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countr y PIC -,260 ,479 Burno ut -3,525 Estimate S.E. C.R. P Label e1 45,625 5,914 7,715 *** e2 14,762 1,731 8,526 *** e3 56,459 6,913 8,166 *** e4 42,378 5,094 8,318 *** e5 148,493 17,231 8,618 *** e6 18,109 2,648 6,838 *** Matrices (Group number 1 - Default model) Table 92: Factor Score Weights (Group number 1 - Default model) - 1,194 ss ws ls - ,008 ,027 ,26 9 ,18 3 appbeli ef moncreatex ec selfre g ,259 ,051 ,110 - ,066 ee dp pa - ,110 -,205 -,041 -,087 ,120 ,200 Table 93: Total Effects (Group number 1 - Default model) country ss ws ls PIC Burnout ws -1,000 ,000 ,000 ,000 ,000 ,000 ls 2,401 2,453 -,047 -1,021 -,814 ,021 PIC 3,043 3,108 -,060 -,027 -1,032 ,027 Burnout -6,532 -2,891 ,062 ,016 -,372 -,016 appbelief 3,043 3,108 -,060 -,027 -,032 ,027 moncreatexec 4,966 5,072 -,097 -,044 -,052 ,044 selfreg 3,033 3,097 -,059 -,027 -,031 ,027 ee -6,532 -2,891 ,062 ,016 -,372 ,984 dp -2,840 -1,257 ,027 ,007 -,162 ,428 pa 6,532 2,891 -,062 -,016 ,372 -,984 Table 94: Standardized Total Effects (Group number 1 - Default model) country ss ws ls PIC Burnout ws -,018 ,000 ,000 ,000 ,000 ,000 ls ,175 ,356 -,190 -1,021 -,720 ,019 PIC ,251 ,510 -,272 -,030 -1,032 ,028 Burnout -,518 -,456 ,271 ,018 -,358 -,016 appbelief ,205 ,417 -,223 -,025 -,026 ,023 moncreatexec ,158 ,321 -,172 -,019 -,020 ,018 selfreg ,171 ,347 -,185 -,021 -,021 ,019 ee -,333 -,293 ,174 ,011 -,230 ,632 dp -,301 -,265 ,157 ,010 -,208 ,571 pa ,353 ,311 -,185 -,012 ,244 -,671 Table 95: Direct Effects (Group number 1 - Default model) country ss ws ls PIC Burnout ws -1,000 ,000 ,000 ,000 ,000 ,000 ls -116,110 -117,102 2,253 ,000 37,541 -1,000 ,081 - ,149
country ss ws ls PIC Burnout PIC ,000 ,000 ,000 1,267 ,000 ,000 Burnout -4,655 -1,000 ,025 ,496 -1,000 ,000 appbelief ,000 ,000 ,000 ,000 1,000 ,000 moncreatexec ,000 ,000 ,000 ,000 1,632 ,000 selfreg ,000 ,000 ,000 ,000 ,997 ,000 ee ,000 ,000 ,000 ,000 ,000 1,000 dp ,000 ,000 ,000 ,000 ,000 ,435 pa ,000 ,000 ,000 ,000 ,000 -1,000 Table 96: Standardized Direct Effects (Group number 1 - Default model) country ss ws ls PIC Burnout ws -,018 ,000 ,000 ,000 ,000 ,000 ls -8,466 -16,989 9,097 ,000 33,212 -,920 PIC ,000 ,000 ,000 1,432 ,000 ,000 Burnout -,369 -,158 ,112 ,539 -,962 ,000 appbelief ,000 ,000 ,000 ,000 ,818 ,000 moncreatexec ,000 ,000 ,000 ,000 ,630 ,000 selfreg ,000 ,000 ,000 ,000 ,680 ,000 ee ,000 ,000 ,000 ,000 ,000 ,643 dp ,000 ,000 ,000 ,000 ,000 ,581 pa ,000 ,000 ,000 ,000 ,000 -,682 Table 97: Indirect Effects (Group number 1 - Default model) country ss ws ls PIC Burnout ws ,000 ,000 ,000 ,000 ,000 ,000 ls 118,512 119,555 -2,300 -1,021 -38,355 1,021 PIC 3,043 3,108 -,060 -1,294 -1,032 ,027 Burnout -1,877 -1,891 ,036 -,480 ,628 -,016 appbelief 3,043 3,108 -,060 -,027 -1,032 ,027 moncreatexec 4,966 5,072 -,097 -,044 -1,684 ,044 selfreg 3,033 3,097 -,059 -,027 -1,028 ,027 ee -6,532 -2,891 ,062 ,016 -,372 -,016 dp -2,840 -1,257 ,027 ,007 -,162 -,007 pa 6,532 2,891 -,062 -,016 ,372 ,016 Table 98: Standardized Indirect Effects (Group number 1 - Default model) country ss ws ls PIC Burnout ws ,000 ,000 ,000 ,000 ,000 ,000 ls 8,641 17,344 -9,287 -1,021 -33,933 ,939 PIC ,251 ,510 -,272 -1,462 -1,032 ,028 Burnout -,149 -,298 ,159 -,522 ,604 -,016 appbelief ,205 ,417 -,223 -,025 -,844 ,023 moncreatexec ,158 ,321 -,172 -,019 -,650 ,018 selfreg ,171 ,347 -,185 -,021 -,702 ,019 ee -,333 -,293 ,174 ,011 -,230 -,010 dp -,301 -,265 ,157 ,010 -,208 -,009
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University of Eötvös Lorand Hunga
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DEDICATION TO MY PARENTS; YOUR HARD
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ABSTRACT A great deal of research h
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3. METHOD……………………
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1. INTRODUCTION 1.1. PURPOSE OF THE
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1981). This questionnaire was and i
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oncology wards (Sherman, 2004). Esc
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(SWB). The meaning of SWB is how pe
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extent demographic variables, work-
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2. LITERATURE REVIEW 2.1. THE THEOR
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different countries in Europe and t
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Foxall, Zimmerman, Standley & Benee
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nurse were both negatively connecte
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elated to stress levels and job sat
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Altun (2002) has pointed out that b
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Demerouti et al. (2005) is also arg
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Halbesleben & Buckley (2004) argued
