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Depression Screening and Patient Outcomes in Cancer: A Systematic Review

Overview of attention for article published in PLOS ONE, November 2011
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1 blog
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2 policy sources
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6 X users

Citations

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151 Mendeley
Title
Depression Screening and Patient Outcomes in Cancer: A Systematic Review
Published in
PLOS ONE, November 2011
DOI 10.1371/journal.pone.0027181
Pubmed ID
Authors

Anna Meijer, Michelle Roseman, Katherine Milette, James C. Coyne, Michael E. Stefanek, Roy C. Ziegelstein, Erin Arthurs, Allison Leavens, Steven C. Palmer, Donna E. Stewart, Peter de Jonge, Brett D. Thombs

Abstract

Several practice guidelines recommend screening for depression in cancer care, but no systematic reviews have examined whether there is evidence that depression screening benefits cancer patients. The objective was to evaluate the potential benefits of depression screening in cancer patients by assessing the (1) accuracy of depression screening tools; (2) effectiveness of depression treatment; and (3) effect of depression screening, either alone or in the context of comprehensive depression care, on depression outcomes.

X Demographics

X Demographics

The data shown below were collected from the profiles of 6 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 151 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Portugal 1 <1%
Netherlands 1 <1%
Italy 1 <1%
United Kingdom 1 <1%
Denmark 1 <1%
Spain 1 <1%
United States 1 <1%
Unknown 144 95%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 25 17%
Researcher 23 15%
Student > Master 19 13%
Student > Bachelor 17 11%
Student > Doctoral Student 12 8%
Other 35 23%
Unknown 20 13%
Readers by discipline Count As %
Medicine and Dentistry 50 33%
Psychology 36 24%
Nursing and Health Professions 13 9%
Social Sciences 9 6%
Computer Science 4 3%
Other 14 9%
Unknown 25 17%