An Integrated Model of Cognition, Emotion, and Vote Choice: Evidence from Taiwan

An Integrated Model of Cognition, Emotion, and Vote Choice: Evidence from Taiwan | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article An Integrated Model of Cognition, Emotion, and Vote Choice: Evidence from Taiwan Chia-hung Tsai This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8291322/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Political behavior research often separates cognitive evaluations from emotional reactions, treating voters as either rational performance evaluators or emotionally driven decision makers. This study advances an integrated cognition–emotion model in which broad political evaluation (e.g., retrospective judgment) and discrete emotional response—anxiety and anger—operate as distinct but interacting pathways shaping electoral choice. Using post-election survey data from Taiwan’s 2024 presidential contest and controlling for lagged vote choice and feelings toward candidates, I show that negative assessments of Taiwan’s international status and cross-Strait relations significantly reduce support for the incumbent. Anxiety about potential conflict independently lowers incumbent support and amplifies the electoral penalty associated with negative evaluations. Anger toward external coercion, by contrast, increases support for the incumbent but does not strengthen the effect of cognitive judgments. Across all robustness checks, the core findings remain substantively identical. These findings offer a framework for understanding how citizens interpret political conditions and how these interpretations—cognition and emotions–shape their vote choices. Figures Figure 1 Figure 2 Introduction Research on voting behavior has long emphasized that citizens rely on cognitive considerations—such as issue preferences, retrospective performance evaluations, and candidate assessments—when making electoral choices (Fiorina 1981 ; Lau and Sears 1981 ; Brody and Page 1972; Jackson 1975 ; Kinder and Kiewit 1979; Lodge, Steenbergen, and Brau 1995 ). A parallel tradition demonstrates that affective predispositions, especially partisanship, guide information processing and shape evaluative orientations (Campbell et al. 1960; Jacoby 1988 ; Greene 1999 ; Bartels 2000 ). This body of work establishes that cognition and affect both matter, but it focuses primarily on attitudes and emotions directed at candidates or parties, rather than the reactions citizens form in response to the political environment they face. By contrast, psychological theories suggest that individuals continually interpret their environment through both evaluative and emotional lenses. Appraisal theory and affective intelligence emphasize that political conditions—uncertainty, risk, coercion, crisis—simultaneously elicit cognitive judgments and emotional reactions, each with distinct behavioral implications (Roseman, 1984 ; Lerner and Keltner, 2000 ; Marcus, Neuman, and MacKuen, 2000 ; Ellsworth and Scherer, 2003 ; Huddy, Feldman, and Cassese 2007). Yet the political behavior literature seldom incorporates these environment-elicited emotions into models of vote choice. Existing work tends to examine emotions triggered by campaign stimuli or candidate impressions (Abelson et al. 1982 ; Glaser and Salovey 1998 ; Isbell and Otatti, 2002). Some research finds how broader political conditions generate emotions and influence attitudes and behavior (Wagner and Morisi 2019 ; Rico, Guinjoan, and Anduiza 2017 ; Vasilopoulos et al. 2019 ), but this work leaves unexplored how these reactions combine with cognitive evaluations to shape electoral decisions. A comprehensive model of vote choice must retain both cognition and emotion because they represent distinct, non-substitutable causal pathways to the ballot box. While cognitive evaluations (like retrospective performance judgments) influence choice through reasoned assessment, discrete emotions (like anxiety or anger) occur in parallel, triggering unique motivational impulses for decision (Erisen 2020 ). Drawing insights from appraisal theory and affective intelligence theory, this research proposes an integrated cognition–emotion model of voting. By “integrated,” I refer to a framework in which cognitive evaluations and discrete emotions operate as distinct and co-occurring pathways rather than competing or sequential explanations. These two mechanisms --broad political evaluation and discrete emotional response—operate independently but may intersect when emotions condition how strongly individuals weight negative evaluations. By theorizing cognition and emotion as simultaneous and mutually reinforcing pathways, this paper offers a nuanced psychological correction to standard voting. The 2024 Taiwan presidential election presents an ideal case for examining these processes. Taiwan faces continuous military and diplomatic coercion from China, making evaluations of international status and cross-Strait relations highly salient. These same conditions trigger anxiety about potential conflict and anger over military incursions. The coexistence of chronic external pressure and competitive multiparty politics allows us to directly test how voters combine cognitive assessments of national conditions with emotional reactions to the surrounding environment. Using high-quality post-election survey data from Taiwan’s 2024 presidential election, this study makes three contributions to research on political behavior. First, it provides clear observational evidence for a cognition–emotion voting model: voters who perceive Taiwan’s international standing or cross-Strait relations as deteriorating are substantially less likely to support the incumbent, consistent with performance-based retrospective voting. Second, anxiety and anger exert independent and opposing effects—anxiety erodes incumbent support, whereas anger strengthens it—demonstrating that emotions are structured components of political judgment rather than epiphenomenal reflections of partisanship. Third, anxiety significantly magnifies the electoral penalty associated with negative evaluations while anger does not, helping resolve ambiguities in the rally-’round-the-flag literature, which typically assumes uniform emotional responses to external threats. These patterns hold even after controlling for lagged vote choice, identity, and candidate affect, increasing confidence in the causal interpretation. More broadly, the findings reframe emotion as a meaningful part of rational political decision-making. Anxiety and anger emerge from appraisal of uncertainty and blame—processes that occur across policy domains—not solely from threats to national security. Economic downturns, corruption scandals, pandemics, and sudden social disruptions similarly generate appraisals of risk, responsibility, and intentionality that activate these same emotional channels. The mechanism identified here—anxiety heightens sensitivity to perceived competence failures while anger shifts responsibility outward and mobilizes defensive support—offers a generalizable account of voter behavior in diverse democratic settings. This cognition–emotion model therefore extends beyond Taiwan, speaking directly to political behavior in democracies such as Korea, Japan, and others where citizens regularly confront uncertainty and contested attributions of blame. The next sections develop the theoretical framework, derive empirical predictions, and evaluate them using original survey data. Cognition and Emotion as Parallel Pathways Citizens judge their government largely through assessments of performance–domestic and foreign policy–such as international reputation or security performance (Aldrich, Sullivan, and Borgida 1989 ; Gelpi, Reifler, and Feaver 2007 ; Druckman and Lupia 2020). Yet purely cognitive accounts often understate the influence of emotion on political judgment (Lodge and Taber 2013 ). A large literature shows that emotions generated by political actors shape evaluation and choice: affective reactions to candidates guide candidate evaluation (Abelson et al. 1982 ; Isbell and Ottatti 2002 ), emotional responses predict vote preference (Markus 1988 ), and affect expressed by candidates increases attention, memory, and favorability (Glaser and Salovey 1998 ). However, these studies focus primarily on candidate-based affect, leaving underexplored the emotional responses that arise from the political environment itself—such as uncertainty, risk, or coercion—and how those emotions combine with cognitive evaluations to shape voter decision-making. Psychological research demonstrates that individuals interpret political events through distinct but interacting cognition and emotion systems, rather than through a linear sequence in which cognition precedes emotion (Zajonc 1984a ; Hoffman 1984). Each pathway carries distinct implications for political judgment. As Izard ( 1984 ) notes, emotional and cognitive capacities develop together and jointly shape complex behaviors. Psychological experiments also show that mere exposure can create affect (emotion) toward a stimulus independently of and prior to the need for conscious cognitive processes (Zajonc 1984b ). Taken together, I argue that voter behavior reflects a dual-pathway process in which cognitive evaluations and emotional appraisals jointly inform electoral choice. Consistent with Crawford’s ( 2000 :156) characterization that “humans make decisions that are always both classically self-interested and emotional,” this study does not treat cognition as the cause of emotion. Instead, cognition and emotion arise simultaneously as inputs of how individuals make voting decisions. Anxiety and Anger AIT identifies distinct emotional systems that regulate attention and behavioral motivation. Anxiety arises when individuals determine a stimulus or event as uncertain, potentially harmful, and beyond personal control. This emotion heightens vigilance, directs attention toward potential losses, increases information seeking, and encourages cautious or change-oriented behavior (Marcus and MacKuen 1993 ; Lerner and Keltner 2000 ; Wagner and Morisi 2019 ). Anxiety motivates behavior aimed at moving away from danger, hiding, or searching the environment for safety (Frijda 1986 ). Anger, by contrast, is elicited by a threat with certainty (Gadarian and Brader 2023:203). It heightens blame, punitive preferences, and mobilization (Banks and Valentino 2012 ; Valentino et al. 2011 ; Banks 2014 ). Anger is linked to the appraisal of other-blame and control (Lazarus 1991 ). It emerges when individuals perceive a threat as certain, intentional, and blameworthy. Therefore, it activates approach motivation, punishment of the responsible actor, and support for assertive or confrontational responses based on optimistic risk assessments (Huddy, Feldman, Weber 2007 ; Lerner