Table 3 Characteristics of studies on burnout among combined populations of healthcare workers in sub-Saharan Africa (N = 18)

Bhagavathula, 2018 [96]

Ethiopia

Healthcare workers at a teaching hospital (N = 248)

MBI

Emotional exhaustion (mean ± SD): 5.4 ± 1.2

Inefficacy: 5.1 ± 1.7

Cynicism: 4.8 ± 2.0

13.7% reported overall burnout.

Burnout was associated with age (p = 0.008), number of patients treated per day (p < 0.001), and shift work (p < 0.001). In multivariable analyses, sex, marital status, profession, and work experience were significantly associated with burnout subscales (p < 0.01).

Biksegn, 2016 [97]

Ethiopia

Healthcare workers at a teaching hospital (N = 334)

CBI

50.3 ± 17.2 (mean ± SD)

Nurses had the highest prevalence (82.8%) of burnout and laboratory technicians had the lowest (2.8%). Job insecurity, history of physical illness, low interest in profession, poor relationship status with managers, worry of contracting infection or illness and physical/verbal abuse were predictors of burnout.

Bonenberger, 2014 [98]

Ghana

Healthcare workers (N = 256)

Instrument to measure motivation with 7 outcome constructs, including burnout

3.3 ± 1.0 (mean ± SD)

Motivation and job satisfaction were significantly associated with career development (OR = 0.56, 95% CI: 0.36–0.86), workload (OR = 0.58, 95% CI: 0.34–0.99), management (OR = 0.51, 95% CI: 0.30–0.84), organizational commitment (OR = 0.36, 95% CI: 0.19–0.66), and burnout (OR = 0.59, 95% CI: 0.39–0.91).

Crabbe, 2004 [99]

South Africa

Healthcare workers in trauma unit of a hospital (N = 38)

MBI

61% had high emotional exhaustion, 50% high depersonalization, and 50% high reduced personal accomplishment

At least half of respondents reported high professional burnout in all 3 MBI subscales.

Fiadzo, 1997 [100]

Ghana

Healthcare workers (N = 287)

MBI

Not reported

Study provides support for burnout progression model

Kim, 2018 [101]

Malawi

Healthcare workers providing clinical care for HIV-positive patients (N = 520)

MBI

62% met criteria for total burnout, with 55% reporting moderate-high emotional exhaustion, 31% moderate-high depersonalization, and 46% low-moderate personal accomplishment.

Burnout was associated with self-reported suboptimal patient care (OR = 3.22, 95% CI: 2.11–4.90; p < 0.0001)

Kokonya, 2014 [102]

Kenya

Healthcare workers at a national hospital (N = 345)

Compassion Fatigue Self-Test

95.4% reported high burnout

96.7% of medical practitioners and 94.1% of nurses reported high burnout. Burnout was not significantly associated with participants’ sex, age, marital status, religion, education, or number of years as a healthcare provider.

Kruse, 2009 [103]

Zambia

Healthcare providers (N = 483 active clinical staff completed questionnaire; N = 50 in focus groups, N = 4 interviews)

Occupational burnout measured on 5-item scale

51% of respondents reported occupational burnout

Occupational burnout was associated with having another job (RR = 1.4, 95% CI: 1.2–1.6) and knowing a co-worker who left in the last year (RR = 1.6, 95% CI: 1.3–2.2).

Ledikwe, 2018 [104]

Botswana

Healthcare workers at a public health facility (N = 1348)

MBI-GS

Professional efficacy (mean ± SD): 4.9 ± 1.1

Exhaustion: 2.3 ± 1.7

Cynicism: 2.4 ± 1.4

Overall job satisfaction assessed by the Job In General Scale was significantly higher for healthcare workers who participated in 7 or more activities as part of the Botswana’s Workplace Wellness Program (WWP) compared with those who did not participate in any activities (p = 0.004). Stress levels (p = 0.006), measured on the Stress in General scale, and exhaustion (p < 0.001), measured on the MBI, were significantly lower among those with high participation in WWP activities.

