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{"title"=>"The association between education and work stress: Does the policy context matter?", "type"=>"journal", "authors"=>[{"first_name"=>"Thorsten", "last_name"=>"Lunau", "scopus_author_id"=>"54416043100"}, {"first_name"=>"Johannes", "last_name"=>"Siegrist", "scopus_author_id"=>"7004851481"}, {"first_name"=>"Nico", "last_name"=>"Dragano", "scopus_author_id"=>"13411221500"}, {"first_name"=>"Morten", "last_name"=>"Wahrendorf", "scopus_author_id"=>"14013424200"}], "year"=>2015, "source"=>"PLoS ONE", "identifiers"=>{"issn"=>"19326203", "isbn"=>"1932-6203", "pmid"=>"25812142", "scopus"=>"2-s2.0-84961342500", "doi"=>"10.1371/journal.pone.0121573", "sgr"=>"84961342500", "pui"=>"603466237"}, "id"=>"370abcbc-59fa-323a-b1c9-d02f89ec8802", "abstract"=>"OBJECTIVES: Several studies report socioeconomic differences in work stress, where people in lower socioeconomic positions (SEP) are more likely to experience this burden. In the current study, we analyse associations between education and work stress in a large sample of workers from 16 European countries. In addition we explore whether distinct national labour market policies are related to smaller inequalities in work stress according to educational attainment.\\n\\nMETHODS: We use data collected in 2010/11 in two comparative studies ('Survey of Health, Ageing and Retirement in Europe' and the 'English Longitudinal Study of Ageing'; N = 13695), with samples of men and women aged 50 to 64 from 16 European countries. We measure highest educational degree according to the international standard classification of education (ISCED) and assess work stress in terms of the demand-control and the effort-reward imbalance model. National labour market policies are measured on the basis of policy indicators which are divided into (1) 'protective' policies offering financial compensation to those excluded from the labour market (e.g. replacement rate), and (2) 'integrative' policies supporting disadvantaged individuals on the labour market (e.g. investments into active labour market policies or possibilities for further qualification in later life). In addition to country-specific analyses, we estimate multilevel models and test for interactions between the indicators of national policies and individual education.\\n\\nRESULTS: Main findings demonstrate consistent associations between lower education and higher levels of work stress in all countries. The strength of this association, however, varies across countries and is comparatively small in countries offering pronounced 'integrative' policies, in terms of high investments into measures of an active labor market policy and high participation rates in lifelong learning activities.\\n\\nCONCLUSIONS: Our results point to different types of policies that may help to reduce educational differences in work stress, in particular policies supporting those who are disadvantaged on the labour market.", "link"=>"http://www.mendeley.com/research/association-between-education-work-stress-policy-context-matter", "reader_count"=>33, "reader_count_by_academic_status"=>{"Unspecified"=>3, "Professor > Associate Professor"=>3, "Librarian"=>1, "Researcher"=>1, "Student > Doctoral Student"=>2, "Student > Ph. D. Student"=>3, "Student > Postgraduate"=>3, "Student > Master"=>9, "Other"=>1, "Student > Bachelor"=>4, "Lecturer > Senior Lecturer"=>1, "Professor"=>2}, "reader_count_by_user_role"=>{"Unspecified"=>3, "Professor > Associate Professor"=>3, "Librarian"=>1, "Researcher"=>1, "Student > Doctoral Student"=>2, "Student > Ph. D. Student"=>3, "Student > Postgraduate"=>3, "Student > Master"=>9, "Other"=>1, "Student > Bachelor"=>4, "Lecturer > Senior Lecturer"=>1, "Professor"=>2}, "reader_count_by_subject_area"=>{"Unspecified"=>4, "Engineering"=>1, "Environmental Science"=>1, "Nursing and Health Professions"=>1, "Materials Science"=>1, "Medicine and Dentistry"=>4, "Agricultural and Biological Sciences"=>1, "Sports and Recreations"=>1, "Psychology"=>6, "Social Sciences"=>11, "Decision Sciences"=>1, "Economics, Econometrics and Finance"=>1}, "reader_count_by_subdiscipline"=>{"Engineering"=>{"Engineering"=>1}, "Materials Science"=>{"Materials Science"=>1}, "Medicine and Dentistry"=>{"Medicine and Dentistry"=>4}, "Social Sciences"=>{"Social Sciences"=>11}, "Decision Sciences"=>{"Decision Sciences"=>1}, "Sports and Recreations"=>{"Sports and Recreations"=>1}, "Psychology"=>{"Psychology"=>6}, "Economics, Econometrics and Finance"=>{"Economics, Econometrics and Finance"=>1}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>1}, "Nursing and Health Professions"=>{"Nursing and Health Professions"=>1}, "Unspecified"=>{"Unspecified"=>4}, "Environmental Science"=>{"Environmental Science"=>1}}, "reader_count_by_country"=>{"Venezuela"=>1, "United Kingdom"=>1}, "group_count"=>2}

