Table 1.
The included studies
| References | Study design | Study sample | Country | Job | Female | Mage | SDage | Burnout measures | Personality measures | Years |
|---|---|---|---|---|---|---|---|---|---|---|
| Manlove [111] | CSS | 188 | USA | Child care workers | 98.94% | 34 | DNA | MBI | EPI | 1993 |
| Deary et al. [48] | CSS | 375 | UK | Medical staff | DNA | DNA | DNA | MBI | NEO-PI-R | 1996 |
| Deary et al. [112] | CSS | 188 | UK | Physicians/surgeons | 9.4% | 47.0 | 1.2 | MBI | NEO-FFI | 1996 |
| Mills et al. [60] | LS | 225 | USA | School psychologists | 73.4% | 40.3 | 9.3 | MBI | NEO-FFI | 1998 |
| Zellars et al. [113] | CSS | 188 | USA | Hospital nurses | 89.9% | 40 | 8.0 | MBI | NEO-FFI | 2000 |
| Zellars et al. [53] | CSS | 296 | USA | Hospital nurses for acute care | DNA | 42.2 | 9.5 | MBI | NEO-FFI | 2001 |
| De Vries et al. [114] | CSS | 765 | Netherland | Workers | 46.5% | 40.3 | 9.7 | MBI | FFPI | 2002 |
| McManus et al. [50] | LS | 1668 | UK | Doctors | DNA | 30.4 | 1.86 | MBI | BFQ | 2004 |
| Zellars et al. [52] | CSS | 290 | USA | Hospital nurses for acute care | DNA | 42.19 | 9.45 | MBI | NEO-FFI | 2004 |
| Cano-García et al. [115] | CSS | 99 | Spain | Teachers | 74% | 42.5 | 8.5 | MBI | NEO-PI-R | 2005 |
| Burke et al. [116] | CSS | 496 | Norway | Nursing home employees | 89.1% | DNA | DNA | BBI | BFI | 2006 |
| Goddard et al. [57] | LS | 79 | Australia | Beginning teachers | 84% | 26 | 7.46 | MBI-ES | EPQ-RS | 2006 |
| Langelaan et al. [117] | CSS | 572 | Netherland | Employees | 17% | 42 | 8.0 | MBI-GS | NEO-FFI | 2006 |
| Mostert et al. [118] | CSS | 1749 | South Africa | Policeman | 18.1% | 34.53 | 6.23 | MBI-GS | PCI | 2006 |
| Bahner et al. [119] | CSS | 115 | USA | BIP workers | 56% | 43 | 11.77 | MBI | COPAS | 2007 |
| Ghorpade et al. [120] | CSS | 265 | USA | Professors | 46.39% | 50 | 10.24 | MBI-ES | Mini-Markers Inventory | 2007 |
| Kim et al. [121] | CSS | 191 | USA | Hotels employees | 62.3% | 36 | DNA | MBI-GS | IPIP | 2007 |
| Teven [122] | CSS | 48 | USA | Professors | 43.75% | 51.15 | 9.86 | MBI | Big Five measure-SF | 2007 |
| Leon et al. [123] | CSS | 203 | USA | Children’s RTCs | 63.50% | 31.64 | 9.41 | MBI | BFI | 2008 |
| Chung et al. [124] | CSS | 103 | UK | Residential community staff | 70% | 37.51 | 10.97 | MBI | NEO-FFI | 2009 |
| De Hoogh et al. [125] | CSS |
91 190 |
Netherlands | Clients of a human resource Employees |
43% 59% |
42 36 |
DNA DNA |
MBI-GS | IPIP | 2009 |
| Gandoy-Crego et al. [126] | CSS | 42 | Spain | Geriatric nurses | 84% | 31 | 5.7 | MBI | BFQ | 2009 |
| Kim et al. [127] | CSS | 187 | USA | Subway employees | 67% | 22 | DNA | MBI-GS | IPIP | 2009 |
| Taormina et al., [128] | CSS | 172 | China | Casino workers | 40.12% | 27.87 | 5.17 | MBI | NEO-PI-R | 2009 |
| Barford et al. [129] | CSS | 94 | Canada | Child and youth care workers | 69.1% | 32.82 | 9.75 | MBI-GS | NEO-FFI | 2010 |
