Evidence map›Paper›PMID 41186661›Full record

ArticleThe patient2026

Reducing Primary Healthcare Bypass Behaviour: A Discrete Choice Experiment Study Exploring the Preferences for Primary Eye Care Services in Rural Xinjiang.

Xiaodong Dong, Junling Zhao, Ziyin Zhao, Can Su, Xiaochen Ma

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Article in The patient, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1 · What the graph read from it

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3 · Its place in the literature

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1 citing paper in PubMed.

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5 · Who and what money

Authors and funding

5 authors.

Xiaodong DongSchool of Public Health, Peking University, Beijing, China.
Junling ZhaoSchool of Public Health, Peking University, Beijing, China.
Ziyin ZhaoSchool of Public Health, Peking University, Beijing, China.
Can SuSchool of Public Health, Peking University, Beijing, China.
Xiaochen MaSchool of Public Health, Peking University, Beijing, China. xma@hsc.pku.edu.cn.

Funding

National Natural Science Foundation of China No. 72174009Peking University No.88412Y0079
6 · The paper itself

Abstract

backgroundBypassing primary healthcare (PHC) in favor of higher-level providers is a persistent issue in many low- and middle-income settings, particularly in rural China, where primary eye care (PEC) remains underutilized. Understanding patient preferences and determinants of care-seeking behavior is crucial for promoting patient-centered outcomes and strengthening PHC utilization.

objectivesThis study aimed to identify the key service attributes and patient characteristics influencing rural residents' preferences for PEC in Xinjiang, China, and to assess the role of health literacy in mitigating PHC bypass behavior.

methodsA discrete choice experiment (DCE) was conducted among 465 rural adults (aged ≥ 18 years) in northern Xinjiang, who were selected using a multistage stratified sampling approach. Six PEC service attributes-cost, convenience, organizational form, provider type, service frequency, and feedback mechanism-were tested. The cost and convenience attributes each had four levels, while the other four attributes had three levels. Respondents completed a structured questionnaire assessing knowledge, attitudes, and practices related to eye health. Data were analyzed using mixed logit and latent class models to estimate preference heterogeneity and willingness to pay (WTP) for different attributes.

resultsRural residents demonstrated strong preferences for services provided by county hospital ophthalmologists, lower costs, shorter travel times, and comprehensive feedback, including medical advice and verbal explanations. PHC-based PEC delivered by township or village doctors was significantly less preferred, requiring monetary compensation to offset perceived utility loss. Enhanced feedback mechanisms and higher health literacy were associated with greater acceptance of PHC-based services. Latent class analysis revealed significant heterogeneity, identifying subgroups that were sensitive to cost and convenience, as well as a large subgroup with low engagement and a tendency to rely on higher-tier care. This subgroup exhibited the lowest preference for PEC services at the PHC level, highlighting a potential barrier to the utilization of local services.

conclusionsEfforts to strengthen PHC-based PEC in rural China must address both structural and perceptual barriers, prioritizing quality improvement, provider-patient communication, and health literacy interventions. Patient-centered service design, informed by DCE-derived preferences, may reduce bypassing and promote more equitable access to eye care.

Indexed as

Choice BehaviorPatient Acceptance of Health CarePatient PreferencePrimary Health CareRural PopulationAdultAgedChinaFemaleHealth Knowledge, Attitudes, PracticeHealth LiteracyHumansMaleMiddle AgedSurveys and QuestionnairesYoung Adult

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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.