and Keltner 2001 ). In sum, anger and anxiety have opposite effects on policy preferences because of their differing appraisals of control and certainty . Anxiety increased risk aversion and reduced support for offensive action but anger increases support for aggressive foreign policy (Huddy et al. 2005 ). Accordingly, I expect anxiety to reduce support for the incumbent, while anger should benefit the incumbent by shifting responsibility toward the external antagonist. Contemporary psychological work emphasizes that cognition and emotion are dynamically intertwined (Roseman, Abelson, and Ewing 1986 ), often arising simultaneously as complementary components of the appraisal process (Ellsworth and Scherer 2003 ). Cognitive appraisal is a necessary antecedent for many emotional responses, and emotion can bias cognitive processing, directing attention and influencing which memories are retrieved. Thus, voters can form cognitive judgments about national conditions—such as deterioration in cross-Strait relations—while also experiencing discrete emotions such as anxiety (from uncertainty about conflict) or anger (from perceiving Chinese military coercion as intentional aggression). Although Taiwan’s 2024 election provides a vivid setting in which external coercion activates strong emotional reactions, the same appraisal processes apply whenever citizens interpret conditions that involve uncertainty, loss, or blame—including economic downturns, corruption scandals, pandemic policy failures, and domestic political conflict. As a result, the cognition–emotion framework offers a general theory of voter behavior that extends beyond threat politics and speaks to foundational debates about accountability, performance voting, and democratic responsiveness. The preceding framework yields clear expectations about how cognition and emotion shape electoral behavior. I formalize these expectations in the following hypotheses. Independent Effects on Incumbent Support Drawing from retrospective voting logic, negative evaluations of national standing should reduce support for the incumbent. When voters perceive worsening international status or heightened cross-Strait tension, they may attribute responsibility to the government and punish it electorally. This establishes the first expectation: H1 (Cognitive Punishment Hypothesis): Voters who perceive Taiwan’s international or cross-Strait situation as deteriorating will be less likely to support the incumbent party. Emotion introduces a second causal pathway. Anxiety, by signaling uncertainty and the potential for harm, encourages citizens to reconsider the status quo and to become risk averse. Anger, in contrast, is associated with blame and mobilization against the perceived threat, which in contexts of external coercion can strengthen defensive solidarity with incumbents. This mechanism parallels—but also refines—arguments in the rally-’round-the-flag literature, which assumes a uniform emotional reaction to threat. By distinguishing anxiety from anger, the theory predicts opposing electoral forces: H2 (Anxiety-induced Weakening Support Hypothesis): Higher levels of anxiety about potential conflict will decrease support for the incumbent party. H3 (Anger-induced Strengthening Support Hypothesis): Higher levels of anger at external coercion will increase support for the incumbent party. Interaction Between Cognitive Evaluation and Anxiety Prior studies suggest that anxiety increases vigilance, heightens attention to potential losses, and expands search for alternatives. When a voter is both anxious and perceives national deterioration , the emotion makes the negative evaluation more consequential. Anger, however, redirects responsibility toward the threatening other. When a voter feels angry over political object or event, that emotional reaction interrupts the usual cognitive mechanism that blames the government. Even if the voter perceives the international situation as worsening, anger cues them to attribute the cause externally. This weakens the electoral relevance of the cognitive judgment. In the Taiwanese context, this means that anxiety about conflict amplifies the electoral consequences of perceived diplomatic deterioration, whereas anger may buffer or reverse them. Because anger shifts blame to the adversary, it should not increase the electoral penalty for negative evaluations; if anything, it may attenuate it. Therefore, I propose the following hypothesis: H4 (Anxiety Amplification Hypothesis): Anxiety will strengthen the negative effect of worsening evaluations of national standing on support for the incumbent. In sum, my theory contains two parallel pathways—cognitive evaluations and discrete emotions—and a key interaction: negative evaluations reduce incumbent support; anxiety further amplifies this effect; anger moves voters in the opposite direction. These propositions guide the empirical analysis that follows. Table 1 summarizes the direction and significance of key results, linking each hypothesis to the corresponding empirical pattern. Table 1 Cognition, Emotion, and Support for Incumbents Variables Cognition Emotion Evaluation of Taiwan’s International Status Deterioration of international status → significant negative effect → supports H1 (perceived decline punishes incumbents) Evaluation of Cross-Strait Relations Deterioration of cross-Strait relations ◊ significant negative effect → supports H1 (perceived decline punishes incumbents) Level of Anxiety about Potential Conflict Worried about conflict → significant negative effect → supports H2 (anxiety increases opposition) Level of Anger over China’s Coercion Upset about drills → significant positive effect → supports H3 (anger mobilizes defense) Interaction of national standing and emotion Deterioration of international status & anxiety→ significant negative effect → supports H4 Deterioration of international status & anger→ insignificant effect Interaction of cross-Strait relations and emotion Deterioration of cross-Strait relations & anxiety ◊ significant negative effect→ supports H4 Deterioration of cross-Strait relations & anger ◊ insignificant effect Source: Author Context: Taiwan’s 2024 Presidential Election The 2024 Taiwan presidential election unfolded amid intensified Chinese military coercion, making cross-Strait relations the dominant issue. The DPP’s Lai Ching-te emphasized deterrence and sovereignty, appealing to voters that oppose China’s aggression. In contrast, the KMT’s Hou Yu-ih advocated dialogue, framing the DPP’s stance as risky and useless. Ko Wen-je of the Taiwan People’s Party offered an ambiguous middle path, criticizing both Beijing and the DPP, which complicate the dichotomy on national security issues. Data and Variables My analysis leverages data from the Taiwan Election and Democratization Study (TEDS) (Chen 2024 ). The 2024 TEDS survey was conducted by the Election Study Center at National Chengchi University between January 15 and May 31, 2024. The research team drew a sample of 14,503 addresses, from which 1,206 face-to-face interviews were completed. This study was approved by Institutional Review Board of National Chengchi University (approve no. NCCU-REC-202007-I073 v.24) on December 23, 2023. Data is deposited at Survey Research Data Archive, Academia Sinica. Independent Variables To test the cognition–emotion framework, I distinguish between citizens’ evaluative judgments of national conditions and their emotional reactions to the same external environment. Consistent with retrospective and foreign-policy voting research, cognitive appraisal is measured using two items that capture respondents’ assessments of Taiwan’s international position: (1) whether Taiwan’s international status has improved, remained the same, or deteriorated over the past four years; and (2) whether cross-Strait relations have improved, remained stable, or worsened. These items directly reflect voters’ judgments about the government’s diplomatic management and perceived national standing. Emotional appraisal is measured using two discrete emotions central to appraisal theory and affective intelligence—anxiety and anger. Anxiety is captured by respondents’ worry about potential military conflict, reflecting an uncertainty-based hazard appraisal. Anger is measured by respondents’ feeling of being upset over China’s encirclement of Taiwan with military aircraft and vessels, reflecting a blame-based appraisal of intentional coercion. Together, these measures align with the theoretical distinction between cognitive evaluations of national conditions and discrete emotional responses, enabling an empirical test of parallel and interactive pathways in the cognition–emotion voting model. People’s responses to foreign threats may reflect the domestic political environment (Myrick 2021 ). To account for partisan alignment without conditioning on a potentially endogenous variable, the models instead include respondents’ vote choice in the 2020 presidential election. This lagged measure—coded as DPP vs. KMT and People’s First Party (PFP)--captures preexisting partisan predispositions while remaining exogenous to the emotional and evaluative processes triggered by recent developments. Analyses using current partisanship as a robustness check yield similar patterns in Table C1 in Appendix C, but the main specification relies on lagged vote to better isolate the causal influence of emotion and cognition on 2024 vote intention. The weighted distribution of 2020 presidential votes in the sample (DPP 64.4%, KMT/PFP 35.6%) slightly overstates support for the incumbent relative to official results (57.1% vs. 42.9%). This deviation likely reflects recall and desirability biases common in post-election surveys. I run a subgroup analysis for people voted for the DPP in 2020 and present the results in Table C2. Since citizens’ feelings toward political leaders strongly predict attitude and behavior (Iyengar et al., 2019 ), it is necessary to rule out affective bias. I include the difference in feeling thermometer scores between Lai and his rivals. These two variables capture candidate-specific affect that may mitigate emotional responses, such as anger, directed toward candidates or their parties. In addition, Taiwanese identity has been the most salient cleavage (Achen and Wang 2017 ). Thus, it is also included in the voting model. See Appendix B for the full question wording. Dependent Variable: Voting Choice Our dependent variable, support for the incumbent, is operationalized as a vote for the DPP ticket (Lai Ching-te/Hsiao Bi-khim), who successfully retained the presidency. Respondents that said they did not turn out to vote or refused to answer this question are dropped from the analysis. Because the dependent variable is dichotomous, I use binary logit regression model to estimate the effect of each independent variable. I