Maintaining Policy Support for Contested Health Reforms: The Role of Trust, Emotion, and Procedural Legitimacy

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In Korea, efforts to expand the medical workforce—and the resulting mass resignations—highlight this challenge. While previous studies examine public trust, how it interacts with perceptions and emotions in response to reform remains less clear. We investigate how trust, problem perception, and emotional responses shape policy support. Methods In December 2024, 1,000 Korean adults aged 19 and over were surveyed using quota sampling. The responses regarding policy support, government trust, and emotions regarding policy conflicts were included. Structural equation modeling tested a moderated mediation model. Findings perceived physician shortage (B = 0.016; 95% CI, 0.010–0.022) and support for expansion policy (indirect = 0.005; direct = 0.066) were positively associated with trust in government. The link between problem perception and policy support was strengthened and weakened by negative emotion (B = 0.225; 95% CI, 0.052–0.399) and procedural justice (B = -0.220; 95% CI, –0.348 to -0.092), respectively. Anger marginally moderated support for expansion (B = 0.203; p < .10), while disappointment significantly reduced support for reform (B = -0.231; p < .01). Interpretation Whether to support the government’s health reform policy depends on both the content and implementation. To achieve sustainability of the current system, health authorities should reinforce ways to make reform policies more inclusive and transparent as well as emotionally resonant. Figures Figure 1 Introduction Even when the need for change is widely acknowledged, efforts to reform health systems often face significant resistance. Across countries, reform initiatives aimed at addressing physician shortages, reallocating resources, or improving system efficiency often stall or provoke backlash, not necessarily due to disagreement over the goals themselves, but how policies are introduced, communicated, and perceived by stakeholders. Institutional design and the power dynamics and political contexts in which such outcomes unfold shape their feasibility and outcomes. In this respect, understanding and sharing context-specific cases is essential for improving future policy design and implementation. A recent case in South Korea illustrates the difficulties of implementing reform, even with widespread support for the objectives, in the absence of public engagement. The government’s announcement of a plan to expand the physician workforce in 2024, which included a proposal to increase medical school enrolment, was met with fierce opposition from physician groups and sparked an ongoing national conflict. Despite long-standing agreement on the need to address the shortage of doctors, the reform failed to maintain sufficient public support. While many factors contributed to this outcome, many have highlighted the government’s ineffective communication strategy and limited public engagement. As of early 2025, medical students have returned to campus, but many continue to boycott lectures and junior doctors remain on strike, ultimately underscoring the unresolved nature of the conflict. This case provides a real-time illustration of how even widely supported reforms can unravel in the absence of public trust, effective communication, and stakeholder engagement. The central role of institutional trust in shaping public attitudes toward health policies, especially during times of crisis such as the COVID-19 pandemic, has been highlighted.¹ , ² Individuals with higher trust in government are more likely to perceive health problems as policy-relevant and support state-led interventions.³ However, trust does not operate in isolation. Rather, it interacts with how people cognitively assess the problem at hand and how they emotionally respond to the political context. Affective reactions, such as frustration or outrage, often arise not from policy content itself, but from perceptions of unfairness or exclusion in the policymaking process. 4 – 6 In this way, public responses are shaped not only by evaluations of policy effectiveness, but also those of procedural legitimacy and emotional engagement. 7 , 8 Building on this understanding, our study examines the following: (1) whether trust in government influences public support for physician workforce expansion and broader healthcare reform, (2) whether this relationship is mediated by perceived problem severity, and (3) how negative emotional responses and perceptions of procedural legitimacy moderate the link between problem perception and policy support. To contribute to a more comprehensive understanding of public support dynamics in the context of high-stake and ongoing health system reform, this study integrates cognitive, affective, and normative dimensions into a single analytical framework. Methods Study Design and Participants Data from a structured online survey conducted in December 2024 were analyzed via a cross-sectional approach. We recruited 1,000 South Korean adults aged 19 years and older using quota sampling stratified by region, sex, and age to ensure representativeness of the national population. The margin of sampling error was ± 3.10 percentage points at the 95% confidence level. Survey Instrument and Measures Participants’ perceptions, evaluations, and emotional responses related to ongoing healthcare reforms were assessed, as well as their sociodemographic characteristics. Participants’ level of support for the four major health reform policies proposed by the South Korean government, including the expansion of medical school admission quotas and broader health system improvements, was assessed using 5-point Likert scales and served as the dependent variable. The primary independent variable, trust in government, was measured on several dimensions, including trust in key institutions (Office of the President, Ministry of Health and Welfare, and Ministry of Education), perceptions of government effectiveness, and belief that the government prioritizes public and patient health in decision-making. Participants’ prior perceptions of the adequacy of physician supply (categorized as shortage, adequate, or surplus) and the perceived need for reform in six health subsystems, each measured using 5-point Likert scales, were assessed as mediators. Moderating effects were examined using perceptions of procedural legitimacy (dummy coded high vs low) and negative emotional reactions to the political conflict (dummy coded present vs absent), which captured experiences of anger, sadness, fear, disappointment, shame, and hatred. In all the analyses, sociodemographic characteristics including sex, age, region, education level and occupation were included as control variables. Details of the survey items are provided in Supplementary Materials A. Statistical Analysis As illustrated in Fig. 1 , structural equation modeling (SEM) was used to assess a moderated mediation effect. The analysis tested whether trust in government was associated with policy support via problem perception and whether negative emotional response and procedural justice to the political support moderated this indirect effect. All models were adjusted for participants’ sex, age, educational attainment, income level, and self-reported political orientation. Bootstrapping methods were used to estimate 95% confidence intervals for indirect and conditional effects. All statistical analyses were conducted using STATA 18 SE. Results Study Sample: Descriptive Characteristics The mean age of participants was 51.4 years (SD, 16.4), and the sample was evenly split by sex (49.8% male and 50.2% female). The mean score for trust in government was 19.2 (SD, 7.3) on a 7–35 scale, which indicates a moderate level of trust. The perceived need for healthcare reform averaged 24.0 (SD, 3.7) on a 6–30 scale, and agreement with reform had a mean of 15.1 (SD, 3.0) on a 4–20 scale, both of which reflect generally high levels (see Table 1 ). Most respondents had completed college (59.5%), followed by high school graduates (25.8%) and those with postgraduate education (12.5%). Regarding political ideology, 28.7%, 41.6%, and 29.7% identified as conservative, moderate, and progressive, respectively. Monthly income was widely distributed, with the largest group (19.6%) earning 3 to less than 4 million KRW. Regarding the perceived supply of physicians, 63.3% considered it insufficient, whereas 29.5% perceived it as adequate. Regarding procedural justice, 26.2% felt the policymaking process was not justified, 51.8% viewed it as partially justified, and 22.0% as fully justified. Emotional responses to the government–physician conflict was predominantly negative (71.6%), with 17.8% reporting positive emotions and 10.6% reporting no particular emotion. Table 1 Characteristics and Key Attitudinal Measures of Study Participants Variable Value Age, mean (SD), year 51.4 (16.4) Trust in government, mean (SD) a 19.2 (7.3) Perceived need for healthcare reform, mean (SD) b 24.0 (3.7) Agreement with healthcare reform, mean (SD) c 15.1 (3.0) Sex, No. (%) Male 498 (49.8) Female 502 (50.2) Education Level, No. (%) ≤ Middle school 22 (2.2) High school graduate 258 (25.8) College graduate 595 (59.5) Postgraduate 125 (12.5) Self-reported political ideology, No. (%) Conservative 287 (28.7) Moderate 416 (41.6) Progressive 297 (29.7) Monthly income, No. (%) Less than 1 million KRW 40 (4.0) 1 million to less than 2 million KRW 59 (5.9) 2 million to less than 3 million KRW 138 (13.8) 3 million to less than 4 million KRW 196 (19.6) 4 million to less than 5 million KRW 150 (15.0) 5 million to less than 6 million KRW 119 (11.9) 6 million to less than 7 million KRW 91 (9.1) 7 million to less than 10 million KRW 139 (13.9) 10 million KRW or more 68 (6.8) Perception of physician supply, No. (%) Insufficient 577 (63.3) Adequate 269 (29.5) More than adequate 65 (7.1) Procedural justice, No. (%) Not justified at all 245 (26.2) Partially justified 485 (51.8) Fully justified 206 (22.0) Emotional response to government-physician conflict, No. (%) Negative emotion 716 (71.6) Positive emotion 178 (17.8) No particular emotion 430 (10.6) a