Back

Job Demands, Social Support, and Burnout among Public Senior High School Teachers, Ghana

Akutey, R.; Ansah, E. W.; Apaak, D.

2023-11-22 occupational and environmental health
10.1101/2023.11.21.23298859 medRxiv
Show abstract

This study aimed to investigate the extent to which job demands and social support predict burnout of public senior high school (S.H.S.) teachers in Ghana, and to determine the mediating effect of job resources in the relation between job demands and burnout among these teachers. Employing a quantitative survey, 1028 public S.H.S. teachers were selected using purposive and voluntary sampling methods. A questionnaire adopted from pre-existing standardized instruments yielded composite reliability between 0.94 and 0.98. Data was analyzed using mean, standard deviation, and multiple linear regression. Results revealed a high level of job demands (M = 3.23, SD = 0.43), social support (M = 3.02, SD = 0.54), and burnout (M = 3.33, SD = 0.92) among the teachers. Also, multiple linear regression results indicate that job demands, and social support predict burnout of the teachers. Furthermore, social support is a partial mediator of the effect of job demands on teachers burnout. Therefore, perceived high level of burnout is an effect of high levels of job demands, which poses a serious threat to the health and well-being of these teachers and compromises teaching quality in Ghanas S.H.S. However, this challenge can be prevented or reduced by providing more social support to the teachers. Hence, government, management, and other educational stakeholders need to provide a strong safety leadership in all matters that concerns teachers health and safety. The school administrators and teachers are also encouraged to promote social support vertically and horizontally.

Matching journals

The top 2 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.