also separate KMT and TPP and run a multinomial logit model with TPP as the baseline category. The results presented in Table C3, C4, and C5 are substantially similar. This survey is post-stratified to be nationally representative. Since my goal is theoretical explanation of emotional and cognitive mechanisms in voting under external coercion but not population estimation, all regression analyses use unweighted data. Weighted descriptive statistics are reported to ensure sample representativeness. Robustness checks using survey weights yield substantively identical results in Table C6. Results Table 2 reports odds ratios from logistic regressions predicting the likelihood of voting for the incumbent. The baseline model includes voters’ electoral decisions in 2020, retrospective evaluations of Taiwan’s international status and cross-Strait relations, emotional responses (anxiety and anger), interaction terms between cognitive evaluations and emotional reactions, and sociodemographic controls. The baseline model shows that voters who perceive Taiwan’s international status becomes worse are significantly less likely to support the DPP (OR ≈ 0.013), even after accounting for previous voting behavior and emotional reactions, implying that voters punish incumbents for perceived diplomatic decline. Voters who perceive Taiwan’s international status as deteriorating are only about 1.3% as likely to support the incumbent DPP compared to those who perceive the status as improving (the reference category). Evaluations of cross-Strait relations are weaker predictors, suggesting that citizens may have normalized the chronic tension with China and instead focus more on Taiwan’s broader international standing. Level of anxiety about potential conflict is negatively associated with voting for the DPP (OR ≈ 0.308). This finding aligns with the appraisal framework that anxiety tends to correlate with withdrawing from the status quo (Plutchik 1984 :200). Level of anger over encircling of Chinese warplanes and warships is positively associated with voting for the DPP (OR ≈ 2.509), which is consistent with the appraisal theory expectation that anger—elicited by perceived external threat—mobilizes defensive solidarity and produces a “rally-’round-the-flag” effect. Table 2 Estimates of Incumbent Voting Choice Models Baseline model Lai and Hou Difference Lai and Ko Difference Intercept 0.069* 0.141 0.603 (0.086) (0.199) (1.115) Voted for DPP in 2020 58.196*** 16.453*** 31.061*** (26.613) (7.945) (17.650) International status unchanged 0.152+ 0.058* 0.015* (0.170) (0.077) (0.026) International status worse 0.013** 0.022* 0.035+ (0.019) (0.038) (0.068) Cross-Strait relations deteriorated 0.412 0.886 0.302 (0.439) (1.104) (0.454) Level of Anxiety about Potential Conflict 0.308** 0.333** 0.189** (0.111) (0.135) (0.107) Level of Anger over China’s Coercion 2.509** 2.021+ 1.718 (0.838) (0.767) (0.828) Difference in Feeling between Lai and Hou 1.563*** (0.099) Difference in Feeling between Lai and Ko 2.233*** (0.204) Taiwanese identity 4.093*** 2.940** 2.554* (1.234) (0.979) (1.008) International status unchanged and Anxiety 1.787 1.927 2.355 (0.683) (0.837) (1.335) International status worse and Anxiety 3.523** 3.010* 1.977 (1.666) (1.573) (1.244) Cross-Strait relations deteriorated and Anxiety 1.388 1.390 2.524+ (0.494) (0.560) (1.302) International status unchanged and Anger 0.764 1.091 1.552 (0.292) (0.485) (0.867) International status worse and Anger 0.641 0.764 1.055 (0.285) (0.363) (0.625) Cross-Strait relations deteriorated and Anger 0.824 0.726 0.609 (0.287) (0.285) (0.296) Num.Obs. 793 784 783 AIC 465.3 394.7 282.3 BIC 563.5 497.3 384.9 Log.Lik. -211.666 -175.350 -119.147 Note: Values presented are Odds Ratios (e ß ) from a logistic regression model. Standard errors are in parentheses below the OR. The reference category for “International Status” is “better”. The reference category for “Cross-Strait relations” is “Improve and the same”. Significance: † p < 0.10; p < 0.05; p < 0.01; p < 0.001 Source: Chen ( 2024 ) Most notably, the interaction between anxiety and perceptions of Taiwan’s worsening international status is significant and positive. Although anxiety alone is related to opposing the incumbent—reflecting vigilance and blame attribution (Forgas 1995 ; Marcus, Neuman, and MacKuen 2000 )—its effect reverses when citizens perceive the nation’s global standing as deteriorating. Under perceived decline, anxiety increases the odds of voting for the ruling party (OR ≈ 3.523). The antagonistic interaction–simple predictors and the interaction have opposite signs–suggests that voters that worry about potential conflict and have negative view about Taiwan’s status may rally behind experienced leadership to restore control or stability. This pattern supports appraisal theory’s prediction that emotions shape coping behavior through context-dependent attributions. When citizens perceive worsening international standing, anxiety may redirect attention from government failure to external danger, mitigating the tendency to punish incumbents. By contrast, interactions involving anger are not statistically significant. The non-significant interactions involving anger suggest that this emotion exerts a generalized rather than conditional influence on voting behavior. While anxiety’s impact depends on citizens’ appraisal of Taiwan’s international status, anger appears less contingent on perceived national conditions. This aligns with research showing that anger activates approach motivation and defensive solidarity, producing stable, directional effects that are less shaped by contextual appraisals. Overall, the results show that voting for the incumbent party is associated with cognition and emotion given the predisposition. I use the baseline model to compute the predicted probability of voting for the incumbent party. Fig. 1 shows a predicted probability plot, illustrating anxiety decreases DPP support when international status is perceived as “about the same”, but less so—or even reverses—when international status becomes worse. Across all levels of anxiety, retrospective evaluation of international status has a strong effect on the predicted DPP vote probability. The solid line indicates that individuals who believe Taiwan's international status has remained unchanged have a consistently high predicted probability of voting for the DPP (around 0.75). The dashed line reveals that individuals who believe Taiwan's international status has been worse have a consistently low predicted probability of voting for the DPP (around 0.25 to 0.50). It is obvious that the two groups react very differently to increasing anxiety, leading to a significant crossover effect. The effect of anxiety is dependent on the voter's underlying belief about Taiwan's international standing. Source: Chen ( 2024 ) Figure 2 shows two lines with positive slopes, indicating that as the anger over China's coercion increases (moving from "Not upset at all" to "Very upset"), the predicted probability of voting for the DPP increases. Individuals who believe Taiwan's international status has remained unchanged have a higher predicted probability of voting for the DPP (ranging from approximately 0.50 to 0.78). The effect of anger in driving votes toward the DPP is attenuated among those who feel Taiwan's international standing has worsened. Source: Chen ( 2024 ) The second and third model adds difference in feeling thermometer between Lai and Hou, and between Lai and Ko, respectively. In the second model, retrospective evaluations of Taiwan’s international standing continue to be significant predictors of voting choice. Anxiety over potential conflict and anger over encircling of Chinese warplanes and warships also remain significant when the model includes the feeling thermometer difference between Lai and Hou. Because these two candidates clearly represented opposing positions on cross-Strait relations, anger about China’s military coercion translated directly into support for the DPP’s more assertive defense stance, a reaction not fully captured by the evaluative difference between Lai and Hou. About the interaction term, people that are anxious about potential conflict and consider that Taiwan’s international status is worse are likely to vote for the DPP. In the third model, assessment of Taiwan’s international standing and anxiety over potential conflict are related to voting choice. However, anger becomes less influential once the difference between Lai and Ko is considered, likely because his narrative blurs the emotional boundary of the “out-group”. Voters who felt angry about the cross-Strait situation could still find expressive satisfaction in supporting Ko, who offered an alternative outlet for frustration without fully endorsing confrontation. Thus, the inclusion of Lai–Ko differences statistically captures part of the emotional channel through which anger influenced vote choice. Similarly, I visualize the interaction between evaluation of international standing and different levels of anxiety and anger in Appendix D. Compared to the baseline model, the difference in the predicted probability between two categories of evaluation of international standing becomes smaller. Robustness Check The first set of robustness checks addresses concerns about endogeneity and the possibility that emotion simply proxies partisan affect. All models include strong controls for partisan predispositions, such as prior vote choice and Taiwanese identity. Because emotions refer specifically to potential conflict and Chinese coercion—events not plausibly caused by vote intention—reverse causality is unlikely. Moreover, the core results remain stable across alternative specifications, including models with expanded controls and different coding of the outcome variable. Collectively, these tests provide strong evidence that cognition and emotion function as independent pathways shaping electoral behavior. Across all robustness checks—including models with current partisanship, Taiwanese identity, candidate affect, multinomial outcomes, and survey-weighted estimations—the core findings remain substantively identical. Conclusion This research provides robust evidence that both cognition and emotion are central to voting behavior. The paper shows that ‘rational’ cognitive evaluations and ‘emotional’ reactions are not substitutes but complementary outputs of appraisal. Voters who feel anxious about potential conflict in the Taiwan Strait are more likely to support opposition parties, while those angered by China’s military coercion tend to rally behind the incumbent DPP. The effect of anger aligns with the classic rally-’round-the-flag hypothesis (Mueller 1970 ; Lambert, Schott, and Scherer 2011 ; Falcó-Gimeno, Muñoz, and Pannico 2025 ), whereas the impact of anxiety—reducing incumbent support under