). A CANADIANDUTCH COMPARISON OF TEACHERS’ BURNOUT. Psychological Reports, 81, 371–382. Horn, J. L. (1965). FACTORS IN FACTOR ANALYSIS. PSYCHOMETRIKA, 30(2), 179– 185. 30
ACCEPTED MANUSCRIPT Hu, L. T., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis : Conventional criteria versus new alternatives Cutoff Criteria for Fit Indexes in Covariance Structure Analysis : Conventional Criteria Versus New Alternatives. A Multidisciplinary Journal, 6(1), 1–55. https://doi.org/10.1080/10705519909540118
PT
Iwanicki, E. F., & Schwab, R. L. (1981). A Cross Validation Study of the Maslach Burnout Inventory. Educational and Psychological Measurement, 41.
RI
https://doi.org/10.1177/001316448104100425
SC
Jackson, D. L., Gillaspy, J. A., & Purc-Stephenson, R. (2009). Reporting Practices in Confirmatory Factor Analysis: An Overview and Some Recommendations.
NU
Psychological Methods, 14(1), 6–23. https://doi.org/10.1037/a0014694
MA
Kanste, O., Miettunen, J., & Kyngäs, H. (2006). Factor structure of the Maslach Burnout Inventory among Finnish nursing staff. Nursing and Health Sciences, 8(4), 201–207.
ED
https://doi.org/10.1111/j.1442-2018.2006.00283.x
EP T
Kaur, A., & Noman, M. (2015). Exploring Classroom Practices in Collectivist Cultures Through the Lens of Hofstede ’ s Model Exploring Classroom Practices in Collectivist
AC C
Cultures Through the Lens. The Qualitative Report, 20(11), 1794–1811. Koki, S. (2000). Prevention and Intervention for Effective Classroom Organization and Management in Pacific Classrooms, (808), 1–12. Kokkinos, C. M. (2006). Factor structure and psychometric properties of the Maslach Burnout Inventory-Educators Survey among elementary and secondary school teachers in Cyprus. Stress and Health, 22(1), 25–33. https://doi.org/10.1002/smi.1079 KotovA, M. B., Rozanov, K. B., Alexandrov, A. A., & Ivanovo, E. I. (2017). Professional burnout and quality of life in teachers. Voprosy Psikhologii, 2017–Janua(2), 67–79.
31
ACCEPTED MANUSCRIPT Kristensen, T. S., Borritz, M., Villadsen, E., & Christensen, B. (2005). The Copenhagen Burnout Inventory : A new tool for the assessment of burnout The Copenhagen Burnout Inventory : A new tool for the. Work & Stress: An International Journal of Work, Health & Organisations, 19(3), 192–207. https://doi.org/10.1080/02678370500297720
PT
Lau, P. S. Y., Yuen, M. A. N. T. A. K., & Chan, R. M. C. (2005a). Do demographic characteristics make a difference to burnout among hong kong secondary school
RI
teachers? Social Indicators Research, (71), 491–516. https://doi.org/10.1007/s11205-
SC
004-8033-z
Lau, P. S. Y., Yuen, M. A. N. T. A. K., & Chan, R. M. C. (2005b). Do demographic
NU
characteristics make a difference to burnout among hong kong secondary school
MA
teachers?, 491–516. https://doi.org/10.1007/s11205-004-8033-z Lauermann, F., & König, J. (2016). Teachers’ professional competence and wellbeing:
ED
Understanding the links between general pedagogical knowledge, self-efficacy and burnout. Learning and Instruction, 45, 9–19.
EP T
https://doi.org/10.1016/j.learninstruc.2016.06.006 Lizano, E. L., & Mor Barak, M. (2015). Job burnout and affective wellbeing: A longitudinal
AC C
study of burnout and job satisfaction among public child welfare workers. Children and Youth Services Review, 55, 18–28. https://doi.org/10.1016/j.childyouth.2015.05.005 Maccallum, R. C., Browne, M. W., & Sugawara, H. M. (1996). Power Analysis and Determination of Sample Size for Covariance Structure Modeling of fit involving a particular measure of model. Psychological Methods, 1(2), 130–149. Maslach, C. (2015). Burnout , Psychology of. International Encyclopedia of Social & Behavioral Sciences (Second Edi, Vol. 2). Elsevier. https://doi.org/10.1016/B978-0-08097086-8.26009-1 32
ACCEPTED MANUSCRIPT Maslach, C., & Jackson, S. E. (1981a). Maslach Burnout Inventory--ES Form. PsycTESTS. https://doi.org/10.1037/t05190-000 Maslach, C., & Jackson, S. E. (1981b). The measurement of experienced burnout. JOURNAL OF OCCUPATIONAL BEHAVIOUR, 2, 99–113.
