Validity of a Job-Exposure Matrix for Psychosocial Job Stressors: Results from the Household Income and Labour Dynamics in Australia Survey.
Identifieur interne : 001415 ( PubMed/Checkpoint ); précédent : 001414; suivant : 001416Validity of a Job-Exposure Matrix for Psychosocial Job Stressors: Results from the Household Income and Labour Dynamics in Australia Survey.
Auteurs : A. Milner [Australie] ; I. Niedhammer [France] ; J-F Chastang [France] ; M J Spittal [Australie] ; A D Lamontagne [Australie]Source :
- PloS one [ 1932-6203 ] ; 2016.
Descripteurs français
- KwdFr :
- MESH :
- Wicri :
- geographic : Australie.
English descriptors
- KwdEn :
- MESH :
- geographic : Australia.
- Adult, Female, Humans, Income, Male, Middle Aged, Occupational Diseases, Stress, Psychological, Surveys and Questionnaires, Young Adult.
Abstract
A Job Exposure Matrix (JEM) for psychosocial job stressors allows assessment of these exposures at a population level. JEMs are particularly useful in situations when information on psychosocial job stressors were not collected individually and can help eliminate the biases that may be present in individual self-report accounts. This research paper describes the development of a JEM in the Australian context.
DOI: 10.1371/journal.pone.0152980
PubMed: 27049527
Affiliations:
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pubmed:27049527Le document en format XML
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Niedhammer</name><affiliation wicri:level="3"><nlm:affiliation>INSERM, UMR_S 1136, Pierre Louis Institute of Epidemiology and Public Health, Department of social epidemiology, Paris, France.</nlm:affiliation><country xml:lang="fr">France</country><wicri:regionArea>INSERM, UMR_S 1136, Pierre Louis Institute of Epidemiology and Public Health, Department of social epidemiology, Paris</wicri:regionArea><placeName><region type="region">Île-de-France</region><region type="old region">Île-de-France</region><settlement type="city">Paris</settlement></placeName></affiliation></author><author><name sortKey="Chastang, J F" sort="Chastang, J F" uniqKey="Chastang J" first="J-F" last="Chastang">J-F Chastang</name><affiliation wicri:level="3"><nlm:affiliation>INSERM, UMR_S 1136, Pierre Louis Institute of Epidemiology and Public Health, Department of social epidemiology, Paris, France.</nlm:affiliation><country xml:lang="fr">France</country><wicri:regionArea>INSERM, UMR_S 1136, Pierre Louis Institute of Epidemiology and Public Health, Department of social epidemiology, Paris</wicri:regionArea><placeName><region type="region">Île-de-France</region><region type="old region">Île-de-France</region><settlement type="city">Paris</settlement></placeName></affiliation></author><author><name sortKey="Spittal, M J" sort="Spittal, M J" uniqKey="Spittal M" first="M J" last="Spittal">M J Spittal</name><affiliation wicri:level="4"><nlm:affiliation>Centre for Mental Health, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Australia.</nlm:affiliation><country xml:lang="fr">Australie</country><wicri:regionArea>Centre for Mental Health, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne</wicri:regionArea><placeName><settlement type="city">Melbourne</settlement><region type="état">Victoria (État)</region><settlement type="city">Melbourne</settlement></placeName><orgName type="university">Université de Melbourne</orgName></affiliation></author><author><name sortKey="Lamontagne, A D" sort="Lamontagne, A D" uniqKey="Lamontagne A" first="A D" last="Lamontagne">A D Lamontagne</name><affiliation wicri:level="3"><nlm:affiliation>Work, Health, & Wellbeing Unit, Population Health Strategic Research Centre, School of Health & Social Development, Deakin University, Melbourne, Australia.