Score calculated as the sum of 7 Likert-scale items (1 = not at all to 5 = very much); total score range: 7 to 35. Higher scores indicate greater confidence in the government’s ability to respond effectively b Score calculated as the sum of 6 Likert-scale items (1 = very low 5 = very high); total score range: 6 to 30. Higher scores indicate stronger need for healthcare reform c Score calculated as the sum of 4 Likert-scale items (1 = very low 5 = very high); total score range: 4 to 20. Higher scores indicate stronger agreement with healthcare reform Correlation between main variables The correlations among the main study variables are reported in Table 2 . Trust in government was positively associated with perception of physician supply adequacy (r = 0.19, p < .001), perceived need for healthcare reform (r = 0.10, p < .01), and procedural justice (r = 0.69, p < .001). Trust was also strongly associated with agreement with increasing the number of doctors (r = 0.52, p < .001) and overall support for healthcare reform (r = 0.35, p < .001). In addition, perceptions of physician supply adequacy and perceived need for reform were positively associated with support for reform policies (r = 0.39 and r = 0.38, respectively; p < .001). Procedural justice was positively associated with agreement with an increasing number of doctors (r = 0.44, p < .001) and overall support for reform (r = 0.25, p < .001). Negative emotional responses were significantly negatively associated with trust in government (r = -0.16, p < .001) and procedural justice (r = -0.22, p < .001). Table 2 Correlation between main variables Variables 1 2 3 4 5 6 7 1 Trust in government 1.00 2 Perception of physician supply 0.19*** 1.00 3 Perceived need for healthcare reform 0.10** 0.21*** 1.00 4 Agreement with increasing the number of doctors 0.52*** 0.39*** 0.30*** 1.00 5 Agreement with healthcare reform 0.35*** 0.27*** 0.38*** 0.78*** 1.00 6 Negative emotional response to government-physician conflict -0.16*** 0.11** 0.07* 0.02 0.11** 1.00 7 Procedural justice 0.69*** 0.13** 0.10** 0.44*** 0.25*** -0.22*** 1.00 ***p < 0.001 **p < 0.01 *p < 0.05 Moderated Mediation Effects of Trust on Policy Support The path coefficients derived from the moderated mediation models are presented in Table 3 . The findings illustrate how trust in government influences policy support through perceived problem severity and how this relationship is conditioned by emotional responses and perceptions of procedural justice. In the physician workforce expansion model, trust in the government was significantly associated with a greater perceived shortage of physicians (B = 0.016; 95% CI, 0.010 to 0.022), which in turn was positively associated with support for policy (B = 0.344; 95% CI, 0.217 to 0.471). The indirect effect of trust in the government on policy support via perceived shortage of physicians was estimated as the product of the two paths (0.016 × 0.344 = 0.005) and was statistically significant based on bootstrapped confidence intervals using 1,000 re-samples (see Supplementary Material B Table S2 ). Moderated mediation analysis revealed that the interaction between perceived physician shortage and negative emotion was significant and positive (B = 0.225; 95% CI, 0.052 to 0.399), which suggests that the relationship between perceived physician supply and support for policy was stronger among participants with higher negative emotional responses. Conversely, regarding procedural justice as a moderator, the interaction term was significant and negative (B = − 0.220; 95% CI, − 0.348 to − 0.092), thereby indicating that the positive relationship between the aforementioned variables weakened when perceptions of procedural justice were higher. In the healthcare reform model, trust in the government was significantly associated with a greater perceived need for reform (B = 0.062; 95% CI, 0.019 to 0.106), which was in turn associated with higher support for reform (B = 0.334; 95% CI, 0.254 to 0.413). The corresponding indirect effect was significant (B = 0.021, 0.062 × 0.334 = 0.021), and the direct path from trust to political support also remained significant (B = 0.146; 95% CI, 0.116 to 0.176). Moderated mediation analysis revealed that the interaction between perceived need for reform and negative emotion was negative but not statistically significant (B = -0.091; 95% CI, -0.200 to 0.017). Similarly, the interaction term for procedural justice was also not significant (B = -0.003; 95% CI, -0.087 to 0.081), thereby suggesting that neither negative emotion nor procedural justice moderated the relationship between perceived need for reform and policy support. These results remained robust across alternative trust indicators, including trust in specific government institutions (see Supplementary Material B Table S1 ). Table 3 Path coefficients from moderated mediation models Outcome Variable Moderator Effect Type Predictor B 95% CI Political support with increasing the number of doctors Negative emotion Indirect Trust in government → Perceived physician supply 0.016 0.010 to 0.022 Indirect Perceived physician supply 0.344 0.217 to 0.471 Direct Trust in government 0.066 0.056 to 0.076 Moderator Perceived physician supply × Negative emotion 0.225 0.052 to 0.399 Procedural justice Indirect Trust in government → Perceived physician supply 0.016 0.010 to 0.022 Indirect Perceived physician supply 0.934 0.643 to 1.224 Direct Trust in government 0.054 0.042 to 0.066 Moderator Perceived physician supply × Procedural justice -0.220 -0.348 to -0.092 Political support on healthcare reform Negative emotion Indirect Trust in government → Perceived need for reform 0.062 0.019 to 0.106 Indirect Perceived need for reform 0.334 0.254 to 0.413 Direct Trust in government 0.146 0.116 to 0.176 Moderator Perceived need for reform × Negative emotion -0.091 -0.200 to 0.017 Procedural justice Indirect Trust in government → Perceived need for reform 0.062 0.019 to 0.105 Indirect Perceived need for reform 0.283 0.106 to 0.459 Direct Trust in government 0.142 0.105 to 0.180 Moderator Perceived need for reform × Procedural justice -0.003 -0.087 to 0.081 All models were adjusted for sex, age, income, education, and political orientation Subgroup Analyses of Negative Emotional Moderation Effects Subgroup analyses were conducted to determine whether specific negative emotions moderated the association between problem perception and policy agreement. The results regarding negative emotional responses are reported in Table 4 . In the model predicting support for physician workforce expansion, the interaction between perceived supply of physicians and anger approached statistical significance at the 10% level (B = 0.203; 95% CI, − 0.024 to 0.430; p < .10). Other emotional responses, including sadness (B = -0.385; 95% CI, -0.851 to 0.080), anxiety (B = 0.065; 95% CI, -0.185 to 0.314), disappointment (B = 0.033; 95% CI, − 0.224 to 0.289), shame (B = 0.192; 95% CI, -0.786 to 1.170), and hate (B = -0.066; 95% CI, -0.505 to 0.373), did not yield statistically significant moderating effects. In the healthcare reform model, the relationship between the perceived need for reform and political reform (B = − 0.231; 95% CI, -0.375 to -0.088; p < .01) was significantly moderated by disappointment. The effects of anger (B = 0.098; 95% CI, − 0.039 to 0.236), sadness (B = 0.086; 95% CI, − 0.222 to 0.393), anxiety (B = 0.031; 95% CI, − 0.160 to 0.222), shame (B = -0.003; 95% CI, -0.325 to 0.318), and hate (B = − 0.026; 95% CI, -0.234 to 0.182) were not statistically significant. Table 4 Subgroup Analysis of Moderating Effects by Type of Negative Emotion Outcome Variable Moderator B 95% CI Political support with increasing the number of doctors Anger 0.203 + -0.024 to 0.430 Sadness -0.385 -0.851 to 0.080 Anxiety 0.065 -0.185 to 0.314 Disappointment 0.033 -0.224 to 0.289 Shame 0.192 -0.786 to 1.170 Hate -0.066 -0.505 to 0.373 Political support on healthcare reform Anger 0.098 -0.039 to 0.236 Sadness 0.086 -0.222 to 0.393 Anxiety 0.031 -0.160 to 0.222 Disappointment -0.231 ** -0.375 to -0.880 Shame -0.003 -0.325 to 0.318 Hate -0.026 -0.234 to 0.182 All models were adjusted for sex, age, income, education, and political orientation ***p < 0.001 **p < 0.01 *p < 0.05 + < 0.1 Discussion We adopted a moderated mediation framework to examine the mechanisms by which trust in government influences public support for physician workforce expansion and broader healthcare reform policies. In both models, perceptions of the problem, whether regarding the adequacy of physician supply or the necessity of reform, consistently mediated the association between trust and political support. These findings suggest that trust not only exerts a direct influence on policy support, but also shapes how individuals interpret the problems that policy seeks to address. However, the strength and direction of this indirect pathway, which links trust to policy support through perceived problem severity, varied depending on how the public emotionally responded to the conflict between the government and medical community over physician workforce expansion. In particular, negative emotional reactions to conflicts between the government and physicians played a notable role. Contrary to expectations, stronger negative emotion was associated with greater support for expansion policies—contrary to expectations. This pattern may reflect a heightened urgency or desire for resolution among those most affected by the conflict in the physician workforce model. By contrast, in the healthcare reform model, negative emotion predicted lower policy support, which aligns with previous research that suggests emotional fatigue or disillusionment can dampen support for complex policy initiatives. 9 Subgroup analyses revealed emotion-specific moderating effects, thus underscoring the importance of distinguishing among discrete emotional responses. In the physician workforce model, anger marginally strengthened the association between problem perception and policy agreement, whereas in the healthcare reform model, disappointment significantly weakened this association. These findings align with those of previous research on the functional roles of discrete emotions. Often triggered by perceived injustice, anger is associated with appraisals of control and blame, and tends to promote approach-oriented behaviors, including political mobilization and support for policy change. 