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Updated: Jun 13, 2026

Murine Model for Non-invasive Imaging to Detect and Monitor Ovarian Cancer Recurrence
Published on: November 2, 2014
Predictors of adjustment and growth in women with recurrent ovarian cancer
Julie Ann Ponto1, Lee Ellington, Suzanne Mellon
1College of Nursing, Winona State University, Rochester, MN, USA. jponto@winona.edu
Purpose/Objectives:
To analyze predictors of adjustment and growth in women who had experienced recurrent ovarian cancer using components of the Resiliency Model of Family Stress, Adjustment, and Adaptation as a conceptual framework.
Design:
Cross-sectional.
Setting:
Participants were recruited from national cancer advocacy groups.
Sample:
60 married or partnered women with recurrent ovarian cancer.
Methods:
Participants completed an online or paper survey.
Main Research Variables:
Independent variables included demographic and illness variables and meaning of illness. Outcome variables were psychological adjustment and post-traumatic growth.
Findings:
A model of five predictor variables (younger age, fewer years in the relationship, poorer performance status, greater symptom distress, and more negative meaning) accounted for 64% of the variance in adjustment but did not predict post-traumatic growth.
Conclusions:
This study supports the use of a model of adjustment that includes demographic, illness, and appraisal variables for women with recurrent ovarian cancer. Symptom distress and poorer performance status were the most significant predictors of adjustment. Younger age and fewer years in the relationship also predicted poorer adjustment.
Implications For Nursing:
Nurses have the knowledge and skills to influence the predictors of adjustment to recurrent ovarian cancer, particularly symptom distress and poor performance status. Nurses who recognize the predictors of poorer adjustment can anticipate problems and intervene to improve adjustment for women.
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