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Occupational Health Risk Among Teachers in Higher Education

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1012))

Abstract

In order to provide an integrated response to the needs of working populations, specifically in mental illness prevention and mental health promotion, a holistic and multidisciplinary perspective must be developed. Prevention measures should be fully integrated in specific work contexts, the first step in the construction of intervention policies and tools being an effective assessment.

The present study intends to investigate Psychosocial Risk factors (PRs) and anxiety underlying work reality in Higher Education (HE) teachers, based on transactional model occupational stress approaches.

An empirical study was carried out involving 97 HE teachers, working at University of Aveiro departments (n = 50) and Polytechnic’s Schools (n = 47). For this assessment, the following instruments were used: Copenhagen Psychosocial Questionnaire (COPSOQ, medium version) and State-Trait Anxiety Inventory (STAI). Our study points to four main findings: (1) work demands dimensions represent the most health risk, with Health/Well-being dimensions presenting the most significant correlations for anxiety increase in HE teachers; (2) a large percentage of respondents presented significant psychological anxiety symptoms, this effect being strongly higher in females;

The present study responds to the research gap in the work-related context of HE teachers, constituting the first step towards the construction of intervention tools integrated in the work specificities, in which health systems must be involved.

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Correspondence to Isabel Souto .

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Souto, I., Pereira, A., Brito, E., Sancho, L., Barros, S. (2019). Occupational Health Risk Among Teachers in Higher Education. In: Cotrim, T., Serranheira, F., Sousa, P., Hignett, S., Albolino, S., Tartaglia, R. (eds) Health and Social Care Systems of the Future: Demographic Changes, Digital Age and Human Factors. HEPS 2019. Advances in Intelligent Systems and Computing, vol 1012. Springer, Cham. https://doi.org/10.1007/978-3-030-24067-7_36

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