Evaluating Stress: A Book of Resources (pp. 191–218).
RI
https://doi.org/10.1017/S0033291798257163
PT
Maslach, C., Jackson, S. E., & Leiter, M. P. (1997). Maslach Burnout Inventory. In
SC
Maslach, C., Schaufeli, W. B., & Leiter, M. P. (2001). Job burnout. Annual Review of
NU
Psychology, 52, 397–422.
McGeary, C. A., & McGeary, D. D. (2012). Occupational Burnout. In R. J. Gatchel & I. Z.
MA
Schultz (Eds.), Handbook of Occupational Health and Wellness (pp. 3–563).
ED
https://doi.org/10.1007/978-1-4614-4839-6
Medvedskaya, E. I., & Sheryagina, E. V. (2017). Empathy and professional burnout of
EP T
Russian and Belarusian teachers. Konsul’tativnaia Psikhologiia I Psikhoterapiia, 25(2), 59–74. https://doi.org/http://dx.doi.org/10.17759/cpp.2017250204
AC C
Mellenbergh, J. (1983). ITEM BIAS AND ITEM RESPONSE. International Journal of Educational Research, 13(2), 127–143. https://doi.org/https://doi.org/10.1016/08830355(89)90002-5
Meredith, W. (1993). MEASUREMENT INVARIANCE, FACTOR ANALYSIS AND FACTORIAL INVARIANCE. PSYCHOMETRIKA, 58(4), 525–543. https://doi.org/10.1007/BF02294825 Meredith, W., & Teresi, J. A. (2006). An essay on measurement and factorial invariance. Medical Care, 44(11), S69–S77. https://doi.org/10.1097/01.mlr.0000245438.73837.89 33
ACCEPTED MANUSCRIPT Mészáros, V., Ádám, S., Szabõ, M., Szigeti, R., & Urbán, R. (2013). The bifactor model of the maslach burnout inventory-human services survey (MBI-HSS) - An alternative measurement model of burnout. Stress and Health, 30(1), 82–88. https://doi.org/10.1002/smi.2481
PT
Mueller, R. O., & Hancock, G. R. (2008). Best practices in structural equation modeling. Best Practices in Quantitative Methods, 488–508. https://doi.org/10.4135/9781412995627
RI
Oh, S. H., & Lee, M. (2009). Examining the psychometric properties of the Maslach Burnout
Youth Services Review, 31(2), 206–210.
NU
https://doi.org/10.1016/j.childyouth.2008.07.012
SC
Inventory with a sample of child protective service workers in Korea. Children and
MA
Palmira Faraci. (2018). TESTING FOR THE DIMENSIONALITY OF THE MASLACH BURNOUT INVENTORY (MBI) ON A SAMPLE OF HIGH SCHOOL TEACHERS.
ED
Clinical Neuropsychiatry, 15(1), 50–59.
EP T
Pérez-Mármol, J. M., & Brown, T. (2018). An Examination of the Structural Validity of the Maslach Burnout Inventory-Student Survey (MBI-SS) Using the Rasch Measurement
AC C
Model. Health Professions Education. https://doi.org/10.1016/j.hpe.2018.05.004 Perrewé, P. L., Hochwarter, W. A., Rossi, A. M., Wallace, A., Maignan, I., Castro, S. L., Van Deusen, C. A. (2002). Are work stress relationships universal? A nine-region examination of role stressors, general self-efficacy, and burnout. Journal of International Management, 8(4), 423. https://doi.org/10.1016/S1075-4253(02)00107-2 Pienaar, J., & Wyk, D. Van. (2006). Teacher burnout : construct equivalence and the role of union membership. South African Journal of Education, 26(4), 541–551. Pines, A. M. (2002a). Teacher Burnout : A psychodynamic existential perspective. Teachers
34
ACCEPTED MANUSCRIPT and Teaching: Theory and Practice, 8(2), 37–41. https://doi.org/10.1080/13540600220127331 Pines, A. M. (2002b). Theory and Practice Teacher Burnout : A psychodynamic existential perspective. Teachers and Teaching: Theory and Practice, 8(2), 37–41.