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Brewer & Shapard (2004) conducted a
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the third dimension of the burnout
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Table 1. Amount of nurses being bur
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environmental variables at the hosp
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and stress levels could be differen
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about a patient’s treatment witho
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Potter (2006) conducted a literatur
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Lin, Hsu, Chao, Luh, Hung et al. (2
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at work are underprivileged in comp
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instructions from their supervisors
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number of years worked as a nurse w
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psychosomatic health, after demogra
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environment, and support from the s
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urnout. The factor which has been h
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Diener & Tov (2005, in Kitayama & C
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form of for example life satisfacti
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develop burnout (see for example La
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Simoni & Paterson (1997) have also
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the psychological immune system (Ol
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positive effect of social support i
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Several authors have shown the effe
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support especially important in rel
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(1999), Tummers et al. (2002), and
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According to Maslach (1982), when i
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2.11. HOW CAN WE PREVENT BURNOUT? 2
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work-related safety in order to dec
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in the organization are not easy to
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at work, and on the nurses’ work-
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3. METHOD 3.1 STUDY POPULATION The
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the head nurse at the second meetin
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• Satisfaction with Life scale (D
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assess people’s satisfaction with
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positive accomplishment in the nurs
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Goal Orientation 0.63 0.52 Impulse
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23,71% Number of children 0-1 2-3 4
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It was shown that the Swedish nurse
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APPENDIX 3); a robust Welch-test fo
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Table 8: ANOVA results of work stre
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In the second part of the second hy
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would be found in the Swedish sampl
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The Monitoring-Creating-Executing S
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4.6.3. Findings for Burnout and Per
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Table 17: Robust Test of Equality o
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Approach-Belief System (r=0.260, p
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p
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Approach-Belief System (1.01) and t
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Marital status Table 23: Burnout me
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generalized to other hospitals in S
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feeling inexperienced would result
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sample. Another researcher who foun
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5.3. BURNOUT AND LIFE SATISFACTION
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the findings in connection to life
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salaries of health care system pers
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urnout simply shows that the area o
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feel supported at home and feel the
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and that lower personality scores g
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connection between age and burnout.
