ArticlePatient preference and adherence2025
Psychosocial and Clinical Factors That Differentiate and Predict Patients' Adaptation to Chronic Diseases.
Article in Patient preference and adherence, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
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Who cites it
2 citing papers in PubMed.
- Perceived Disease Burden and Social Support Among Adults on Hemodialysis in Northern Colombia: A Cross-Sectional Study.Nursing reports (Pavia, Italy) · 2026Article
- The Mediating Roles of Self-Efficacy, Resilience, and Social Support in the Relationship Between Clinical Factors and Adaptation to Chronic Disease.Journal of multidisciplinary healthcare · 2026Article
Corrections and comments
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Authors and funding
16 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Purpose: Adaptation to chronic disease is an important factor for the quality of life of patients and their families. This research aimed to identify the psychosocial and clinical factors that determine significant differences and best predict the patients' adaptation to chronic diseases. Understanding these factors enables the design of evidence-based preventive interventions that promote early adaptation. Patients and Methods: A quantitative, non-experimental comparative and predictive study design was conducted. Several clinical, demographic, and psychological factors were measured with an online questionnaire. This study was conducted on a convenience sample of 263 patients with chronic diseases: 63 (24%) had chronic kidney disease with dialysis dependency, 49 (18.6%) had solid neoplasms, 61 (23.2%) had hemopathies, 64 (24.3%) had HIV infection, and 26 (9.9%) had tuberculosis. Results: Adaptation to chronic disease varies based on the type of diagnosis, with lower adaptation seen in conditions that significantly impact daily life, involve comorbidities, and require frequent treatments, like chronic kidney disease. The most significant predictor of adaptation to the chronic disease is the female gender. Other predictive factors are medication adherence, social support, and self-efficacy in managing chronic disease. Patients without comorbidities and fewer medications are more prone to illness denial, alongside younger, urban, employed, and higher-educated patients, potentially neglecting treatment. Patients with comorbidities and the older patients require greater emotional support, with psychological counseling and support groups being beneficial. Conclusion: Current data underlines the need for an individualized approach to chronic disease management, which should consider demographic and psychological factors in addition to clinical ones. It is important to design early interventions for the development of adaptation to chronic disease, which could include individual and family counseling and education programs for medication administration, treatment at home, adherence to a healthy lifestyle, and inclusion of the patient and his family in social support groups.
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