Table 3.
Characteristics of the Studies on Burnout among Military Personnel
|
First author;
Year; Country |
Type of Study;
Burnout Instrument |
Study Population;
Sample Size |
Age and Sex (Men, No.
(%)) |
Reported Burnout | Main findings |
|---|---|---|---|---|---|
| Morgan; 2002; United States [22] |
Cross-sectional; MBI | Mixed; (N = 41) |
Age: NR Sex: NR |
OB: 31 ± 13 EE: 14 ± 7.3 DP: 7 ± 4.5 PA: 37 ± 7 | Soldiers with higher burnout reported at baseline showed significantly less performance gain (more errors, slower swim times, and poorer underwater navigation ability). |
| Shirom; 2003; Israel [23] |
Cross-sectional; 16-Item BM-Rep | Army; (N = 707) |
Age: Mean, 38 Sex: NR |
OB*: 2.2 ± 0.6 | In the questionnaire with BM items and all other strain items, four dimensions (anxiety, depression, worn out, and lack of vigor) were measured. Burnout and anxiety (r = 0.51) and burnout and depression (r = 0.83) were found to be significantly correlated. |
| Bakker; 2007; Netherlands [24] |
Two-way factorial design; 16-Item MBI-GS | Army; (N = 101) |
Age: Mean, 21.6 (SD, 3.9) Sex: 85 (84.2) |
Not Reported | The crossover of cynicism and the level of professional efficacy (but not exhaustion) were observed from one individual to another. A moderation of the crossover of cynicism was seen when the sender and the receiver were similar, taking place only for those with the same degree. |
| Cole; 2007; United States [25] |
Cross-sectional; 9-Item EE Subscale of MBI-HSS | Air Force; (N = 828) |
Age: NR Sex: NR |
EE*: 3.3 ± 1.1 | The relationship between emotional exhaustion and work commitment was moderated by transformational leadership-consensus (TLC) and laissez-faire leadership consensus (LFLC). In case of high (low) TLC and low (high) LFLC, there was a negative (weak) association between emotional exhaustion and work commitment. |
| Moran; 2008; Israel [26] |
Longitudinal; subjective assessment of burnout on a scale of 1 to 7 | Army; (N = 219). |
Age: Range,18-19 Sex: 0 (0) |
OB among females with stress fracture: 3.9 ± 0.8, without stress fracture: 3.4 ± 1.1 |
In the final model, the variables predicting stress fracture included height, iron blood level, burnout, BMI and Ferritin. The probability of having stress fracture was higher in females with higher burnout scores (adjusted OR = 1.59; 95% CI: 1.05-2.42). |
| Tvaryanas; 2009; United States [27] |
Cross-sectional; MBI (version not specified) for EE subscale only | Air Force; (N = 66) |
Age: Mean, 34.9 (SD, 8.7) Sex: 61 (92.4) |
Not Reported | EE was associated with gender (female relative to male: β = 9.45, SE = 1.91, p < 0.01) and crew position (sensor operators relative to pilots: β = 7.67, SE = 2.7, p < 0.01). |
| Vinokur; 2009; United States [28] |
Longitudinal Study; Subset of 9 of the 12 items of the SMBM | Air Force; (N = 1009) |
Age: Mean, 38.2, ≤ 30 yr: 27.2%, 31-40: 31.9, > 40 yr: 40.9 Sex: 506 (50.1) |
Baseline*: OB: 2.9 ± 1.2 PF: 3.7 ± 1.4 EE: 2.9 ± 1.6 CW: 2.4 ± 1.3 Follow-up*: OB: 3 ± 1.2 PE: 3.7 ± 1.4 EE: 2.9 ± 1.5 CW: 2.5 ± 1.2 |
There was a negative association between perceived health and job burnout (Baseline: r = −0.33, p < 0.001, Follow-up: r = -0.2, p < 0.001). Perceived health and job burnout in the baseline could predict a decline of job burnout and diminished perceived health in the follow-up, respectively. The predicted impact of perceived health on job burnout was found to be significantly greater than that of burnout on health. |
| Chambel; 2010; Portugal [29] |
Longitudinal Study (T1: Baseline, T2: During the Mission, T3: End of the Mission); EE and CY subscales from Portuguese version of MBI-GS | Army; (N = 387) |
Age: Mean, 25.2 Sex: 373 (96.4) |
T1*: Ex: 1.6 ± 1.2 Cy: 1.6 ± 0.8 T2*: Ex:1.6 ± 1.2 Cy: 1.7 ± 0.9 T3*: Ex: 1.7 ± 1.1 Cy: 1.9 ± 1.1 |
