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acessibilidade

http://hdl.handle.net/10071/15629
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acessibilidade
DC FieldValueLanguage
dc.contributor.authorGrilo, L. M.-
dc.contributor.authorGrilo, H. L.-
dc.contributor.authorBogas, S. P.-
dc.contributor.authorJunça Silva, A.-
dc.date.accessioned2018-04-17T10:28:55Z-
dc.date.available2018-04-17T10:28:55Z-
dc.date.issued2017-
dc.identifier.isbn978-0-7354-1596-6-
dc.identifier.issn1551-7616por
dc.identifier.urihttps://ciencia.iscte-iul.pt/id/ci-pub-47599-
dc.identifier.urihttp://hdl.handle.net/10071/15629-
dc.description.abstractIn European countries, namely in Portugal, it is common to hear some people mentioning that they are exposed to excessive and continuous psychosocial stressors at work. This is increasing in diverse activity sectors, such as, the Services sector. A representative sample was collected from a Portuguese Services’ organization, by applying a survey (internationally validated), which variables were measured in five ordered categories in Likert-type scale. A multinomial logistic regression model is used to estimate the probability of each category of the dependent variable general health perception where, among other independent variables, burnout appear as statistically significant.por
dc.language.isoengpor
dc.publisherAmerican Institute of Physicspor
dc.relationinfo:eu-repo/grantAgreement/FCT/5876/147442/PTpor
dc.rightsopenAccess-
dc.subjectLogistic regressionpor
dc.subjectBurnoutpor
dc.titleMultinomial logistic regression in worker’s healthpor
dc.typeconferenceObjecten_US
dc.pagination1-6por
dc.publicationstatusPublicadopor
dc.peerreviewedyespor
dc.journalAIP Conference Proceedingspor
dc.distributionInternacionalpor
dc.volume1906por
degois.publication.firstPage1por
degois.publication.lastPage6por
degois.publication.titleAIP Conference Proceedingspor
dc.date.updated2018-04-17T10:28:05Z-
dc.identifier.doi10.1063/1.5012392-
Appears in Collections:BRU-CRI - Comunicações a conferências internacionais

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