10 , 11 By contrast, disappointment is linked to unmet expectations and low perceived efficacy, often resulting in withdrawal or disengagement. 4 The divergent effects suggest that aggregating all negative emotions into a single category may obscure important psychological and behavioral dynamics in the policy domain. Further research is required to examine how specific emotional experiences interact with cognitive appraisals and institutional trust to shape public support for reform. These findings resonate with the growing body of literature that emphasizes the importance of discrete emotions in shaping policy preferences. For example, Wang et al. (2018) demonstrated that specific emotional responses, such as anger, hope, and fear, predict support for climate policy more strongly than general attitudes or beliefs. 12 Extending this perspective to the context of healthcare reform, our study documents that anger and disappointment operate in functionally distinct ways. Anger appears to mobilize support for physician workforce expansion, whereas disappointment suppresses support for broader reforms. These patterns underscore that not all negative emotions hinder policy support; some such as anger may heighten political engagement when individuals perceive injustice or accountability failures. This suggests that understanding the emotional landscape surrounding policy conflicts is critical not only for academic modeling of policy attitudes but also for the development of targeted and emotionally attuned public communication strategies. 12 In addition to emotion-specific effects, we also examined procedural justice, that is, citizens’ perceptions of fairness and transparency in policy processes, as a cognitive moderator. In the physician workforce model, higher perceptions of procedural fairness were associated with weaker links between problem perception and policy support, potentially reflecting a ceiling effect among those predisposed to support reform. This moderating effect was not observed in the broader healthcare reform model, which suggests that the relevance of fairness perceptions may depend on the salience and specificity of the policy issue. Taken together, these findings highlight the importance of considering both emotional and cognitive dimensions in understanding public support for reform. Notably, this study adds to the existing literature by examining how distinct emotions, not just general negativity, differentially shape policy attitudes. These insights underscore the value of moving beyond broad measures of trust or negativity toward more differentiated accounts of how people experience and process conflict-laden policy environments. In particular, focusing on how reforms are implemented, including perceptions of procedural fairness and the emotional impact of decision-making processes, may be critical to reinforcing legitimacy and support. Recognizing and addressing the elements that provoke emotional outrage, such as perceived injustice or exclusion, is essential not only for understanding resistance, but also for designing more robust and publicly acceptable reform strategies. Despite these contributions, this study has several limitations that should be noted. Emotional responses were measured using single-item indicators; future research could incorporate validated multi-item emotion scales to capture greater nuance. In addition, the cross-sectional nature limits causal inference, and longitudinal designs can better track how trust, emotional responses, and policy support evolve over time. Conclusion Overall, our findings highlight the layered nature of policy reasoning. Public support for health reform is not only a function of how people assess the content of policy, but also how they feel about the institutions behind it, the problems it aims to solve, and the fairness of the process through which it is developed. Pairing strong policy rationale with transparent, inclusive processes that foster both trust and emotional resonance may be beneficial for future reform efforts. Declarations a. Ethics approval and consent to participate This study was approved by the Institutional Review Board at Seoul National University (IRB No. 2412/003-013) and conducted in accordance with the ethical standards of the institutional and national research ethics guidelines. Informed consent was obtained from all participants prior to data collection. Clinical trial number: not applicable b. Consent for publication Not applicable c. Availability of data and materials The data that support the findings of this study are available from the corresponding author upon reasonable request. d. Competing interests None declared e. Funding This work was supported by the Graduate School of Public Health, Seoul National University. f. Acknowledgments None Author contributions Yoonkyoung Lee: As the first author, Yoonkyoung Lee led the overall conceptualization, methodology development, and formal analysis. She contributed actively to both supply and demand analyses and coordinated scenario modelling and played a central role in data integration and visualization. She drafted the original manuscript, supervised the research process, and participated in the critical review and editing. Yoonkyoung Lee holds the final responsibility for the decision to submit the manuscript. Jisoo Yoon: As the second author, Jisoo Yoon contributed to the development of the survey instrument, coordinated data collection, and conducted preliminary statistical analyses. She participated in data interpretation and actively contributed to the drafting and revision of the manuscript. She was also involved in quality control during data processing and ensured consistency across the analyses. Kyujoo Min: As the third author, Kyujoo Min supported the design of the analytical framework and provided input on statistical modeling. She contributed to the interpretation of the key findings and offered critical feedback during manuscript revision. She also assisted in aligning the study with the relevant policy contexts and literature. Myoungsoon You: As a co-corresponding author, Myoungsoon You provided conceptual and theoretical guidance throughout this study. She framed the research questions, interpreted the results, and refined the discussion. She was closely involved in reviewing and editing the manuscript and shares responsibility for the final decision to submit the manuscript for publication. Tae-Jin Lee : As the corresponding author, Tae-Jin Lee supervised the entire study, providing overall strategic guidance and critical review throughout the research process. He contributed to the study’s conceptualization and interpretation of findings and approved the final manuscript for submission. All authors collaborated on the data interpretation and contributed jointly to the analysis. All authors reviewed and approved the final version of the manuscript. References Blair RA, Morse BS, Tsai LL. Public health and public trust: survey evidence from the Ebola Virus Disease epidemic in Liberia. Soc Sci Med. 2017;172:89-97. Han Q, Zheng B, Cristea M, Agostini M, Bélanger JJ, Gützkow B, et al. Trust in government regarding COVID-19 and its associations with preventive health behaviour and prosocial behaviour during the pandemic: a cross-sectional and longitudinal study. Psychol Med. 2023;53(1):149-59. Herian MN, Shank NC, Abdel‐Monem TL. Trust in government and support for governmental regulation: the case of electronic health records. Health Expect. 2014;17(6):784-794. Bell E, Christensen J, Hansen KJ. Resistance or capitulation? How discrete emotions shape citizens’ interactions with the administrative state. Am Rev Public Adm. 2022;52(8):535-57. doi:10.1177/02750740221128554. Yokoyama M, Ohnuma S, Osawa H, Ohtomo S, Hirose Y. Public acceptance of nuclear waste disposal sites: a decision-making process utilising the ‘veil of ignorance’ concept. Humanit Soc Sci Commun. 2023;10(623). https://doi.org/10.1057/s41599-023-02139-2 Rodriguez‐Sanchez C, Schuitema G, Claudy M, Sancho‐Esper F. How trust and emotions influence policy acceptance: The case of the Irish water charges. Br J Soc Psychol. 2018; 57(3), 610-29. Reid JC, Brown SJ, Dmello J. COVID-19, diffuse anxiety, and public (mis)trust in government: empirical insights and implications for crime and justice. Crim Justice Rev. 2024;49(2):117-34. Rockers PC, Kruk ME, Laugesen MJ. Perceptions of the health system and public trust in government in low- and middle-income countries: evidence from the World Health Surveys. J Health Polit Policy Law. 2012; 37(3):405-437. doi:10.1215/03616878-1573076 Chang K, Park J. Negative emotions, projection bias, and the vote choice in South Korea. Hum Soc Sci Commun, 2025; 12(1), 1-11. Roseman, IJ. Functions of anger in the emotion system. The function of emotions: When and why emotions help us, 2018; 141-73. Lerner JS, Keltner D. Beyond valence: toward a model of emotion-specific influences on judgement and choice. Cogn Emot. 2000; 14(4), 473-93. Wang S, Leviston Z, Hurlstone M, Lawrence C, Walker I. Emotions predict policy support: Why it matters how people feel about climate change. Global Environ Change. 