In T2, psychological contract breach increased burnout (β = 0.24, p < 0.001) and decreased engagement (β = –0.23, p < 0.001). In T3, while psychological contract breach decreased engagement (β = –0.28, p < 0.001), it had no impact on burnout (β = 0.08, NS). Psychological contract breach in T2 had no impact on burnout and engagement of soldiers in T3. |
| Boxmeer; 2011; Netherlands [30] |
Cross-sectional; 8-Item UBOS for EE and Cy subscales | International Security Assistance Force (ISAF); (N = 3004) |
Age: Mean, 28.5 (SD, 9.1) Sex: 2554 (85) |
EE: 1.9 ± 0.9 Cy: 2.3 ± 1.1 |
Not Reported |
| Chang; 2011; China [31] |
Cross-sectional; 10-Item burnout subscale of ProQOL | Army; (N = 102) |
Age: Mean, 22.7 (SD, 4.9) Sex: 102 (100) |
OB*: 1.9 ± 0.7 | The multivariable analysis revealed that among satisfaction, resilience and burnout, only burnout could predict secondary trauma, explaining only 30% of the variance. |
| Chappelle; 2011; United States [32] |
Cross-sectional; 16-Item MBI-GS | Air Force: Predator/Reaper Operators (PRO, 40.98%), Global Hawk Operators (GHO, 18.04%), Noncombatant Airmen (NCA, 40.98%); (N = 1464) |
Age (18-30, 31-39, ≥ 40 yr; No, %): PRO: (307, 51.8), (118, 19.9), (168, 28.3) GHO: (192, 72.7), (32, 12.1), (40, 15.2) NCA: (402, 67.2), (89, 14.9), (107, 17.9) Sex: PRO: 509 (84.8) GHO: 197 (74.6) NCA: 534 (89) |
PRO: Ex: 12.3 ± 7.7 Cy: 9.5 ± 7.9 PE: 26.5 ± 6.3 GHO: Ex: 14.9 ± 8.4 Cy: 12.4 ± 7.9 PE: 25 ± 6.9 NCA: Ex: 10.5 ± 7.8 Cy: 10.9 ± 8.1 PE:25.6 ± 7.5 |
Comparisons of means for Ex between PRO and GHO (t = -4.43, p < 0.01) and between PRO and NCA (t = 4.06, p < 0.01) showed that the differences were significant. Comparisons of means for Cy were significant between PRO and GHO (t = -4.88, p < 0.01), PRO and NCA (t = -2.96, p < 0.01), and GHO and NCA (t = 2.50, p < 0.01). As for the mean comparisons of PE, it was revealed that they were significant between PRO and NCA (t = 2.29, p < 0.01) as well as PRO and GHO (t = 3.18, p < 0.05). High stress, shift work, supervisory position, and poor quality of sleep were associated with high Ex. |
| Morgan; 2011; United States [33] |
Longitudinal; 16-Item MBI-GS | Marine Corps; (N = 32) | Age: Mean, 24.1 (SD, 3.3), Range, 18-32 Sex: 32 (100) |
Ex: 6.8 ± 4.7 Cy: 4.2 ± 3.7 PE: 31.5 ± 4.1 Compared to norms: Ex > 4.6: 37.5% Cy > 3.5: 56.2% PE < 3.6: 0% |
PE scores were negatively associated with GMLT errors during all three field-based phases of training using the repeated-measures ANCOVA in the presence of education, Cy and GMLT at baseline, with stronger negative associations in phase 3 as compared with phases 1 and 2. In phase 2, this association was stronger than in phase 1. |
| Ouma; 2011; United States [34] |
Cross-sectional; 16-Item MBI-GS | Air Force: Active Duty participants (69.5%) and National Guard/Reserve (NG/R) participants (30.5%); (N = 426) |
Age (18-30, 31-40, > 40 yr; No, %): Active Duty: (178, 60.1), (57, 19.3), (56, 18.9) NG/R: (27, 20.8), (35, 26.9), (66, 50.8) Sex: Active Duty: 266 (90.8) NG/R: 123 (94.6) |
Active Duty: Ex: 13.6 ± 8.1 Cy: 10.6 ± 8.3 PE: 26.4 ± 6.6 NG/R: Ex: 10.5 ± 6.6 Cy: 7.9 ± 6.3 PE: 27 ± 5.7 |
When compared to NG/R operators (OR = 2.2, p < 0.01), Active Duty operators were 2.2 times more likely to report high levels of Ex. Also, these operators were 2.62 times more likely to report high levels of Cy when compared to NG/R operators (OR = 2.62, p < 0.01). In terms of PE, no significant difference was observed between Active Duty operators and NG/R operators. |
| Vinokur; 2011; United States [35] |
Longitudinal Study; 12- Item of the SMBM | Air Force; (N = 1009) |
Age: Mean, 38.2 Sex: 506 (50.1) |
Baseline*: OB: 2.9 ± 1.2 Follow-up*: OB: 2.8 ± 1.1 |
