The authors have declared that no competing interests exist.
Faculty members face demands such as research, outreach programs, and management activities. Such demands may expose faculty to burnout. Burnout affects the physical, psychological and social health of faculty members, but it is still unclear how it affects their quality of life. We aimed to assess the impact of burnout on the quality of life (QoL) of faculty members from different fields of knowledge.
Cross-sectional study using validated tools for measuring burnout and QoL (
More than a third of the faculty members (n = 127; 36.6%) suffered from burnout. Men had higher scores of quality of life than women in the physical health (p = 0.001; d<0.5), psychological (p = 0.001; d<0.5) and social relationships (p = 0.048; d<0.5) domains. Women were more exhausted than men (p = 0.001; d<0.5). Faculty members’ perception of quality of life and burnout did not differ according to their field of knowledge (p>0.05). Participants who felt tired before arriving at work were less likely to report good quality of life (OR = 0.46; 95% CI = 0.21–0.99). Faculty members who stated they needed more time to relax after work were less likely to be satisfied with their health (OR = 0.20; 95% CI = 0.10–0.40). Burnout showed a negative association with quality of life (λ = 0.87; p < 0,001; df = 8).
Burnout negatively affects faculty members’ quality of life, regardless of their field of knowledge. Our results suggest the implementation of programs and actions to prevent burnout to faculty members, especially to women, as their quality of life may affect the quality of the education provided.
Working at university as a faculty member may provide satisfactory experiences. However, university teaching can also be stressful and may deteriorate workers’ quality of life [
Many studies [
Studies on quality of life of university faculty members are scarce [
Our hypothesis is that faculty members’ field of knowledge and burnout may affect their quality of life. We aimed to verify (i) the differences in quality of life and burnout according to faculty members’ gender and field of knowledge and (ii) the association between burnout and faculty members’ quality of life. Identifying groups that have higher risks of presenting worse quality of life may help educational managers to direct strategies towards faculty members’ health and retention.
This is a cross-sectional study approved by the institutional research ethics committee. This study was held at a public university, with 90 undergraduate programs, 20 PhD programs, 44 academic master’s degree programs, and several other post-graduation programs. Participating faculty members were selected from different academic units and fields of knowledge: applied human/social sciences, life/health sciences, and exact/ technological sciences. As an inclusion criterion, participants should have been working for at least one year in the institution.
When the study was carried out, 1,324 faculty members met the inclusion criterion. In order to determine the differences with a medium effect size (f2 = 0.15; p<0.05), with sampling error set at 5% and statistic power at 80%, the sample size comprised 298 participants [
Studies have shown that the response rate regarding the study population is between 17% and 35% [
After signing an informed consent, eligible faculty members answered, in their workplace, a self-administered questionnaire with socio-demographic data (age, gender, marital status, working time in the institution, weekly workload, field of knowledge, academic degree), the Oldenburg Burnout Inventory (OLBI), and the World Health Organization Quality of Life-Abbreviated version (WHOQOL-Bref).
OLBI assessed the burnout syndrome in the study population [
The Brazilian validated version of WHOQOL-Bref, a self-administered general questionnaire on quality of life, assessed participants’ quality of life [
Descriptive statistics (frequency, percentage, mean, and standard deviation) were used to describe the sample, quality of life, and the burnout syndrome. The assumptions of structural equation modeling (SEM) were verified–sample size, normality, missing data, outliers, multicollinearity, singularity, linearity, homoscedasticity [
The reliability of each scale in this study was assured through internal consistency (Cronbach’s alpha) [
We also carried out a binary logistic regression analysis to assess which items of the OLBI scale are more probable to affect the general perception of quality of life and satisfaction with health. In this case, OLBI and WHOQOL-Bref answers were dichotomized (0 = disagree, 1 = agree for OLBI; 0 = poor, 1 = good for quality of life, 0 = dissatisfied, 1 = satisfied with health).