external pressure—offers an important corrective to existing theories. Based on the results shown in Table 2 and two figures, the primary implication is that anxiety acts as a salience booster, making voters more sensitive to the incumbent's policy failures. Anger and anxiety have distinct, and even opposite, interactive effects on political behavior (voting for the DPP), depending on a voter's evaluation of Taiwan's international status. For a country under external pressure, the results suggest that mobilizing a resistant public requires leaders to successfully convert fear and uncertainty into actionable anger and defiance. If unmanaged anxiety subsumes anger, political fragmentation or a preference for non-confrontational change may take center stage. The key theoretical implication is that the power of AIT in a cross-national, security context is validated. This emotional–cognitive dynamic underscores that democratic accountability operates not only through reasoned judgment but also through affective reactions. The emotional logic of democratic survival has broader implications for other democracies facing security challenges, such as South Korea or Japan. Both countries are facing pressure from North Korea, China, and Russia. Korean and Japanese people have expressed their anger on street and place their hope on new leadership, respectively. Recognizing the emotional dimension of threat perception enriches theories of political behavior and democratic resilience under stress. The third implication concerns polarization. Previous polarization literature that emphasizes anger that result from conflict in identity between in-group and out-group (e.g. Achen and Bartels 2016 ; Hetherington and Weiler 2018 ; Iyengar and Westwood 2015 ). Whereas anger can generate defensive solidarity, anxiety tends to heighten uncertainty and blame, potentially widening partisan divides. Thus, external threats can either unify or fragment public opinion depending on which emotion dominates. This research confirms the function of two core psychological mechanisms—anxiety and anger—in shaping political behavior under security threat. Importantly, these mechanisms are not confined to wartime or international crises. “Peacetime” issues can also be understood as alternative forms of threat that activate the same emotional systems of appraisal and response. For example, voters anxious about an economic downturn prioritized the economy in the 2008 U.S. presidential election, contributing to Barack Obama’s decisive victory amid the financial crisis (Singer 2011 ). Similarly, receiving negative information can trigger individuals’ anxiety toward a policy issue, which in turn motivates political participation such as voting in a referendum (Tsai 2024 ). Rising anger during domestic political conflict can also heighten motivation for aggressive or punitive action (Schnakenberg and Wayne 2024), while feelings of humiliation—appraising oneself as unjustly demeaned—may fuel risk-taking behavior aimed at restoring honor or autonomy (Barnhart 2020 ). These examples reveal a coherent emotional logic across contexts: whether the perceived threat stems from foreign coercion, economic instability, or political confrontation. In the future, this study of emotional–cognitive dynamic can be improved by measuring people’s cognition and emotion before and after important events occur (Ladd and Lenz 2008 ). It is also necessary to consider experimental design, making causal inference about the sequencing between cognition and emotion. Moreover, while Taiwan provides a compelling case, its unique geopolitical environment may limit external validity. Future research could employ panel or experimental designs across multiple democracies—such as South Korea or Japan—to test the generalizability of emotion-based voting under different types of threats. Certainly, we should expand our scope of research to the source and behavioral responses of both positive and negative emotion. Declarations Funding This research received no external funding. Author Contribution The author prepares the whole manuscript alone. Acknowledgement Data analyzed in this article were from "Taiwan's Election and Democratization Study, 2024-2028". The document code for this study is TEDS2024. "Taiwan's Election and Democratization Study" (TEDS) was an inter-university research project initiated by Professor Chi Huang in 2000. The principal investigator from 2024 to 2028 is Research Fellow Lu-huei Chen (Election Study Center, National Chengchi University). More information is on TEDS website (http://www.tedsnet.org). The author appreciates the assistance in providing data by the institute and individuals aforementioned. The author is alone responsible for views expressed herein. The author also wants to extends his gratitude to Chi Huang for his extraordinary leadership of data collection for more than two decades, and to Lu-huei Chen for continuing this crucial effort. Data Availability Taiwan’s Election and Democratization Study, 2020–2024 (IV): The Survey of Presidential and Legislative Elections, 2024 (TEDS2024) were deposited into the Survey Research Data Archive, Academia Sinica, and are available at the following URL: https://doi.org/10.6141/TW-SRDA-D00260-1 References Abelson, R. P., Kinder, D. R., Peters, M. D., & Fiske, S. T. (1982). Affective and semantic components in political person perception. Journal of Personality and Social Psychology: Attitudes and Social Cognition , 42 (4), 619–630. https://doi.org/10.1037/0022-3514.42.4.619 Achen, C. H. (1992). Social psychology, demographic variables, and linear regression. Political Behavior , 14 (3), 195–211. Achen, C. H., & Bartels, L. (2016). Democracy for Realists: Why Elections Do Not Produce Responsive Government . Princeton University Press. Achen, C., & Wang, T. Y. (2017). The Taiwan Voter: An introduction. In C. Achen, & T. Y. Wang (Eds.), The Taiwan Voter . 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Footnotes tails about Taiwan’s 2024 presidential election, see Appendix A. Due to the fact that only 357 cases fall in the group of voting for KMT or PFP, the estimates of binary logit regression model are not reliable. Therefore, I only report the results from the model for people the voted for the DPP in 2020. I control for gender, age (20 to 29 years old, 30 to 39 years old, 40 to 49 years old, 50 to 59 years old, and more than 60 years old), and education (elementary school, high school, and university) in every regression models. For convenience of interpretation, those coefficients are not shown in the tables. Predicted probabilities were calculated using the fitted values from the logistic regression model. For each combination of anxiety level (1–4) and perception of international status (“About the same” and “Worse”), I set all other covariates to their observed means (for continuous variables) or modal categories (for categorical variables). I then used the estimated coefficients to compute the linear predictor (log-odds), which was transformed into a probability using the logistic function. 95% confidence intervals were derived using simulation from the variance–covariance matrix of the model. The datagrid() and predictions() functions in the marginaleffects package in R were used to generate predicted values and their 95% confidence intervals. China’s aggregation gets Korean and Japanese people’s nerve. In Korea, an increasing number of anti-China rallies not only mark escalation of anti-Chinese tourism but also reflect tensions with China (Lee, 2025; Rashid, 2025 ). In a 2024 opinion poll, 90 percent of Japanese respondents had a negative view of China, citing the Senkaku Island and Taiwan issues (Japan Times, 2024). The newly-elected Japan’s prime minister, Takaichi Senae, is well-known for her hawkish on China. As for Russia, Japan and Korea have joined Western sanctions after the invasion of Ukraine. The growing embrace of Russia and North-Korea also increases the tensions between Russia and these two countries. Additional Declarations No competing interests reported. Supplementary Files APPENDIXPB.docx Cite Share Download PDF Status: Posted Version 1 posted 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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1","display":"","copyAsset":false,"role":"figure","size":114726,"visible":true,"origin":"","legend":"\u003cp\u003eInteraction of Anxiety and Retrospective Evaluation of Taiwan’s International Status\u003c/p\u003e\n\u003cp\u003eSource: Chen (2024)\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8291322/v1/991d48f0b75091efd26b48a0.jpeg"},{"id":100181312,"identity":"a1fa67a2-d3c8-47cc-8ed5-f04d490a70ba","added_by":"auto","created_at":"2026-01-13 19:37:40","extension":"jpeg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":120060,"visible":true,"origin":"","legend":"\u003cp\u003eInteraction of Anger and Retrospective Evaluation of Taiwan’s International Status\u003c/p\u003e\n\u003cp\u003eSource: Chen 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class=\"CitationRef\"\u003e1975\u003c/span\u003e; Kinder and Kiewit 1979; Lodge, Steenbergen, and Brau \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e1995\u003c/span\u003e). A parallel tradition demonstrates that affective predispositions, especially partisanship, guide information processing and shape evaluative orientations (Campbell et al. 1960; Jacoby \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e1988\u003c/span\u003e; Greene \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e1999\u003c/span\u003e; Bartels \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2000\u003c/span\u003e). This body of work establishes that cognition and affect both matter, but it focuses primarily on attitudes and emotions directed at candidates or parties, rather than the reactions citizens form in response to the political environment they face.