When Average Isn't Good Enough : Identifying Meaningful Subgroups in Clinical Data
Journal article
Gloster, Andrew, Nadler, Matthias, Block, Victoria, Haller, Elisa, Rubel, Julian, Benoy, Charles, Villanueva, Jeanette, Bader, Klaus, Walter, Marc, Lang, Undine, Hofmann, Stefan, Ciarrochi, Joseph and Hayes, Steven. (2024). When Average Isn't Good Enough : Identifying Meaningful Subgroups in Clinical Data. Cognitive Therapy and Research. 48, pp. 537-551. https://doi.org/10.1007/s10608-023-10453-x
Authors | Gloster, Andrew, Nadler, Matthias, Block, Victoria, Haller, Elisa, Rubel, Julian, Benoy, Charles, Villanueva, Jeanette, Bader, Klaus, Walter, Marc, Lang, Undine, Hofmann, Stefan, Ciarrochi, Joseph and Hayes, Steven |
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Abstract | Background: Clinical data are usually analyzed with the assumption that knowledge gathered from group averages applies to the individual. Doing so potentially obscures patients with meaningfully different trajectories of therapeutic change. Needed are “idionomic” methods that first examine idiographic patterns before nomothetic generalizations are made. The objective of this paper is to test whether such an idionomic method leads to different clinical conclusions. Methods: 51 patients completed weekly process measures and symptom severity over a period of eight weeks. Change trajectories were analyzed using a nomothetic approach and an idiographic approach with bottom-up clustering of similar individuals. The outcome was patients’ well-being at post-treatment. Results: Individuals differed in the extent that underlying processes were linked to symptoms. Average trend lines did not represent the intraindividual changes well. The idionomic approach readily identified subgroups of patients that differentially predicted distal outcomes (well-being). Conclusions: Relying exclusively on average results may lead to an oversight of intraindividual pathways. Characterizing data first using idiographic approaches led to more refined conclusions, which is clinically useful, scientifically rigorous, and may help advance individualized psychotherapy approaches |
Keywords | Intraindividual differences; Idionomic analysis; Nomothetic ; Processes |
Year | 01 Jan 2024 |
Journal | Cognitive Therapy and Research |
Journal citation | 48, pp. 537-551 |
Publisher | Springer New York LLC |
ISSN | 0147-5916 |
Digital Object Identifier (DOI) | https://doi.org/10.1007/s10608-023-10453-x |
Web address (URL) | https://link.springer.com/article/10.1007/s10608-023-10453-x |
Open access | Open access |
Research or scholarly | Research |
Page range | 537-551 |
Publisher's version | License File Access Level Open |
Output status | Published |
Publication dates | |
Online | 28 Jan 2024 |
Publication process dates | |
Accepted | 11 Nov 2023 |
Deposited | 03 Oct 2024 |
Additional information | © The Author(s) 2024 |
This article is licensed under a Creative Commons | |
Place of publication | United States |
https://acuresearchbank.acu.edu.au/item/90z0x/when-average-isn-t-good-enough-identifying-meaningful-subgroups-in-clinical-data
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Publisher's version
OA_Ciarrochi_2024_When_Average_Isn't_Good_Enough_Identifying.pdf | |
License: CC BY 4.0 | |
File access level: Open |
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