Symptom management in cancer care: An evolutionary concept analysis for a digitally enabled collaborative framework

Area of Science:

• Nursing
• Health Sciences
• Digital Health

Background:

• Symptom management is crucial in patient care, particularly in oncology.
• Existing conceptualizations may not fully capture the complexities of modern healthcare, including digital integration.

Purpose of the Study:

• To conduct an evolutionary concept analysis of "symptom management" to clarify its core attributes, antecedents, and consequences.
• To develop an updated conceptual framework for symptom management that integrates digital health and collaborative care.

Main Methods:

• Employed Rodgers' evolutionary concept analysis method.
• Systematically searched major scientific databases (Web of Science, PubMed, Embase, Cochrane Library, CINAHL, Chinese databases).
• Included 23 studies focused on cancer symptom management for the analysis.

Main Results:

• Identified six core attributes: dynamism, continuity, multidimensionality, multi-stakeholder collaboration, diverse interventions, and individual variability.
• Delineated key antecedents (patient capacity, health literacy, assessment, support) and outcomes (quality of life, symptom burden, risks).
• Distinguished symptom management from "symptom control," "palliative care," and "self-management," proposing a novel paradigm with digital empowerment and collaboration.

Conclusions:

• Symptom management is a complex, dynamic, multidimensional process requiring collaboration.
• The analysis provides a clear definition and framework, informing research, interventions, and practice.
• Established a foundation for integrating digital health and collaborative care models, emphasizing patient-centeredness in future research and practice.