Literature DB >> 28820510

Implementation and Use of a Patient Symptom Diary During Chemotherapy: A Mixed-Methods Evaluation of the Nurse Perspective.

Annemarie Coolbrandt1, Erika Bruyninckx1, Chris Verslype1, Ester Steffens2, Ellen Vanhove1, Hans Wildiers1, Koen Milisen1.   

Abstract

PURPOSE/
OBJECTIVES: To gain a deeper understanding of nurses' experience working with a patient diary for tracking and treating side effects during chemotherapy.
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DESIGN: A mixed-methods design was used to learn about oncology nurses' use and perceptions of a symptom diary. 
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SETTING: Six oncology wards and two outpatient clinics at the University Hospitals Leuven, Belgium.
. SAMPLE: 79 nurses completed a survey, and 14 nurses participated in focus group discussions.
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METHODS: First, a survey sampled nurses' use and perceptions of the diary. Next, focus group discussions were held with the aim of arriving at a deeper understanding of the survey results.
. MAIN RESEARCH VARIABLES: Use and perceptions of a symptom diary.
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FINDINGS: Most nurses reported performing diary-related behavior to some extent. The survey and focus groups indicated that many nurses strongly believed in the value of the diary, but some were still hesitant or had concerns about patients' perceptions of the diary. The focus group results showed that nurses' use of the diary in daily practice was influenced by their personal beliefs about the value of the diary, the team's, and those of their patients.
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CONCLUSIONS: Although a positive trend was noted, nurses' use of the symptom diary was suboptimal six months after its implementation.
. IMPLICATIONS FOR NURSING: This study highlights important issues that need to be addressed to advance the successful implementation of the symptom diary.

Entities:  

Keywords:  chemotherapy; self-reporting; symptom management

Mesh:

Substances:

Year:  2017        PMID: 28820510     DOI: 10.1188/17.ONF.E213-E222

Source DB:  PubMed          Journal:  Oncol Nurs Forum        ISSN: 0190-535X            Impact factor:   2.172


  2 in total

1.  Bayesian hierarchical vector autoregressive models for patient-level predictive modeling.

Authors:  Feihan Lu; Yao Zheng; Harrington Cleveland; Chris Burton; David Madigan
Journal:  PLoS One       Date:  2018-12-14       Impact factor: 3.240

2.  The cancer patients' perspective on feasibility of using a fatigue diary and the benefits on self-management: results from a longitudinal study.

Authors:  Marlena Milzer; Karen Steindorf; Paul Reinke; Martina E Schmidt
Journal:  Support Care Cancer       Date:  2022-10-13       Impact factor: 3.359

  2 in total

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