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Meaning-making and psychological adjustment to cancer: Development of an intervention and pilot results

Journal

ONCOLOGY NURSING FORUM
Volume 33, Issue 2, Pages 291-302

Publisher

ONCOLOGY NURSING SOC
DOI: 10.1188/06.ONF.291-302

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Purpose/Objectives: To develop an intervention that uniquely addresses the existential impact of cancer through meaning-making coping strategies and to explore the intervention's impact on psychological adjustment. Design: Descriptive, qualitative approach to develop the intervention; one-group pre- and post-test design to pilot test the intervention. Setting: Patients' homes or ambulatory oncology clinics affiliated with a university health center in eastern Canada. Sample: 18 participants who were newly diagnosed in the past three months (n = 14), had completed treatment (n = 1), or were facing recurrence (n = 3) of breast (n = 10) or colorectal (n = 8) cancer. Methods: Data were collected during interviews using a prototype intervention for trauma patients, and content was analyzed on an ongoing basis to fit the needs of the cancer population. Pretest and post-test questionnaires were administered to determine the intervention's effect. Main Research Variables: Meaning-making intervention (MMI), patients' background variables, disease- or treatment-related symptoms, and psychological adjustment, Findings: The MMI for patients with cancer consisted of as many as four two-hour, individualized sessions and involved the acknowledgment of losses and life threat, the examination of critical past challenges, and plans to stay committed to life goals. At post-test, participants significantly improved in self-esteem and reported a greater sense of security in facing the uncertainty of cancer. Conclusions: Findings suggest that meaning-making coping can be facilitated and lead to positive psychological outcomes following a cancer diagnosis. Implications for Nursing: The MMI offers a potentially effective and structured approach to address and monitor cancer-related existential issues. Findings are useful for designing future randomized, controlled trials.

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