PT
https://doi.org/10.1080/13540600220127331 Poghosyan, L., Aiken, L. H., & Sloane, D. M. (2009). Factor structure of the Maslach
RI
burnout inventory: An analysis of data from large scale cross-sectional surveys of nurses
NU
https://doi.org/10.1016/j.ijnurstu.2009.03.004
SC
from eight countries. International Journal of Nursing Studies, 46(7), 894–902.
Reise, S. P., Widaman, K. F., & Pugh, R. H. (1993). Confirmatory factor analysis and item
MA
response theory: two approaches for exploring measurement invariance. Psychological Bulletin, 114(3), 552–566. https://doi.org/10.1037/0033-2909.114.3.552
ED
Richardsen, A. M., & Martinussen, M. (2004). The Maslach Burnout Inventory : Factorial
EP T
validity and consistency across occupational groups in Norway. Journal of Occupational and Organizational Psychology, (77), 377–384.
AC C
https://doi.org/0.1348/0963179041752691 Rizzo, J. R., House, R. J., & Lirtzman, S. I. (1970). Role Conflict and Ambiguity in Complex Organizations. Administrative Science Quarterly, 15(2), 150–163. Russell, D. W., Altmaier, E., & Vanvelzen, D. (1987). Job-related stress, social support, and burnout among classroom teachers. Journal of Applied Psychology, 72(2), 269–274. Salloum, A., Kondrat, D. C., Johnco, C., & Olson, K. R. (2015). The role of self-care on compassion satisfaction, burnout and secondary trauma among child welfare workers. Children and Youth Services Review, 49, 54–61.
35
ACCEPTED MANUSCRIPT https://doi.org/10.1016/j.childyouth.2014.12.023 Salmela-Aro, K., & Read, S. (2017). Study engagement and burnout profiles among Finnish higher education students. Burnout Research, 7, 21–28. https://doi.org/10.1016/j.burn.2017.11.001
RI
Study. Australian Journal of Education, 34(2), 145–152.
PT
Sarros, A. M., & Sarros, J. (1990). How Burned out are our Teachers ? A Cross-cultural
SC
``, J. C. (1990). How Burned out are our Teachers ? A Cross-cultural Study, 34(2), 145–152. Sass, D. A. (2011). Testing measurement invariance and comparing latent factor means
NU
within a confirmatory factor analysis framework. Journal of Psychoeducational
MA
Assessment, 29(4), 347–363. https://doi.org/10.1177/0734282911406661 Schaufeli, W. B. (2017). Applying the Job Demands-Resources model: A “how to” guide to
ED
measuring and tackling work engagement and burnout. Organizational Dynamics, 46(2), 120–132. https://doi.org/10.1016/j.orgdyn.2017.04.008
EP T
Schaufeli, W. B., Daamen, J., & Mierlo, H. Van. (1994). Burnout among Dutch teachers: An MBI-Validity study. Educational and Psychological Measurement, 54(3), 803–812.
AC C
https://doi.org/10.1177/0013164494054003027 Schaufeli, W. B., & Van Dierendonck, D. (1993). The construct validity of two emotional exhaustion measures. J Ournal of Organizational Behavior, 14(February 1991), 631– 647. https://doi.org/10.1002/job.4030140703 Schimmenti, A. (2016). Psychometric properties of the Adolescent Dissociative Experiences Scale in a sample of Italian adolescents. Journal of Trauma and Dissociation, 17(2), 244–257. https://doi.org/10.1080/15299732.2015.1064507 Schutte, N., Toppinen, S., Kalimo, R., & Schaufeli, W. B. (2000). The factorial validity of the 36
ACCEPTED MANUSCRIPT Maslach Burnout Inventory - General Survey (MBI-GS) across occupational groups and nations. Schwarzer, R., Schmitz, G. S., & Tang, C. (2000). Teacher Burnout in Hong Kong and Germany: A Cross-Cultural Validation of the Maslach Burnout Inventory. Anxiety,
PT
Stress & Coping, 13(3), 309–326. https://doi.org/10.1080/10615800008549268 Siegrist, J., Starke, D., Chandola, T., Godin, I., Marmot, M., Niedhammer, I., & Peter, R.