</nlm:affiliation><country xml:lang="fr">Australie</country><wicri:regionArea>Work, Health, & Wellbeing Unit, Population Health Strategic Research Centre, School of Health & Social Development, Deakin University, Melbourne</wicri:regionArea><placeName><settlement type="city">Melbourne</settlement><region type="état">Victoria (État)</region></placeName></affiliation></author></analytic><series><title level="j">PloS one</title><idno type="eISSN">1932-6203</idno><imprint><date when="2016" type="published">2016</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Adult</term><term>Australia</term><term>Female</term><term>Humans</term><term>Income</term><term>Male</term><term>Middle Aged</term><term>Occupational Diseases</term><term>Stress, Psychological</term><term>Surveys and Questionnaires</term><term>Young Adult</term></keywords><keywords scheme="KwdFr" xml:lang="fr"><term>Adulte</term><term>Adulte d'âge moyen</term><term>Australie</term><term>Enquêtes et questionnaires</term><term>Femelle</term><term>Humains</term><term>Jeune adulte</term><term>Maladies professionnelles</term><term>Mâle</term><term>Revenu</term><term>Stress psychologique</term></keywords><keywords scheme="MESH" type="geographic" xml:lang="en"><term>Australia</term></keywords><keywords scheme="MESH" xml:lang="en"><term>Adult</term><term>Female</term><term>Humans</term><term>Income</term><term>Male</term><term>Middle Aged</term><term>Occupational Diseases</term><term>Stress, Psychological</term><term>Surveys and Questionnaires</term><term>Young Adult</term></keywords><keywords scheme="MESH" xml:lang="fr"><term>Adulte</term><term>Adulte d'âge moyen</term><term>Australie</term><term>Enquêtes et questionnaires</term><term>Femelle</term><term>Humains</term><term>Jeune adulte</term><term>Maladies professionnelles</term><term>Mâle</term><term>Revenu</term><term>Stress psychologique</term></keywords><keywords scheme="Wicri" type="geographic" xml:lang="fr"><term>Australie</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">A Job Exposure Matrix (JEM) for psychosocial job stressors allows assessment of these exposures at a population level. JEMs are particularly useful in situations when information on psychosocial job stressors were not collected individually and can help eliminate the biases that may be present in individual self-report accounts. This research paper describes the development of a JEM in the Australian context.</div></front></TEI><pubmed><MedlineCitation Status="MEDLINE" Owner="NLM"><PMID Version="1">27049527</PMID><DateCreated><Year>2016</Year><Month>04</Month><Day>07</Day></DateCreated><DateCompleted><Year>2016</Year><Month>08</Month><Day>22</Day></DateCompleted><DateRevised><Year>2016</Year><Month>04</Month><Day>23</Day></DateRevised><Article PubModel="Electronic-eCollection"><Journal><ISSN IssnType="Electronic">1932-6203</ISSN><JournalIssue CitedMedium="Internet"><Volume>11</Volume><Issue>4</Issue><PubDate><Year>2016</Year></PubDate></JournalIssue><Title>PloS one</Title><ISOAbbreviation>PLoS ONE</ISOAbbreviation></Journal><ArticleTitle>Validity of a Job-Exposure Matrix for Psychosocial Job Stressors: Results from the Household Income and Labour Dynamics in Australia Survey.</ArticleTitle><Pagination><MedlinePgn>e0152980</MedlinePgn></Pagination><ELocationID EIdType="doi" ValidYN="Y">10.1371/journal.pone.0152980</ELocationID><Abstract><AbstractText Label="INTRODUCTION" NlmCategory="BACKGROUND">A Job Exposure Matrix (JEM) for psychosocial job stressors allows assessment of these exposures at a population level. JEMs are particularly useful in situations when information on psychosocial job stressors were not collected individually and can help eliminate the biases that may be present in individual self-report accounts. This research paper describes the development of a JEM in the Australian context.</AbstractText><AbstractText Label="METHODS" NlmCategory="METHODS">The Household Income Labour Dynamics in Australia (HILDA) survey was used to construct a JEM for job control, job demands and complexity, job insecurity, and fairness of pay. Population median values of these variables for all employed people (n = 20,428) were used to define individual exposures across the period 2001 to 2012. The JEM was calculated for the Australian and New Zealand Standard Classification of Occupations (ANZSCO) at the four-digit level, which represents 358 occupations. Both continuous and binary exposures to job stressors were calculated at the 4-digit level. We assessed concordance between the JEM-assigned and individually-reported exposures using the Kappa statistic, sensitivity and specificity assessments. We conducted regression analysis using mental health as an outcome measure.