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Nurs Outlook. 2016 Sep-Oct;64(5):499-506. doi: 10.1016/j.outlook.2016.05.008. Epub 2016 May 29.

National Institutes of Health Symptom Science Model sheds light on patient symptoms.

Author information

1
Division of Intramural Research, Department of Health and Human Services, National Institute of Nursing Research, National Institutes of Health, Bethesda, MD. Electronic address: Ann.cashion@nih.gov.
2
Division of Intramural Research, Department of Health and Human Services, National Institute of Nursing Research, National Institutes of Health, Bethesda, MD.
3
Division of Science Policy and Public Liaison, Department of Health and Human Services, National Institute of Nursing Research, National Institutes of Health, Bethesda, MD.

Abstract

Since the establishment of the nursing profession, identifying and alleviating the subjective symptoms experienced by patients has been at the core of nursing practice. In supporting the scientific foundation for clinical practice, nursing science has maintained a consistent commitment to prevent, manage, and eliminate symptoms. Scientists from the intramural research program at the National Institute of Nursing Research (NINR), a component of the National Institutes of Health, developed a National Institutes of Health Symptom Science Model (NIH-SSM) to guide symptom science research programs engaged in the use of emerging "omic" methods such as the genotyping of symptom phenotypes. The NIH-SSM was developed based on the NINR intramural research program's success in designing and implementing methods for examining identified symptoms or symptom clusters. The NIH-SSM identifies the research process of characterizing symptom phenotypes, identifying and testing biomarkers, and ultimately developing clinical interventions in cancer-related fatigue, gastrointestinal disorders, and traumatic brain injuries. The purpose of this article was to demonstrate how scientists can apply the NIH-SSM, leading the broader scientific community in advancing personalized and precise clinical interventions.

KEYWORDS:

Biomarkers; Genotype; Model; Phenotype; Research; Symptom science

PMID:
27349632
PMCID:
PMC5014584
DOI:
10.1016/j.outlook.2016.05.008
[Indexed for MEDLINE]
Free PMC Article

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