\u003c/p\u003e \u003cp\u003eBy contrast, psychological theories suggest that individuals continually interpret their environment through both evaluative and emotional lenses. Appraisal theory and affective intelligence emphasize that political conditions\u0026mdash;uncertainty, risk, coercion, crisis\u0026mdash;simultaneously elicit cognitive judgments and emotional reactions, each with distinct behavioral implications (Roseman, \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e1984\u003c/span\u003e; Lerner and Keltner, \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2000\u003c/span\u003e; Marcus, Neuman, and MacKuen, \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2000\u003c/span\u003e; Ellsworth and Scherer, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2003\u003c/span\u003e; Huddy, Feldman, and Cassese 2007). Yet the political behavior literature seldom incorporates these environment-elicited emotions into models of vote choice. Existing work tends to examine emotions triggered by campaign stimuli or candidate impressions (Abelson et al. \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1982\u003c/span\u003e; Glaser and Salovey \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e1998\u003c/span\u003e; Isbell and Otatti, 2002). Some research finds how broader political conditions generate emotions and influence attitudes and behavior (Wagner and Morisi \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Rico, Guinjoan, and Anduiza \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Vasilopoulos et al. \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), but this work leaves unexplored how these reactions combine with cognitive evaluations to shape electoral decisions. A comprehensive model of vote choice must retain both cognition and emotion because they represent distinct, non-substitutable causal pathways to the ballot box. While cognitive evaluations (like retrospective performance judgments) influence choice through reasoned assessment, discrete emotions (like anxiety or anger) occur in parallel, triggering unique motivational impulses for decision (Erisen \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eDrawing insights from appraisal theory and affective intelligence theory, this research proposes an \u003cem\u003eintegrated cognition\u0026ndash;emotion model\u003c/em\u003e of voting. By \u0026ldquo;integrated,\u0026rdquo; I refer to a framework in which cognitive evaluations and discrete emotions operate as distinct and co-occurring pathways rather than competing or sequential explanations. These two mechanisms --broad political evaluation and discrete emotional response\u0026mdash;operate independently but may intersect when emotions condition how strongly individuals weight negative evaluations. By theorizing cognition and emotion as simultaneous and mutually reinforcing pathways, this paper offers a nuanced psychological correction to standard voting.\u003c/p\u003e \u003cp\u003eThe 2024 Taiwan presidential election presents an ideal case for examining these processes. Taiwan faces continuous military and diplomatic coercion from China, making evaluations of international status and cross-Strait relations highly salient. These same conditions trigger anxiety about potential conflict and anger over military incursions. The coexistence of chronic external pressure and competitive multiparty politics allows us to directly test how voters combine cognitive assessments of national conditions with emotional reactions to the surrounding environment.\u003c/p\u003e \u003cp\u003eUsing high-quality post-election survey data from Taiwan\u0026rsquo;s 2024 presidential election, this study makes three contributions to research on political behavior. First, it provides clear observational evidence for a cognition\u0026ndash;emotion voting model: voters who perceive Taiwan\u0026rsquo;s international standing or cross-Strait relations as deteriorating are substantially less likely to support the incumbent, consistent with performance-based retrospective voting. Second, anxiety and anger exert independent and opposing effects\u0026mdash;anxiety erodes incumbent support, whereas anger strengthens it\u0026mdash;demonstrating that emotions are structured components of political judgment rather than epiphenomenal reflections of partisanship. Third, anxiety significantly magnifies the electoral penalty associated with negative evaluations while anger does not, helping resolve ambiguities in the rally-\u0026rsquo;round-the-flag literature, which typically assumes uniform emotional responses to external threats. These patterns hold even after controlling for lagged vote choice, identity, and candidate affect, increasing confidence in the causal interpretation.\u003c/p\u003e \u003cp\u003eMore broadly, the findings reframe emotion as a meaningful part of rational political decision-making. Anxiety and anger emerge from appraisal of uncertainty and blame\u0026mdash;processes that occur across policy domains\u0026mdash;not solely from threats to national security. Economic downturns, corruption scandals, pandemics, and sudden social disruptions similarly generate appraisals of risk, responsibility, and intentionality that activate these same emotional channels. The mechanism identified here\u0026mdash;anxiety heightens sensitivity to perceived competence failures while anger shifts responsibility outward and mobilizes defensive support\u0026mdash;offers a generalizable account of voter behavior in diverse democratic settings. This cognition\u0026ndash;emotion model therefore extends beyond Taiwan, speaking directly to political behavior in democracies such as Korea, Japan, and others where citizens regularly confront uncertainty and contested attributions of blame.\u003c/p\u003e \u003cp\u003eThe next sections develop the theoretical framework, derive empirical predictions, and evaluate them using original survey data.\u003c/p\u003e\n\u003ch3\u003eCognition and Emotion as Parallel Pathways\u003c/h3\u003e\n\u003cp\u003eCitizens judge their government largely through assessments of performance\u0026ndash;domestic and foreign policy\u0026ndash;such as international reputation or security performance (Aldrich, Sullivan, and Borgida \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e1989\u003c/span\u003e; Gelpi, Reifler, and Feaver \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Druckman and Lupia 2020). Yet purely cognitive accounts often understate the influence of emotion on political judgment (Lodge and Taber \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). A large literature shows that emotions generated by political actors shape evaluation and choice: affective reactions to candidates guide candidate evaluation (Abelson et al. \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1982\u003c/span\u003e; Isbell and Ottatti \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2002\u003c/span\u003e), emotional responses predict vote preference (Markus \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e1988\u003c/span\u003e), and affect expressed by candidates increases attention, memory, and favorability (Glaser and Salovey \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e1998\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eHowever, these studies focus primarily on candidate-based affect, leaving underexplored the emotional responses that arise from the political environment itself\u0026mdash;such as uncertainty, risk, or coercion\u0026mdash;and how those emotions combine with cognitive evaluations to shape voter decision-making. Psychological research demonstrates that individuals interpret political events through distinct but interacting cognition and emotion systems, rather than through a linear sequence in which cognition precedes emotion (Zajonc \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e1984a\u003c/span\u003e; Hoffman 1984). Each pathway carries distinct implications for political judgment. As Izard (\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e1984\u003c/span\u003e) notes, emotional and cognitive capacities develop together and jointly shape complex behaviors. Psychological experiments also show that mere exposure can create affect (emotion) toward a stimulus independently of and prior to the need for conscious cognitive processes (Zajonc \u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e1984b\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eTaken together, I argue that voter behavior reflects a dual-pathway process in which cognitive evaluations and emotional appraisals jointly inform electoral choice. Consistent with Crawford\u0026rsquo;s (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2000\u003c/span\u003e:156) characterization that \u0026ldquo;humans make decisions that are always both classically self-interested and emotional,\u0026rdquo; this study does not treat cognition as the cause of emotion. Instead, cognition and emotion arise simultaneously as inputs of how individuals make voting decisions.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eAnxiety and Anger\u003c/h2\u003e \u003cp\u003eAIT identifies distinct emotional systems that regulate attention and behavioral motivation. Anxiety arises when individuals determine a stimulus or event as uncertain, potentially harmful, and beyond personal control. This emotion heightens vigilance, directs attention toward potential losses, increases information seeking, and encourages cautious or change-oriented behavior (Marcus and MacKuen \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e1993\u003c/span\u003e; Lerner and Keltner \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2000\u003c/span\u003e; Wagner and Morisi \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Anxiety motivates behavior aimed at moving away from danger, hiding, or searching the environment for safety (Frijda \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e1986\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAnger, by contrast, is elicited by a threat with certainty (Gadarian and Brader 2023:203). It heightens blame, punitive preferences, and mobilization (Banks and Valentino \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Valentino et al. \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Banks \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Anger is linked to the appraisal of \u003cem\u003eother-blame\u003c/em\u003e and \u003cem\u003econtrol\u003c/em\u003e (Lazarus \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e1991\u003c/span\u003e). It emerges when individuals perceive a threat as certain, intentional, and blameworthy. Therefore, it activates approach motivation, punishment of the responsible actor, and support for assertive or confrontational responses based on optimistic risk assessments (Huddy, Feldman, Weber \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Lerner and Keltner \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2001\u003c/span\u003e). In sum, anger and anxiety have opposite effects on policy preferences because of their differing appraisals of \u003cem\u003econtrol\u003c/em\u003e and \u003cem\u003ecertainty\u003c/em\u003e. Anxiety increased risk aversion and reduced support for offensive action but anger increases support for aggressive foreign policy (Huddy et al. \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2005\u003c/span\u003e). Accordingly, I expect anxiety to reduce support for the incumbent, while anger should benefit the incumbent by shifting responsibility toward the external antagonist.