2018; 50, 25-40. Additional Declarations No competing interests reported. Supplementary Files SupplementaryA.docx SupplementaryB.docx Cite Share Download PDF Status: Under Review Version 1 posted Reviewers invited by journal 26 Sep, 2025 Editor assigned by journal 04 Jul, 2025 Editor invited by journal 03 Jul, 2025 Submission checks completed at journal 03 Jul, 2025 First submitted to journal 11 Jun, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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09:30:06","extension":"html","order_by":12,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":110008,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-6844611/v1/3fa521254e9241fce684ff09.html"},{"id":93026222,"identity":"a60043ab-fdb0-41a4-88e3-c25f895d1dd9","added_by":"auto","created_at":"2025-10-08 09:30:06","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":181316,"visible":true,"origin":"","legend":"\u003cp\u003eModerated Mediation Model of Policy Support in the Context of South Korea’s Ongoing Physician Workforce Reform Conflict (2024–2025)\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-6844611/v1/7ff6489b4f44c7608ba56822.png"},{"id":93029000,"identity":"196c68cf-316d-49c7-9d91-f42ba7dccc49","added_by":"auto","created_at":"2025-10-08 09:54:11","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":934726,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6844611/v1/b56a29e2-d6ae-446d-9dbc-5e889ed4767a.pdf"},{"id":93026225,"identity":"704e90d9-4f81-440b-9884-4252185c7328","added_by":"auto","created_at":"2025-10-08 09:30:06","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":28557,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryA.docx","url":"https://assets-eu.researchsquare.com/files/rs-6844611/v1/d1bed9516e47d4f6a3c4ef85.docx"},{"id":93026236,"identity":"5f9ce926-0217-4bc6-acea-41c1c0878c0c","added_by":"auto","created_at":"2025-10-08 09:30:10","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":23222,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryB.docx","url":"https://assets-eu.researchsquare.com/files/rs-6844611/v1/194886745aaa9b9db884c402.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Maintaining Policy Support for Contested Health Reforms: The Role of Trust, Emotion, and Procedural Legitimacy","fulltext":[{"header":"Introduction","content":"\u003cp\u003eEven when the need for change is widely acknowledged, efforts to reform health systems often face significant resistance. Across countries, reform initiatives aimed at addressing physician shortages, reallocating resources, or improving system efficiency often stall or provoke backlash, not necessarily due to disagreement over the goals themselves, but how policies are introduced, communicated, and perceived by stakeholders. Institutional design and the power dynamics and political contexts in which such outcomes unfold shape their feasibility and outcomes. In this respect, understanding and sharing context-specific cases is essential for improving future policy design and implementation.\u003c/p\u003e\u003cp\u003eA recent case in South Korea illustrates the difficulties of implementing reform, even with widespread support for the objectives, in the absence of public engagement. The government\u0026rsquo;s announcement of a plan to expand the physician workforce in 2024, which included a proposal to increase medical school enrolment, was met with fierce opposition from physician groups and sparked an ongoing national conflict. Despite long-standing agreement on the need to address the shortage of doctors, the reform failed to maintain sufficient public support. While many factors contributed to this outcome, many have highlighted the government\u0026rsquo;s ineffective communication strategy and limited public engagement. As of early 2025, medical students have returned to campus, but many continue to boycott lectures and junior doctors remain on strike, ultimately underscoring the unresolved nature of the conflict. This case provides a real-time illustration of how even widely supported reforms can unravel in the absence of public trust, effective communication, and stakeholder engagement.\u003c/p\u003e\u003cp\u003eThe central role of institutional trust in shaping public attitudes toward health policies, especially during times of crisis such as the COVID-19 pandemic, has been highlighted.\u0026sup1;\u003csup\u003e,\u003c/sup\u003e\u0026sup2; Individuals with higher trust in government are more likely to perceive health problems as policy-relevant and support state-led interventions.\u0026sup3; However, trust does not operate in isolation. Rather, it interacts with how people cognitively assess the problem at hand and how they emotionally respond to the political context. Affective reactions, such as frustration or outrage, often arise not from policy content itself, but from perceptions of unfairness or exclusion in the policymaking process.\u003csup\u003e\u003cspan additionalcitationids=\"CR5\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e In this way, public responses are shaped not only by evaluations of policy effectiveness, but also those of procedural legitimacy and emotional engagement.\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e,\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\u003cp\u003eBuilding on this understanding, our study examines the following: (1) whether trust in government influences public support for physician workforce expansion and broader healthcare reform, (2) whether this relationship is mediated by perceived problem severity, and (3) how negative emotional responses and perceptions of procedural legitimacy moderate the link between problem perception and policy support. To contribute to a more comprehensive understanding of public support dynamics in the context of high-stake and ongoing health system reform, this study integrates cognitive, affective, and normative dimensions into a single analytical framework.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eStudy Design and Participants\u003c/h2\u003e\u003cp\u003eData from a structured online survey conducted in December 2024 were analyzed via a cross-sectional approach. We recruited 1,000 South Korean adults aged 19 years and older using quota sampling stratified by region, sex, and age to ensure representativeness of the national population. The margin of sampling error was \u0026plusmn;\u0026thinsp;3.10 percentage points at the 95% confidence level.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eSurvey Instrument and Measures\u003c/h3\u003e\n\u003cp\u003eParticipants\u0026rsquo; perceptions, evaluations, and emotional responses related to ongoing healthcare reforms were assessed, as well as their sociodemographic characteristics.\u003c/p\u003e\u003cp\u003eParticipants\u0026rsquo; level of support for the four major health reform policies proposed by the South Korean government, including the expansion of medical school admission quotas and broader health system improvements, was assessed using 5-point Likert scales and served as the dependent variable. The primary independent variable, trust in government, was measured on several dimensions, including trust in key institutions (Office of the President, Ministry of Health and Welfare, and Ministry of Education), perceptions of government effectiveness, and belief that the government prioritizes public and patient health in decision-making. Participants\u0026rsquo; prior perceptions of the adequacy of physician supply (categorized as shortage, adequate, or surplus) and the perceived need for reform in six health subsystems, each measured using 5-point Likert scales, were assessed as mediators. Moderating effects were examined using perceptions of procedural legitimacy (dummy coded high vs low) and negative emotional reactions to the political conflict (dummy coded present vs absent), which captured experiences of anger, sadness, fear, disappointment, shame, and hatred. In all the analyses, sociodemographic characteristics including sex, age, region, education level and occupation were included as control variables.\u003c/p\u003e\u003cp\u003eDetails of the survey items are provided in Supplementary Materials A.\u003c/p\u003e\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003eStatistical Analysis\u003c/h2\u003e\u003cp\u003eAs illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, structural equation modeling (SEM) was used to assess a moderated mediation effect. The analysis tested whether trust in government was associated with policy support via problem perception and whether negative emotional response and procedural justice to the political support moderated this indirect effect. All models were adjusted for participants\u0026rsquo; sex, age, educational attainment, income level, and self-reported political orientation. Bootstrapping methods were used to estimate 95% confidence intervals for indirect and conditional effects. All statistical analyses were conducted using STATA 18 SE.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\u003ch2\u003eStudy Sample: Descriptive Characteristics\u003c/h2\u003e\u003cp\u003eThe mean age of participants was 51.4 years (SD, 16.4), and the sample was evenly split by sex (49.8% male and 50.2% female). The mean score for trust in government was 19.2 (SD, 7.3) on a 7\u0026ndash;35 scale, which indicates a moderate level of trust. The perceived need for healthcare reform averaged 24.0 (SD, 3.7) on a 6\u0026ndash;30 scale, and agreement with reform had a mean of 15.1 (SD, 3.0) on a 4\u0026ndash;20 scale, both of which reflect generally high levels (see Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eMost respondents had completed college (59.5%), followed by high school graduates (25.8%) and those with postgraduate education (12.5%). Regarding political ideology, 28.7%, 41.6%, and 29.7% identified as conservative, moderate, and progressive, respectively. Monthly income was widely distributed, with the largest group (19.6%) earning 3 to less than 4\u0026nbsp;million KRW. Regarding the perceived supply of physicians, 63.3% considered it insufficient, whereas 29.5% perceived it as adequate. Regarding procedural justice, 26.2% felt the policymaking process was not justified, 51.8% viewed it as partially justified, and 22.0% as fully justified. Emotional responses to the government\u0026ndash;physician conflict was predominantly negative (71.6%), with 17.8% reporting positive emotions and 10.6% reporting no particular emotion.