</AbstractText><AbstractText Label="RESULTS" NlmCategory="RESULTS">Kappa statistics indicate good agreement between individually-reported and JEM-assigned dichotomous measures for job demands and control, and moderate agreement for job insecurity and fairness of pay. Job control, job demands and security had the highest sensitivity, while specificity was relatively high for the four exposures. Regression analysis shows that most individually reported and JEM measures were significantly associated with mental health, and individually-reported exposures produced much stronger effects on mental health than the JEM-assigned exposures.</AbstractText><AbstractText Label="DISCUSSION" NlmCategory="CONCLUSIONS">These JEM-based estimates of stressors exposure provide a conservative proxy for individual-level data, and can be applied to a range of health and organisational outcomes.</AbstractText></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Milner</LastName><ForeName>A</ForeName><Initials>A</Initials><AffiliationInfo><Affiliation>Work, Health, & Wellbeing Unit, Population Health Strategic Research Centre, School of Health & Social Development, Deakin University, Melbourne, Australia.</Affiliation></AffiliationInfo><AffiliationInfo><Affiliation>Centre for Health Equity, Melbourne School of Population and Global Health, University of Melbourne, Melbourne, Australia.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Niedhammer</LastName><ForeName>I</ForeName><Initials>I</Initials><AffiliationInfo><Affiliation>INSERM, UMR_S 1136, Pierre Louis Institute of Epidemiology and Public Health, Department of social epidemiology, Paris, France.</Affiliation></AffiliationInfo><AffiliationInfo><Affiliation>Sorbonne Universités, UPMC Univ Paris 06, UMR_S 1136, Pierre Louis Institute of Epidemiology and Public Health, Department of social epidemiology, Paris, France.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Chastang</LastName><ForeName>J-F</ForeName><Initials>JF</Initials><AffiliationInfo><Affiliation>INSERM, UMR_S 1136, Pierre Louis Institute of Epidemiology and Public Health, Department of social epidemiology, Paris, France.</Affiliation></AffiliationInfo><AffiliationInfo><Affiliation>Sorbonne Universités, UPMC Univ Paris 06, UMR_S 1136, Pierre Louis Institute of Epidemiology and Public Health, Department of social epidemiology, Paris, France.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Spittal</LastName><ForeName>M J</ForeName><Initials>MJ</Initials><AffiliationInfo><Affiliation>Centre for Mental Health, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Australia.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>LaMontagne</LastName><ForeName>A D</ForeName><Initials>AD</Initials><AffiliationInfo><Affiliation>Work, Health, & Wellbeing Unit, Population Health Strategic Research Centre, School of Health & Social Development, Deakin University, Melbourne, Australia.</Affiliation></AffiliationInfo><AffiliationInfo><Affiliation>Centre for Health Equity, Melbourne School of Population and Global Health, University of Melbourne, Melbourne, Australia.</Affiliation></AffiliationInfo></Author></AuthorList><Language>eng</Language><PublicationTypeList><PublicationType UI="D016428">Journal 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Psychological</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D011795" MajorTopicYN="N">Surveys and Questionnaires</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D055815" MajorTopicYN="N">Young Adult</DescriptorName></MeshHeading></MeshHeadingList><OtherID Source="NLM">PMC4822951</OtherID></MedlineCitation><PubmedData><History><PubMedPubDate PubStatus="received"><Year>2015</Year><Month>08</Month><Day>08</Day></PubMedPubDate><PubMedPubDate PubStatus="accepted"><Year>2016</Year><Month>03</Month><Day>22</Day></PubMedPubDate><PubMedPubDate PubStatus="entrez"><Year>2016</Year><Month>4</Month><Day>7</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="pubmed"><Year>2016</Year><Month>4</Month><Day>7</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate 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