| Perry et al. [51] | CSS |
252 392 |
USA |
Customer service providers Manual laborers for repair and construction services |
83% DNA |
34.7 DNA |
9.83 DNA |
Exhaustion scale MBI-GS |
Personal Characteristics Inventory Big Five factor markers |
2010 |
| Ghorpade et al. [130] | CSS | 263 | USA | Professors | 46.4% | 50.14 | 10.24 | MBI | Mini-Markers Inventory | 2011 |
| Hudek-Knežević et al. [59] | LS | 118 | Croatia | Hospital nurses | 100% | 36.47 | 7.02 | MBI | BFI | 2011 |
| Salami [131] | CSS | 340 | Nigeria | Teachers | 29.42% | 36.70 | 4.50 | MBI-GS | NEO-FFI | 2011 |
| Sterud et al. [61] | LS | 298 | Norway | Ambulance workers | 16.9% | 38.2 | 8.9 | MBI-HSS | BCI | 2011 |
| Armon et al. [54] | LS | 1105 | Israel | Health workers | 37% | DNA | DNA | SMBM | Big-Five mini markers scale | 2012 |
| Zimmerman et al. [132] | CSS | 587 | USA | Employees | 11% | 49 | DNA | MBI | Big-Five mini markers scale | 2012 |
| De la Fuente Solana et al. [133] | CSS | 747 | Spain | Policeman | 11.8% | 35.7 | 8.33 | MBI | NEO-FFI | 2013 |
| Garbarino et al. [134] | CSS | 289 | Italy | Policeman | 0% | 35.4 | 7.5 | MBI | BFQ | 2013 |
| Hurt et al. [135] | CSS | 113 | USA | ABA therapists | 95.6% | DNA | DNA | MBI-GS | M5-120 | 2013 |
| Lin et al. [136] | CSS | 228 | China | Employees | 19.79% | 27.9 | 3.9 | MBI | EPQ | 2013 |
| Gan et al. [56] | LS | 160 | China | IT employees | 36.2% | 27.78 | 3.91 | MBI-GS | NEO-FFI-SF | 2014 |
| Reinke et al. [137] | CSS | 201 | UK | Workers | 51.74% | 34.78 | 9.49 | OLBI | TIPI | 2014 |
| Taycan et al. [138] | CSS | 139 | Turkey | Physicians | 33.1% | 31.05 | 4.84 | MBI-HSS | EPQ-RS | 2014 |
| Yilmaz, [139] | CSS | 303 | Turkey | Teachers | 53.5% | DNA | DNA | MBI | Mini-IPIP | 2014 |
| Cañadas-De la Fuente et al. [140] | CSS | 676 | Spain | Nurses | 66% | 44.58 | 8.18 | MBI | NEO-FFI | 2015 |
| Srivastava et al. [141] | CSS | 152 | Europe and Asia | Senior organizational managers who regularly use ICT | 23.7% | 37,96 | 6,73 | MBI | TIPI | 2015 |
| Ang et al. [142] | CSS | 1826 | Singapore | Nurses | 61.5% | DNA | DNA | MBI | NEO-FFI | 2016 |
| Iorga et al. [143] | CSS | 37 | Romania | Forensic physicians | 54.05% | 39.13 | 11.78 | MBI | BFI | 2016 |
| Vaulerin et al. [144] | CSS | 220 | France | Firefighters | 0% | 36.23 | 6.94 | SMBM | BFI | 2016 |
| Zhou et al. [145] | CSS | 1129 | China | Physicians | 58.17% | 38.04 | 7.74 | MBI | EPQ-RS | 2016 |
| De la Fuente-Solana et al. [146] | CSS | 101 | Spain | Oncology nurses | 69.3% | DNA | DNA | MBI | NEO-FFI | 2017 |
| Geuens et al. [147] | CSS | 587 | Belgium | Nurses | 82% | 40 | 10.8 | MBI | NEO-FFI | 2017 |
| Iorga et al. [148] | CSS | 116 | Romania | Obstetrics and gynecology physicians | 69.83% | DNA | DNA | MBI | BFI | 2017 |
| Lovell et al. [149] | CSS | 120 | UK | Prison officers | 40.7% | 41.72 | 10.73 | MBI-HSS | NEO-PI | 2017 |