Lower levels of job burnout at baseline (β = -0.09; p < 0.01) could be predicted by deployment to the theater of war. Exposure to trauma predicted an impact on job burnout at baseline (β = 0.20, p < 0.001) and follow-up (βs = 0.19, p < 0.01). A decrease (increase) in follow-up job burnout could be predicted by baseline (follow-up) PTS symptoms and loss of resources. Members of the Active Duty Force experienced significantly higher job burnout scores (β = 0.17, p < 0.001) as compared with the Reserve Force members. |
| Mohammad; 2012; Egypt [36] |
Cross-sectional; 22-Item MBI-HSS | Mixed; (N = 20) |
Age: Mean, 39.5 (SD, 13) Sex: 8 (40) |
severe OB: 40% high EE ( ≥ 27): 40% high DP ( ≥ 13): 40% low PA ( ≤ 31): 60% |
EE, DP and PA were found to be associated with sex (p = 0.02, p = 0.02, p < 0.001, respectively), marital status (p = 0.03, p = 0.03, p = 0.01, respectively) and duration of work (p = 0.001, p = 0.001, p < 0.001, respectively). Also, DHEA-S and cortisone levels as well as the ratio between them were significantly and negatively correlated with burnout syndrome (p = 0.001, 0.009, 0.002, respectively). |
| Prince; 2012; United states [37] |
Cross-sectional; 16-Item MBI-GS | Air Force: distributed common ground system (DCGS) intelligence exploitation Personnel (IEP, 53.87%), DCGS Support/System Sustainment Personnel (SSP, 19.92%), Noncombatant Airmen (NCA, 26.21%); (N = 763) |
Age (18-30, 31-39, ≥ 40 yr; No, %): IEP: (279, 68.6), (92, 22.6), (36, 8.8) SSP: (91, 61.1), (37, 24.8), (21, 14.1) NCA: (107, 54.3), (69, 35), (21, 10.7) Sex: IEP: 277 (67.4) SSP: 118 (77.6) NCA: 153 (76.5) |
IEP: Ex: 13.4 ± 8.1 Cy: 11.4 ± 8.3 PE: 24.4 ± 7.9 SSP: Ex: 8.7 ± 7.5 Cy: 8.1 ± 7.8 PE: 25.6 ± 8 NCA: Ex: 9 ± 7 Cy: 8.1 ± 6.9 PE:24.6 ± 8.6 |
Comparisons of means for Ex and Cy (but not PE) showed significant differences between IEP and SSP and between IEP and NCA. Night shift workers were 2 (3.2) times more likely to be at the risk of high emotional exhaustion (cynicism). Those with chronically long work hours (50 hours or more per week), those who slept an average of 4 hours or less prior to work and those experiencing high vicarious combat exposure were 2 (95% CI: 1.2-3.15), 4 (95% CI: 2.15-10.73) and 5.48 (95% CI: 1.3-6.4) times more likely to report high emotional exhaustion, respectively. |
| Serec; 2012; Slovenia [38] |
Cross-sectional; 22-Item MBI-HSS | Army; (N = 390) |
Age: Mean, 30.7 (SD, 7.6) Sex: 342 (88) |
EE: 16.5 ± 11.7 DP: 8.7 ± 6.2 PA: 30.4 ± 7.6 |
Emotional exhaustion (personal accomplishment) was lower (higher) in the soldiers compared to US norms. There was a positive (negative) association between emotional exhaustion (depersonalization) and neuroticism on one hand, and emotion-oriented coping on the other. Positive associations were found between depersonalization and psychoticism, and between personal accomplishment and extraversion and problem-oriented coping. |
| Bue; 2013; Belgium [39] |
Cross-sectional; EE and Cy subscales of 20-Item UBOS | International Security and Assistance Force (ISAF); (N = 171) |
Age: Mean, 29.9 (SD, 7.5), Range, 20-51 Sex: 166 (97.1) |
EE: 5 ± 4.1 Cy: 5.8 ± 4.1 |
Hardiness was negatively associated with Cy (univariable: r = -0.56, p < 0.001; multivariable: β = -0.56, p < 0.001) and EE (univariable: r = -0.45, p < 0.001; multivariable: β = -0.48, p < 0.001). The relationship between vigor and EE (but not between dedication and Cy) was moderated by hardiness (Interaction: β = 0.66, p < 0.001). |
| Chappelle; 2013; United States [40] |
Cross-sectional; 16-Item MBI-GS | Air Force: Active-Duty Cyber Warfare Operators (ADCW, 28.33%), Civilian/Contract Cyber Warfare Operators (CCW, 11.76%), active duty noncyber control group (ADNC, 59.91%); (N = 1327) |
