Advancing the science of symptom management.

Published

Journal Article (Review)

UNLABELLED:Since the publication of the original Symptom Management Model (Larson et al. 1994), faculty and students at the University of California, San Francisco (UCSF) School of Nursing Centre for System Management have tested this model in research studies and expanded the model through collegial discussions and seminars. AIM:In this paper, we describe the evidence-based revised conceptual model, the three dimensions of the model, and the areas where further research is needed. BACKGROUND/RATIONALE:The experience of symptoms, minor to severe, prompts millions of patients to visit their healthcare providers each year. Symptoms not only create distress, but also disrupt social functioning. The management of symptoms and their resulting outcomes often become the responsibility of the patient and his or her family members. Healthcare providers have difficulty developing symptom management strategies that can be applied across acute and home-care settings because few models of symptom management have been tested empirically. To date, the majority of research on symptoms was directed toward studying a single symptom, such as pain or fatigue, or toward evaluating associated symptoms, such as depression and sleep disturbance. While this approach has advanced our understanding of some symptoms, we offer a generic symptom management model to provide direction for selecting clinical interventions, informing research, and bridging an array of symptoms associated with a variety of diseases and conditions. Finally, a broadly-based symptom management model allows the integration of science from other fields.

Full Text

Duke Authors

Cited Authors

  • Dodd, M; Janson, S; Facione, N; Faucett, J; Froelicher, ES; Humphreys, J; Lee, K; Miaskowski, C; Puntillo, K; Rankin, S; Taylor, D

Published Date

  • March 2001

Published In

Volume / Issue

  • 33 / 5

Start / End Page

  • 668 - 676

PubMed ID

  • 11298204

Pubmed Central ID

  • 11298204

Electronic International Standard Serial Number (EISSN)

  • 1365-2648

International Standard Serial Number (ISSN)

  • 0309-2402

Digital Object Identifier (DOI)

  • 10.1046/j.1365-2648.2001.01697.x

Language

  • eng