| Ntantana et al. [150] | CSS |
149 320 |
Greece |
Physicians ICU nurses |
33.4% 19.2% |
DNA DNA |
DNA DNA |
MBI | EPQ | 2017 |
| Al Shbail et al. [151] | CSS | 187 | Jordan | Internal auditors | 7.5% | DNA | DNA | BM | NEO-PI-R | 2018 |
| Bergmüller et al. [152] | CSS | 97 | Germany | Ambulance doctors | 41.24% | 37.0 | 12.21 | MBI-GS | FPI | 2018 |
| Bianchi et al. [153] | CSS | 257 | Switzerland | Teachers | 76% | 44.84 | 10.46 | SMBM | NEO-FFI | 2018 |
| Bianchi, [19] | CSS | 1759 | France | Teachers | 77% | 40.81 | 9.63 | SMBM | NEO-FFI | 2018 |
| Harizanova et al. [49] | CSS | 307 | Bulgaria | Correctional officers | DNA | DNA | DNA | MBI | EPQ | 2018 |
| Hildenbrand et al. [58] | LS | 148 | Germany | Employees of a manufacturing company | 22% | DNA | DNA | OLBI | MRS-30 | 2018 |
| Iorga et al. [154] | CSS | 78 | Romania | Hospital pharmacists | 89.7% | 45.57 | 10.12 | MBI | BFI | 2018 |
| Tang et al. [155] | CSS | 862 | China | Clinical health professionals | 80.4% | DNA | DNA | MBI-HSS | Brief Big five Personality Scale | 2018 |
| Tatalović Vorkapić et al. [156] | CSS | 203 | Croatia | Educators | 100% | 38.73 | 10.69 | Scale of professional burnout of educators | BFI | 2018 |
| Yao et al. [157] | CSS | 860 | China | Nurses | 94.42% | DNA | DNA | MBI-GS | EPQ-RS | 2018 |
| Zaninotto et al. [158] | CSS | 215 | Italy | Mental health professionals | 59.1% | 46.98 | 8.09 | MBI | TIPI | 2018 |
| Bahadori et al. [159] | CSS | 308 | Iran | Technicians of emergency medical personnel | 0% | 30 | 5.43 | MBI | NEO-FFI | 2019 |
| Brown et al. [160] | CSS | 77 | Canada and Jamaica | Primary care physicians | 79% | DNA | DNA | MBI-HSS | BFI | 2019 |
| Castillo-Gualda et al. [62] |
CSS LS |
237 59 |
Spain | Teachers |
65.4% 66.10% |
44.32 41.12 |
10.54 9.91 |
MBI-ES | BFI | 2019 |
| De la Fuente-Solana et al. [161] | CSS | 96 | Spain | Oncology nurses | 68.8% | 45.5 | 8.02 | MBI | NEO-FFI | 2019 |
| De Looff et al. [55] | LS | 110 | Netherland | Nurses for forensic psychiatric hospitals | 59% | 35.5 | 10.0 | MBI | NEO-FFI | 2019 |
| Farfán et al. [162] | CSS | 237 | Spain | Workers of State Security Forces and Corps | 24.05% | 37.72 | DNA | MBI-GS | NEO-PI-R | 2019 |
| Khedhaouria et al. [163] | CSS | 161 | France | Senior managers who regularly use ICT | 49.61% | 39 | DNA | SMBM | TIPI | 2019 |
| Pérez-Fuentes et al. [17] | CSS | 1236 | Spain | Nurses | 85.5% | 31.50 | 6.18 | CBB | BFI-10 | 2019 |
| Ye et al. [164] | CSS | 622 | China | HSR drivers | 0% |
37.2 DNA |
2.31 DNA |
MBI-GS | BFI | 2019 |
| Banasiewicz et al. [165] | CSS | 181 | Poland | Midwives participating and non-participating in pregnancy terminations | 100% | 40.79 | 8.55 | OLBI | EPQ-R | 2020 |
| Bhowmick et al. [166] | CSS | 152 | India | Policeman | 2% | 43.4 | 9.34 | MBI | Big-Five mini markers scale | 2020 |