We performed structural equation modeling (SEM) to confirm the theoretical framework proposed in this study: the impact of the burnout syndrome in faculty members’ quality of life. In the model, OLBI dimensions (disengagement and exhaustion) behaved as independent variables; and the four domains of WHOQOL-Bref (physical health, psychological, social relationships, and environment) behaved as dependent variables. We used the maximum likelihood method and the traditional chi-square, the chi-square/degrees of freedom ratio (χ2/gl), the Root Mean Square Residual (RMR), the Goodness-of-Fit Index (GFI), the Adjusted Goodness-of-Fit Index (AGFI), the Comparative Fit Index (CFI), and the Root-Mean-Square Error of Approximation (RMSEA) as indices of SEM [
The significance level was set at 5% for all tests. SPSS Statistics (Statistical Package for Social Sciences) and AMOS (Analysis of Moment Structures) were used for data analysis.
The final sample comprised 366 participants. Most of them (59.3%) were men, aged between 28 and 69 years (M = 44.8 years; SD = 9.96), and married (74%). They have been working in the institution for 12.3 years (mean) (SD = 11.12). Regarding their field of knowledge, 101 (27.6%) were from exact/technological sciences, 124 (33.9%) from applied human/social sciences, and 141 (38.5%) from health/life sciences. Most participants (85%) had a PhD degree and worked with exclusive dedication to the university (40 hours/week) (86.1%) (
Study variables | |||
---|---|---|---|
Gender, n(%), N = 366 | Male | 217 | (59.3) |
Female | 148 | (40.4) | |
Not answered | 1 | (0.3) | |
Marital status, n(%), N = 366 | Single | 53 | (14.5) |
Married/stable union | 271 | (74.0) | |
Widowed | 3 | (0.8) | |
Divorced | 39 | (10.7) | |
Mean age, years (SD) | 44.8 | (9.96) | |
Years working in the instituition, mean (SD) | 12.34 | (11.12) | |
Field of knowledge, n(%), N = 366 | Exact/technological sciences | 101 | (27.6) |
Human/social sciences | 124 | (33.9) | |
Health/life sciences | 141 | (38.5) | |
Week workload, n(%), N = 366 | 20 hours | 5 | (1.4) |
40 hours | 45 | (12.3) | |
40 hours (exclusive dedication) | 315 | (86.1) | |
Not answered | 1 | (0.3) | |
Degree, n(%), N = 366 | Specialization | 13 | (3.6) |
Mater'sdegree | 42 | (11.5) | |
PhD Degree | 233 | (63.7) | |
Post-doctorate | 78 | (21.3) | |
WHOQOL-Bref domain, mean (SD), N = 347 | Physical health | 71.13 | (16.81) |
Psychological | 71.63 | (15.69) | |
Social relationships | 67.40 | (19.17) | |
Environment | 65.10 | (13.87) | |
WHOQOL-Bref(1)—"How would you rate your quality of life?" n(%), N = 347 | Very poor | 0 | (0.0) |
Poor | 18 | (5.2) | |
Neither poor nor good | 53 | (15.3) | |
Good | 213 | (61.4) | |
Very good | 62 | (17.9) | |
Not answered | 1 | (0.3) | |
WHOQOL-Bref(2)—"How satisfied are you with your health?" n(%), N = 347 | Very dissatisfied | 1 | (0.3) |
Dissatisfied | 43 | (12.4) | |
Neither satisfied nor dissatisfied | 64 | (18.4) | |
Satisfied | 184 | (53.0) | |
Very satisfied | 55 | (15.9) | |
OLBI classification, n(%), N = 347 | Without burnout | 102 | (29.4) |
Disengagement | 27 | (7.8) | |
Exhaustion | 91 | (26.2) | |
With burnout | 127 | (36.6) |
Male participants presented higher scores for quality of life in the physical health, psychological and social relationships domains (p<0.05; 0.22≤
Domains | Male (n = 207) | Female (n = 139) | p | ||||
---|---|---|---|---|---|---|---|
M | SD | M | SD | ||||
73.64 | 15.72 | 67.62 | 17.62 | 3.33 | 0.001 | 0.36 | |
74.50 | 13.44 | 67.57 | 17.66 | 4.13 | 0.001 | 0.45 | |
