E. Charzyńska
AB0130 PROFILES OF WELL-BEING AND THEIR RELATIONSHIPS WITH SELF-FORGIVENESS, FORGIVENESS OF OTHERS, AND GRATITUDE AMONG PATIENTS WITH RHEUMATIC AND MUSCULOSKELETAL DISEASES
Charzyńska, E.; Offenbächer, M.; Halverson, K.; Hirsch, J.; Kohls, N.; Hanshans, C.; Sirois, F.; Toussaint, L.
Authors
M. Offenbächer
K. Halverson
J. Hirsch
N. Kohls
C. Hanshans
Professor Fuschia Sirois fuschia.sirois@durham.ac.uk
Professor
L. Toussaint
Abstract
Background:
Chronic conditions such as rheumatic and musculoskeletal diseases (RMDs) can cause significant distress and reduced well-being. Commonly, research has emphasized understanding distress (depression, anxiety, and pain symptoms) to the relative exclusion of well-being. Moreover, research on the well-being of patients with RMDs has been dominated by a variable-centered approach. Since this approach assumes that all participants are derived from a uniform population, it neglects a possible heterogeneity in aspects of well-being for this group. Moreover, it limits the conclusions that may be drawn from exploring relationships between well-being and positive psychological factors.
Objectives:
To address these issues, in the current study, we used the person-centered approach. The study aimed to identify profiles of positive (life satisfaction and health status) and negative (depression, anxiety, fatigue, and stress) indicators of well-being among patients with RMDs. Moreover, positive psychological (self-forgiveness, forgiveness of others, and gratitude) and sociodemographic (gender and age) factors, and disease type (arthritis versus fibromyalgia (FM)), were tested as correlates of latent profile membership.
Methods:
The sample consisted of 892 patients with RMDs attending a healing gallery in Bad Gastein, Austria, including 759 patients with arthritis and 133 with FM. The healing gallery is a unique therapeutic environment that combines high humidity, warmth and radon and attracts patients with chronic conditions from around the globe. Patients (N = 6465) were invited to participate in an online survey. The survey was comprised of validated measures of positive and negative psychological experiences and moral virtues. The measures included: The Patient Health Questionnaire, Perceived Stress Scale, Multidimensional Fatigue Inventory, Forgiveness Scale, Gratitude Questionnaire, and single item life satisfaction and health status measures. A latent profile analysis (LPA) was applied to determine the optimal number of profiles of well-being. Predictors of latent profile membership were tested with multinomial logistic regression using the three-step estimation (R3STEP) command.
Results:
LPA identified four profiles of well-being: (1) “life dissatisfaction” (9.2%), (2) “high well-being” (43.4%), (3) “suboptimal well-being” (35.2%), and (4) “very poor well-being” (12.2%) (see Figure 1). Results of multinomial logistic regression analyses are shown in Table 1. Members of Profile 2 had higher levels of self-forgiveness and gratitude than members of the remaining profiles, had higher levels of forgiveness of others than Profile 3, and were older than members of Profile 4. Moreover, members of Profile 2 had a higher proportion of (a) men to women than Profile 4 and (b) patients with arthritis to those with FM than all other profiles.
Conclusion:
Patients with RMDs have heterogeneous patterns of well-being. As suggested by the results, low levels of negative indicators of well-being do not imply high levels of positive ones (and vice versa). Moreover, positive indicators of well-being may co-occur with negative ones. These findings suggest that both types of indicators should be included together in future well-being studies. Regarding the treatment of patients with RMDs, special attention should be paid to the well-being of women, patients with FM, and younger patients since they seem to be more susceptible to poor well-being than their counterparts. Self-forgiveness, gratitude, and forgiveness of others (to a lesser degree) may serve as psychological capital that protects patients against poor well-being and, as such, are recommended to be incorporated into psychological interventions dedicated to patients with RMDs. To this end, evidence-based methods of improving self-forgiveness, gratitude, and forgiveness of others are currently available and could be used in future studies to examine the benefits of these virtues in living with RMDs.
Citation
Charzyńska, E., Offenbächer, M., Halverson, K., Hirsch, J., Kohls, N., Hanshans, C., Sirois, F., & Toussaint, L. (2024). AB0130 PROFILES OF WELL-BEING AND THEIR RELATIONSHIPS WITH SELF-FORGIVENESS, FORGIVENESS OF OTHERS, AND GRATITUDE AMONG PATIENTS WITH RHEUMATIC AND MUSCULOSKELETAL DISEASES. Annals of the Rheumatic Diseases, 83(1), 1298-1299. https://doi.org/10.1136/annrheumdis-2024-eular.456
Journal Article Type | Article |
---|---|
Acceptance Date | May 10, 2024 |
Online Publication Date | Jun 10, 2024 |
Publication Date | 2024-06 |
Deposit Date | Jan 20, 2025 |
Journal | Annals of the Rheumatic Diseases |
Print ISSN | 0003-4967 |
Electronic ISSN | 1468-2060 |
Publisher | BMJ Publishing Group |
Peer Reviewed | Peer Reviewed |
Volume | 83 |
Issue | 1 |
Pages | 1298-1299 |
DOI | https://doi.org/10.1136/annrheumdis-2024-eular.456 |
Keywords | arthritis; fibromyalgia; forgiveness; gratitude; latent profile analysis; person‐centred approach; well‐being |
Public URL | https://durham-repository.worktribe.com/output/3332301 |
You might also like
Procrastination and health: A longitudinal test of the roles of stress and health behaviours
(2023)
Journal Article
The role of self‐compassion in the mental health of adults with ADHD
(2022)
Journal Article
Downloadable Citations
About Durham Research Online (DRO)
Administrator e-mail: dro.admin@durham.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