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Resource loss, resource gain, and psychological resilience and dysfunction following cancer diagnosis: A growth mixture modeling approach.

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DOI: https://doi.org/10.1037/a0020809

Abstract

This study investigated trajectories of psychological distress and their relationships with change in psychosocial resources in the year following cancer diagnosis.Chinese colorectal cancer (CRC) patients (n = 234) were assessed within 12 weeks of diagnosis (T1) and again at 3-month (T2) and 12-month (T3) follow-ups. Growth mixture modeling was used to analyze the longitudinal data.Psychological distress was measured at the three time-points using Hospital Anxiety and Depression Scale (HADS).Growth mixture models identified four classes: chronic distress (7-9%), delayed distress (10-13%), recovery (13-16%), and resilient (65-67%). People in chronic distress were more likely to demonstrate loss in physical functioning and social relational quality than those in delayed distress, and loss in physical functioning, optimism, and hope than those in recovery, but more likely to demonstrate stability/gain in optimistic personalities than those in delayed distress and resilient. People in resilient were more likely to report stability/gain in optimistic personalities than those in delayed distress but not those in recovery.Understanding differential outcome trajectories and associated change in coping resources has implications for developing ongoing psychological services for cancer patients during the diagnosis and treatment process.

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Pixel-Bot Summary

AI-generated analysis

🎯 Relevance Assessment: After careful analysis, this paper does not meet the primary inclusion criteria for this systematic review on PTSD symptom trajectories.

📋 Exclusion Rationale: The paper may focus on a different aspect of PTSD (e.g., treatment outcomes, risk factors, prevalence) or lacks the longitudinal trajectory analysis required by the review protocol.

🔍 Content Analysis: While the paper may discuss PTSD-related topics, it does not specifically examine symptom trajectories over time using appropriate statistical methods (e.g., growth curve modeling, latent class analysis).

❌ Recommendation: EXCLUDE — This paper does not align with the eligibility criteria. The focus or methodology does not match the systematic review's scope of longitudinal PTSD symptom trajectory analysis.

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