RI
(2004). The measurement of effort-reward imbalance at work: European comparisons.
SC
Social Science and Medicine, 58(8), 1483–1499. https://doi.org/10.1016/S0277-
NU
9536(03)00351-4
Squires, A., Finlayson, C., Gerchow, L., Cimiotti, J. P., Matthews, A., Schwendimann, R., …
MA
Sermeus, W. (2014). Methodological considerations when translating "burnout" Burnout Research, 1(2), 59–68.
ED
https://doi.org/10.1016/j.burn.2014.07.001
EP T
Stoeber, J., & Rennert, D. (2008). Perfectionism in school teachers : Relations with stress appraisals , coping styles, and burnout. Anxiety, Stress & Coping: An International
AC C
Journal, 21(1), 37–53. https://doi.org/10.1080/10615800701742461 Suñer-Soler, R., Grau-Martín, A., Flichtentrei, D., Prats, M., Braga, F., Font-Mayolas, S., & Gras, M. E. (2014). The consequences of burnout syndrome among healthcare professionals in Spain and Spanish speaking Latin American countries. Burnout Research, 1(2), 82–89. https://doi.org/10.1016/j.burn.2014.07.004 Tabachnick, B. G., & Fidell, L. S. (2007). Using Multivariate Statistics, (5th ed.). Needham Heights, MA: Allyn and Bacon Publishers. Needham Heights, MA: Allyn and Bacon Publishers.
37
ACCEPTED MANUSCRIPT Unesco. (2015). Education for all 2015 National Review. Unesco, 1–67. UNESCO. (2008). Countries on the Move. UNESCO Education for All GlobalMonotoring Report. Retrieved from: http://www.unesco.org/education/gmr2008/press/chapter3.pdf. Valente, M. do S. da S., Wang, Y. P., & Menezes, P. R. (2018). Structural validity of the
PT
Maslach Burnout Inventory and influence of depressive symptoms in banking workplace: Unfastening the occupational conundrum. Psychiatry Research, 267(March),
RI
168–174. https://doi.org/10.1016/j.psychres.2018.05.069
SC
Vandenberg, R. J., & Lance, C. E. (2000). A Review and Synthesis of the Measurement
NU
Invariance Literature: Suggestions, Practices, and Recommendations for Organizational Research. Organizational Research Methods, 3(1), 4–70.
MA
https://doi.org/10.1177/109442810031002
Veldhoven, M., & Meijman, T. (1994). Het meten van psychosociale arbeidsbelasting met
ED
een vragenlijst: de vragenlijst beleving en beoordeling van de arbeid (VBBA).
EP T
Measuring psychosocial workload with a survey: the questionnaire on the experience and evaluation of work (QEEW). Amsterdam: NIA.
AC C
Walkey, F. H., & Green, D. E. (1992). An Exhaustive Examination of the Replicable Factor Structure of the Maslach Burnout Inventory. Educational and Psychological Measurement, 52.
Woodside, J. R., Miller, M. N., Floyd, M. R., McGowen, K. R., & Pfortmiller, D. T. (2008). Observations on burnout in family medicine and psychiatry residents. Academic Psychiatry, 32(1), 13–19. https://doi.org/10.1176/appi.ap.32.1.13 Worley, J. A., Vassar, M., Wheeler, D. L., & Barnes, L. L. B. (2008). Factor Structure of Scores From the Maslach Burnout Inventory. Educational and Psychological
38
ACCEPTED MANUSCRIPT Measurement, 68(5), 797–823. https://doi.org/10.1177/0013164408315268 Xanthopoulou, D., Bakker, A. B., Kantas, A., & Demerouti, E. (2012). Measuring burnout and work engagement: Factor structure, invariance, and latent mean differences across Greece and the Netherlands. International Journal of Business Science and Applied
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SC
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Management, 7(2), 40–52. https://doi.org/10.1080/09585192.2012.751438
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ACCEPTED MANUSCRIPT Acknowledgement This study was funded by the Zhejiang Normal University (Graduate School PhD candidates’ sponsorship). We further extend our sincere thank you, to prof. Fan Chong Jun, Business School, the University of Shanghai for Science & Technology (USST) and prof. Yun-Fei Shao, University of Electronic Science and Technology of China for their statistical support and tutelage in the conduct of this study.
