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Cited by 448

The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.

Calibrating the Physician: Personal Awareness and Effective Patient Care

Novack, Dennis H.·1997·JAMA

Abstract

Physicians' personal characteristics, their past experiences, values, attitudes, and biases can have important effects on communication with patients; being aware of these characteristics can enhance communication. Because medical training and continuing education programs rarely undertake an organized approach to promoting personal awareness, we propose a "curriculum" of 4 core topics for reflection and discussion. The topics are physicians' beliefs and attitudes, physicians' feelings and emotional responses in patient care, challenging clinical situations, and physician self-care. We present examples of organized activities that can promote physician personal awareness such as support groups, Balint groups, and discussions of meaningful experiences in medicine. Experience with these activities suggests that through enhancing personal awareness physicians can improve their clinical care and increase satisfaction with work, relationships, and themselves.

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Crossref · 10.1001/jama.1997.03550060078040

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Metadata

Authors
Novack, D. H.
Venue
JAMA
Published
1997-08-13
Volume
278
Issue
6
Pages
502
ISSN
  • 0002-9955 (ISSN-L)
  • 0098-7484
OpenAlex
W2025198380
Cited by
448
References
3
FWCI
11.97
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Calibrating the Physician: Personal Awareness and Effective Patient Care. https://app.cochat.ai/papers/10.1001/jama.1997.03550060078040
The paper
Novack, D. H. (1997). Calibrating the Physician: Personal Awareness and Effective Patient Care. JAMA. https://doi.org/10.1001/jama.1997.03550060078040

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

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.