What contributes to resilience in cancer patients? A principal component analysis of the Connor-Davidson Resilience Scale.

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5 Citations (Scopus)


Purpose: Research suggests resilience is a complex multifactorial construct, which may improve health outcomes in cancer, but significant controversy exists regarding its definition and measurement. This study aimed to determine the components of resilience and their relative weight, as measured by the Connor–Davidson Resilience Scale in cancer patients. Methods: As part of a larger study, a questionnaire including the Connor–Davidson Resilience Scale was distributed to 228 cancer patients. Principal component analysis was performed to identify the components of resilience measured by the Connor–Davidson Resilience Scale. Results: Principal component analysis yielded six factors: (1) personal strength and problem-based coping, (2) spirituality/fate, (3) social support, (4) adaptability and flexibility, (5) giving best efforts and (6) self-determination, explaining 64.27% of the variance. Conclusion: The Connor–Davidson Resilience Scale accounts for approximately two-thirds of variance in resilience in cancer patients, but 36% of the total variance remains unexplained, suggesting there are still unexplored determinants of resilience in cancer. Identification of these determinants may improve measurement of resilience in cancer through refinement of existing resilience measures or development of cancer-specific measures. Given the associations found within this study, interventions targeted towards improving coping strategies in at-risk individuals, and ensuring they have adequate social and spiritual support may improve resilience, although additional research is required to verify this.

Original languageEnglish
Pages (from-to)e115-e119
Number of pages5
JournalAsia-Pacific Journal of Clinical Oncology
Issue number5
Publication statusPublished - Oct 2019


  • adaptation
  • Connor–Davidson Resilience Scale
  • neoplasms
  • , principal component analysis
  • psychological
  • resilience
  • principal component analysis


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