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• http://doi.org/10.1080/23311975.2018.1517588

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• {"id"=>"711846821371494400", "text"=>"European study shows the educational gradient in work stress is smaller in countries with ‘integrative’ policies https://t.co/N7UJPVMRhN", "created_at"=>"2016-03-21T09:28:02Z", "user"=>"HydeM1976", "user_name"=>"Martin Hyde", "user_profile_image"=>"http://pbs.twimg.com/profile_images/624568092736270336/0stZSmNg_normal.jpg"}

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• {"files"=>["https://ndownloader.figshare.com/files/1989851"], "description"=>"<p>Note. ^a For the analyses, we followed previous procedures [<a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0121573#pone.0121573.ref049\" target=\"_blank\">49</a>] and weighted measures (% of GDP) according to existing unemployment rates. This prevents the possibility that country's higher expenditures were simply related to higher levels of unemployment [<a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0121573#pone.0121573.ref050\" target=\"_blank\">50</a>].</p><p>Policy indicators.</p>", "links"=>[], "tags"=>["National labour market policies", "Policy Context Matter", "attainment.MethodsWe use data", "activities.ConclusionsOur results point", "labor market policy", "sep", "labour market policies", "ObjectivesSeveral studies report", "labour market", "ISCED", "work stress"], "article_id"=>1356916, "categories"=>["Biological Sciences", "Science Policy", "Ecology"], "users"=>["Thorsten Lunau", "Johannes Siegrist", "Nico Dragano", "Morten Wahrendorf"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0121573.t001", "stats"=>{"downloads"=>3, "page_views"=>11, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Policy_indicators_/1356916", "title"=>"Policy indicators.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2015-03-26 03:32:21"}
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• {"files"=>["https://ndownloader.figshare.com/files/1989836"], "description"=>"<p>Note. Results are based on weighted data.</p>", "links"=>[], "tags"=>["National labour market policies", "Policy Context Matter", "attainment.MethodsWe use data", "activities.ConclusionsOur results point", "labor market policy", "sep", "labour market policies", "ObjectivesSeveral studies report", "labour market", "ISCED", "work stress"], "article_id"=>1356911, "categories"=>["Biological Sciences", "Science Policy", "Ecology"], "users"=>["Thorsten Lunau", "Johannes Siegrist", "Nico Dragano", "Morten Wahrendorf"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0121573.g001", "stats"=>{"downloads"=>1, "page_views"=>72, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Average_levels_of_work_stress_mean_score_by_education_and_country_/1356911", "title"=>"Average levels of work stress (mean score) by education and country.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2015-03-26 03:32:21"}
• {"files"=>["https://ndownloader.figshare.com/files/1989837"], "description"=>"<p>Note. Mean differences are adjusted for age, sex, self-employment and work time (based on <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0121573#pone.0121573.t002\" target=\"_blank\">Table 2</a>).</p>", "links"=>[], "tags"=>["National labour market policies", "Policy Context Matter", "attainment.MethodsWe use data", "activities.ConclusionsOur results point", "labor market policy", "sep", "labour market policies", "ObjectivesSeveral studies report", "labour market", "ISCED", "work stress"], "article_id"=>1356912, "categories"=>["Biological Sciences", "Science Policy", "Ecology"], "users"=>["Thorsten Lunau", "Johannes Siegrist", "Nico Dragano", "Morten Wahrendorf"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0121573.g002", "stats"=>{"downloads"=>4, "page_views"=>24, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Educational_differences_in_work_stress_low_vs_high_education_and_lifelong_learning_of_older_worker_in_further_education_/1356912", "title"=>"Educational differences in work stress (low vs. high education) and lifelong learning (% of older worker in further education).", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2015-03-26 03:32:21"}
• {"files"=>["https://ndownloader.figshare.com/files/1989854"], "description"=>"<p>Note. All models are adjusted for sex, age groups, employment status and work time. Expenditures into active (ALMP) and passive labour market policies (PLMP) are weighted by unemployment rate.</p><p>Association between policy indicators and work stress (model 1) and interactions between education and policy indicators (model 2): Results of random intercept linear multilevel regressions. Unstandardized regression coefficients (p-values).</p>", "links"=>[], "tags"=>["National labour market policies", "Policy Context Matter", "attainment.MethodsWe use data", "activities.ConclusionsOur results point", "labor market policy", "sep", "labour market policies", "ObjectivesSeveral studies report", "labour market", "ISCED", "work stress"], "article_id"=>1356919, "categories"=>["Biological Sciences", "Science Policy", "Ecology"], "users"=>["Thorsten Lunau", "Johannes Siegrist", "Nico Dragano", "Morten Wahrendorf"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0121573.t004", "stats"=>{"downloads"=>2, "page_views"=>6, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Association_between_policy_indicators_and_work_stress_model_1_and_interactions_between_education_and_policy_indicators_model_2_Results_of_random_intercept_linear_multilevel_regressions_Unstandardized_regression_coefficients_p_values_/1356919", "title"=>"Association between policy indicators and work stress (model 1) and interactions between education and policy indicators (model 2): Results of random intercept linear multilevel regressions. Unstandardized regression coefficients (p-values).", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2015-03-26 03:32:21"}
