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The impact of COVID-19 and socioeconomic status on psychological distress in cancer patients

. 2023 Oct-Dec;23(4):100404. doi: 10.1016/j.ijchp.2023.100404. Epub 2023 Aug 22. The impact of COVID-19 and socioeconomic status on psychological distress in cancer patients Matthias Knefel  1   3 Carmen Schneckenreiter  1 Jakob Pietschnig  4 Simone Lubowitzki  1 Matthias Unseld  2   5 Thorsten Füreder  6 Rupert Bartsch  6 Eva Katharina Masel  5 Feroniki Adamidis  5 Lea Kum  5 Barbara Kiesewetter  6 Sabine Zöchbauer-Müller  6 Markus Raderer  6 Maria Theresa Krauth  1   7 Philipp B Staber  1 Peter Valent  1   7 Alexander Gaiger  1   7

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The impact of COVID-19 and socioeconomic status on psychological distress in cancer patients

Elisabeth Lucia Zeilinger et al. Int J Clin Health Psychol. 2023 Oct-Dec.

. 2023 Oct-Dec;23(4):100404. doi: 10.1016/j.ijchp.2023.100404. Epub 2023 Aug 22. Authors Elisabeth Lucia Zeilinger  1   2 Matthias Knefel  1   3 Carmen Schneckenreiter  1 Jakob Pietschnig  4 Simone Lubowitzki  1 Matthias Unseld  2   5 Thorsten Füreder  6 Rupert Bartsch  6 Eva Katharina Masel  5 Feroniki Adamidis  5 Lea Kum  5 Barbara Kiesewetter  6 Sabine Zöchbauer-Müller  6 Markus Raderer  6 Maria Theresa Krauth  1   7 Philipp B Staber  1 Peter Valent  1   7 Alexander Gaiger  1   7 Affiliations

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Abstract

Objective: We aimed to investigate the impact of the COVID-19 pandemic on psychological symptom burden against the socioeconomic background of cancer patients using data from routine assessments before and during the pandemic.

Method: In this cross-sectional study, standardised assessment instruments were applied in N = 1,329 patients to screen for symptoms of anxiety, depression, post-traumatic stress, and fatigue from 2018 to 2022. Two MANOVAs with post-hoc tests were computed. First, only time was included as predictor to examine the isolated impact of the pandemic. Second, income level and education level were included as further predictors to additionally test the predictive power of socioeconomic factors.

Results: In the final model, only income had a significant impact on all aspects of psychological symptom burden, with patients with low income being highly burdened (partial η² = .01, p = .023). The highest mean difference was found for depressive symptoms (MD = 0.13, CI = [0.07; 0.19], p < .001). The pandemic had no further influence on psychological distress.

Conclusions: Although the pandemic is a major stressor in many respects, poverty may be the more important risk factor for psychological symptom burden in cancer outpatients, outweighing the impact of the pandemic.

Keywords: COVID-19; Cancer; Psycho-oncology; Socioeconomic status.

© 2023 The Author(s).

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Conflict of interest statement

The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Rupert Bartsch: Consulting fees: Astra-Zeneca, Daiichi, Eisai, Eli-Lilly, Gilead, Gruenenthal, MSD, Novartis, Pfizer, Pierre-Fabre, Puma, Roche, Seagen. Lecture Honoraria: Astra-Zeneca, Daichi, Eisai, Eli-Lilly, Gilead, Gruenenthal, MSD, Novartis, Pfizer, Pierre-Fabre, Roche, Seagen. Support for attending meetings and/or travel: AstraZeneca, Daiichi, MSD, Roche. Peter Valent: Consulting fees: Novartis, Blueprint, BMS/Celgene, Pfizer, Cogent, and AOP Orphan. All other authors have nothing to disclose.

Figures

Fig. 1

Anxiety, depression, PTSS, and fatigue…

Fig. 1

Anxiety, depression, PTSS, and fatigue before and during the pandemic. The Figure shows…

Fig. 1

Anxiety, depression, PTSS, and fatigue before and during the pandemic. The Figure shows the psychological symptom burden before the pandemic, as well as across several time periods within the pandemic. Scores have been z-transformed to aid visual interpretation.

Fig. 2

Symptoms of anxiety, depression, PTSS,…

Fig. 2

Symptoms of anxiety, depression, PTSS, and fatigue across all income levels. The Figure…

Fig. 2

Symptoms of anxiety, depression, PTSS, and fatigue across all income levels. The Figure shows the psychological symptom burden across income levels. Scores have been z-transformed to aid visual interpretation. This transformation standardizes each scale to a mean of zero and a standard deviation of one, ensuring direct comparability between scales.

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