Tendências e diversidade na utilização empírica do Modelo Demanda-Controle de Karasek (estresse no trabalho): uma revisão sistemática Trends and diversity in the empirical use of Karasek's demand-control model (job strain): a systematic review
Bibliographic record
Abstract
INTRODUÇÃO: O modelo demanda-controle de Karasek tem sido utilizado para investigar associação entre estresse no trabalho e desfechos de saúde. Entretanto, diferentes instrumentos e definições têm sido adotados para aferir a exposição "alta exigência no trabalho", o que dificulta a comparação de resultados entre estudos. OBJETIVO: Descrever os instrumentos e as definições adotadas para a variável de exposição "estresse no trabalho", avaliada segundo o modelo demanda-controle, nos estudos observacionais publicados até 2010. MÉTODOS: Revisão sistemática de estudos observacionais publicados até dezembro de 2010, que avaliaram a exposição "estresse no trabalho", aferido segundo o modelo demanda-controle de Karasek e utilizaram o JCQ ou seus derivados, desde que explicitado nos textos. RESULTADOS: Entre 877 resumos selecionados, 496 (57%) preencheram os critérios de inclusão. Identificou-se tendência à produção bibliográfica crescente no tema. A maioria dos estudos foi de natureza seccional; não encontramos diferenças relevantes entre as populações de estudo masculinas e femininas. Suécia, EUA, Japão e Canadá concentraram 57% das publicações, em sua maioria incluindo mais de 1.000 participantes e ocupações diversificadas. Desfechos cardiovasculares e seus fatores de risco foram os mais estudados (45%), seguidos por aqueles relacionados à saúde mental (25%). Em 71% dos estudos foi utilizado o Job Content Questionnaire (com 2 a 49 itens) e, em 19% do total, a versão sueca (Demand Control Swedish Questionnaire). Quadrantes de exposição demanda-controle foram utilizados em 51% dos trabalhos, mas com variados pontos de corte; escores das duas dimensões foram analisados em separado em 27%, e sua razão em 14% do total. Apoio social no trabalho foi avaliado em 44% dos estudos. CONCLUSÃO: O modelo Karasek deverá continuar a suscitar pesquisas epidemiológicas e esperamos que os pesquisadores enfrentem essas questões teóricas e metodológicas ainda pendentes. INTRODUCTION: Karasek's demand-control model has been used to investigate association between job strain and health outcomes. However, different instruments and definitions have been utilized to assess the exposure 'high strain at work', which makes difficult the comparison of results across studies. OBJECTIVE: To describe the measurement instruments and the definitions adopted for the exposure variable 'job strain', according to the demand-control model, by observational studies published until 2010. METHODS: Systematic review of observational studies published until December 2010, addressing the exposure 'job strain', measured according to the demand-control model and used the JCQ or its derivatives, since explicit. RESULTS: Among 877 selected abstracts, 496 (57%) met the inclusion criteria. It identified a trend towards the increasing production literature on the subject. Most studies were sectional; found no relevant differences among study populations of men and women. Sweden, USA, Japan and Canada accounted for 57% of publications, mostly including more than 1000 participants and diverse occupations. Cardiovascular outcomes and their risk factors were the most studied (45%), followed by those related to mental health (25%). In 71% of the studies used the Job Content Questionnaire (from 2 to 49 items) and 19% of the total, the Swedish version (Demand-Control Questionnaire Swedish). Quadrants of the demand-control exposure were used in 51% of the work, but with different cutoff points; scores of the two dimensions were analyzed separately in 27%, and its ratio in 14% of the total. Social support at work was assessed in 44% of the studies. CONCLUSION: Karasek's model should continue to raise epidemiological studies and we hope that researchers face these theoretical and methodological issues outstanding.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.103 | 0.241 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.006 | 0.014 |
| Bibliometrics | 0.013 | 0.017 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.010 | 0.006 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".