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Mishel's uncertainty in illness theory: Informing nursing diagnoses and care planning.

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PURPOSE Patients with glioblastoma multiforme (GBM) face uncertainty during the illness trajectory that decreases their quality of life. Uncertainty manifests as an altered state of mind in patients with GBM… Click to show full abstract

PURPOSE Patients with glioblastoma multiforme (GBM) face uncertainty during the illness trajectory that decreases their quality of life. Uncertainty manifests as an altered state of mind in patients with GBM and increases the burden of managing their diagnosis. The uncertainty in illness theory (UIT) can be used to guide nursing practice and create care plans to decrease this uncertainty. DATA SOURCES The UIT and conceptual model were used to pair diagnoses from NANDA-I Nursing Diagnoses to form care plans for patients with GBM. METHODS In a stepwise approach, concepts from the UIT were organized and cross-walked into an integrated theory-driven practice framework to enhance care planning. CONCLUSIONS The UIT helps define and identify circumstances of uncertainty in patients experiencing illness, and Nursing Diagnoses provide engagement and outcomes for those uncertainty-based diagnoses. Some examples of the UIT guiding Nursing Diagnoses includes a patient's cognitive level guiding a Nursing Diagnosis care plan of Risk for Acute Confusion. Social Support can guide the care plan of Risk for Loneliness, and appraisal of uncertainty can guide a care plan for Ineffective Individual Coping. Using the UIT to guide theory-driven practice links interventions and outcomes in patients with GBM. IMPLICATIONS FOR PRACTICE The UIT can guide NANDA-I Nursing Diagnoses to assist nurses in creating a nursing care plan for nursing engagement to decrease uncertainty and increase the quality of life in patients with GBM. Theory-driven research defines the application of the UIT in GBM and provides foundational knowledge for theory-driven practice to occur.

Keywords: theory; uncertainty illness; nursing; nursing diagnoses; uncertainty; care

Journal Title: International journal of nursing knowledge
Year Published: 2022

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