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Profiles of depressive symptoms and the association with anxiety and quality of life in breast cancer survivors: a latent profile analysis

  • Eun Jung Shim
  • , Donghee Jeong
  • , Hyeong Gon Moon
  • , Dong Young Noh
  • , So Youn Jung
  • , Eunsook Lee
  • , Zisun Kim
  • , Hyun Jo Youn
  • , Jihyoung Cho
  • , Jung Eun Lee*
  • *Corresponding author for this work
  • Pusan National University
  • Seoul National University
  • National Cancer Center Korea
  • Soonchunhyang University
  • Keimyung University

Research output: Contribution to journalJournal articlepeer-review

Abstract

Purpose: The aim of this study was to examine profiles of depressive symptoms and the association with anxiety and quality of life (QOL) in breast cancer survivors. Methods: A cross-sectional multicenter survey involving 5 hospitals in Korea was implemented between February 2015 and January 2017. A self-report survey included the Patient Health Questionnaire-9, Short Form 36, and State and Trait Anxiety Scale. Data from 347 patients were analyzed. Results: Latent profile analysis identified five profiles of depressive symptoms: (1) “no depression” (63.98%); (2) “mild depression with sleep problems” (16.43%); (3) “mild depression” (8.65%); (4) “moderate depression with anhedonia” (7.78%); and (5) “moderately severe depression” (3.17%). Results from Fisher’s exact test and analysis of variance (ANOVA) to examine whether sociodemographic and clinical characteristics distinguish the classes indicated that marital status, income and education as well as C-reactive protein distinguished a few classes. Multivariate analysis of covariance and analysis of covariance results indicated that both types of anxiety as well as several dimensions of QOL differed between the identified classes. Conclusions: The current results suggest that although identified classes were characterized overall by severity of depression, a few classes also reflected pronounced individual symptom patterns, warranting tailored interventions for these symptom patterns, along with overall severity of depression.

Original languageEnglish
Pages (from-to)421-429
Number of pages9
JournalQuality of Life Research
Volume29
Issue number2
DOIs
StatePublished - 2020.02.1

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • Anxiety
  • Breast cancer
  • Depression
  • Latent profile analysis
  • Quality of life

Quacquarelli Symonds(QS) Subject Topics

  • Medicine

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