• {"files"=>["https://ndownloader.figshare.com/files/1989855"], "description"=>"<div><p>Objectives</p><p>Several studies report socioeconomic differences in work stress, where people in lower socioeconomic positions (SEP) are more likely to experience this burden. In the current study, we analyse associations between education and work stress in a large sample of workers from 16 European countries. In addition we explore whether distinct national labour market policies are related to smaller inequalities in work stress according to educational attainment.</p><p>Methods</p><p>We use data collected in 2010/11 in two comparative studies (‘Survey of Health, Ageing and Retirement in Europe’ and the ‘English Longitudinal Study of Ageing’; N = 13695), with samples of men and women aged 50 to 64 from 16 European countries. We measure highest educational degree according to the international standard classification of education (ISCED) and assess work stress in terms of the demand-control and the effort-reward imbalance model. National labour market policies are measured on the basis of policy indicators which are divided into (1) ‘protective’ policies offering financial compensation to those excluded from the labour market (e.g. replacement rate), and (2) ‘integrative’ policies supporting disadvantaged individuals on the labour market (e.g. investments into active labour market policies or possibilities for further qualification in later life). In addition to country-specific analyses, we estimate multilevel models and test for interactions between the indicators of national policies and individual education.</p><p>Results</p><p>Main findings demonstrate consistent associations between lower education and higher levels of work stress in all countries. The strength of this association, however, varies across countries and is comparatively small in countries offering pronounced ‘integrative’ policies, in terms of high investments into measures of an active labor market policy and high participation rates in lifelong learning activities.</p><p>Conclusions</p><p>Our results point to different types of policies that may help to reduce educational differences in work stress, in particular policies supporting those who are disadvantaged on the labour market.</p></div>", "links"=>[], "tags"=>["National labour market policies", "Policy Context Matter", "attainment.MethodsWe use data", "activities.ConclusionsOur results point", "labor market policy", "sep", "labour market policies", "ObjectivesSeveral studies report", "labour market", "ISCED", "work stress"], "article_id"=>1356920, "categories"=>["Biological Sciences", "Science Policy", "Ecology"], "users"=>["Thorsten Lunau", "Johannes Siegrist", "Nico Dragano", "Morten Wahrendorf"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0121573", "stats"=>{"downloads"=>1, "page_views"=>9, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_The_Association_between_Education_and_Work_Stress_Does_the_Policy_Context_Matter_/1356920", "title"=>"The Association between Education and Work Stress: Does the Policy Context Matter?", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2015-03-26 03:32:21"}
• {"files"=>["https://ndownloader.figshare.com/files/1989853"], "description"=>"<p>Note. All models are adjusted for sex, age groups, employment status and work time.</p><p>Associations between education and work stress scores by country: Results of linear regression models (unstandardized regression coefficients and p-values).</p>", "links"=>[], "tags"=>["National labour market policies", "Policy Context Matter", "attainment.MethodsWe use data", "activities.ConclusionsOur results point", "labor market policy", "sep", "labour market policies", "ObjectivesSeveral studies report", "labour market", "ISCED", "work stress"], "article_id"=>1356918, "categories"=>["Biological Sciences", "Science Policy", "Ecology"], "users"=>["Thorsten Lunau", "Johannes Siegrist", "Nico Dragano", "Morten Wahrendorf"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0121573.t003", "stats"=>{"downloads"=>1, "page_views"=>20, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Associations_between_education_and_work_stress_scores_by_country_Results_of_linear_regression_models_unstandardized_regression_coefficients_and_p_values_/1356918", "title"=>"Associations between education and work stress scores by country: Results of linear regression models (unstandardized regression coefficients and p-values).", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2015-03-26 03:32:21"}
• {"files"=>["https://ndownloader.figshare.com/files/1989850"], "description"=>"<p>Note. Expenditures into active (ALMP) and passive labour market policies (PLMP) are weighted by unemployment rate. Results are based on <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0121573#pone.0121573.t004\" target=\"_blank\">Table 4</a>, model 2.</p>", "links"=>[], "tags"=>["National labour market policies", "Policy Context Matter", "attainment.MethodsWe use data", "activities.ConclusionsOur results point", "labor market policy", "sep", "labour market policies", "ObjectivesSeveral studies report", "labour market", "ISCED", "work stress"], "article_id"=>1356915, "categories"=>["Biological Sciences", "Science Policy", "Ecology"], "users"=>["Thorsten Lunau", "Johannes Siegrist", "Nico Dragano", "Morten Wahrendorf"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0121573.g004", "stats"=>{"downloads"=>1, "page_views"=>10, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Predicted_levels_of_work_stress_by_education_at_different_levels_of_policy_indicators_/1356915", "title"=>"Predicted levels of work stress by education at different levels of policy indicators.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2015-03-26 03:32:21"}