Age (18-30, 31-39, ≥ 40 yr; No, %): ADCW: (207, 55.5), (140, 37.5), (26, 7) CCW: (24, 15.6), (24, 15.6), (106, 68.8) ADNC: (596, 75.3), (169, 21.3), (27, 3.4) Sex: ADCW: 303 (81.7) CCW: 127 (82.5) ADNC: 684 (86.5) |
ADCW: Ex: 13.4 ± 7.8 Cy: 10.7 ± 7.8 PE: 23.8 ± 7.5 CCW: Ex: 10.3 ± 7.6 Cy: 8.3 ± 7.1 PE: 26.2 ± 8.0 ADNC: Ex: 10.1 ± 7.7 Cy: 10.3 ± 7.9 PE:25.4 ± 7.8 |
Comparisons of means for Ex showed significant differences between ADCW and CCW (t = 3.11, p < 0.01) and between ADCW and ADNC (t = 3.34, p < 0.01). Comparisons of means for Cy showed significant differences between ADCW and CCW (t = 2.34, p < 0.01), and CCW and ADNC (t = 1.94, p < 0.01). As for the mean comparisons of PE, it was revealed that there were significant differences between ADCW and CCW (t = -2.43, p < 0.01) and ADCW and ADNC (t = -1.58, p < 0.01). |
| Salimi; 2013; Iran [41] |
Cross-sectional; 22-Item MBI-HSS | Mixed; (N = 250) |
Age: Mean, 33.7 (SD, 5.5); Range, 25-55 Sex: NR |
Not Reported | Significant associations were found between mental health and the frequency aspect of burnout subscales (EE: r = 0.237, p < 0.001, DP: r = 0.154, p = 0.002, PA: r = 0.289, p < 0.001), the intensity aspect of EE (r = 0.279, p < 0.001) and PA (r = 0.258, p < 0.001), but not DP (r = 0.265, p = 0.280). |
| Chappelle; 2014; United States [42] |
Cross-sectional; 16-Item MBI-GS | Air Force: Air Combat Command (ACC, 66.8%), Air National Guard (ANG, 20.2%), Air Force Special Operations Command (AFSOC, 13%); (N = 1094) | Age (18-30, 31-39, ≥ 40 yr; No, %): ACC: (448, 61.3), (207, 28.3), (74, 10.1) ANG: (64, 29), (75, 33.9), (82, 37.1) AFSOC: (77, 54.2), (53, 37.3), (12, 8.5) Sex: ACC: 653 (89.3) ANG: 192 (86.9) AFSOC: 120 (84.5) |
ACC: Ex: 12 ± 7.4 Cy: 9.1 ± 7.2 PE: 26.1 ± 6.6 ANG: Ex: 11.3 ± 6.8 Cy: 7.7 ± 6.7 PE: 26.9 ± 5.9 AFSOC: Ex: 15.9 ± 7.8 Cy: 10.6 ± 7.5 PE: 24.7 ± 6.5 |
ANCOVA revealed that AFSOC was associated with higher levels of Ex and Cy than ANG (d = 0.62, 0.42, p < 0.01, p < 0.01, respectively) and ACC (d = 0.51, 0.21, p < 0.01, p < 0.05, respectively) operators. Based on multiple logistic regression, working swing or night shifts (OR = 1.82), working 51 or more hours a week (OR = 2.05), serving in current duty position for 25 months or longer (OR = 1.89), duty status as an officer-pilot (OR = 1.43), and classification as an AFSOC drone operator (OR = 1.54) were identified as variables which were predictors of high Ex. This analysis also showed that the variables of age (OR = 2.34), 25 months or longer periods of working in the current duty position (OR = 1.62), and officer status (OR = 1.59) could predict high Cy. |
| Ojedokun; 2014; Nigeria [43] |
Cross-sectional; 22-Item MBI-HSS | Mixed; (N = 256) |
Age: Mean, 35 (SD, 8.5), Range, 19-65 Sex: 136 (53.1) |
Not Reported | There was a significant negative relationship between emotional intelligence, self-efficacy, organization-based self-esteem, and optimism on the one hand and total burnout, EE and DP on the other. PA was found to have a positive association with emotional intelligence, self-efficacy, organization-based self-esteem, and optimism. |
| Smith; 2015; United States [44] |
Cross-sectional; 22-Item MBI-HSS | Air Force: Active-Duty (72.2%) and NG/R (27.8%); (N = 194) | Age: Mean, 30.4 (SD, 6), Range, 21-48 Sex: 194 (100) |
EE: 18.4 ± 9.8 DP: 11.9 ± 5.8 PA: 39.4 ± 8.2 Active duty: EE: 19 ± 8.9 DP: 11.4 ± 5.6 PA: 39.4 ± 8.2 NG/R: EE:19.5 ± 10.5 DP: 13.4 ± 5.9 PA: 39.5 ± 8.1 |