\u003c/p\u003e \u003cp\u003eContemporary psychological work emphasizes that cognition and emotion are dynamically intertwined (Roseman, Abelson, and Ewing \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e1986\u003c/span\u003e), often arising simultaneously as complementary components of the appraisal process (Ellsworth and Scherer \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2003\u003c/span\u003e). Cognitive appraisal is a necessary antecedent for many emotional responses, and emotion can bias cognitive processing, directing attention and influencing which memories are retrieved. Thus, voters can form cognitive judgments about national conditions\u0026mdash;such as deterioration in cross-Strait relations\u0026mdash;while also experiencing discrete emotions such as anxiety (from uncertainty about conflict) or anger (from perceiving Chinese military coercion as intentional aggression).\u003c/p\u003e \u003cp\u003eAlthough Taiwan\u0026rsquo;s 2024 election provides a vivid setting in which external coercion activates strong emotional reactions, the same appraisal processes apply whenever citizens interpret conditions that involve uncertainty, loss, or blame\u0026mdash;including economic downturns, corruption scandals, pandemic policy failures, and domestic political conflict. As a result, the cognition\u0026ndash;emotion framework offers a general theory of voter behavior that extends beyond threat politics and speaks to foundational debates about accountability, performance voting, and democratic responsiveness.\u003c/p\u003e \u003cp\u003eThe preceding framework yields clear expectations about how cognition and emotion shape electoral behavior. I formalize these expectations in the following hypotheses.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eIndependent Effects on Incumbent Support\u003c/h3\u003e\n\u003cp\u003eDrawing from retrospective voting logic, negative evaluations of national standing should reduce support for the incumbent. When voters perceive worsening international status or heightened cross-Strait tension, they may attribute responsibility to the government and punish it electorally. This establishes the first expectation:\u003c/p\u003e\n\u003ch3\u003eH1 (Cognitive Punishment Hypothesis):\u003c/h3\u003e\n\u003cp\u003e \u003cem\u003eVoters who perceive Taiwan\u0026rsquo;s international or cross-Strait situation as deteriorating will be less likely to support the incumbent party.\u003c/em\u003e \u003c/p\u003e \u003cp\u003eEmotion introduces a second causal pathway. Anxiety, by signaling uncertainty and the potential for harm, encourages citizens to reconsider the status quo and to become risk averse. Anger, in contrast, is associated with blame and mobilization against the perceived threat, which in contexts of external coercion can strengthen defensive solidarity with incumbents. This mechanism parallels\u0026mdash;but also refines\u0026mdash;arguments in the rally-\u0026rsquo;round-the-flag literature, which assumes a uniform emotional reaction to threat. By distinguishing anxiety from anger, the theory predicts opposing electoral forces:\u003c/p\u003e\n\u003ch3\u003eH2 (Anxiety-induced Weakening Support Hypothesis):\u003c/h3\u003e\n\u003cp\u003e \u003cem\u003eHigher levels of anxiety about potential conflict will decrease support for the incumbent party.\u003c/em\u003e \u003c/p\u003e\n\u003ch3\u003eH3 (Anger-induced Strengthening Support Hypothesis):\u003c/h3\u003e\n\u003cp\u003e \u003cem\u003eHigher levels of anger at external coercion will increase support for the incumbent party.\u003c/em\u003e \u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eInteraction Between Cognitive Evaluation and Anxiety\u003c/h2\u003e \u003cp\u003ePrior studies suggest that anxiety increases vigilance, heightens attention to potential losses, and expands search for alternatives. When a voter is both \u003cem\u003eanxious\u003c/em\u003e and \u003cem\u003eperceives national deterioration\u003c/em\u003e, the emotion makes the negative evaluation more consequential. Anger, however, redirects responsibility toward the threatening other. When a voter feels angry over political object or event, that emotional reaction interrupts the usual cognitive mechanism that blames the government. Even if the voter perceives the international situation as worsening, anger cues them to attribute the cause externally. This weakens the electoral relevance of the cognitive judgment.\u003c/p\u003e \u003cp\u003eIn the Taiwanese context, this means that anxiety about conflict amplifies the electoral consequences of perceived diplomatic deterioration, whereas anger may buffer or reverse them. Because anger shifts blame to the adversary, it should not increase the electoral penalty for negative evaluations; if anything, it may attenuate it. Therefore, I propose the following hypothesis:\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eH4 (Anxiety Amplification Hypothesis):\u003c/h3\u003e\n\u003cp\u003e \u003cem\u003eAnxiety will strengthen the negative effect of worsening evaluations of national standing on support for the incumbent.\u003c/em\u003e \u003c/p\u003e \u003cp\u003eIn sum, my theory contains two parallel pathways\u0026mdash;cognitive evaluations and discrete emotions\u0026mdash;and a key interaction: negative evaluations reduce incumbent support; anxiety further amplifies this effect; anger moves voters in the opposite direction. These propositions guide the empirical analysis that follows. Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e summarizes the direction and significance of key results, linking each hypothesis to the corresponding empirical pattern.\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\u003eCognition, Emotion, and Support for Incumbents\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCognition\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEmotion\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEvaluation of Taiwan\u0026rsquo;s International Status\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDeterioration of international status \u0026rarr; significant negative effect \u0026rarr; supports H1 (perceived decline punishes incumbents)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEvaluation of Cross-Strait Relations\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDeterioration of cross-Strait relations \u0026loz; significant negative effect \u0026rarr; supports H1 (perceived decline punishes incumbents)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLevel of Anxiety about Potential Conflict\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWorried about conflict \u0026rarr; significant negative effect \u0026rarr; supports H2 (anxiety increases opposition)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLevel of Anger over China\u0026rsquo;s Coercion\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eUpset about drills \u0026rarr; significant positive effect \u0026rarr; supports H3 (anger mobilizes defense)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInteraction of national standing and emotion\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDeterioration of international status \u0026amp; anxiety\u0026rarr; significant negative effect \u0026rarr; supports H4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDeterioration of international status \u0026amp; anger\u0026rarr; insignificant effect\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInteraction of cross-Strait relations and emotion\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDeterioration of cross-Strait relations \u0026amp; anxiety \u0026loz; significant negative effect\u0026rarr; supports H4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDeterioration of cross-Strait relations \u0026amp; anger \u0026loz; insignificant effect\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"3\"\u003eSource: Author\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e\n\u003ch3\u003eContext: Taiwan’s 2024 Presidential Election\u003c/h3\u003e\n\u003cp\u003eThe 2024 Taiwan presidential election unfolded amid intensified Chinese military coercion, making cross-Strait relations the dominant issue. The DPP\u0026rsquo;s Lai Ching-te emphasized deterrence and sovereignty, appealing to voters that oppose China\u0026rsquo;s aggression. In contrast, the KMT\u0026rsquo;s Hou Yu-ih advocated dialogue, framing the DPP\u0026rsquo;s stance as risky and useless. Ko Wen-je of the Taiwan People\u0026rsquo;s Party offered an ambiguous middle path, criticizing both Beijing and the DPP, which complicate the dichotomy on national security issues.\u003ca class=\"FNLink\" href=\"#Fn1\" id=\"#FNLinkFn1\"\u003e\u003c/a\u003e\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eData and Variables\u003c/h2\u003e \u003cp\u003eMy analysis leverages data from the Taiwan Election and Democratization Study (TEDS) (Chen \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). The 2024 TEDS survey was conducted by the Election Study Center at National Chengchi University between January 15 and May 31, 2024. The research team drew a sample of 14,503 addresses, from which 1,206 face-to-face interviews were completed. This study was approved by Institutional Review Board of National Chengchi University (approve no. NCCU-REC-202007-I073 v.24) on December 23, 2023. Data is deposited at Survey Research Data Archive, Academia Sinica.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eIndependent Variables\u003c/h2\u003e \u003cp\u003eTo test the cognition\u0026ndash;emotion framework, I distinguish between citizens\u0026rsquo; evaluative judgments of national conditions and their emotional reactions to the same external environment. Consistent with retrospective and foreign-policy voting research, cognitive appraisal is measured using two items that capture respondents\u0026rsquo; assessments of Taiwan\u0026rsquo;s international position: (1) whether Taiwan\u0026rsquo;s \u003cem\u003einternational status\u003c/em\u003e has improved, remained the same, or deteriorated over the past four years; and (2) whether \u003cem\u003ecross-Strait relations\u003c/em\u003e have improved, remained stable, or worsened. These items directly reflect voters\u0026rsquo; judgments about the government\u0026rsquo;s diplomatic management and perceived national standing. Emotional appraisal is measured using two discrete emotions central to appraisal theory and affective intelligence\u0026mdash;anxiety and anger. Anxiety is captured by respondents\u0026rsquo; worry about potential military conflict, reflecting an uncertainty-based hazard appraisal. Anger is measured by respondents\u0026rsquo; feeling of being upset over China\u0026rsquo;s encirclement of Taiwan with military aircraft and vessels, reflecting a blame-based appraisal of intentional coercion. Together, these measures align with the theoretical distinction between cognitive evaluations of national conditions and discrete emotional responses, enabling an empirical test of parallel and interactive pathways in the cognition\u0026ndash;emotion voting model.