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eCharacteristics and Key Attitudinal Measures of Study Participants\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"2\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariable\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eValue\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge, mean (SD), year\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e51.4 (16.4)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTrust in government, mean (SD)\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e19.2 (7.3)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePerceived need for healthcare reform, mean (SD) \u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e24.0 (3.7)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAgreement with healthcare reform, mean (SD) \u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e15.1 (3.0)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSex, No. (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e498 (49.8)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e502 (50.2)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEducation Level, No. (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026le; Middle school\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e22 (2.2)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHigh school graduate\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e258 (25.8)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCollege graduate\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e595 (59.5)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePostgraduate\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e125 (12.5)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSelf-reported political ideology, No. (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eConservative\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e287 (28.7)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eModerate\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e416 (41.6)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eProgressive\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e297 (29.7)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMonthly income, No. (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLess than 1\u0026nbsp;million KRW\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e40 (4.0)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1\u0026nbsp;million to less than 2\u0026nbsp;million KRW\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e59 (5.9)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2\u0026nbsp;million to less than 3\u0026nbsp;million KRW\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e138 (13.8)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e3\u0026nbsp;million to less than 4\u0026nbsp;million KRW\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e196 (19.6)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e4\u0026nbsp;million to less than 5\u0026nbsp;million KRW\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e150 (15.0)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e5\u0026nbsp;million to less than 6\u0026nbsp;million KRW\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e119 (11.9)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e6\u0026nbsp;million to less than 7\u0026nbsp;million KRW\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e91 (9.1)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e7\u0026nbsp;million to less than 10\u0026nbsp;million KRW\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e139 (13.9)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e10\u0026nbsp;million KRW or more\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e68 (6.8)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePerception of physician supply, No. (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eInsufficient\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e577 (63.3)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAdequate\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e269 (29.5)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMore than adequate\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e65 (7.1)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eProcedural justice, No. (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNot justified at all\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e245 (26.2)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePartially justified\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e485 (51.8)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFully justified\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e206 (22.0)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEmotional response to government-physician conflict, No. (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNegative emotion\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e716 (71.6)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePositive emotion\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e178 (17.8)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo particular emotion\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e430 (10.6)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"2\"\u003e\u003csup\u003ea\u003c/sup\u003e Score calculated as the sum of 7 Likert-scale items (1\u0026thinsp;=\u0026thinsp;not at all to 5\u0026thinsp;=\u0026thinsp;very much); total score range: 7 to 35. Higher scores indicate greater confidence in the government\u0026rsquo;s ability to respond effectively\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"2\"\u003e\u003csup\u003eb\u003c/sup\u003e Score calculated as the sum of 6 Likert-scale items (1\u0026thinsp;=\u0026thinsp;very low 5\u0026thinsp;=\u0026thinsp;very high); total score range: 6 to 30. Higher scores indicate stronger need for healthcare reform\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"2\"\u003e\u003csup\u003ec\u003c/sup\u003e Score calculated as the sum of 4 Likert-scale items (1\u0026thinsp;=\u0026thinsp;very low 5\u0026thinsp;=\u0026thinsp;very high); total score range: 4 to 20. Higher scores indicate stronger agreement with healthcare reform\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003eCorrelation between main variables\u003c/h2\u003e\u003cp\u003eThe correlations among the main study variables are reported in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. Trust in government was positively associated with perception of physician supply adequacy (r\u0026thinsp;=\u0026thinsp;0.19, p\u0026thinsp;\u0026lt;\u0026thinsp;.001), perceived need for healthcare reform (r\u0026thinsp;=\u0026thinsp;0.10, p\u0026thinsp;\u0026lt;\u0026thinsp;.01), and procedural justice (r\u0026thinsp;=\u0026thinsp;0.69, p\u0026thinsp;\u0026lt;\u0026thinsp;.001). Trust was also strongly associated with agreement with increasing the number of doctors (r\u0026thinsp;=\u0026thinsp;0.52, p\u0026thinsp;\u0026lt;\u0026thinsp;.001) and overall support for healthcare reform (r\u0026thinsp;=\u0026thinsp;0.35, p\u0026thinsp;\u0026lt;\u0026thinsp;.001).\u003c/p\u003e\u003cp\u003eIn addition, perceptions of physician supply adequacy and perceived need for reform were positively associated with support for reform policies (r\u0026thinsp;=\u0026thinsp;0.39 and r\u0026thinsp;=\u0026thinsp;0.38, respectively; p\u0026thinsp;\u0026lt;\u0026thinsp;.001). Procedural justice was positively associated with agreement with an increasing number of doctors (r\u0026thinsp;=\u0026thinsp;0.44, p\u0026thinsp;\u0026lt;\u0026thinsp;.001) and overall support for reform (r\u0026thinsp;=\u0026thinsp;0.25, p\u0026thinsp;\u0026lt;\u0026thinsp;.001). Negative emotional responses were significantly negatively associated with trust in government (r = -0.16, p\u0026thinsp;\u0026lt;\u0026thinsp;.001) and procedural justice (r = -0.22, p\u0026thinsp;\u0026lt;\u0026thinsp;.001).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eCorrelation between main variables\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"9\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eVariables\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c9\"\u003e\u003cp\u003e7\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTrust in government\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePerception of physician supply\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.19***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePerceived need for healthcare reform\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.10**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.21***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAgreement with increasing \u003c/p\u003e\u003cp\u003ethe number of doctors\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.52***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.39***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.30***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e1.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAgreement with healthcare reform\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.35***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.27***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.38***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.78***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e1.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNegative emotional response \u003c/p\u003e\u003cp\u003eto government-physician conflict\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e-0.16***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.11**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.07*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.11**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e1.