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Declaration of Conflicting Interests The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
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ACCEPTED MANUSCRIPT Highlights
Explored the factorial validity of the MBI-ES and burnout differences across three cultural contexts and gender. The MBI-ES fitted the three cultures after item-level modifications were made.
Significant differences in teacher burnout across countries and gender were found.
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ACCEPTED MANUSCRIPT Table 1: Sample demographics and work characteristics, stratified by country (N=869) Descriptive statistics: China(n=274)
Participants’ demographics & work characteristics
Frequency (%)
Demographic Profile of ECTs Gender M ale Female Age category <30 years 30 to 39 40
Descriptive statistics: Ghana(n=285) Frequency (%)
M ean±SD
101(%)
93(%) 181(%) 33.1 ±7.59
34.45±10.03
34(12%) 81(28%) 93(33%) 77(27%)
55(17.7%) 23(7.4%) 206(66.5%) 26(8.4%)
145(51%) 129(45%) 9(3%) 2(1%)
188(60.6%) 116(37.4%) 5(1.6%) 1(0.3%)
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250(81%) 52(17%) 7(2%) 0(0%)
8.7±6.84
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149(48%) 106(34%) 54(18%) 259(84%) 50(16%)
10.62±8.52
8.07±6.30
132(46%) 70(25%) 83(29%)
165(53.2%) 88(28.4%) 57(18.4%)
141(49.5%) 144(50.5%)
154(49.7%) 156(50.3%) 32.96±6.20
32.30±8.3
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33.33±8.40 29(10%) 58(21%) 92(32%) 106(37%)
17(5.5%) 23(7.4%) 115(37.1%) 155(50%)
2(1%) 95(31%) 212(68%)
51(18%) 192(67%) 42(15%)
40(12.9%) 259(83.5%) 11(3.5%)
3(1%) 21(7%) 157(51%) 128(41%)
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2.24±1.18
2.74±.99
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78(25%) 55(18%) 174(56%) 2(1%)
31.82±6.6
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1.94±.67
M ean±SD
140(45.2%) 122(39.4%) 48(15.5%)
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112(39%) 75(26%) 98(35%)
Educational level
Frequency (%)
97(%) 213(%)
184(%)
109(35%) 120(39%) 80(26%)
Junior High School High/Technical School College/Undergraduate/Diploma M asters + M arital Status M arried Single, Never M arried Single, Divorced Single, Widow (er) ECTs Work-related Characteristics Work experience 6 years or below 7 to 15 years >15 years School Type Public Private Class Size 15 16 to 25 26 to 35 >35 Job Task Child Caring Child Teaching Caring & Teaching Work hours/day 5 hours/day >5 hours/day Notes: ECTs= early childhood education range 18 to 59 (M age =33.27, SD=10.03)
M ean±SD
Descriptive statistics: Pakistan(n=310)
8.65±1.13 6.21±1.01 3(1%) 0(0%) 13(4.2%) 306(99%) 285(100) 297(95.8%) teachers. The final data comprised of male (n=291) and female (n=578) with age
6.28±2.27
Table 2: Fit of the original 22-item MBI-ES factor model across cultures: result of confirmatory factor analysis
Models M1 . 3-Factor proposed M2 . 2-Factor alternative M3 . 1-Factor alternative
χ2 [df] 1601.62[206] 1922.04[208] 2417.86[209]
X/df 7.78 9.24 11.57
CFI/TLI .67/.63 .60/.56 .48/.43
RMSEA .08 .09 .11
SRMR .09 .10 .11
Comparison M1 - M2 M1 - M3
Note: df= degree of freedom; TLI= Tucker Lewise Index; CFI= comparative fit index; RM SE= root mean squar approximation; SRM R=standardized root mean square residuals; AIC= Akaike’s information criterion. ***p<.001
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Dχ2[Dd
320.41[ 816.23
ACCEPTED MANUSCRIPT Table 3: Descriptive statistics, CFA factor loadings, validity and reliability of the original 22-item and reduced 16-item MBI-ES Overall item statistics Skewness Kurtosis MeanSD 3.382.02
.41 -.02 .12 .91 .39 .97 -.48 1.26 1.25
4.342.06 3.842.23
-1.11 -.56 -1.44 -.48 -1.17 -.26 .06 .66 .46
