Evidence map›Paper›PMID 41968190›Full record

ArticlePrevention science : the official journal of the Society for Prevention Research2026

Area Between Trajectories: Insights into Optimal Group Selection and Trajectory Heterogeneity in Group-Based Trajectory Modeling.

Yi-Chen Hsiao, Chun-Yuan Chen, Mei-Fen Tang

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Article in Prevention science : the official journal of the Society for Prevention Research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

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.

2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Yi-Chen Hsiao *Institute of Health and Welfare Policy, School of Medicine, National Yang-Ming University, Taipei, Taiwan.
Chun-Yuan Chen *Institute of Health Policy and Management, College of Public Health, National Taiwan University, Room 651, 6Th Floor, No. 17, Xuzhou Road, Zhongzheng District, 100025, Taipei, Taiwan. d98845002@ntu.edu.tw.ORCID 0000-0002-6244-8455
Mei-Fen TangDepartment of Nursing, Wan Fang Hospital, Taipei Medical University, Taipei, Taiwan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Group-based trajectory modeling (GBTM) is commonly used to identify longitudinal patterns in health outcomes among older adults, with determining the optimal number of groups being a crucial step. While statistically grounded criteria are primarily relied upon, clinical relevance is gradually emphasized in medicine to ensure that the identified trajectory heterogeneity appropriately reflects changes in a disease or symptom over time. However, such considerations are often judged through visual comparisons, without concrete approaches for their application. To address this, the area between trajectories (ABT) was introduced as insights for quantifying trajectory group differences. Using a simulated sleep quality dataset, GBTM was applied to build and compare models. Subsequently, ABT was demonstrated to show how it works, while also highlighting its limitations and potential applications.

Indexed as

Models, StatisticalHumansLongitudinal StudiesSleep QualityArea between trajectoriesGroup-based trajectory modelingLongitudinal patternsOptimal number of groupsTrajectory heterogeneity

Identifiers

PMID41968190

What OpenQuestion holds

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Registered trials

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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.