ArticleJournal of behavioral medicine2026
Application of the random-intercept cross-lagged panel model to behavioral intervention outcomes: a methodological tutorial assessing model fit.
Article in Journal of behavioral medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- Comment on "Constipation as a Hidden Barrier to Pelvic Floor Tele-Rehabilitation: A Randomized Controlled Trial in Women with Stress Urinary Incontinence".International urogynecology journal · 2026Article
- Data analysis for behavioral medicine: an introduction to the special issue.Journal of behavioral medicine · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
Abstract
The Random-Intercept Cross-Lagged Panel Model (RICLPM) has gained popularity in longitudinal research due to its ability to disaggregate within- and between-subjects variance. This approach more accurately depicts processes over time compared to traditional Cross-Lagged Panel Models (CLPMs). While RICLPMs are increasingly used, their application to data from behavioral interventions still is underexplored. This study aims to address this gap by demonstrating the application of RICLPM using data from a clinical trial of the digital Unified Protocol (iUP), a transdiagnostic cognitive-behavioral intervention applicable to mental and physical health comorbidities. We focus specifically on how RICLPM can be used to examine dynamic psychological processes during treatment, a central yet under-addressed question in behavioral medicine. We provide a methodological tutorial on adapting the model to intervention outcomes data, compare model fit statistics from an RICLPM and a traditional CLPM, and interpret results specifically in the context of psychological processes during a cognitive-behavioral intervention. Our findings show that RICLPM offers superior fit and more precise estimates of within-subject processes, underscoring its value in clinical research. We argue that adopting RICLPM in behavioral medicine research can help accurately identify psychological mechanisms and processes during behavioral interventions in health settings, aiding intervention personalization. The tutorial offers a resource for researchers interested in using RICLPM for more robust longitudinal analyses of behavioral intervention outcomes.
Indexed as
Identifiers
41417172What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.