{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,3]],"date-time":"2026-08-03T05:45:27Z","timestamp":1785735927396,"version":"3.56.0"},"reference-count":49,"publisher":"Wiley","license":[{"start":{"date-parts":[[2026,8,2]],"date-time":"2026-08-02T00:00:00Z","timestamp":1785628800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"},{"start":{"date-parts":[[2026,8,2]],"date-time":"2026-08-02T00:00:00Z","timestamp":1785628800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Journal of Clinical Nursing"],"abstract":"ABSTRACT<\/jats:title>\n \n Aim(s)<\/jats:title>\n To identify latent fatigue profiles in adolescent and young adult (AYA) cancer patients and explore associated clinical and socioeconomic factors to guide precision nursing.<\/jats:p>\n <\/jats:sec>\n \n Design<\/jats:title>\n A cross\u2010sectional observational study.<\/jats:p>\n <\/jats:sec>\n \n Methods<\/jats:title>\n A total of 218 AYA cancer patients were recruited from a tertiary cancer center between December 2025 and February 2026. Latent Profile Analysis was used to identify fatigue subgroups based on the Piper Fatigue Scale\u2010Revised. Multinomial logistic regression was applied to examine correlates.<\/jats:p>\n <\/jats:sec>\n \n Results<\/jats:title>\n \n Three distinct profiles emerged: \u2018Low\u2010Fatigue Well\u2010Adapted\u2019 (32.6%), \u2018High\u2010Fatigue Somatic\u2010Dominant\u2019 (38.1%), and \u2018High\u2010Fatigue Emotional\u2010Cognitive Exhaustion\u2019 (29.4%). The Somatic\u2010Dominant group exhibited severe sensory fatigue but mild distress, strongly associated with chemotherapy (OR\u2009=\u20092.42, 95% CI: 1.03\u20135.68,\n p<\/jats:italic>\n \u2009=\u20090.041) and non\u2010working status (OR\u2009=\u20093.02, 95% CI: 1.38\u20136.58,\n p<\/jats:italic>\n \u2009=\u20090.006). Conversely, the Emotional\u2010Cognitive Exhaustion group showed severe affective and cognitive exhaustion. This profile was significantly linked to active chemotherapy (OR\u2009=\u20094.95, 95% CI: 1.98\u201312.38,\n p<\/jats:italic>\n \u2009<\u20090.001), lower income levels (higher income: OR\u2009=\u20090.52, 95% CI: 0.38\u20130.71,\n p<\/jats:italic>\n \u2009<\u20090.001), and gastrointestinal cancer (OR\u2009=\u20093.15, 95% CI: 1.12\u20138.85,\n p<\/jats:italic>\n \u2009=\u20090.029).\n <\/jats:p>\n <\/jats:sec>\n \n Conclusion<\/jats:title>\n Fatigue in AYA patients appears highly heterogeneous, manifesting either as somatic\u2010dominant patterns potentially associated with chemotherapy or multidimensional exhaustion linked to survival and economic pressures.<\/jats:p>\n <\/jats:sec>\n \n Implications for the Profession and\/or Patient Care<\/jats:title>\n Nursing practice should transition from a uniform approach to phenotype\u2010based precision symptom management. Patients with somatic\u2010dominant fatigue require physical rehabilitation, whereas those experiencing emotional\u2010cognitive exhaustion urgently need integrated nutritional, psychological, and socioeconomic support to mitigate their multidimensional burden.<\/jats:p>\n <\/jats:sec>\n \n Impact<\/jats:title>\n \n \n \n \n What problem did the study address?\n \n \n The study addressed the limitation of treating cancer\u2010related fatigue as a uniform symptom in AYA patients, which masks individual variability and the hidden burden of chronic socioeconomic constraints.<\/jats:p>\n <\/jats:list-item>\n <\/jats:list>\n <\/jats:p>\n <\/jats:list-item>\n \n \n What were the main findings?\n \n \n Three distinct fatigue phenotypes were identified, revealing significant symptom heterogeneity. Severe emotional\u2010cognitive exhaustion was strongly linked not only to chemotherapy but also to chronic economic constraints of maintaining employment while ill.<\/jats:p>\n <\/jats:list-item>\n <\/jats:list>\n <\/jats:p>\n <\/jats:list-item>\n \n \n Where and on whom will the research have an impact?\n \n \n This research will impact oncology nurses, social workers, and clinical policymakers globally by providing an evidence\u2010based framework for precision symptom management and targeted socioeconomic interventions for vulnerable AYA cancer survivors.<\/jats:p>\n <\/jats:list-item>\n <\/jats:list>\n <\/jats:p>\n <\/jats:list-item>\n <\/jats:list>\n <\/jats:p>\n <\/jats:sec>\n \n Reporting Method<\/jats:title>\n This study adhered to the STROBE reporting guidelines for cross\u2010sectional studies.<\/jats:p>\n <\/jats:sec>\n \n Patient or Public Contribution<\/jats:title>\n No patient or public contribution.<\/jats:p>\n <\/jats:sec>","DOI":"10.1111\/jocn.70475","type":"journal-article","created":{"date-parts":[[2026,8,3]],"date-time":"2026-08-03T05:10:32Z","timestamp":1785733832000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Latent Profile Analysis of Multidimensional Fatigue in Adolescent and Young Adult Cancer Patients: Implications for Personalized Fatigue Management"],"prefix":"10.1111","author":[{"ORCID":"https:\/\/orcid.org\/0009-0004-0297-0665","authenticated-orcid":false,"given":"Yingjie","family":"Yao","sequence":"first","affiliation":[{"name":"Hunan Cancer Hospital\/The Affiliated Cancer Hospital of Xiangya School of Medicine Central South University Changsha Hunan China"},{"name":"Xiangya School of Nursing Central South University Changsha Hunan 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