69.16 | 18.35 | 65.02 | 19.99 | 1.99 | 0.048 | 0.22 | |
65.59 | 13.70 | 64.73 | 13.56 | 0.58 | 0.565 | - | |
2.07 | 0.58 | 2.09 | 0.65 | -0.23 | 0.817 | - | |
2.31 | 0.69 | 2.64 | 0.74 | -4.29 | 0.001 | 0.47 |
Domains | Exact/technological sciences (n = 96) | Human/social sciences (n = 114) | Health/life sciences(n = 137) | F | p | |||
---|---|---|---|---|---|---|---|---|
M | SD | M | SD | M | SD | |||
72.54 | 16.12 | 68.73 | 17.74 | 72.13 | 16.40 | 1.75 | 0.175 | |
73.00 | 14.46 | 70.94 | 15.65 | 71.23 | 16.57 | 0.52 | 0.595 | |
67.45 | 19.42 | 66.12 | 19.15 | 68.43 | 19.08 | 0.45 | 0.637 | |
62.86 | 12.07 | 66.10 | 13.80 | 65.85 | 14.98 | 1.76 | 0.174 | |
2.03 | 0.62 | 2.02 | 0.59 | 2.17 | 0.61 | 2.27 | 0.105 | |
2.34 | 0.70 | 2.50 | 0.74 | 2.47 | 0.74 | 1.48 | 0.230 |
ANOVA; df = 2.344
Concerning the general perception of quality of life, participants who agreed with the items “There are days when I feel tired before I arrive at work” and “After work, I tend to need more time than in the past in order to relax and feel better” were less likely to report good quality of life (OR = 0.46; 95% CI = 0.21–0.99; p = 0.048; OR = 0.28; 95% CI = 0.12–0.63; p = 0.002; respectively). Concerning the general perception of health, faculty members who agreed with the item “After work, I tend to need more time than in the past in order to relax and feel better” were also less likely to report satisfaction with their health (OR = 0.20; 95% CI = 0.10–0.40) (
Variable | QoL N/Total(%) | OR [95%CI] | Health N/Total(%) | OR [95%CI] | ||
---|---|---|---|---|---|---|
Poor | Good | Dissatisfied | Satisfied | |||
Over time, one can become disconnected from this type of work. | 34/71(47.9) | 59/275(21.4) | 0.60[0.21–1.70] | 53/108(49.1) | 41/239(17.1) | 1.11[0.44–2.76] |
I feel more and more engaged in my work. | 33/71(46.5) | 195/275(70.9) | 1.07[0.43–2.65] | 49/108(45.4) | 179/239(74.9) | 1.44[0.66–3.17] |
Lately, I tend to think less at work and do my job almost mechanically. | 32/71(45.1) | 52/275(18.9) | 0.67[0.31–1.47] | 44/108(40.7) | 41/239(17.1) | 1.02[0.49–2.14] |
I find my work to be a positive challenge. | 49/71(69.0) | 248/275(90.2) | 2.28[0.96–5.37] | 77/108(71.3) | 220/239(92.0) | 2.11[0.92–4.85] |
It happens more and more often that I talk about my work in a negative way. | 30/71(42.2) | 44/275(16.0) | 0.67[0.30–1.50] | 42/108(38.9) | 33/239(13.8) | 1.00[0.46–2.16] |
Sometimes I feel sickened by my work tasks. | 47/71(66.2) | 82/275(29.8) | 0.72[0.32–1.62] | 67/108(62.0) | 63/239(26.4) | 0.68[0.33–1.43] |
There are days when I feel tired before I arrive at work. | 55/70(78.6) | 116/275(42.2) | 77/107(72.0) | 95/239(39.7) | 0.81[0.42–1.59] | |
After work, I tend to need more time than in the past in order to relax and feel better. | 57/71(80.3) | 103/275(37.4) | 86/108(79.6) | 75/239(31.4) | ||
After my work, I usually feel worn out and weary. | 52/71(73.2) | 107/275(38.9) | 1.03[0.46–2.31] | 78/108(72.2) | 82/239(34.3) | 0.83[0.41–1.68] |
** p ≤ 0,01
* p ≤ 0,05; OR = odds ratio; CI = confidence interval; QoL = quality of life
We confirmed the theoretical framework proposed in this study using the maximum likelihood method. Burnout showed a significant negative association with quality of life (λ = 0.87; p < 0.001; df = 8) (
Parameters:
This study confirms that work issues affect faculty members’ quality of life. This is a pioneer study in approaching the effect of the burnout syndrome on the quality of life of faculty members from different fields of knowledge.