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eProcedural justice\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.69***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.13**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.10**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.44***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.25***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e-0.22***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e1.00\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"9\"\u003e***p\u0026thinsp;\u0026lt;\u0026thinsp;0.001 **p\u0026thinsp;\u0026lt;\u0026thinsp;0.01 *p\u0026thinsp;\u0026lt;\u0026thinsp;0.05\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eModerated Mediation Effects of Trust on Policy Support\u003c/h3\u003e\n\u003cp\u003eThe path coefficients derived from the moderated mediation models are presented in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. The findings illustrate how trust in government influences policy support through perceived problem severity and how this relationship is conditioned by emotional responses and perceptions of procedural justice. In the physician workforce expansion model, trust in the government was significantly associated with a greater perceived shortage of physicians (B\u0026thinsp;=\u0026thinsp;0.016; 95% CI, 0.010 to 0.022), which in turn was positively associated with support for policy (B\u0026thinsp;=\u0026thinsp;0.344; 95% CI, 0.217 to 0.471). The indirect effect of trust in the government on policy support via perceived shortage of physicians was estimated as the product of the two paths (0.016 \u0026times; 0.344\u0026thinsp;=\u0026thinsp;0.005) and was statistically significant based on bootstrapped confidence intervals using 1,000 re-samples (see Supplementary Material B Table \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003e). Moderated mediation analysis revealed that the interaction between perceived physician shortage and negative emotion was significant and positive (B\u0026thinsp;=\u0026thinsp;0.225; 95% CI, 0.052 to 0.399), which suggests that the relationship between perceived physician supply and support for policy was stronger among participants with higher negative emotional responses. Conversely, regarding procedural justice as a moderator, the interaction term was significant and negative (B = \u0026minus;\u0026thinsp;0.220; 95% CI, \u0026minus;\u0026thinsp;0.348 to \u0026minus;\u0026thinsp;0.092), thereby indicating that the positive relationship between the aforementioned variables weakened when perceptions of procedural justice were higher.\u003c/p\u003e\u003cp\u003eIn the healthcare reform model, trust in the government was significantly associated with a greater perceived need for reform (B\u0026thinsp;=\u0026thinsp;0.062; 95% CI, 0.019 to 0.106), which was in turn associated with higher support for reform (B\u0026thinsp;=\u0026thinsp;0.334; 95% CI, 0.254 to 0.413). The corresponding indirect effect was significant (B\u0026thinsp;=\u0026thinsp;0.021, 0.062 \u0026times; 0.334\u0026thinsp;=\u0026thinsp;0.021), and the direct path from trust to political support also remained significant (B\u0026thinsp;=\u0026thinsp;0.146; 95% CI, 0.116 to 0.176). Moderated mediation analysis revealed that the interaction between perceived need for reform and negative emotion was negative but not statistically significant (B = -0.091; 95% CI, -0.200 to 0.017). Similarly, the interaction term for procedural justice was also not significant (B = -0.003; 95% CI, -0.087 to 0.081), thereby suggesting that neither negative emotion nor procedural justice moderated the relationship between perceived need for reform and policy support.\u003c/p\u003e\u003cp\u003eThese results remained robust across alternative trust indicators, including trust in specific government institutions (see Supplementary Material B Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003ePath coefficients from moderated mediation models\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOutcome Variable\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eModerator\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eEffect\u003c/p\u003e\u003cp\u003eType\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePredictor\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eB\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003e95% CI\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"7\" rowspan=\"8\"\u003e\u003cp\u003ePolitical support \u003c/p\u003e\u003cp\u003ewith increasing\u003c/p\u003e\u003cp\u003ethe number of doctors\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003eNegative \u003c/p\u003e\u003cp\u003eemotion\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eIndirect\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eTrust in government \u0026rarr; Perceived physician supply\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.016\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.010 to 0.022\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eIndirect\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePerceived physician supply\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.344\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.217 to 0.471\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDirect\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eTrust in government\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.066\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.056 to 0.076\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eModerator\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePerceived physician supply \u003c/p\u003e\u003cp\u003e\u0026times; Negative emotion\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.225\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.052 to 0.399\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003eProcedural justice\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eIndirect\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eTrust in government \u0026rarr; Perceived physician supply\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.016\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.010 to 0.022\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eIndirect\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePerceived physician supply\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.934\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.643 to 1.224\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDirect\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eTrust in government\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.054\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.042 to 0.066\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eModerator\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePerceived physician supply \u003c/p\u003e\u003cp\u003e\u0026times; Procedural justice\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e-0.220\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-0.348 to -0.092\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"7\" rowspan=\"8\"\u003e\u003cp\u003ePolitical support\u003c/p\u003e\u003cp\u003eon healthcare reform\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003eNegative \u003c/p\u003e\u003cp\u003eemotion\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eIndirect\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eTrust in government \u0026rarr; Perceived need for reform\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.062\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.019 to 0.106\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eIndirect\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePerceived need for reform\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.334\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.254 to 0.413\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDirect\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eTrust in government\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.146\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.116 to 0.176\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eModerator\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePerceived need for reform\u003c/p\u003e\u003cp\u003e\u0026times; Negative emotion\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e-0.091\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-0.200 to 0.017\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003eProcedural justice\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eIndirect\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eTrust in government \u0026rarr; Perceived need for reform\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.062\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.019 to 0.105\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eIndirect\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePerceived need for reform\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.283\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.106 to 0.459\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDirect\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eTrust in government\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.142\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.105 to 0.180\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eModerator\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePerceived need for reform\u003c/p\u003e\u003cp\u003e\u0026times; Procedural justice\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e-0.003\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-0.087 to 0.081\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eAll models were adjusted for sex, age, income, education, and political orientation\u003c/p\u003e\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\u003ch2\u003eSubgroup Analyses of Negative Emotional Moderation Effects\u003c/h2\u003e\u003cp\u003eSubgroup analyses were conducted to determine whether specific negative emotions moderated the association between problem perception and policy agreement. The results regarding negative emotional responses are reported in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e. In the model predicting support for physician workforce expansion, the interaction between perceived supply of physicians and anger approached statistical significance at the 10% level (B\u0026thinsp;=\u0026thinsp;0.203; 95% CI, \u0026minus;\u0026thinsp;0.024 to 0.430; p\u0026thinsp;\u0026lt;\u0026thinsp;.10). Other emotional responses, including sadness (B = -0.385; 95% CI, -0.851 to 0.080), anxiety (B\u0026thinsp;=\u0026thinsp;0.065; 95% CI, -0.185 to 0.314), disappointment (B\u0026thinsp;=\u0026thinsp;0.033; 95% CI, \u0026minus;\u0026thinsp;0.224 to 0.289), shame (B\u0026thinsp;=\u0026thinsp;0.192; 95% CI, -0.786 to 1.170), and hate (B = -0.066; 95% CI, -0.505 to 0.373), did not yield statistically significant moderating effects.