Nikki L. van Eijk
A latent class analysis using the integrated motivational-volitional model of suicidal behaviour: Understanding suicide risk over 36 months
van Eijk, Nikki L.; Wetherall, Karen; Ferguson, Eamonn; O'Connor, Daryl B.; O'Connor, Rory C.
Authors
Karen Wetherall
Professor EAMONN FERGUSON eamonn.ferguson@nottingham.ac.uk
PROFESSOR OF HEALTH PSYCHOLOGY
Daryl B. O'Connor
Rory C. O'Connor
Abstract
The use of latent class analysis (LCA) to understand suicide risk is often not guided by theoretical frameworks. This study used the Integrated Motivational-Volitional (IMV) Model of Suicidal Behaviour to inform the classification of subtypes of young adults with a suicidal history. Data from young adults in Scotland (n = 3508) were used in this study including a subgroup of participants (n = 845) with a history of suicidality. LCA using risk factors from the IMV model was conducted on this subgroup, and the subgroups and non-suicidal control group were compared. Trajectories of suicidal behaviour over 36 months was compared between the classes. Three classes were identified. Class 1 (62 %) had low scores on all risk factors, Class 2 (23 %) had moderate scores, and Class 3 (14 %) had high scores on all risk factors. Those in Class 1 had a stable low risk of suicidal behaviour, while those in Class 2 and 3 showed marked variation over time, although Class 3 had the highest risk across all timepoints. The rate of suicidal behaviour in the sample was low, and differential dropout may have impacted the findings. These findings suggest that young adults can be classified into different profiles based on suicide risk variables derived from the IMV model, which still distinguishes them 36 months later. Such profiling may help determining who is most at risk for suicidal behaviour over time.
Citation
van Eijk, N. L., Wetherall, K., Ferguson, E., O'Connor, D. B., & O'Connor, R. C. (2023). A latent class analysis using the integrated motivational-volitional model of suicidal behaviour: Understanding suicide risk over 36 months. Journal of Affective Disorders, 336, 9-14. https://doi.org/10.1016/j.jad.2023.05.028
Journal Article Type | Article |
---|---|
Acceptance Date | May 11, 2023 |
Online Publication Date | May 15, 2023 |
Publication Date | Sep 1, 2023 |
Deposit Date | Jun 7, 2023 |
Publicly Available Date | May 16, 2024 |
Journal | Journal of Affective Disorders |
Electronic ISSN | 1573-2517 |
Publisher | Elsevier |
Peer Reviewed | Peer Reviewed |
Volume | 336 |
Pages | 9-14 |
DOI | https://doi.org/10.1016/j.jad.2023.05.028 |
Keywords | Latent class analysis, Integrated motivational-volitional (IMV) model, Suicide, Theory |
Public URL | https://nottingham-repository.worktribe.com/output/21630354 |
Additional Information | This is a pre-copyedited, author-produced version of an article accepted for publication in Journal of Affective Disorders. The published version of record Nikki L. van Eijk, Karen Wetherall, Eamonn Ferguson, Daryl B. O'Connor, Rory C. O'Connor, A latent class analysis using the integrated motivational-volitional model of suicidal behaviour: Understanding suicide risk over 36 months, Journal of Affective Disorders, Volume 336, 2023, Pages 9-14 is available online at: https://doi.org/10.1016/j.jad.2023.05.028 |
Files
A Latent Class Analysis Using The Integrated Motivational-Volitional Model Of Suicidal Behaviour Understanding Suicide Risk Over 36 Months
(635 Kb)
PDF
You might also like
Blood Donor Incentives across 63 Countries: The BEST Collaborative Study
(2023)
Journal Article
Blood Donor Incentives across 63 Countries: The BEST Collaborative Study
(2023)
Journal Article
Downloadable Citations
About Repository@Nottingham
Administrator e-mail: discovery-access-systems@nottingham.ac.uk
This application uses the following open-source libraries:
SheetJS Community Edition
Apache License Version 2.0 (http://www.apache.org/licenses/)
PDF.js
Apache License Version 2.0 (http://www.apache.org/licenses/)
Font Awesome
SIL OFL 1.1 (http://scripts.sil.org/OFL)
MIT License (http://opensource.org/licenses/mit-license.html)
CC BY 3.0 ( http://creativecommons.org/licenses/by/3.0/)
Powered by Worktribe © 2025
Advanced Search