Evidence map›Paper›PMID 20077153›Full record

ReviewJournal of general internal medicine2010

Integration of women veterans into VA quality improvement research efforts: what researchers need to know.

Elizabeth M Yano, Patricia Hayes, Steven Wright, Paula P Schnurr, Linda Lipson, Bevanne Bean-Mayberry, Donna L Washington

Abstract readReview
In one paragraph

Review in Journal of general internal medicine, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 46 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
46citing papers in PubMed, 3 pooled it
–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

46 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. Pooled it
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  10. Review
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  18. A positive screen for military sexual trauma is associated with greater risk for substance use disorders in women veterans.Psychology of addictive behaviors : journal of the Society of Psychologists in Addictive Behaviors · 2019
    Article
  19. Observational
  20. 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

7 authors.

Elizabeth M YanoVA Greater Los Angeles HSR&D Center of Excellence, 16111 Plummer Street, Sepulveda, CA 91343, USA. Elizabeth.yano@va.gov
Patricia Hayes
Steven Wright
Paula P Schnurr
Linda Lipson
Bevanne Bean-Mayberry
Donna L Washington

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The Department of Veterans Affairs (VA) and other federal agencies require funded researchers to include women in their studies. Historically, many researchers have indicated they will include women in proportion to their VA representation or pointed to their numerical minority as justification for exclusion. However, women's participation in the military-currently 14% of active military-is rapidly changing veteran demographics, with women among the fastest growing segments of new VA users. These changes will require researchers to meet the challenge of finding ways to adequately represent women veterans for meaningful analysis. We describe women veterans' health and health-care use, note how VA care is organized to meet their needs, report gender differences in quality, highlight national plans for women veterans' quality improvement, and discuss VA women's health research. We then discuss challenges and potential solutions for increasing representation of women veterans in VA research, including steps for implementation research.

Indexed as

Biomedical ResearchFemaleHealth Plan ImplementationHospitals, VeteransHumansMaleQuality of Health CareResearch PersonnelSex FactorsUnited StatesUnited States Department of Veterans AffairsVeterans

Identifiers

PMID20077153
PMCPMC2806960

What OpenQuestion holds

Textmetadata
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.