Evidence map›Paper›PMID 29746368›Full record

ArticleEpidemiology (Cambridge, Mass.)2018

Contrasting Causal Effects of Workplace Interventions.

Monika A Izano, Daniel M Brown, Andreas M Neophytou, Erika Garcia, Ellen A Eisen

Abstract read
In one paragraph

Article in Epidemiology (Cambridge, Mass.), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Monika A IzanoFrom the School of Public Health, University of California, Berkeley, CA.
Daniel M Brown
Andreas M Neophytou
Erika Garcia
Ellen A Eisen

Funding

Risk factors for Alzheimer's Disease and Related Dementia: Evidence from a Large Occupational CohortR01AG026291 · NIA · YALE UNIVERSITY · PI CANTLEY, LINDA, EISEN, ELLEN AURA · 2006 to 2021
$12.9M
Disease, Disability and Death in an Aging WorkforceR56AG026291 · NIA · STANFORD UNIVERSITY · PI CANTLEY, LINDA, CULLEN, MARK RICHARD · 2016 to 2016
$1.2M
Healthy Worker Effect, Occupational Exposure to PM and Cardiopulmonary MortalityR01OH010028 · OH · UNIVERSITY OF CALIFORNIA BERKELEY · PI EISEN, ELLEN AURA · 2012 to 2014
$869k
ACL HHS T42OH008429NIA NIH HHS R01 AG026291NIA NIH HHS R56 AG026291NIOSH CDC HHS R01 OH010028NIOSH CDC HHS T42 OH008429
6 · The paper itself

Abstract

Occupational exposure guidelines are ideally based on estimated effects of static interventions that assign constant exposure over a working lifetime. Static effects are difficult to estimate when follow-up extends beyond employment because their identifiability requires additional assumptions. Effects of dynamic interventions that assign exposure while at work, allowing subjects to leave and become unexposed thereafter, are more easily identifiable but result in different estimates. Given the practical implications of exposure limits, we explored the drivers of the differences between static and dynamic interventions in a simulation study where workers could terminate employment because of an intermediate adverse health event that functions as a time-varying confounder. The two effect estimates became more similar with increasing strength of the health event and outcome relationship and with increasing time between health event and employment termination. Estimates were most dissimilar when the intermediate health event occurred early in employment, providing an effective screening mechanism.

Indexed as

Health PromotionOccupational DiseasesOccupational ExposureWorkplaceCohort StudiesHumansPulmonary Disease, Chronic Obstructive

Identifiers

PMID29746368
PMCPMC6126532

What OpenQuestion holds

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Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.