Latent transitions of ego depletion during pharmacological therapy in newly diagnosed rheumatoid arthritis patients: implications for self-management behaviors

Objective To delineate latent transition patterns of ego depletion during csDMARD induction in newly diagnosed rheumatoid arthritis (RA) and their association with self-management in this observational cohort. Methods In this single-centre cohort, 255 newly diagnosed RA patients were enrolled and 230 completed assessments at baseline (T0), 3 (T1) and 6 months (T2). Ego depletion (SEDS) and self-management (RASMS) were evaluated. Latent profile analysis was conducted at each occasion and latent transition analysis modelled T1 → T2 transitions. Classification uncertainty was propagated with the Bolck–Croon–Hagenaars three-step method, and modal assignment served as a sensitivity analysis. Associations with T2 self-management were estimated with lagged models adjusted for the baseline score and for time-varying treatment and disease-activity covariates. Results Two latent classes were identified at T0 (low depletion 58.0%, moderate 42.0%) and three at T1 and T2 (low 25.2% and 32.2%, moderate 47.0% and 45.2%, high 27.8% and 22.6%). Entropy was 0.873–0.892; average posterior probabilities were 0.897–0.938, with classification error of 9.7% at T1 and 8.7% at T2. From T1 to T2 the moderate class was the most stable (88.89%) and the high class the least stable (65.63%); 13.9% of patients moved to a lower and 4.3% to a higher depletion class. Three transition cells contained 2–4 participants and were pooled. The T1 high depletion class was associated with a lower T2 total self-management score ( β = −14.32, 95% CI: −17.86 to −10.78, P < 0.001). Stable high depletion was associated with low-level self-management (OR = 4.106, 95% CI: 1.724–9.778) and poor medication adherence (OR = 4.482, 95% CI: 1.926–10.432); exposure and outcome were concurrent, so these are not temporal predictions. Conclusions In this exploratory, single-centre cohort, ego depletion was heterogeneous and partly reversible during csDMARD induction. Persistent high depletion was associated with poorer self-management and medication adherence, but the observational and partly concurrent design precludes causal inference. Because only the T1–T2 interval was modelled, we cannot conclude that 3–6 months is uniquely a critical intervention window. External validation and intervention trials are required before targeted monitoring or psychological empowerment can be recommended.

Authors

Institutions

Publication Details

Journal
Frontiers in Medicine
Published
2026-11-06
DOI
https://doi.org/10.3389/fmed.2026.1947407
Primary Topic
Rheumatoid Arthritis Research and Therapies
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
NOV
article

Latent transitions of ego depletion during pharmacological therapy in newly diagnosed rheumatoid arthritis patients: implications for self-management behaviors

Shuping Guo, Dongli Wang, Lei Zhou, Xiao-qing Bao
3 links
Frontiers in Medicine
Rheumatoid Arthritis Research and Therapies
article

Latent transitions of ego depletion during pharmacological therapy in newly diagnosed rheumatoid arthritis patients: implications for self-management behaviors

Shuping Guo, Dongli Wang, Lei Zhou, Xiao-qing Bao
article en

Abstract

Objective To delineate latent transition patterns of ego depletion during csDMARD induction in newly diagnosed rheumatoid arthritis (RA) and their association with self-management in this observational cohort. Methods In this single-centre cohort, 255 newly diagnosed RA patients were enrolled and 230 completed assessments at baseline (T0), 3 (T1) and 6 months (T2). Ego depletion (SEDS) and self-management (RASMS) were evaluated. Latent profile analysis was conducted at each occasion and latent transition analysis modelled T1 → T2 transitions. Classification uncertainty was propagated with the Bolck–Croon–Hagenaars three-step method, and modal assignment served as a sensitivity analysis. Associations with T2 self-management were estimated with lagged models adjusted for the baseline score and for time-varying treatment and disease-activity covariates. Results Two latent classes were identified at T0 (low depletion 58.0%, moderate 42.0%) and three at T1 and T2 (low 25.2% and 32.2%, moderate 47.0% and 45.2%, high 27.8% and 22.6%). Entropy was 0.873–0.892; average posterior probabilities were 0.897–0.938, with classification error of 9.7% at T1 and 8.7% at T2. From T1 to T2 the moderate class was the most stable (88.89%) and the high class the least stable (65.63%); 13.9% of patients moved to a lower and 4.3% to a higher depletion class. Three transition cells contained 2–4 participants and were pooled. The T1 high depletion class was associated with a lower T2 total self-management score ( β = −14.32, 95% CI: −17.86 to −10.78, P < 0.001). Stable high depletion was associated with low-level self-management (OR = 4.106, 95% CI: 1.724–9.778) and poor medication adherence (OR = 4.482, 95% CI: 1.926–10.432); exposure and outcome were concurrent, so these are not temporal predictions. Conclusions In this exploratory, single-centre cohort, ego depletion was heterogeneous and partly reversible during csDMARD induction. Persistent high depletion was associated with poorer self-management and medication adherence, but the observational and partly concurrent design precludes causal inference. Because only the T1–T2 interval was modelled, we cannot conclude that 3–6 months is uniquely a critical intervention window. External validation and intervention trials are required before targeted monitoring or psychological empowerment can be recommended.

Frontiers in MedicineVol. 13
Ningxia Medical University General Hospital (CN)
Good health and well-being
Openalex Percentile: Top 14%
Rheumatoid Arthritis Research and Therapies
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Laika access coming soon