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Published on: January 19, 2024
Decision Fatigue and Associated Factors Among Patients with Hematologic Malignancies: Implications for
Haiyan Hu1,2, Min Wang2, Xiaocui Wang2
1School of Nursing, Anhui Medical University, Hefei, Anhui, 230032, People's Republic of China.
Background:
Patients with hematologic malignancies frequently face complex, repeated treatment decisions that may increase decision fatigue (DF) risk. However, evidence on DF and its correlates in this population remains scarce. This study aimed to investigate the level of DF and identify associated factors among patients with hematologic malignancies.
Methods:
A cross-sectional study was conducted with 322 patients receiving treatment at a tertiary hospital in Anhui, China, between October 2024 and May 2025. Participants completed validated scales assessing DF, decision preparation, decision self-efficacy, anxiety, depression, and sleep quality. Independent-samples t-tests, one-way analysis of variance (ANOVA), Pearson correlation analysis, and multiple linear regression were performed to identify factors associated with DF.
Results:
The mean DF score was 13.30 ± 5.02, which was close to the midpoint of the 0-27 Decision Fatigue Scale. DF was negatively correlated with decision preparation and decision self-efficacy (both P < 0.001), and positively correlated with anxiety, depression, and poor sleep quality (all P < 0.001). Female gender, caregiver presence, shorter disease duration, disease recurrence, lower decision preparation, lower decision self-efficacy, and poorer sleep quality were independently associated with higher DF levels (all P < 0.05). The regression model explained 69.0% of the variance in DF.
Conclusion:
Patients with hematologic malignancies exhibit decision fatigue levels near the scale midpoint, which are associated with multiple psychological and contextual factors. These findings can inform the development of patient-centered decision support strategies, though longitudinal and interventional studies are needed to confirm causal pathways and intervention efficacy.
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