Madede, 2017 [105]

Mozambique

Healthcare workers (quantitative: N = 92 baseline and 49 post-intervention; N = 17 qualitative interviews)

MBI

At baseline, 67.1% low, 15.9% moderate, and 17.1% high burnout. After intervention, 71.1% low, 17.8% moderate, 11.1% high burnout.

There were no significant differences in emotional exhaustion between baseline and post intervention, for any intervention groups. Job satisfaction, emotional exhaustion and work engagement showed no significant differences between baseline and post intervention.

McAuliffe, 2009 [106]

Malawi

Healthcare workers in public and private facilities (N = 153)

MBI

31% reported high emotional exhaustion, 5% reported high depersonalization, and 45% reported low personal accomplishment

The adequate resources subscale of the Health Care Providers Work Index correlates with emotional exhaustion on the MBI.

Mutale, 2013 [107]

Zambia

Healthcare workers from health facilities (N = 96)

“I feel emotionally drained at the end of the day” and “Sometimes when I get up in the morning, I dread having to face another day at work.”

Not reported

Burnout was higher among women as compared to men in 2 of the 3 districts. Linear regressions showed major determinants of higher motivation were female (p = 0.008) and working in non-clinical areas (for example, pharmacists or laboratory technicians, p = 0.039).

Ndetei, 2008 [108]

Kenya

Healthcare workers at a psychiatric hospital (N = 121)

MBI-HSS and MBI-GS

Emotional exhaustion (mean ± SD): 17.2 ± 9.8

Depersonalization: 7.3 ± 5.8

Personal accomplishment: 29.3 ± 10.3

Emotional exhaustion was significantly associated with younger age (p < 0.001), number of children (p = 0.003), number of years worked (p = 0.049), heavy workload (p < 0.001) and low morale (p = 0.001). Depersonalization was significantly associated with heavy workload (p = 0.034). Reduced personal accomplishment was associated with younger age (p = 0.03).

Nel, 2013 [109]

South Africa

Healthcare workers at public and private hospitals (N = 511)

MBI-HSS

Emotional exhaustion (mean ± SD): 15.2 ± 7.2

Mental distance: 13.6 ± 9.3

The proposed structural model shows paths between job demands and job resources; job demands, emotional intelligence and work wellness; job resources, emotional intelligence and work wellness.

Ojedokun, 2013 [110]

Nigeria

Healthcare workers working in AIDs care (N = 242)

MBI

66.4 ± 21.5 (mean ± SD)

Burnout was significantly associated with aggressive tendency and perceived fear of AIDS (p < 0.01)

Olley, 2003 [111]

Nigeria

Healthcare workers at a teaching hospital (N = 260)

MBI

Not reported

Nurses reported higher scores on burnout subscales compared to other healthcare providers (p < 0.05). Significant differences were found between nurses and other healthcare providers on the General Health Questionnaire-12 (p < 0.01) and the State Trait Anxiety Inventory (p < 0.05).

Thorsen, 2011 [112]

Malawi

Healthcare workers in a referral hospital (N = 101)

MBI-HSS

Emotional exhaustion (mean ± SD): 23.1 ± 9.7

Depersonalization: 6.2 ± 4.8

Personal accomplishment: 37.8 ± 7.5

Sociodemographic characteristics were not associated with the emotional exhaustion subscale of burnout. For the depersonalization and personal accomplishment subscales, number of children was the only significant predictor (p < 0.05).

Weldegebriel, 2016 [113]

Ethiopia

Healthcare workers at public hospitals (N = 304)

Organizational burnout measured as a subdimension of motivation

3.6 ± 1.3 (mean ± SD)

Performance review was the only significant predictor of the burnout dimension of motivation. Respondents who never had a performance review conducted had an average decrease of 0.155 units (95% CI: −0.875 to −0.122) in burnout motivation score as compared to those with formal performance assessment.