There was an association between depression (Univariable: rs = 0.36, Multivariable: B = 1.098, SE = 0.392, β = 0.286, p = 0.004) and posttraumatic stress (Univariable: rs = 0.34, Multivariable: B = 0.320, SE = 0.171, b = 0.194, p = 0.053) on the one hand, and higher levels of EE on the other. Posttraumatic stress was associated with higher levels of DP (Univariable: rs = 0.41, Multivariable: B = 0.316, SE = 0.088, b = 0.353, p < 0.001). Moreover, depersonalization was significantly higher among NG/R personnel as compared with Active Duty personnel (B = 2.287, SE = 1.035, β = 0.203, p = 0.029). |
| Chambel; 2015; Portugal [45] |
Cross-sectional; 10-Item Portuguese version MBI-GS for Ex (5 Items) and Cy (5 Items) subscales | Army; (N = 1045) |
Age: Mean, 23.7 (SD, 4), Range, 19-56 Sex: 956 (91.5) |
Ex: 4.1 ± 1.4 Cy: 3.8 ± 1.3 |
In the univariable analysis, autonomous work motivation associated negatively with soldiers’ Ex (r = -0.21, p < 0.01) and Cy (r = -0.26, p < 0.01). Controlled work motivation was positively related to soldiers’ Ex (r = 0.21, p < 0.01) and Cy (r = 0.15, p < 0.01). Based on structural equation modeling, a significantly negative association was found between autonomous work motivation and burnout (β = 0.26, p < 0.01). A partially mediating role was found for autonomous work motivation in the impacts of perceived organizational support (and leader–member exchange) on burnout. |
| Matthew; 2015; United Kingdom [46] |
Cross-sectional; 16-Item MBI-GS | Mixed: Permanent Resistance Instructors (PRI, 42.5%) and External Resistance Instructors (ERI, 57.5%), Mixed; (N = 40) | Age: NR Sex: NR |
All RI: Ex: 7.7 ± 7.5 Cy: 7.2 ± 7.5 PE: 28.8 ± 7.4 PRI: Ex: 5.7 ± 5.2 Cy: 5.2 ± 5.6 PE: 29.8 ± 6.8 (22, 55%) ERI: Ex: 9.2 ± 8.6 Cy: 8.6 ± 8.5 PE: 28 ± 7.8 |
As compared to permanent RIs, external RIs reported higher levels of Cy and Ex as well as a lower level of PE. Nevertheless, no statistical difference was found between the responses of permanent and external RIs. |
| Taghva; 2015; Iran [47] |
Cross-sectional; 22-Item MBI-HSS | Army; (N = 215) |
Age: Mean, 31.1 (SD, 4.7) Sex: 215 (100) |
Not Reported | Burnout (β = 0.24, P < 0.01) and depression (β = 0.56, P < 0.01) directly affected self-destructive behavior. Burnout had an indirect (β = 0.35) and total (β = 0.59) effect on self-destructive behavior. |
| Tao; 2015; China [48] |
Cross-sectional; 15-Item CMBI | Army: Soldiers stationed in the arid desert region of Xinjiang (AD, 30%) and in an urban area of Xinjiang (UA, 70%); (N = 820) |
Age: Mean, 21.4 (SD, 3.3), Range, 16-44 Sex: NR |
AD: OB: 43.9 ± 14.6 EE: 15.3 ± 7.9 DP: 10.2 ± 5.6 PA: 19.6 ± 7.9 UA: OB: 41.2 ± 15.1 EE: 13.6 ± 7.1 DP: 9.6 ± 5.2 PA: 19.0 ± 8.2 |
Comparing the arid desert group with the urban group, it was found that the degree of OB (p < 0.001), EE (p < 0.001) and PA (p = 0.001) were significantly higher in the former group. The multivariable analysis revealed that being an only child (OR = 0.394, p = 0.025), heat shock protein (HSP-70) levels (OR = 1.740, p = 0.022), cortisol levels (OR = 1.124, p = 0.041), and adrenocorticotropic hormone (ACTH) levels (OR = 1.316, p = 0.033) were independently associated with job burnout. Weak correlations were found between HSP-70 levels and OB (r = 0.078, p = 0.011), cortisol levels and PA (r = 0.123, p = 0.002), and ACTH levels and PA (r = 0.126, p = 0.001). |
| Zheng; 2015; United States [49] |
Cross-sectional; 5-Item revised MBI-GS for Ex only | Mixed; (N = 338) |
Age (No, %): < 20 yr: (47, 13.9) 20-25 yr: (157, 46.4) 26-30 yr: (87, 25.7) 31-40 yr: (41, 12.1) > 40 yr: (6, 1.8) Sex: 271 (80.2) |
Ex: 3.0 ± 1.0 | There was a negative relationship between ethical leadership (r = -0.35, p < 0.01) and team cohesion (r = -0.31, p < 0.01) on the one hand and Ex on the other. Ethical leadership had both direct (β = -0.19, p = 0.002) and indirect (99%CI: (-0.15, -0.04)) effects on Ex via team cohesion. Therefore, the relationship between ethical leadership and Ex was partially mediated by team cohesion. Conscientiousness moderated the direct effect of ethical leadership and team cohesion on Ex. |