\u003c/p\u003e \u003cp\u003ePeople\u0026rsquo;s responses to foreign threats may reflect the domestic political environment (Myrick \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). To account for partisan alignment without conditioning on a potentially endogenous variable, the models instead include respondents\u0026rsquo; vote choice in the 2020 presidential election. This lagged measure\u0026mdash;coded as DPP vs. KMT and People\u0026rsquo;s First Party (PFP)--captures preexisting partisan predispositions while remaining exogenous to the emotional and evaluative processes triggered by recent developments. Analyses using current partisanship as a robustness check yield similar patterns in Table C1 in Appendix C, but the main specification relies on lagged vote to better isolate the causal influence of emotion and cognition on 2024 vote intention. The weighted distribution of 2020 presidential votes in the sample (DPP 64.4%, KMT/PFP 35.6%) slightly overstates support for the incumbent relative to official results (57.1% vs. 42.9%). This deviation likely reflects recall and desirability biases common in post-election surveys. I run a subgroup analysis for people voted for the DPP in 2020 and present the results in Table C2.\u003ca class=\"FNLink\" href=\"#Fn2\" id=\"#FNLinkFn2\"\u003e\u003c/a\u003e\u003c/p\u003e \u003cp\u003eSince citizens\u0026rsquo; feelings toward political leaders strongly predict attitude and behavior (Iyengar et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), it is necessary to rule out affective bias. I include the difference in feeling thermometer scores between Lai and his rivals. These two variables capture candidate-specific affect that may mitigate emotional responses, such as anger, directed toward candidates or their parties. In addition, Taiwanese identity has been the most salient cleavage (Achen and Wang \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Thus, it is also included in the voting model. See Appendix B for the full question wording.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eDependent Variable: Voting Choice\u003c/h2\u003e \u003cp\u003eOur dependent variable, support for the incumbent, is operationalized as a vote for the DPP ticket (Lai Ching-te/Hsiao Bi-khim), who successfully retained the presidency. Respondents that said they did not turn out to vote or refused to answer this question are dropped from the analysis. Because the dependent variable is dichotomous, I use binary logit regression model to estimate the effect of each independent variable. I also separate KMT and TPP and run a multinomial logit model with TPP as the baseline category. The results presented in Table C3, C4, and C5 are substantially similar.\u003c/p\u003e \u003cp\u003eThis survey is post-stratified to be nationally representative. Since my goal is theoretical explanation of emotional and cognitive mechanisms in voting under external coercion but not population estimation, all regression analyses use unweighted data. Weighted descriptive statistics are reported to ensure sample representativeness. Robustness checks using survey weights yield substantively identical results in Table C6.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e reports odds ratios from logistic regressions predicting the likelihood of voting for the incumbent. The baseline model includes voters\u0026rsquo; electoral decisions in 2020, retrospective evaluations of Taiwan\u0026rsquo;s international status and cross-Strait relations, emotional responses (anxiety and anger), interaction terms between cognitive evaluations and emotional reactions, and sociodemographic controls.\u003ca class=\"FNLink\" href=\"#Fn3\" id=\"#FNLinkFn3\"\u003e\u003c/a\u003e The baseline model shows that voters who perceive Taiwan\u0026rsquo;s international status becomes worse are significantly less likely to support the DPP (OR\u0026thinsp;\u0026asymp;\u0026thinsp;0.013), even after accounting for previous voting behavior and emotional reactions, implying that voters punish incumbents for perceived diplomatic decline. Voters who perceive Taiwan\u0026rsquo;s international status as \u003cem\u003edeteriorating\u003c/em\u003e are only about 1.3% as likely to support the incumbent DPP compared to those who perceive the status as \u003cem\u003eimproving\u003c/em\u003e (the reference category). Evaluations of cross-Strait relations are weaker predictors, suggesting that citizens may have normalized the chronic tension with China and instead focus more on Taiwan\u0026rsquo;s broader international standing. Level of anxiety about potential conflict is negatively associated with voting for the DPP (OR\u0026thinsp;\u0026asymp;\u0026thinsp;0.308). This finding aligns with the appraisal framework that anxiety tends to correlate with withdrawing from the status quo (Plutchik \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e1984\u003c/span\u003e:200). Level of anger over encircling of Chinese warplanes and warships is positively associated with voting for the DPP (OR\u0026thinsp;\u0026asymp;\u0026thinsp;2.509), which is consistent with the appraisal theory expectation that anger\u0026mdash;elicited by perceived external threat\u0026mdash;mobilizes defensive solidarity and produces a \u0026ldquo;rally-\u0026rsquo;round-the-flag\u0026rdquo; effect.\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\u003eEstimates of Incumbent Voting Choice Models\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\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBaseline model\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLai and Hou Difference\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLai and Ko Difference\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIntercept\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.069*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.141\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.603\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(0.086)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.199)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(1.115)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVoted for DPP in 2020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e58.196***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16.453***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e31.061***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(26.613)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(7.945)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(17.650)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInternational status unchanged\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.152+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.058*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.015*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(0.170)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.077)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(0.026)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInternational status worse\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.013**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.022*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.035+\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(0.019)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.038)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(0.068)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCross-Strait relations deteriorated\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.412\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.886\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.302\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(0.439)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(1.104)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(0.454)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLevel of Anxiety about Potential Conflict\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.308**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.333**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.189**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(0.111)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.135)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(0.107)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLevel of Anger over China\u0026rsquo;s Coercion\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.509**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.021+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.718\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(0.838)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.767)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(0.828)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDifference in Feeling between Lai and Hou\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.563***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.099)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDifference in Feeling between Lai and Ko\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.233***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(0.204)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTaiwanese identity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.093***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.940**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.554*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(1.234)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.979)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(1.008)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInternational status unchanged and Anxiety\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.787\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.927\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.355\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(0.683)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.837)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(1.335)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInternational status worse and Anxiety\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.523**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.010*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.977\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(1.666)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(1.573)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(1.244)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCross-Strait relations deteriorated and Anxiety\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.388\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.390\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.524+\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(0.494)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.560)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(1.302)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInternational status unchanged and Anger\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.764\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.091\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.552\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(0.292)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.485)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(0.867)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInternational status worse and Anger\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.641\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.764\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.055\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(0.285)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.363)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(0.625)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCross-Strait relations deteriorated and Anger\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.824\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.726\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.609\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(0.287)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.285)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(0.296)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNum.Obs.