NAGIOS: RODERIC FUNCIONANDO

Brazilian Teachers' Absenteeism: Work Design Predictive Model

Repositori DSpace/Manakin

IMPORTANT: Aquest repositori està en una versió antiga des del 3/12/2023. La nova instal.lació está en https://roderic.uv.es/

Brazilian Teachers' Absenteeism: Work Design Predictive Model

Mostra el registre parcial de l'element

dc.contributor.author Pérez Nebra, Amalia Raquel
dc.contributor.author Greghi Sticca, Marina
dc.contributor.author Queiroga, Fabiana
dc.contributor.author Tordera Santamatilde, María Nuria
dc.date.accessioned 2022-04-27T08:54:43Z
dc.date.available 2022-04-27T08:54:43Z
dc.date.issued 2021
dc.identifier.citation Pérez Nebra, Amalia Raquel Greghi Sticca, Marina Queiroga, Fabiana Tordera Santamatilde, María Nuria 2021 Brazilian Teachers' Absenteeism: Work Design Predictive Model International Journal of Educational Organization and Leadership 28 2 117 130
dc.identifier.uri https://hdl.handle.net/10550/82412
dc.description.abstract Sickness-related absenteeism in teachers represents financial, social, and human costs. This study aimed to analyze the relationship between work characteristics and lengths of absence. The main hypothesis is that different work characteristics are predictors of different lengths of absenteeism. In total, 1,530 teachers participated in the study. The results supported the main hypothesis and suggested that physical demands, task identity, and job complexity are useful to explain absenteeism. It is concluded that analyzing different absenteeism lengths makes it possible to broaden the phenomenon discussion and qualify the relationship between work characteristics and absenteeism. This study has implications for interventions to reduce absenteeism.
dc.language.iso eng
dc.relation.ispartof International Journal of Educational Organization and Leadership, 2021, vol. 28, num. 2, p. 117-130
dc.subject Treball
dc.subject Procediment del treball
dc.subject Treball Mesurament
dc.subject Absentisme laboral
dc.title Brazilian Teachers' Absenteeism: Work Design Predictive Model
dc.type journal article es_ES
dc.date.updated 2022-04-27T08:54:43Z
dc.identifier.doi 10.18848/2329-1656/CGP/v28i02/117-130
dc.identifier.idgrec 151843
dc.rights.accessRights open access es_ES

Visualització       (396.6Kb)

Aquest element apareix en la col·lecció o col·leccions següent(s)

Mostra el registre parcial de l'element

Cerca a RODERIC

Cerca avançada

Visualitza

Estadístiques