| Delahaij; 2016; Netherlands [50] |
Longitudinal study; 8-Item MBI-GS (adapted for the Dutch military) for Ex and Cy subscales | International Security and Assistance Force (ASAF): Police Training Group (PTG, 75%), Air Task Force (ATF, 25%); (N = 164)s |
Age: PTG: Mean, 32 ATF: Mean, 37 Sex: PTG: 121 (98.4) ATF: 39 (95.1) |
OB: 1 ± 0.75 | The univariable analysis showed a positive correlation between burnout and work engagement (r = 0.61, p < 0.01). Based on the findings of the multiple regression analysis on burnout, a three-way interaction was observed among self-efficacy, family support, and threat exposure (b = 0.12, p < 0.05). |
| Villar; 2017; Brazil [51] |
Case-Control; One question worded: “Do you feel tired and/or exhausted?” | Air Force: military professional servants in the function of Air Traffic Controllers (Study group: SG, 50%) and Other civil or military servants (Control Group: CG, 50%); (N = 60) |
The groups were paired according to age and gender Age: Range, 21-44 SG: Mean, 26.9 CG: Mean, 26.9 Sex: SG: 16 (53.3) CG: 16 (53.3) |
Sometimes, usually or always fatigue and/or exhausted, No., %: SG: 26, 86.7% CG: 18, 60% |
Their univariable analysis revealed that burnout in the SG group was statistically higher than that in the CG group (p = 0.004). However, burnout was not found to be a significant predictor based on multiple logistic regression. |
| Alessandri; 2018; Italy [52] |
Longitudinal study; 10-Item MBI-GS for Ex and Cy subscales and 7-Item ISW for IS subscale | Mixed; (N = 363) |
Age: Mean, 22.9 (SD, 9.3), Range, 19-32 Sex: 250 (68.9) |
Not Reported | The individuals’ higher scores in the variable of self-efficacy beliefs in managing negative emotions at work (EFN-W) were a significant predictor of their lower levels of burnout over time (β = -0.13, p = 0.041). The relationship between emotional stability and burnout over time (indirect effect = -0.064, 95%CI = (-0.001, -0.163)) was significantly mediated by EFN-W. Moreover, higher EFN-W predicted higher scores of individuals in emotional stability over time (β = 0.18, p = 0.003). |
| Bryan; 2018; United States [53] |
Cross-sectional; 16-Item MBI-GS | Air Force; (N = 6138) |
Age (No, %): 17-25 yr: (1494, 24.5) 26-30 yr: (1743, 28.5) 31-35 yr: (1395, 22.8) 36-40 yr: (841, 13.7) > 40 yr: (645, 10.5) Sex: 4858 (79.6) |
Ex: 13.4 ± 8.3 Cy: 11.7 ± 8.3 PE: 24.4 ± 7.3 |
Based on the employed univariable analysis, Ex, Cy and PE in high psychological distress (13.4 ± 8.4, 11.8 ± 8.2 and 24.4 ± 7.3) were not significantly different from Ex in low psychological distress (13.4 ± 8.3, 11.6 ± 8.3 and 24.4 ± 7.3). According to their multivariable analysis, Ex (OR = 0.99, p = 0.419), Cy (OR = 1, p = 0.684) and PE (OR = 1, p = 0.633) were not predictors of psychological distress. |
| Carvalho; 2018; Portugal [54] |
Cross-sectional; 10-Item Portuguese version MBI-GS for Ex and Cy subscales | Marine Corps; (N = 175) | Age: NR Sex: 155 (88.6) |
Ex: 2.5 ± 1.6 Cy: 1.9 ± 1.6 |
In their univariable analysis, Work–Family Conflict (WFC) on the one hand, and Ex and Cy on the other were found to be positively correlated (r = 0.44, p < 0.01; r = 0.42, p < 0.01, respectively). The structural equation modeling approach also confirmed this association. Therefore, burnout was predicted by WFC (β = 0.62, p < 0.001). Yet, the relationship between job demands (or supervisor support but not job autonomy) and burnout were mediated by WFC. |
| Goodman; 2018; United States [55] |
Cross-sectional; 16-Item MBI-GS | Air Force; (N = 3513) |
Age: 18-30 yr: (1844,52.6) 31-40 yr: (1297,37.1) > 40 yr: (362,10.3) Sex: 2777 (79.6) |
