Literature DB >> 29947548

Latent Profile Analyses of Depressive Symptoms in Younger and Older Oncology Patients.

Rebecca M Saracino1,2, Heining Cham2, Barry Rosenfeld1,2, Christian J Nelson1.   

Abstract

The aging of America will include a significant increase in the number of older patients with cancer, many of whom will experience significant depressive symptoms. Although geriatric depression is a well-studied construct, its symptom presentation in the context of cancer is less clear. Latent profile analysis was conducted on depressive symptoms in younger (40-64 years) and older (≥65 years) patients with cancer (N = 636). The sample was clinically heterogeneous (i.e., included all stages, dominated by advanced stage disease). Participants completed questionnaires including the Center for Epidemiological Studies Depression Scale, which was used for the latent profile analysis. A four-class pattern was supported for each age group. However, the four-class pattern was significantly different between the younger and older groups in terms of the item means within each corresponding latent class; differences were primarily driven by severity such that across classes, older adults endorsed milder symptoms. An unexpected measurement issue was uncovered regarding reverse-coded items, suggesting that they may generate unreliable scores on the Center for Epidemiological Studies Depression Scale for a significant subset of patients. The results indicate that cancer clinicians can expect to see depressive symptoms along a continuum of severity for patients of any age, with less severe symptoms among older patients.

Entities:  

Keywords:  aging; cancer; depression; geriatric; latent profile analysis; screening

Mesh:

Year:  2018        PMID: 29947548      PMCID: PMC6358508          DOI: 10.1177/1073191118784653

Source DB:  PubMed          Journal:  Assessment        ISSN: 1073-1911


  55 in total

1.  Comparison of the hospital anxiety and depression scale and the center for epidemiological studies depression scale for detecting depression in women with breast or gynecologic cancer.

Authors:  Lesley Stafford; Fiona Judd; Penny Gibson; Angela Komiti; Michael Quinn; G Bruce Mann
Journal:  Gen Hosp Psychiatry       Date:  2013-11-05       Impact factor: 3.238

2.  Making Sense of Variations in Prevalence Estimates of Depression in Cancer: A Co-Calibration of Commonly Used Depression Scales Using Rasch Analysis.

Authors:  Sylvie D Lambert; Kerrie Clover; Julie F Pallant; Benjamin Britton; Madeleine T King; Alex J Mitchell; Gregory Carter
Journal:  J Natl Compr Canc Netw       Date:  2015-10       Impact factor: 11.908

3.  Latent Class Analysis With Distal Outcomes: A Flexible Model-Based Approach.

Authors:  Stephanie T Lanza; Xianming Tan; Bethany C Bray
Journal:  Struct Equ Modeling       Date:  2013-01       Impact factor: 6.125

4.  Heterogeneity in depression symptoms and health status among older adults.

Authors:  Pablo A Mora; Teerah Beamon; LeAnn Preuitt; Marco DiBonaventura; Elaine A Leventhal; Howard Leventhal
Journal:  J Aging Health       Date:  2012-04-03

5.  Age and recognition of depression: implications for a cohort effect in major depression.

Authors:  D Hasin; B Link
Journal:  Psychol Med       Date:  1988-08       Impact factor: 7.723

Review 6.  Aging-related diagnostic variations: need for diagnostic criteria appropriate for elderly psychiatric patients.

Authors:  Dilip V Jeste; Dan G Blazer; Michael First
Journal:  Biol Psychiatry       Date:  2005-08-15       Impact factor: 13.382

7.  Substituting nonsomatic for somatic symptoms in the diagnosis of depression in elderly male medical patients.

Authors:  S R Rapp; S Vrana
Journal:  Am J Psychiatry       Date:  1989-09       Impact factor: 18.112

8.  Age-cohort changes in the lifetime occurrence of depression and other mental disorders.

Authors:  P M Lewinsohn; P Rohde; J R Seeley; S A Fischer
Journal:  J Abnorm Psychol       Date:  1993-02

9.  Association of Personality Profiles with Depressive, Anxiety, and Cancer-related Symptoms in Patients Undergoing Chemotherapy.

Authors:  Stefana Morgan; Bruce Cooper; Steven Paul; Marilyn J Hammer; Yvette P Conley; Jon D Levine; Christine Miaskowski; Laura B Dunn
Journal:  Pers Individ Dif       Date:  2017-06-04

10.  Ineffectiveness of reverse wording of questionnaire items: let's learn from cows in the rain.

Authors:  Eric van Sonderen; Robbert Sanderman; James C Coyne
Journal:  PLoS One       Date:  2013-07-31       Impact factor: 3.240

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  4 in total

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

Authors:  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
Journal:  Qual Life Res       Date:  2019-10-18       Impact factor: 4.147

2.  Personality Profiles and Personal Factors Associated with Psychological Distress in Chinese Nurses.

Authors:  Wentao Huang; Shu Cai; Ye Zhou; Jingxin Huang; Xibin Sun; Yunhui Su; Meifen Dai; Yutao Lan
Journal:  Psychol Res Behav Manag       Date:  2021-10-02

3.  The Difficult Task of Diagnosing Depression in Elderly People with Cancer: A Systematic Review.

Authors:  Elena Massa; Clelia Donisi; Nicole Liscia; Clelia Madeddu; Valentino Impera; Stefano Mariani; Mario Scartozzi; Eleonora Lai
Journal:  Clin Pract Epidemiol Ment Health       Date:  2021-12-31

4.  What Is the Optimal Cut-Off Point of the 10-Item Center for Epidemiologic Studies Depression Scale for Screening Depression Among Chinese Individuals Aged 45 and Over? An Exploration Using Latent Profile Analysis.

Authors:  Hanlin Fu; Lulu Si; Ruixia Guo
Journal:  Front Psychiatry       Date:  2022-03-14       Impact factor: 4.157

  4 in total

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