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• {"unique-ip"=>"124", "full-text"=>"156", "pdf"=>"6", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"1", "supp-data"=>"2", "cited-by"=>"1", "year"=>"2020", "month"=>"4"}
• {"unique-ip"=>"127", "full-text"=>"157", "pdf"=>"6", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"8", "supp-data"=>"0", "cited-by"=>"1", "year"=>"2020", "month"=>"5"}
• {"unique-ip"=>"77", "full-text"=>"102", "pdf"=>"6", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"2", "cited-by"=>"1", "year"=>"2020", "month"=>"6"}
• {"unique-ip"=>"67", "full-text"=>"87", "pdf"=>"9", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"1", "cited-by"=>"0", "year"=>"2020", "month"=>"7"}
• {"unique-ip"=>"65", "full-text"=>"93", "pdf"=>"6", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"2", "year"=>"2020", "month"=>"8"}
• {"unique-ip"=>"84", "full-text"=>"117", "pdf"=>"8", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2020", "month"=>"9"}
• {"unique-ip"=>"86", "full-text"=>"122", "pdf"=>"2", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"1", "cited-by"=>"1", "year"=>"2020", "month"=>"10"}
• {"unique-ip"=>"95", "full-text"=>"163", "pdf"=>"6", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2020", "month"=>"11"}
• {"unique-ip"=>"76", "full-text"=>"111", "pdf"=>"5", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"1", "year"=>"2020", "month"=>"12"}

Relative Metric

{"start_date"=>"2015-01-01T00:00:00Z", "end_date"=>"2015-12-31T00:00:00Z", "subject_areas"=>[]}

F1000Prime