Not Reported | According to the univariable and multivariable (in the absence of psychological distress in the model) analyses, the risk ratios which were significant were those of Rarely (vs Never) suicide ideation in high Ex group, high Cy group, and low PE group (vs others: Univariable: RR = 3.26, 3.53, 2.38; Multivariable: RR = 2.02, 2.04, 1.80, respectively). The other significant risk ratios belonged to Sometimes to Always (vs Never) suicide ideation in the high Ex group, high Cy group, and low PE group (vs Others: Univariable: RR = 4.54, 5.32, 5.00; Multivariable: RR = 2.62, 2.61, 3.25, respectively). However, in the presence of psychological distress in the model, the only significant risk ratios were those of Rarely (vs Never) suicide ideation in high Cy group and Sometimes to Always (vs Never) suicide ideation in low PE group (vs Others: RR = 1.58, 2.67, respectively). |
| Ivey; 2018; Canada [56] |
Cross-sectional; 8-Item OBI | Mixed; (N = 3500) |
Age: NR Sex: NR |
OB: 2.4 ± 0.8 | Workload overload, work-family conflict, and job stress positively predicted job burnout. Moreover, job burnout positively predicted psychological distress and turnover intentions. |
| Topa; 2018; Spain [57] |
Cross-sectional; 6-Item CBB for EE subscale | Army: professional soldiers (PS, 41.8%), and prison officers (PO, 58.2%); (N = 184) |
Age: PS: Mean, 28.4 (SD, 7.9) PO: Mean, 38.3 (SD, 7.2) Sex: NR |
PS: EE: 2.9 ± 0.8 PO: EE: 3.2 ± 0.8 |
The univariable analysis showed a negative correlation between EE and workday among professional soldiers and a positive correlation between EE and psychological contract breach among prison officers (r = -0.3, 0.41). The multivariable analysis showed that EE could be positively predicted by psychological contract breach among soldiers (b = 0.33, p < 0.05) and prison officers (b = 0.52, p < 0.001). |
| Chappelle; 2019; United states [58] |
Cross-sectional; 16-Item MBI-GS | Air Force: Active duty (84.62%), Air National Guard (ANG, 6.85%), Reserve (8.53%); (N = 2029) |
Age (No., %): Active duty: 18-25 yr: (536, 31.3) 26-35 yr: (915, 53.4) ≥ 36 yr: (264, 15.4) ANG: 18-25 yr: (11, 7.9) 26-35 yr: (54, 38.9) ≥ 36 yr: (74, 53.2) Reserve: 18-25 yr: (15, 8.7) 26-35 yr: (76, 44.2) ≥ 36 yr: (81,47.1) Sex: Active duty: 1221 (71.4) ANG: 113 (83.1) Reserve: 105 (61.4) |
High Ex ≥ 20, High Cy ≥ 20, Low PE ≤ 12, (No., %) Active duty (n = 1436): OB: (38, 2.7) Ex: (410, 28.6) Cy: (337, 23.5) PE: (101, 7) ANG (n = 114): OB: (1, 0.9) Ex: (28, 24.6) Cy: (12, 10.5) PE: (8, 7) Reserve (n = 120): OB: (2, 1.7) Ex: (17, 14.2) Cy: (11, 9.2) PE: (6, 5) |
The multivariable analysis showed that high Ex was significantly higher in females (RR = 1.32), those working in current duties for > 24 months (RR = 1.32), the shift work group (RR = 1.67), and those working > 51 hours at week (RR = 1.63) as compared to the other groups. As the multivariable analysis revealed, high Cy was significantly higher in > 36 age range group (RR = 2.07), the single group (RR = 1.51), the respondents with no children and dependents living at home (RR = 1.42), the Enlisted rank group (RR = 1.47), those with > 24 months in current duties (RR = 1.44), Not a supervisor group (RR = 1.27) and the shift work group (RR = 1.91) than the other groups. This analysis also showed that low PE was significantly higher in females (RR = 1.69) and the non- supervisor group (RR = 1.42) as compared with the other groups. Another predictor for high Ex and high Cy (but Not low PE) was the shift rotation frequency. |
| Dobbs; 2019; United States [59] |
Cross-sectional; 4-Item CATCS for organizational Cy subscale only | Air Force; (N = 285) |
Age: NR Sex: 193 (67.7) |
