Health Psychology Research / HPR / Volume 11 / Issue 1 / DOI: 10.52965/​001c.74879
GENERAL

The same but different. Multidimensional assessment of depression   in students of natural science and music

Michaela Korte1 Deniz Cerci2* Roman Wehry3 Renee Timmers1 Victoria J. Williamson4
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1 The University of Sheffield, UK
2 Klinik für Forensische Psychiatrie, Universitätsmedizin Rostock, Germany
3 Helios Klinikum, Hildesheim, Germany
4 Independent Academic, Independent Academic
Published: 23 May 2023
© 2023 by the Author(s). Licensee Health Psychology Research, USA. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution -Noncommercial 4.0 International License (CC BY-NC 4.0) ( https://creativecommons.org/licenses/by-nc/4.0/ )
Abstract

Depression is one of the most common and debilitating health problems, however, its heterogeneity makes a diagnosis challenging. Thus far the restriction of depression variables explored within groups, the lack of comparability between groups, and the heterogeneity of depression as a concept limit a meaningful interpretation, especially in terms of predictability. Research established students in late adolescence to be particularly vulnerable, especially those with a natural science or musical study main subject. This study used a predictive design, observing the change in variables between groups as well as predicting which combinations of variables would likely determine depression prevalence. 102 under- and postgraduate students from various higher education institutions participated in an online survey. Students were allocated into three groups according to their main study subject and type of institution: natural science students, music college students and a mix of music and natural science students at university with comparable levels of musical training and professional musical identity. Natural science students showed significantly higher levels of anxiety prevalence and pain catastrophizing prevalence, while music college students showed significantly higher depression prevalence compared to the other groups. A hierarchical regression and a tree analysis found that depression for all groups was best predicted with a combination of variables: high anxiety prevalence and low burnout of students with academic staff. The use of a larger pool of depression variables and the comparison of at-risk groups provide insight into how these groups experience depression and thus allow initial steps towards personalized support structures.

Keywords
depression
anxiety
pain management
adolescent development
prediction model
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Conflict of interest
There are no conflicts of interests.
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Health Psychology Research, Electronic ISSN: 2420-8124 Published by Health Psychology Research