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2.731.96 3.442.04 2.711.93 5.082.14 2.421.74 2.381.83 5.911.54
-1.53 -1.17 -.55 -.45 -1.82 -.71 -.81 -.63
1.58 .17 -1.19 -1.05 2.55 -.99 -.38 -.87
2.16 2.01 1.60 2.65 1.39
5.53 3.95 1.51 6.32 1.24
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5.691.75 4.912.18 4.721.99
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6.091.50 4.942.22 5.351.69 5.071.88 2.953.35
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1. Emotional Exhaustion MBI 1. I feel used up MBI 2. Emotionally drained MBI 3. I’m working too hard MBI 6. frustrated MBI 8. Fatigued when I get up MBI 13. burned out MBI 14. Working with people MBI 16. At the end of my rope MBI 20. People puts too much stress on me Personal Accomplishment MBI 4. I feel exhilarated MBI 7. I feel energetic MBI 9. I deal with emotional problems MBI 12. I can understand my students MBI 17. I have accomplished many things MBI 18. I deal effectively with problems MBI 19. I’ m positively influencing MBI 21. I can create atmosphere 3. Depersonalization MBI 5. students blame me ♦ MBI 10. More callous towards people♦ MBI 11. Job is hardening me MBI 15. I don’ t really care ♦ MBI 22. Some students were impersonal object
1.911.59 2.051.64
Standardized CFA Load 22-Item MBI-ES 16-i .85 a .77(.60) .73 .72(.52) .71 .74(.55) .78 .58(.33) .60 .67(.45) .66 .21(.04) __ .04(.00) __ .36(.13) __ .45(.21) __ .71 a .51(.26) .45 .61(.37) .54 .59(.34) .65 .39(.15) .35 .49(.24) .64 -.11(.01) __ .41(.17) .38 .41(.17) .40 .77 a .17(.03) __ .75(.56) .74 .57(.33) .59 .49(.24) .49 .35(.12) .34
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Items: shortened items
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1.611.44 2.271.39 Note: CFA Standardized estimates and squared multiple correlations (R2) were recorded from the three-factor M BI-ES model in the cross-cultural sample. Items: 5, 13, 14, 16, 18, & 20 are excluded in the reduced M BI-ES due to low loadings and cross loadings. a= Cronbach’s alpha estimates for internal consistency ; b= square roots of average variance explained for discriminant validity; CR= Composite reliability, AVE= average variance explained, M SV= maximum shared variance; ♦Items with violations of normality (Log10 transformed). Item loadings are significant at ***p<.001 and **p<.01.
ms abbreviated
ional Exhaustion S 1 S 2 S 3 S 6 S 8 S 13 S 14 S 16 S 20 nalAccomplishment S 4 S 7 S 9 S 12
AC C
Table 4: Country-level and Cross-cultural exploration of the MBI-ES factor structure: Results of exploratory factor analyses (EFA) Factor Loadings
1 .82 .80 .85 .63 .70 .31 .31 .38 .41
-.20 -.21
GHANA
2
3
.15
.12 .12
.56
.60 .71 .68 .36
.24 .32 .65 -.10 .64 .49
Factor Loadings
1
2
.81 .84 .82 .59 .70 .35 .26 .32 .58
.21 .16 .12
.19 .14
.52 .52 .48 .55
.25 -.24
.54 -.16
CHINA
3
.28 .24 .61 -.21 .57 .41
.21
43
Factors Loadings
1 .74 .73 .65 .34 .68 .38 .28 .30 .26
-.15 -.17
2
-.13 -.10
-.19
.61 .50 .67 .52
P AKISTAN
Factor Loadings CROSS
3
1
.21
.80 .77 .82 .54 .63 .32 .30 .35 .33
.27 .57 .29 .38 .52 .55 .52
-.21 -.22 -.24
2 .10
.11
.60 .65 .64 .44
3 .16 .11 .11 .28 .27 .59 .61 .65 .55
.19
-CULTU
ACCEPTED MANUSCRIPT
S 17 S 18 S 19 S 21 rsonalization S 5 S 10 S 11 S 15 S 22
.39 -.14
.42
.57 .10 .47 .36
-.18 -.42 -.24 -.19
-.31 -.21 -.10 -.20 -.12
-.24 .51 .62 .43 .40
.14
.52 .67 .72 .60 .28
.14 -.15 .12
-.10
.18 -.24
-.14 .25 .74 .66 .54 .50
.17 .14
.52 .15 .45 .45
-.35 .27
.60 .48 .50 .48
.48 .73 .62 .69 .55
-.12
.30 -.10 -.19 -.14
-.22 -.31 -.18 -.13 -.25 .63 .68 .56 .44
SC
RI
PT
Note: M BI-ES= M aslach Burnout Inventory, Educators Survey; substantial loadings rounded .40 are bolded, crossloadings rounded30 are italicized. h2= item communalities (recorded from the cross-cultural sample).
