Evidence map›Paper›PMID 42380833›Full record

ArticleBMC primary care2026

Urban residents' choice preferences for hospitals at different tiers and influencing factors: a study based on latent class analysis and Andersen's model of health service utilization.

Ke Wang, Hang Chen, Yu Jin, Rui Min

Abstract read
In one paragraph

Article in BMC primary care, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
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

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.

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

4 authors.

Ke WangSchool of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China.
Hang ChenSchool of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China.
Yu JinSchool of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China.
Rui MinSchool of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China. minrui0801@hust.edu.cn.

Funding

National Natural Science Foundation of China 72204091
6 · The paper itself

Abstract

backgroundChina's health system faces widespread bypassing behavior, where residents prefer high-level hospitals, leading to inefficient primary resource use. This study aimed to identify distinct preference groups in urban residents' choices of hospitals and to examine how predisposing, enabling, and need factors from Andersen's Model differentially influence healthcare-seeking intention across groups.

methodsA cross-sectional survey was conducted in Wuhan, China, from July 2023 to August 2024, involving 2,890 participants. Latent Class Analysis (LCA) was employed to segment the population based on seven consideration attributes for choosing hospitals. Multinomial logistic regression was then used to analyze the influence of predisposing, enabling, and need factors. Specifically, it examined how these factors affected healthcare-seeking intention within each identified latent class.

resultsLCA identified four distinct preference groups: the Core Resource Preference Group (29.9%), the Medical Technology Preference Group (35.6%), the High-Quality & Low-Cost Preference Group (11.1%), and the Convenient Transportation Preference Group (23.5%). Healthcare-seeking intention varied significantly: the Medical Technology Group had the highest tertiary hospital selection rate (68.0%), while the Convenient Transportation Group had the highest combined rate for self-medication and primary care (57.6%). Regression analyses revealed heterogeneous influences: in the Core Resource and Convenient Transportation groups, higher confidence in family finances was associated with lower odds of choosing tertiary hospitals. In contrast, in the Medical Technology Group, worse past-year health status increased the likelihood of selecting secondary hospitals. Higher education consistently predicted tertiary hospital use across all groups.

conclusionUrban residents' hospital-choice preferences are heterogeneous, and the factors influencing their healthcare-seeking intention vary significantly across different preference profiles. These findings suggest that "one-size-fits-all" policies are inadequate, and targeted interventions are needed. This study provides empirical evidence for designing more effective, population-specific strategies to promote a rational hierarchical healthcare system. Moreover, these findings indicate that the mechanisms underlying the healthcare-seeking intention of different preference groups require further exploration.

Indexed as

Choice BehaviorHospitalsPatient Acceptance of Health CareUrban PopulationAdultChinaCross-Sectional StudiesFemaleHumansLatent Class AnalysisMaleMiddle AgedAndersen's Model of Health Service UtilizationHealthcare-seeking intentionHospital preferenceLatent Class AnalysisUrban resident

Identifiers

PMID42380833
PMCPMC13591714

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.