Most participants were satisfied with their quality of life and health. Satisfaction refers to a positive general and emotional state. Faculty members’ affective commitment is closely related to job satisfaction and involvement [
In our study, female participants had a lower perception of their quality of life in the physical health, psychological, and social relationships domains in comparison to their male peers. They were also more exhausted than male faculty members were. Studies have shown that men and women show different risk behaviors, and men seem to give less importance to their physical and psychological symptoms when compared to women [
No significant difference was found among faculty members from different fields of knowledge. Perhaps, the institutional work environment and faculty members’ relation with work have a direct effect on their quality of life, regardless of the field of knowledge or particularities of the work process. The high levels of burnout among faculty members may be another explanation for these results. More than a third of participants suffered from burnout. This result was already expected, since studies carried out in Portugal, Germany, Spain, Mexico, Colombia, United States, and Canada have shown that the prevalence of the burnout syndrome among faculty members is high [
The structural equation modeling confirms that burnout may negatively affect faculty members’ quality of life. General feelings of work overload, a strong need for rest, and a state of physical exhaustion are considered important risk factors for the general perception of quality of life and satisfaction with health. Faculty members who feel tired and lack energy are the most affected. Those members have more chances of not enjoying life outside work, not seeing a meaning in their lives, and needing constant medical care. In addition, they are unsatisfied with themselves, with their sleep, their physical appearance, their concentration, their ability to carry out daily activities, and their ability to work. They also have more chances of having negative feelings, such as bad humor, despair, anxiety, and depression. Our results corroborate previous research stating a negative effect of burnout on healthcare faculty members’ quality of life [
Quality of life and burnout among faculty members are not solely determined by the intrinsic character of the job. They are also influenced by how their work is organized, how the educational institution deals with their faculty, and how faculty members see their relationship with their institution [
Our research has some methodological limitations. It is a cross-sectional study with a convenience sample from only one public higher education institution, which restricts generalizations of our results to similar institutions. The use of a generic quality of life questionnaire may have limited conclusions about specific aspects related to work. However, this research used valid and reliable tools to investigate the quality of life and burnout among faculty members, which allows replication and comparisons with further studies. In addition, our study confirms the theoretical model on the effect of burnout on faculty members’ quality of life, with practical and important implications for managers. Knowing how burnout relates to quality of life may support and guide more effective health promotion strategies in the work environment of these professionals.
For future research, other methodological designs can be used (with longitudinal studies and probabilistic sampling), by including universities of different legal natures (public and private), inserting other variables to explain quality of life, e.g. personal (control locus, personality factors) and organizational variables (quality of life at work, perceptions of organizational justice, organizational health, social support, and organizational values–important aspects of the institutional culture). The development of future qualitative studies focused on the causes of faculty members’ distress may also contribute to their work, considering individual and social repercussions in their own health and in the quality of the education provided.