\u003c/p\u003e\u003cp\u003eIn the healthcare reform model, the relationship between the perceived need for reform and political reform (B = \u0026minus;\u0026thinsp;0.231; 95% CI, -0.375 to -0.088; p\u0026thinsp;\u0026lt;\u0026thinsp;.01) was significantly moderated by disappointment. The effects of anger (B\u0026thinsp;=\u0026thinsp;0.098; 95% CI, \u0026minus;\u0026thinsp;0.039 to 0.236), sadness (B\u0026thinsp;=\u0026thinsp;0.086; 95% CI, \u0026minus;\u0026thinsp;0.222 to 0.393), anxiety (B\u0026thinsp;=\u0026thinsp;0.031; 95% CI, \u0026minus;\u0026thinsp;0.160 to 0.222), shame (B = -0.003; 95% CI, -0.325 to 0.318), and hate (B = \u0026minus;\u0026thinsp;0.026; 95% CI, -0.234 to 0.182) were not statistically significant.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eSubgroup Analysis of Moderating Effects by Type of Negative Emotion\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOutcome Variable\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eModerator\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eB\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e95% CI\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"5\" rowspan=\"6\"\u003e\u003cp\u003ePolitical support with increasing\u003c/p\u003e\u003cp\u003ethe number of doctors\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAnger\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.203 \u003csup\u003e+\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.024 to 0.430\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSadness\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.385\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.851 to 0.080\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAnxiety\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.065\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.185 to 0.314\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDisappointment\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.033\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.224 to 0.289\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eShame\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.192\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.786 to 1.170\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHate\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.066\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.505 to 0.373\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"5\" rowspan=\"6\"\u003e\u003cp\u003ePolitical support \u003c/p\u003e\u003cp\u003eon healthcare reform\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAnger\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.098\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.039 to 0.236\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSadness\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.086\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.222 to 0.393\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAnxiety\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.031\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.160 to 0.222\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDisappointment\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.231 **\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.375 to -0.880\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eShame\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.003\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.325 to 0.318\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHate\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.026\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.234 to 0.182\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eAll models were adjusted for sex, age, income, education, and political orientation\u003c/p\u003e\u003cp\u003e***p\u0026thinsp;\u0026lt;\u0026thinsp;0.001 **p\u0026thinsp;\u0026lt;\u0026thinsp;0.01 *p\u0026thinsp;\u0026lt;\u0026thinsp;0.05\u0026thinsp;+\u0026thinsp;\u0026lt;\u0026thinsp;0.1\u003c/p\u003e\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eWe adopted a moderated mediation framework to examine the mechanisms by which trust in government influences public support for physician workforce expansion and broader healthcare reform policies. In both models, perceptions of the problem, whether regarding the adequacy of physician supply or the necessity of reform, consistently mediated the association between trust and political support. These findings suggest that trust not only exerts a direct influence on policy support, but also shapes how individuals interpret the problems that policy seeks to address.\u003c/p\u003e\u003cp\u003eHowever, the strength and direction of this indirect pathway, which links trust to policy support through perceived problem severity, varied depending on how the public emotionally responded to the conflict between the government and medical community over physician workforce expansion. In particular, negative emotional reactions to conflicts between the government and physicians played a notable role. Contrary to expectations, stronger negative emotion was associated with greater support for expansion policies\u0026mdash;contrary to expectations. This pattern may reflect a heightened urgency or desire for resolution among those most affected by the conflict in the physician workforce model. By contrast, in the healthcare reform model, negative emotion predicted lower policy support, which aligns with previous research that suggests emotional fatigue or disillusionment can dampen support for complex policy initiatives.\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\u003cp\u003eSubgroup analyses revealed emotion-specific moderating effects, thus underscoring the importance of distinguishing among discrete emotional responses. In the physician workforce model, anger marginally strengthened the association between problem perception and policy agreement, whereas in the healthcare reform model, disappointment significantly weakened this association. These findings align with those of previous research on the functional roles of discrete emotions. Often triggered by perceived injustice, anger is associated with appraisals of control and blame, and tends to promote approach-oriented behaviors, including political mobilization and support for policy change.\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e,\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e By contrast, disappointment is linked to unmet expectations and low perceived efficacy, often resulting in withdrawal or disengagement.\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e The divergent effects suggest that aggregating all negative emotions into a single category may obscure important psychological and behavioral dynamics in the policy domain. Further research is required to examine how specific emotional experiences interact with cognitive appraisals and institutional trust to shape public support for reform.\u003c/p\u003e\u003cp\u003eThese findings resonate with the growing body of literature that emphasizes the importance of discrete emotions in shaping policy preferences. For example, Wang et al. (2018) demonstrated that specific emotional responses, such as anger, hope, and fear, predict support for climate policy more strongly than general attitudes or beliefs.\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e Extending this perspective to the context of healthcare reform, our study documents that anger and disappointment operate in functionally distinct ways. Anger appears to mobilize support for physician workforce expansion, whereas disappointment suppresses support for broader reforms. These patterns underscore that not all negative emotions hinder policy support; some such as anger may heighten political engagement when individuals perceive injustice or accountability failures. This suggests that understanding the emotional landscape surrounding policy conflicts is critical not only for academic modeling of policy attitudes but also for the development of targeted and emotionally attuned public communication strategies.\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\u003cp\u003eIn addition to emotion-specific effects, we also examined procedural justice, that is, citizens\u0026rsquo; perceptions of fairness and transparency in policy processes, as a cognitive moderator. In the physician workforce model, higher perceptions of procedural fairness were associated with weaker links between problem perception and policy support, potentially reflecting a ceiling effect among those predisposed to support reform. This moderating effect was not observed in the broader healthcare reform model, which suggests that the relevance of fairness perceptions may depend on the salience and specificity of the policy issue.\u003c/p\u003e\u003cp\u003eTaken together, these findings highlight the importance of considering both emotional and cognitive dimensions in understanding public support for reform. Notably, this study adds to the existing literature by examining how distinct emotions, not just general negativity, differentially shape policy attitudes. These insights underscore the value of moving beyond broad measures of trust or negativity toward more differentiated accounts of how people experience and process conflict-laden policy environments. In particular, focusing on how reforms are implemented, including perceptions of procedural fairness and the emotional impact of decision-making processes, may be critical to reinforcing legitimacy and support. Recognizing and addressing the elements that provoke emotional outrage, such as perceived injustice or exclusion, is essential not only for understanding resistance, but also for designing more robust and publicly acceptable reform strategies.\u003c/p\u003e\u003cp\u003eDespite these contributions, this study has several limitations that should be noted. Emotional responses were measured using single-item indicators; future research could incorporate validated multi-item emotion scales to capture greater nuance. In addition, the cross-sectional nature limits causal inference, and longitudinal designs can better track how trust, emotional responses, and policy support evolve over time.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eOverall, our findings highlight the layered nature of policy reasoning. Public support for health reform is not only a function of how people assess the content of policy, but also how they feel about the institutions behind it, the problems it aims to solve, and the fairness of the process through which it is developed. Pairing strong policy rationale with transparent, inclusive processes that foster both trust and emotional resonance may be beneficial for future reform efforts.