Table 5: Fit of the reduced 16-item MBI-ES factor model: result of confirmatory factor analysis (χ2 [df])
CFI/TLI
NU
X/df
RMSEA SRMR
Comparison
(∆χ2 [df])
2.53 4.35 5.72
.91/.90 .79/.73 .70/.62
.06 .09 .10
.06 .09 M1a-M2a .11 M1a-M3a
176.37[2]** 310.89[3]**
244.02[92] 402.65[94] 635.24[95]
2.65 4.28 6.69
.90/.90 .80/.75 .65/.56
.06 .09 .11
.06 .09 M1b -M2b .11 M1b -M3b
158.63[2]** 391.22[3]**
335.69[92] 660.54[94] 1027.27[95]
3.65 7.03 10.81
.92/90 .81/.76 .69/.61
.06 .08 .11
.05 .09 M1 -M2 .11 M1 -M3
324.85[2]** 691.58[3]**
ED
MA
232.77[92] 409.14[94] 543.66[95]
EP T
Models Calibration sample M1a. 3-Factor proposed M2a. 2-Factor alternative M3a. 1-Factor alternative Validation sample M1b . 3-Factor proposed M2b . 2-Factor alternative M3b . 1-Factor alternative Cross-Validation Whole sample M1 . 3-Factor proposed M2 . 2-Factor alternative M3 . 1-Factor alternative
AC C
Note: df= degree of freedom; TLI= Tucker Lewise Index; CFI= comparative fit index; RM SE= root mean squar approximation; SRM R=standardized root mean square residuals; AIC= Akaike’s information criterion. ***p<.001
Table 6: Validity of the reduced 16-item MBI-ES tested within several structural equation modelling Model
Cross-cultural model Workload Emotional demands Work family conflict Role conflict Total stress
Standardized Regression Coefficients Emotional Exhaustion Depersonalization Personal Accomplishment S.t Est (S.E)/R2 S.t Est (S.E)/R2 S.t Est (S.E)/R2 .18***(.11)/.03 .14***(.07)/.02 .29***(.07))/.09 .15***(.06)/.02 .27***(.03)/.07
.07+(.06)/.004 .07*(.04)/.01 .13***(.04)/.02 .11**(.03)/.01 .14***(.02)/.02
-.01(.08)/00 -.08*(.03)/.02 -.02(.06)/00 -.05(.04)/.002 -.12**(.03)/.06
Model fit RMSEA
.02 .03 .04 .02 .02
Note: St. Est.= Standardized Estimates, S.E=Standard Error, R=Explained variance of the M BI-ES latent factors due to the predictors (work stressors). Each row represent one SEM , Degree of freedom for all model =1, RM SEA= root mean squar approximation; CFI= comparative fit index; TLI = Tucker Lewise Index. + p<.10 *p<.05
44
Statistic
CFI/TLI
.99/.97 .99/.97 .99/.96 .99/.99 .99/.99
ACCEPTED MANUSCRIPT **p<.01 ***p<.001
Table 7: Test of invariance of the reduced 16-item three-factor MBI-ES across cultures; result of MGCFA
χ2 [df]
Models (g: Pk., Cn., Gh.)
