期刊
EUROPEAN JOURNAL OF ONCOLOGY NURSING
卷 66, 期 -, 页码 -出版社
ELSEVIER SCI LTD
DOI: 10.1016/j.ejon.2023.102374
关键词
Resilience; Heterogeneity; Patterns; Growth; Newly diagnosed cancer; Exploratory; Piecewise growth mixture model analysis; Psycho-oncology; Quality of life
This study aimed to explore the impact of a new cancer diagnosis on patients' resilience and whether resilience patterns could predict Quality of Life (QoL) in the first year. Results showed five discrete resilience trajectories with two growing trends, and advanced stage, colorectal cancer, and receiving surgery therapy were significant predictors of negative resilience trajectories.
Purpose: This study was designed to explore the impact of a new cancer diagnosis on resilience of patients and whether the resilience patterns could predict Quality of Life (QoL) in the first year.Methods: An exploratory linear piecewise growth mixture modeling (PGMM) with one hypothetical dot (3 months since diagnosis, T1) was employed to identify different resilience patterns and growth in 289 patients with different cancer diagnoses at five assessment occasions (T0-T4). Logistic regression analysis was performed to select potential predictors and receiver operating characteristic (ROC) curve analysis was utilized to test PGMM's discriminative ability against 1-year QoL.Results: Five discrete resilience trajectories with two growing trends were identified, including Transcendence (7.3%), Resilient (47.4%), Recovery (18.7%), Damaged (14.9%) and Maladaption (11.8%). Advanced stage, colorectal cancer, and receiving surgery therapy were significant predictors of negative resilience tra-jectories (Damaged or Maladaption). Discriminative ability was good for PGMM (AUC = 0.81, 95%CI, 0.76-0.85, P < 0.0001).Conclusion: Heterogeneity is identified in resilience growth before and after 3 months since diagnosis. 26.7% newly diagnosed patients need additional attention especially for those with advanced colorectal cancer and receiving surgery therapy.
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