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003ea. Ethics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was approved by the Institutional Review Board at Seoul National University (IRB No. 2412/003-013) and conducted in accordance with the ethical standards of the institutional and national research ethics guidelines. Informed consent was obtained from all participants prior to data collection.\u003c/p\u003e\n\u003cp\u003eClinical trial number: not applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eb. Consent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ec. Availability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data that support the findings of this study are available from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ed. Competing interests \u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNone declared\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ee. Funding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by the Graduate School of Public Health, Seoul National University. \u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ef. Acknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNone\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions \u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eYoonkyoung Lee:\u003c/strong\u003e As the first author, Yoonkyoung Lee led the overall conceptualization, methodology development, and formal analysis. She contributed actively to both supply and demand analyses and coordinated scenario modelling and played a central role in data integration and visualization. She drafted the original manuscript, supervised the research process, and participated in the critical review and editing. Yoonkyoung Lee holds the final responsibility for the decision to submit the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eJisoo Yoon:\u003c/strong\u003e As the second author, Jisoo Yoon contributed to the development of the survey instrument, coordinated data collection, and conducted preliminary statistical analyses. She participated in data interpretation and actively contributed to the drafting and revision of the manuscript. She was also involved in quality control during data processing and ensured consistency across the analyses.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eKyujoo Min:\u003c/strong\u003e As the third author, Kyujoo Min supported the design of the analytical framework and provided input on statistical modeling. She contributed to the interpretation of the key findings and offered critical feedback during manuscript revision. She also assisted in aligning the study with the relevant policy contexts and literature.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMyoungsoon You:\u003c/strong\u003e As a co-corresponding author, Myoungsoon You provided conceptual and theoretical guidance throughout this study. She framed the research questions, interpreted the results, and refined the discussion. She was closely involved in reviewing and editing the manuscript and shares responsibility for the final decision to submit the manuscript for publication.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTae-Jin Lee\u003c/strong\u003e: As the corresponding author, Tae-Jin Lee supervised the entire study, providing overall strategic guidance and critical review throughout the research process. He contributed to the study’s conceptualization and interpretation of findings and approved the final manuscript for submission.\u003c/p\u003e\n\u003cp\u003eAll authors collaborated on the data interpretation and contributed jointly to the analysis. All authors reviewed and approved the final version of the manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eBlair RA, Morse BS, Tsai LL. Public health and public trust: survey evidence from the Ebola Virus Disease epidemic in Liberia. Soc Sci Med. 2017;172:89-97.\u003c/li\u003e\n\u003cli\u003eHan Q, Zheng B, Cristea M, Agostini M, B\u0026eacute;langer JJ, G\u0026uuml;tzkow B, et al. Trust in government regarding COVID-19 and its associations with preventive health behaviour and prosocial behaviour during the pandemic: a cross-sectional and longitudinal study. Psychol Med. 2023;53(1):149-59.\u003c/li\u003e\n\u003cli\u003eHerian MN, Shank NC, Abdel‐Monem TL. Trust in government and support for governmental regulation: the case of electronic health records. Health Expect. 2014;17(6):784-794.\u003c/li\u003e\n\u003cli\u003eBell E, Christensen J, Hansen KJ. Resistance or capitulation? How discrete emotions shape citizens\u0026rsquo; interactions with the administrative state. Am Rev Public Adm. 2022;52(8):535-57. doi:10.1177/02750740221128554.\u003c/li\u003e\n\u003cli\u003eYokoyama M, Ohnuma S, Osawa H, Ohtomo S, Hirose Y. Public acceptance of nuclear waste disposal sites: a decision-making process utilising the \u0026lsquo;veil of ignorance\u0026rsquo; concept. Humanit Soc Sci Commun. 2023;10(623). https://doi.org/10.1057/s41599-023-02139-2\u003c/li\u003e\n\u003cli\u003eRodriguez‐Sanchez C, Schuitema G, Claudy M, Sancho‐Esper F. How trust and emotions influence policy acceptance: The case of the Irish water charges. Br J Soc Psychol. 2018; 57(3), 610-29.\u003c/li\u003e\n\u003cli\u003eReid JC, Brown SJ, Dmello J. COVID-19, diffuse anxiety, and public (mis)trust in government: empirical insights and implications for crime and justice. Crim Justice Rev. 2024;49(2):117-34.\u003c/li\u003e\n\u003cli\u003eRockers PC, Kruk ME, Laugesen MJ. Perceptions of the health system and public trust in government in low- and middle-income countries: evidence from the World Health Surveys. J Health Polit Policy Law. 2012; 37(3):405-437. doi:10.1215/03616878-1573076\u003c/li\u003e\n\u003cli\u003eChang K, Park J. Negative emotions, projection bias, and the vote choice in South Korea. Hum Soc Sci Commun, 2025; 12(1), 1-11.\u003cbr\u003e \u003c/li\u003e\n\u003cli\u003eRoseman, IJ. Functions of anger in the emotion system. The function of emotions: When and why emotions help us, 2018; 141-73.\u003c/li\u003e\n\u003cli\u003eLerner JS, Keltner D. Beyond valence: toward a model of emotion-specific influences on judgement and choice. Cogn Emot. 2000; 14(4), 473-93.\u003c/li\u003e\n\u003cli\u003eWang S, Leviston Z, Hurlstone M, Lawrence C, Walker I. Emotions predict policy support: Why it matters how people feel about climate change. Global Environ Change. 2018; 50, 25-40.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pubh","sideBox":"Learn more about [BMC Public Health](http://bmcpublichealth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pubh/default.aspx","title":"BMC Public Health","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-6844611/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6844611/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eHealth reform often faces resistance from key stakeholders, thus making public support essential to achieving reform goals. In Korea, efforts to expand the medical workforce—and the resulting mass resignations—highlight this challenge. While previous studies examine public trust, how it interacts with perceptions and emotions in response to reform remains less clear. We investigate how trust, problem perception, and emotional responses shape policy support.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn December 2024, 1,000 Korean adults aged 19 and over were surveyed using quota sampling. The responses regarding policy support, government trust, and emotions regarding policy conflicts were included. Structural equation modeling tested a moderated mediation model.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFindings\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eperceived physician shortage (B = 0.016; 95% CI, 0.010–0.022) and support for expansion policy (indirect = 0.005; direct = 0.066) were positively associated with trust in government. The link between problem perception and policy support was strengthened and weakened by negative emotion (B = 0.225; 95% CI, 0.052–0.399) and procedural justice (B = -0.220; 95% CI, –0.348 to -0.092), respectively. Anger marginally moderated support for expansion (B = 0.203; p \u0026lt; .10), while disappointment significantly reduced support for reform (B = -0.231; p \u0026lt; .01).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInterpretation\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWhether to support the government’s health reform policy depends on both the content and implementation. To achieve sustainability of the current system, health authorities should reinforce ways to make reform policies more inclusive and transparent as well as emotionally resonant.\u003c/p\u003e","manuscriptTitle":"Maintaining Policy Support for Contested Health Reforms: The Role of Trust, Emotion, and Procedural Legitimacy","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-08 09:30:01","doi":"10.21203/rs.3.rs-6844611/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewersInvited","content":"","date":"2025-09-26T05:10:00+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-07-04T06:56:28+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-07-03T12:49:20+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-07-03T12:40:12+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Public Health","date":"2025-06-11T20:16:34+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pubh","sideBox":"Learn more about [BMC Public Health](http://bmcpublichealth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pubh/default.aspx","title":"BMC Public Health","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"5f3a9395-b7e4-4d33-b41e-60b0f46725d0","owner":[],"postedDate":"October 8th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2025-10-08T09:30:01+00:00","versionOfRecord":[],"versionCreatedAt":"2025-10-08 09:30:01","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6844611","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6844611","identity":"rs-6844611","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}