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connection to them was not thought
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and young nurses working in the int
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extensively researched all around t
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what if the Hungarian nurses would
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immunity between different countrie
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care workers (usually nurses). In s
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more efficient if they would be dir
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Aries, M. & Ritter, I. Z. (1999). N
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Brooks I. & Swailes S. (2002). Anal
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Chang, E. M., Bidewell, J. W., Hunt
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Cronin-Stubbs, D. & Rooks, C. A. (1
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Diener, E., Suh, E., Lucas, R. E. &
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Ghorpade, J., Lackritz, J. & Singh,
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Hupcey, J. E. (1998). Clarifying th
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Lakin, B., Leon, S. C. & Miller, S.
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Leiter, M. P. (1993). In Halbeslebe
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Maslach, C. (1982). Burnout: a soci
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Murrells, T., Robinson, S. & Griffi
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Piko, B. F. (1999). Work-related st
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Sherman, D. W. (2004). Nurses’ St
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Taris, T. W., Schreurs, P. J. G. &
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Wright, T. A. & Cropanzano, R. (199
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a. Age…………..years old b. Wh
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6.I do not particularly like differ
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4) I am interested in how you feel
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APPENDIX C ORIGINAL SPSS OUTPUTS Se
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Cases Reliability Scale: ALPHA Case
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Cases Case Processing Summary N % V
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RELIABILITY /VARIABLES=pici7 pici23
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Cases Case Processing Summary N % V
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Reliability Statistics Cronbach's A
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Section 6: Correlations of the test
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Emotional exhaustion_ mbi Depersona
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Table 11: Robust Tests of Equality
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ience d Worklo ad Stress related to
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Table 17: Coefficients(a) Unstandar
Page 221 and 222: Table 23: Excluded Variables(b) Par
Page 223 and 224: Table 30: Test of Homogeneity of Va
Page 225 and 226: a Predictors in the Model: (Constan
Page 227 and 228: 5 6 country 4,870 ,772 ,342 6,305 ,
Page 229 and 230: Social support questionnaire ,145(b
Page 231 and 232: Being unprepaired and feeling inexp
Page 233 and 234: Social mobilizing capac. subscale_P
Page 235 and 236: Section 16: Correlations of the PIC
Page 237 and 238: Table 48: Correlations: (Group numb
Page 239 and 240: Positive thinking subscale_PIC I Se
Page 241 and 242: Positive thinking subscale_PICI Sen
Page 243 and 244: Approach-Belief System Monitoring-C
Page 245 and 246: Approach-Belief System Monitoring-
Page 247 and 248: Model 1 Variables Entered Work stre
Page 249 and 250: Change and Challenge orient. subsca
Page 251 and 252: Married -,160(c) -2,798 ,006 -,208
Page 253 and 254: Relationship with the patient’s r
Page 255 and 256: More than 5 years worked as a nurse
Page 257 and 258: Work and private life ,006(b) ,079
Page 259 and 260: Social creation capac. subscale_PIC
Page 261 and 262: 6 7 Residual 6334,172 172 36,827 To
Page 263 and 264: Self-Efficacy subscale_PICI ,109(a)
Page 265 and 266: Significant other subscale_ social
Page 267 and 268: Stress related to tasks -,109(d) -1
Page 269 and 270: 7 Age Relationship with patients Wo
Page 271: Estimate S.E. C.R. P Label Burnout
Page 275 and 276: Table 106: ECVI Model ECVI LO 90 HI
Page 277 and 278: coun try 2,41 8 dp -,723 ss ls PICI
Page 279 and 280: Table 120: tandardized Indirect Eff
Page 281 and 282: ment_mbi Emotional exhaustion_mbi D
Page 283 and 284: Personal accomplishment _mbi single
Page 285 and 286: 2 Model 1 2 Married . a Dependent V
Page 287 and 288: Number of years at the current work
Page 289 and 290: edu Total How many years have you w
Page 291 and 292: Table 160: Chi-Square Tests Value d
Page 293 and 294: Death, dying Conflic ts with doctor
Page 295 and 296: Death, dying Conflic ts with doctor
Page 297 and 298: ** Correlation is significant at th
Page 299 and 300: Estimate S.E. C.R. P Label e12 2,40
Page 301 and 302: APPMONSYS CREEXSYS SELFREGSYS Goal
Page 303 and 304: Table 184: RMSEA Model RMSEA LO 90
Page 305 and 306: Table 192: Correlations: (Group num
Page 307 and 308: APPMONSYS CREEXSYS SELFREGSYS Self-
Page 309: Table 204: NCP Model NCP LO 90 HI 9
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