A latent profile analysis to assess physical, cognitive and emotional symptom clusters in women with breast cancer.

Current research on the physical and psychological functioning of breast cancer survivors often takes an approach where symptoms are studied independently even though they often occur in clusters This paper aims to identify physical and psychological symptom clusters among breast cancer survivors wh...

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Publicado en:Psychology & Health Vol. 37; no. 10; pp. 1253 - 1270
Autores principales: St Fleur, Ruth G., St. George, Sara M., Ream, Molly, Antoni, Michael H.
Formato: research tables/charts Journal Article
Publicado: Taylor & Francis Ltd Oct2022
Acceso en línea:Ver este registro en EBSCOhost
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      dt: Oct2022
      vid: 37
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      pub: Taylor & Francis Ltd
      place: Philadelphia, Pennsylvania
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        10.1080/08870446.2021.1941960
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        atl: A latent profile analysis to assess physical, cognitive and emotional symptom clusters in women with breast cancer.
      aug:
        au:
          St Fleur, Ruth G.
          St. George, Sara M.
          Ream, Molly
          Antoni, Michael H.
        affil: Department of Public Health Sciences, University of Miami Miller School of Medicine, Miami, FL, USA
      sug:
        subj:
          Breast Neoplasms Symptoms
          Cancer Survivors
          Healthcare Disparities
          Cognition
          Postoperative Period
          Human
          Female
          Neoplasm Staging
          Latent Structure Analysis
          Scales
          Questionnaires
          Depression
          Impact of Events Scale
          Social Class
          Secondary Analysis
          Descriptive Statistics
          Odds Ratio
          Confidence Intervals
          Coping
          Female
      ab: Current research on the physical and psychological functioning of breast cancer survivors often takes an approach where symptoms are studied independently even though they often occur in clusters This paper aims to identify physical and psychological symptom clusters among breast cancer survivors while assessing clinical, psychosocial and demographic characteristics that predict subgroup membership. Using post-surgical data collected from 240 women with stage 0–III breast cancer, symptom clusters were identified using latent profile analysis of patient-reported symptoms. Baseline measures included the Pittsburg Sleep Quality Index, the Fatigue Symptom Inventory, the Hamilton Rating Scales for depression and anxiety and the Impact of Event Scale. Three distinct classes were identified: (1) mild physical, cognitive and emotional symptoms, (2) moderate across all domains and (3) high levels of all symptoms. Lower socio-economic status, minority ethnicity, younger age, advanced disease stage along with lower self-efficacy and less internal locus of control were significantly associated with a higher likelihood of class 3 membership. By identifying those most at risk for severe physical and psychological symptoms in the post-surgical period, our results can guide the development of tailored interventions to optimise quality of life during breast cancer treatment.
      pubtype: Academic Journal
      doctype:
        research
        tables/charts
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      ougenre: Article
    language: English
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