Cy: 2.1 ± 0.8 | Organizational cynicism and several dimensions of toxic leadership were found to be correlated (ranging from r = 0.26 to r = 0.38). The multivariable analysis showed that the only significant predictor of organizational cynicism (β = 0.33, SE = 0.05, p < 0.001) was the self-promotion (SP) toxic leadership style. |
| Merlini; 2019; United States [60] |
Cross-sectional; 3-Item MBI-GS for Ex subscales only | Mixed; (N = 1912) |
Age: NR Sex: 1415 (74) |
Ex: 2.4 ± 0.8 (N = 1790) |
Burnout mediated the prediction of intent to leave by perceived inclusion; since, inclusion negatively and directly affected burnout (effect = -0.42, p < 0.01). Burnout also positively and directly affected the intent to leave (effect = 0.49, p < 0.01). Lastly, evidence of an indirect effect of inclusion on the intent to leave was observed through burnout (indirect effect = -0.20, 95%CI = (-0.27, -0.14)). |
| Sipos; 2019; United States [61] |
Cross-sectional; Burnout measured on 1-item scale | Army; (N = 737) |
Age (No., %): 18-24 yr: (411, 55.8) 25-29 yr: (205, 27.8) ≥ 30 yr: (119, 16.1) Sex: 536 (72.7) |
(No., %) High burnout: (320, 43.4) |
Based on multiple logistic regression, burnout was significantly higher in the age category of 25-29 years of age than in 18-24-year-olds (OR = 2.07). Besides, it was found that the odds of burnout increased as a result of increasing classroom hours (OR = 1.4) and military duty hours (OR = 1.21) but decreased by enhancing the time management score (OR = 0.98) and the classroom climate score (OR = 0.96). |
| Vojvodić; 2019; Serbia [62] |
Cross-sectional; 22-Item MBI-HSS | Army; (N = 55) |
Age: Range, 25-55, (No., %) ≤ 30 yr: (41, 74.5) > 30 yr: (11, 25.5) Sex: 48 (87.3) |
No. (%) of low, moderate and high, respectively EE: 49 (89.1), 6 (10.9), 0 (0) DP: 48 (87.3), 7 (12.7), 0 (0) PA: 36 (65.5), 7 (12.7), 12 (21.8) |
EE and DP were associated with anxiety and physical health. Burnout was also correlated with part of defense mechanism (DM). With regard to the DP categories, humor DM and acting out DM were significantly different. Regarding the PA categories, humor DM, altruism DM, rationalization DM, and devaluation DM were found to be significantly different. |
| Ndongo; 2020; Cameroon [63] |
Cross-sectional; 16-Item MBI-GS | Army; (N = 354) |
Age: Mean, 33 (SD, 8) Sex: 319 (90.1) |
(No., %) moderate or high OB: (302, 85.3) Low, Moderate and High Ex: (104, 29.4), (74,20.9), (176, 49.7) Cy: (27, 7.6), (116, 32.8), (211, 59.6) PE: (85, 24), (95, 26.8), (174, 49.2) |
The significant presence of high Cy (P < 0.001) in the army (59.6%), as compared to other occupations, was confirmed. |
| Vojvodic; 2020; Serbia [64] |
Cross-sectional; 22-Item MBI-HSS | Army; (N = 311) |
Age: (No., %) 23-30 yr: (98, 31.5) 31-39 yr: (140, 45) 40-53 yr: (73, 23.5) Sex: 284 (91.3) |
EE: 8.8 ± 7.5 DP: 3.2 ± 4.2 PA: 40.5 ± 7.8 |
Age groups significantly differed only on the EE subscale (23-30: 9.37 ± 7.16, 31-39: 8.26 ± 6.94, 40-53: 8.97 ± 8.78, p = 0.016). Increasing anxiety led to an increase of EE and DP but decreased PA. |
MBI = Maslach Burnout Inventory; BM-Rep = subset of 16 items of the Pines-Aronson-Kafry Burnout Measure; MBI-GS = Maslach Burnout Inventory- General Survey; MBI-HSS = Maslach Burnout Inventory- Human Services Survey; SMBM = Shirom–Melamed Burnout Measure; ProQOL = Professional Quality of Life Scale; UBOS = Utrecht Burnout Scale (Dutch adaptation of the MBI); CMBI = Chinese Maslach Burnout Inventory; OBI = Oldenburg Burnout Inventory; CBB = Cuestionario Breve de Burnout (the Brief Burnout Questionnaire); CATCS = Cynical Attitudes Toward College Scale; OB = Overall Burnout; EE = Emotional Exhaustion; DP = Depersonalization; PA = Personal Accomplishment; PE = professional efficacy; Cy = Cynicism; Ex = Exhaustion; PF = Physical fatigue; CW = Cognitive weariness; yr = Year.