| De Vine et al. [167] | CSS | 127 | South Africa | Workers | 64% | 33.21 | 12.17 | MBI-GS | BTI | 2020 |
| Dionigi, [168] | CSS | 160 | Italy | Clown doctors | 72,5% | 38.63 | 11.42 | MBI | BFI | 2020 |
| Farfán et al. [169] | CSS | 971 | Spain | Workers | 56.95% | 37.58 | DNA | MBI | Mini-IPIP | 2020 |
| Liu et al. [170] | CSS | 451 | China | Employee-supervisor dyads | 19.82% | 33.16 | 9.49 | MBI-GS | IPIP | 2020 |
| Mahoney et al. [171] | CSS | 246 | USA | Nurse anesthetists | 60% | 48.03 | 11.34 | OLBI | TIPI | 2020 |
| Malka et al. [172] | CSS | 311 | Israel | Social workers | 90% | 42.8 | 8.9 | SBM | BFI | 2020 |
| Tasic et al. [173] | CSS | 302 | Serbia | Nursery teachers | 100% | 38 | 9.2 | MBI-GS | Big Five Plus Two questionnaire-SF | 2020 |
| Bianchi et al. [174] | CSS |
4394 611 514 |
France Spain Swiss |
Teachers |
86% 70% 68% |
44.78 45.98 44.95 |
9.35 9.39 10.54 |
MBI-ES | NEO-FFI | 2021 |
| De la Fuente-Solana, Pradas-Hernández, González-Fernández, et al. [175] | CSS | 94 | Spain | Paediatric nurses | 78.7% | 43.89 | 10.50 | MBI-HSS | NEO-FFI | 2021 |
| De la Fuente‐Solana, Suleiman‐Martos, Velando‐Soriano, et al.,[176] | CSS | 150 | Spain | Midwives and nurses | 78.7% | 44.85 | 11.563 | MBI | NEO-FFI | 2021 |
ABA Applied Behaviour Analysis; BBI Bergen Burnout Indicator; BCI Basic Character Inventory; BFI, Big Five Inventory; BFQ, Big Five Questionnaire; BIP, Batterer Intervention Program; BM, Burnout Measure; BTI, Basic Traits Inventory; CBB, Brief Burnout Questionnaire; COPAS, Comprehensive Personality and Affect Scales; CSS, Cross-sectional study; DNA, Data Not Available; EPI, Eysenck Personality Inventory; EPQ-R, Eysenck Personality Questionnaire Revised; EPQ-RS, Eysenck Personality Questionnaire Revised Short Scale; EPQ, Eysenck Personality Questionnaire; FFPI, Five-Factor Personality Inventory; FPI, Freiburg Personality Inventory; ICT, Information and Communication Technologies; ICU, Intensive Care Unit; IPIP, International Personality Item Pool; IT, information technology; LS, Longitudinal study; M, Mean; MBI-ES, Maslach Burnout Inventory-Educators Survey; MBI-GS, Maslach Burnout Inventory-General Survey; MBI-HSS, Maslach Burnout Inventory-Human Services Survey; MBI, Maslach Burnout Inventory; MRS, Minimal Redundant Scales; NEO-FFI-PI-R, Neuroticism Extraversion Openness Five Factor Inventory Personality Inventory-Revised; NEO-FFI-PI, Neuroticism Extraversion Openness Five Factor Inventory Personality Inventory; NEO-FFI, Neuroticism Extraversion Openness Five-Factor Inventory; NEO-PI, Neuroticism Extraversion Openness Personality Inventory; NEO-PI-R, Neuroticism Extraversion Openness Personality Inventory Revised; OLBI, Oldenburg Burnout Inventory; PCI, Personality Characteristics Inventory; RTC, Residential Treatment Center; SD; Standard Deviation; SF, Short Form; SMBM, Shirom-Melamed Burnout Measure; TIPI, Ten-Item Personality Inventory