Exploring the medical decision-making patterns and influencing factors among the general Chinese public: a binary logistic regression analysis

Abstract Objective With the ongoing evolution of the healthcare system and shifts in cultural paradigms, there is a pressing need to delve into the medical decision-making behaviors of general Chinese public and understand their underlying motivations. This research seeks to elucidate the prevailing...

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Main Authors: Yuwen Lyu, Qian Xu, Junrong Liu
Format: Article
Language:English
Published: BMC 2024-03-01
Series:BMC Public Health
Subjects:
Online Access:https://doi.org/10.1186/s12889-024-18338-8
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author Yuwen Lyu
Qian Xu
Junrong Liu
author_facet Yuwen Lyu
Qian Xu
Junrong Liu
author_sort Yuwen Lyu
collection DOAJ
description Abstract Objective With the ongoing evolution of the healthcare system and shifts in cultural paradigms, there is a pressing need to delve into the medical decision-making behaviors of general Chinese public and understand their underlying motivations. This research seeks to elucidate the prevailing tendencies in these decision-making processes and to empirically validate the pivotal factors that shape their choices, offering valuable insights for healthcare policymakers and institutions. Method A comprehensive survey was administered to 2,696 Chinese residents to examine their medical decision-making patterns. These patterns were classified into two primary categories: Unilateral Decision-making (Doctor-dominant, Family-centric, and Patient-driven subtypes) and Collaborative Decision-making (Doctor-led, Doctor-Patient, Patient-Family, and Doctor-Patient-Family subtypes). Binary logistic regression analysis was employed to empirically pinpoint the significant factors influencing these decision-making frameworks. Results The study's analysis reveals distinct preferences in medical decision-making among Chinese residents. In the Collaborative Decision-making category, chosen by 70.81% of participants, the subtypes are as follows: Doctor-led (29.90%), Doctor-Patient (13.54%), Patient-Family (2.93%), and Doctor-Patient-Family (24.44%). The Unilateral Decision-making, preferred by 29.19%, includes Doctor-dominant (23.22%), Family-centric (1.74%), and Patient-driven (4.23%) models. The preference for Collaborative Decision-making is associated with higher educational levels, specific marital statuses (particularly married but childless), and choices of rural residents' basic medical insurance or occupational basic medical insurance. In contrast, Unilateral Decision-making correlates with males, individuals with religious beliefs, certain occupational roles (like civil servants), and holders of commercial or publicly funded medical insurance. Conclusion This study elucidates the complex interplay of socio-cultural and individual determinants shaping medical decision-making in China. The findings reveal a marked inclination towards collaborative models, closely linked to educational level, marital status, and specific insurance types, reflecting an evolving trend towards participatory healthcare. Simultaneously, the persistence of unilateral models, influenced by gender, religious beliefs, and occupational roles, highlights the heterogeneity within Chinese healthcare preferences. These insights are crucial for policymakers and healthcare practitioners, underscoring the need for adaptable, culturally attuned healthcare frameworks that cater to this diversity, thereby enhancing patient engagement and healthcare efficacy.
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spelling doaj.art-663b79950bbd4c5fa1585d585088c87b2024-03-31T11:37:51ZengBMCBMC Public Health1471-24582024-03-0124111210.1186/s12889-024-18338-8Exploring the medical decision-making patterns and influencing factors among the general Chinese public: a binary logistic regression analysisYuwen Lyu0Qian Xu1Junrong Liu2Institute of Humanities and Social Sciences, Guangzhou Medical UniversitySchool of Health Management, Guangzhou Medical UniversityInstitute of Humanities and Social Sciences, Guangzhou Medical UniversityAbstract Objective With the ongoing evolution of the healthcare system and shifts in cultural paradigms, there is a pressing need to delve into the medical decision-making behaviors of general Chinese public and understand their underlying motivations. This research seeks to elucidate the prevailing tendencies in these decision-making processes and to empirically validate the pivotal factors that shape their choices, offering valuable insights for healthcare policymakers and institutions. Method A comprehensive survey was administered to 2,696 Chinese residents to examine their medical decision-making patterns. These patterns were classified into two primary categories: Unilateral Decision-making (Doctor-dominant, Family-centric, and Patient-driven subtypes) and Collaborative Decision-making (Doctor-led, Doctor-Patient, Patient-Family, and Doctor-Patient-Family subtypes). Binary logistic regression analysis was employed to empirically pinpoint the significant factors influencing these decision-making frameworks. Results The study's analysis reveals distinct preferences in medical decision-making among Chinese residents. In the Collaborative Decision-making category, chosen by 70.81% of participants, the subtypes are as follows: Doctor-led (29.90%), Doctor-Patient (13.54%), Patient-Family (2.93%), and Doctor-Patient-Family (24.44%). The Unilateral Decision-making, preferred by 29.19%, includes Doctor-dominant (23.22%), Family-centric (1.74%), and Patient-driven (4.23%) models. The preference for Collaborative Decision-making is associated with higher educational levels, specific marital statuses (particularly married but childless), and choices of rural residents' basic medical insurance or occupational basic medical insurance. In contrast, Unilateral Decision-making correlates with males, individuals with religious beliefs, certain occupational roles (like civil servants), and holders of commercial or publicly funded medical insurance. Conclusion This study elucidates the complex interplay of socio-cultural and individual determinants shaping medical decision-making in China. The findings reveal a marked inclination towards collaborative models, closely linked to educational level, marital status, and specific insurance types, reflecting an evolving trend towards participatory healthcare. Simultaneously, the persistence of unilateral models, influenced by gender, religious beliefs, and occupational roles, highlights the heterogeneity within Chinese healthcare preferences. These insights are crucial for policymakers and healthcare practitioners, underscoring the need for adaptable, culturally attuned healthcare frameworks that cater to this diversity, thereby enhancing patient engagement and healthcare efficacy.https://doi.org/10.1186/s12889-024-18338-8Medical decisionDecision-making patternsInfluencing factorsLogistic regression
spellingShingle Yuwen Lyu
Qian Xu
Junrong Liu
Exploring the medical decision-making patterns and influencing factors among the general Chinese public: a binary logistic regression analysis
BMC Public Health
Medical decision
Decision-making patterns
Influencing factors
Logistic regression
title Exploring the medical decision-making patterns and influencing factors among the general Chinese public: a binary logistic regression analysis
title_full Exploring the medical decision-making patterns and influencing factors among the general Chinese public: a binary logistic regression analysis
title_fullStr Exploring the medical decision-making patterns and influencing factors among the general Chinese public: a binary logistic regression analysis
title_full_unstemmed Exploring the medical decision-making patterns and influencing factors among the general Chinese public: a binary logistic regression analysis
title_short Exploring the medical decision-making patterns and influencing factors among the general Chinese public: a binary logistic regression analysis
title_sort exploring the medical decision making patterns and influencing factors among the general chinese public a binary logistic regression analysis
topic Medical decision
Decision-making patterns
Influencing factors
Logistic regression
url https://doi.org/10.1186/s12889-024-18338-8
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