Modifiable workplace risk factors contributing to workplace absence across health conditions: A stakeholder-centered best-evidence synthesis of systematic reviews
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: A challenge facing stakeholders is the identification and translation of relevant high quality research to inform policy and practice. This study engaged academic and community stakeholders in conducting a best evidence-synthesis to enhance knowledge use. OBJECTIVES: To identify modifiable workplace disability risk and protective factors across common health conditions impacting work-related absence. METHODS: We searched MEDLINE, Embase, CINHAL, The Cochrane Library, PsycINFO, BusinessSourceComplete, and ABI/Inform from 2000 to 2011. Systematic reviews that employed quantitative, qualitative, or mixed methods of work-focused population were considered for inclusion. Two or more independent reviewers reviewed titles only, titles and abstracts, and/or full articles when assessing eligibility for inclusion. Selected articles underwent methodological screening. RESULTS: The search strategy, expert input and grey literature identified 2,467 unique records from which 142 full text articles underwent comprehensive review. Twenty-seven systematic reviews met eligibility criteria. Modifiable work factors found to have consistent evidence across two or more health conditions included lack of social support, increased physical demands at work, job strain, lack of supervisory support, increased psychological demands, low job satisfaction, low worker control of job, and poor leadership quality. CONCLUSIONS: The active engagement of stakeholders led to greater understanding of relevance of the study findings for community stakeholders and appreciation of the mutual benefits of collaboration.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.017 | 0.026 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.001 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.004 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.000 | 0.004 |
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 it