CFI
RMSEA
SRMR
Comparison
CFI
.030 .028 .034 .030 .033 .031
.0623 .0628 .0623 .0629 .0634 .0640
M 1a-M 2a M 2a-M 3a M 2a-M 4a M 4a-M 5a M 4a-M 6a
.00 .06 .01 .07 .01
1.76 1.68 2.02 1.79 1.97 1.81
.91 .91 .85 .90 .83 .89
663.40[368] 699.37[407] 888.25[455] 796.97[440] 1061.61[533] 817.84[458]
1.80 1.72 1.95 1.81 1.99 1.79
.91 .91 .86 .90 .83 .89
.030 .029 .033 .031 .034 .030
.0655 .066 .0661 .066 .0656 .0659
M 1b -M 2b M 2b -M 3b M 2b -M 4b M 4b -M 5b M 4b -M 6b
.00 .05 .01 .07 .01
.92 .92 .86 .91 .84 .89
.027 .026 .032 .028 .032 .029
.0585 .0589 .0587 .059 .0591 .0595
M 1 -M 2 M 2 -M 3 M 2 -M 4 M 4 -M 5 M 4 -M 6
.00 .06 .01 .07 .02
RI
SC
NU
830.99[368] 873.46[407] 1263.03[455] 1055.93[440] 1459.17[533] 1110.02[458]
2.26 2.15 2.78 2.40 2.74 2.42
PT
646.35[368] 683.59[407] 917.49[455] 786.01[440] 1049.53[533] 829.79[458]
MA
Calibration sample M 1a. Configural inv. M 2a. Metric inv. M 3a. Scalar inv. M 4a. Partial Scalar inv.a M 5a. Residual inv. M 6a. Structural inv. Cross-validating Validation sample M 1b . Configural inv. M 2b . Metric inv. M 3b . Scalar inv. M 4b . Partial inv.a M 5b . Residual inv. M 6b . Structural inv. Whole sample M 1 . Configural inv. M 2 . Metric inv. M 3 . Scalar inv. M 4 . Partial inv.a M 5 . Residual inv. M 6 . Structural inv.
χ2 /df
-
-
-
AC C
EP T
ED
Note: g = groups involved in the measurement invariance test, Pk.= Pakistan, Cn.=China, Gh.= Ghana, inv.= invariance, TLI= Tucker Lewise Index; CFI= comparative fit index; RM SEA= root mean square approximation; SRM R= standardize root mean square residuals; AIC= Akaike’s information criterion. a. Intercepts of the items “M BI-ES 2, 7, 9, 11, 12” were freely estimated across groups.
Table 8: Test of invariance of the reduced 16-item three-factor MBI-ES across gender; result of MGCFA Models (g: male & female) Calibration sample M 1a. Configural inv. M 2a. Metric inv. M 3a. Strong factorial inv. M 4a. Residual inv. M 5a. Structural inv. Cross-validation Validation sample M 1b . Configural inv. M 2b . Metric inv. M 3b . Strong factorial inv.
χ2 [df]
χ2 /df
CFI
RMSEA
SRMR
Comparison
CFI
RMSEA
568.37[276] 578.82[302] 637.03[334] 688.85[396] 651.85[346]
2.06 1.92 1.91 1.74 1.88
.90 .91 .90 .90 .90
.035 .033 .032 .029 .032
.0623 .0622 .0622 .0623 .0622
M 1a-M 2a M 2a-M 3a M 3a-M 4a M 3a-M 5a
-.01 .01 .00 .00
.0 .0 .0 .0
567.75[276] 604.10[302] 679.55[330]
2.06 2.00 2.04
.91 .90 .90
.035 .034 .035
.0655 .0655 .0657
M 1b -M 2b M 2b -M 3b
.01 .00
.0 -.0
45
ACCEPTED MANUSCRIPT M 4b . Residual inv. M 5b . Structural inv. Whole sample M 1 . Configural inv. M 2 . Metric inv. M 3 . Strong factorial inv. M 4 . Residual inv. M 5 . Structural inv.
755.58[396] 686.68[346]
1.91 1.99
.88 .89
.032 .034
.0655 .0657
M 3b -M 4b M 3b -M 5b
.02 .01
.0 .0
762.59[276] 788.16[302] 911.47[334] 999.29[396] 932.73[346]
2.76 2.61 2.73 2.52 2.69
.92 .92 .91 .90 .90
.032 .030 .032 .030 .031
.0585 .0583 .0584 .0585 .0585
M 1 -M 2 M 2 -M 3 M 3 -M 4 M 3 -M 5
.00 .01 .00 .01
.0 -.0 .0 .0
PT
Note: g = groups involved in the measurement invariance test, inv.= invariance, TLI = Tucker Lewise Index; CFI= comparative fit index; RM SEA= root mean squar approximation; SRM R= standardized root mean square residuals; AIC= Akaike’s information criterion.
AC C
EP T
ED
MA
NU
SC
RI
Fig.1 Trend of burnout syndrome across cultures Fig.2 Trend of burnout syndrome across gender
46
Figure 1
Figure 2