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Cited by 558

The DOI matches its Crossref record; 9 of the 9 references it cites were found in a registry or an index.

Measurement of Depression in Patients With Cancer

Endicott, Jean·1984·Cancer

Abstract

The recognition or detection of depressive symptoms and syndromes in patients with cancer is of value to the patient because his mental distress may respond to treatment, and to the clinician because some of the clinical complications or difficulties in diagnosis and treatment of the patient may be reduced. Many factors militate against the diagnosis of depressive syndromes in patients with cancer. These include problems with the application of standard sets of criteria for depression, the assumption on the part of medical staff, family, and patients that depression is a "natural" response and therefore not treatable, and the pressure on all involved to "think positive." Some ways of modifying the usual screening and diagnostic procedures for depressive disorders are suggested.

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Crossref · 10.1002/cncr.1984.53.s10.2243

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Citations

Cites

Show all 9 references

Research works printed but not linked: 2

  1. Raskin A., 1971, Depression in the 70's, 8
  2. The Task Force on Nomenclature and Statistics of the American Psychiatric Association, 1977, DSM III: Diagnostic and Statistical Manual of Mental Disorders

Cited by

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Metadata

Authors
Endicott, J.
Venue
Cancer
Publisher
Wiley
Published
1984-05
Volume
53
Issue
S10
Pages
2243-2248
ISSN
  • 0008-543X (ISSN-L)
  • 1097-0142
OpenAlex
W42339444
Cited by
558
References
9
FWCI
1.82
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Measurement of Depression in Patients With Cancer. https://app.cochat.ai/papers/10.1002/cncr.1984.53.s10.2243
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Endicott, J. (1984). Measurement of Depression in Patients With Cancer. Cancer. https://doi.org/10.1002/cncr.1984.53.s10.2243

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.