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e793\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e784\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e783\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAIC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e465.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e394.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e282.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBIC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e563.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e497.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e384.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLog.Lik.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-211.666\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-175.350\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-119.147\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eNote: Values presented are Odds Ratios (e\u003csup\u003e\u0026szlig;\u003c/sup\u003e ) from a logistic regression model. Standard errors are in parentheses below the OR. The reference category for \u0026ldquo;International Status\u0026rdquo; is \u0026ldquo;better\u0026rdquo;. The reference category for \u0026ldquo;Cross-Strait relations\u0026rdquo; is \u0026ldquo;Improve and the same\u0026rdquo;.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eSignificance: \u0026dagger; p\u0026thinsp;\u0026lt;\u0026thinsp;0.10; p\u0026thinsp;\u0026lt;\u0026thinsp;0.05; p\u0026thinsp;\u0026lt;\u0026thinsp;0.01; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eSource: Chen (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2024\u003c/span\u003e)\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eMost notably, the interaction between anxiety and perceptions of Taiwan\u0026rsquo;s worsening international status is significant and positive. Although anxiety alone is related to opposing the incumbent\u0026mdash;reflecting vigilance and blame attribution (Forgas \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e1995\u003c/span\u003e; Marcus, Neuman, and MacKuen \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2000\u003c/span\u003e)\u0026mdash;its effect reverses when citizens perceive the nation\u0026rsquo;s global standing as deteriorating. Under perceived decline, anxiety increases the odds of voting for the ruling party (OR\u0026thinsp;\u0026asymp;\u0026thinsp;3.523). The antagonistic interaction\u0026ndash;simple predictors and the interaction have opposite signs\u0026ndash;suggests that voters that worry about potential conflict and have negative view about Taiwan\u0026rsquo;s status may rally behind experienced leadership to restore control or stability. This pattern supports appraisal theory\u0026rsquo;s prediction that emotions shape coping behavior through context-dependent attributions. When citizens perceive worsening international standing, anxiety may redirect attention from government failure to external danger, mitigating the tendency to punish incumbents.\u003c/p\u003e \u003cp\u003eBy contrast, interactions involving anger are not statistically significant. The non-significant interactions involving anger suggest that this emotion exerts a generalized rather than conditional influence on voting behavior. While anxiety\u0026rsquo;s impact depends on citizens\u0026rsquo; appraisal of Taiwan\u0026rsquo;s international status, anger appears less contingent on perceived national conditions. This aligns with research showing that anger activates approach motivation and defensive solidarity, producing stable, directional effects that are less shaped by contextual appraisals. Overall, the results show that voting for the incumbent party is associated with cognition and emotion given the predisposition.\u003c/p\u003e \u003cp\u003eI use the baseline model to compute the predicted probability of voting for the incumbent party.\u003ca class=\"FNLink\" href=\"#Fn4\" id=\"#FNLinkFn4\"\u003e\u003c/a\u003e Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e shows a predicted probability plot, illustrating anxiety decreases DPP support when international status is perceived as \u0026ldquo;about the same\u0026rdquo;, but less so\u0026mdash;or even reverses\u0026mdash;when international status becomes worse. Across all levels of anxiety, retrospective evaluation of international status has a strong effect on the predicted DPP vote probability. The solid line indicates that individuals who believe Taiwan's international status has remained unchanged have a consistently high predicted probability of voting for the DPP (around 0.75). The dashed line reveals that individuals who believe Taiwan's international status has been worse have a consistently low predicted probability of voting for the DPP (around 0.25 to 0.50). It is obvious that the two groups react very differently to increasing anxiety, leading to a significant crossover effect. The effect of anxiety is dependent on the voter's underlying belief about Taiwan's international standing.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eSource: Chen (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2024\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e shows two lines with positive slopes, indicating that as the anger over China's coercion increases (moving from \"Not upset at all\" to \"Very upset\"), the predicted probability of voting for the DPP increases. Individuals who believe Taiwan's international status has remained unchanged have a higher predicted probability of voting for the DPP (ranging from approximately 0.50 to 0.78). The effect of anger in driving votes toward the DPP is attenuated among those who feel Taiwan's international standing has worsened.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eSource: Chen (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2024\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eThe second and third model adds difference in feeling thermometer between Lai and Hou, and between Lai and Ko, respectively. In the second model, retrospective evaluations of Taiwan\u0026rsquo;s international standing continue to be significant predictors of voting choice. Anxiety over potential conflict and anger over encircling of Chinese warplanes and warships also remain significant when the model includes the feeling thermometer difference between Lai and Hou. Because these two candidates clearly represented opposing positions on cross-Strait relations, anger about China\u0026rsquo;s military coercion translated directly into support for the DPP\u0026rsquo;s more assertive defense stance, a reaction not fully captured by the evaluative difference between Lai and Hou. About the interaction term, people that are anxious about potential conflict and consider that Taiwan\u0026rsquo;s international status is worse are likely to vote for the DPP.\u003c/p\u003e \u003cp\u003eIn the third model, assessment of Taiwan\u0026rsquo;s international standing and anxiety over potential conflict are related to voting choice. However, anger becomes less influential once the difference between Lai and Ko is considered, likely because his narrative blurs the emotional boundary of the \u0026ldquo;out-group\u0026rdquo;. Voters who felt angry about the cross-Strait situation could still find expressive satisfaction in supporting Ko, who offered an alternative outlet for frustration without fully endorsing confrontation. Thus, the inclusion of Lai\u0026ndash;Ko differences statistically captures part of the emotional channel through which anger influenced vote choice. Similarly, I visualize the interaction between evaluation of international standing and different levels of anxiety and anger in Appendix D. Compared to the baseline model, the difference in the predicted probability between two categories of evaluation of international standing becomes smaller.\u003c/p\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eRobustness Check\u003c/h2\u003e \u003cp\u003eThe first set of robustness checks addresses concerns about endogeneity and the possibility that emotion simply proxies partisan affect. All models include strong controls for partisan predispositions, such as prior vote choice and Taiwanese identity. Because emotions refer specifically to potential conflict and Chinese coercion\u0026mdash;events not plausibly caused by vote intention\u0026mdash;reverse causality is unlikely.\u003c/p\u003e \u003cp\u003eMoreover, the core results remain stable across alternative specifications, including models with expanded controls and different coding of the outcome variable. Collectively, these tests provide strong evidence that cognition and emotion function as independent pathways shaping electoral behavior. Across all robustness checks\u0026mdash;including models with current partisanship, Taiwanese identity, candidate affect, multinomial outcomes, and survey-weighted estimations\u0026mdash;the core findings remain substantively identical.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis research provides robust evidence that both cognition and emotion are central to voting behavior. The paper shows that \u0026lsquo;rational\u0026rsquo; cognitive evaluations and \u0026lsquo;emotional\u0026rsquo; reactions are not substitutes but complementary outputs of appraisal. Voters who feel anxious about potential conflict in the Taiwan Strait are more likely to support opposition parties, while those angered by China\u0026rsquo;s military coercion tend to rally behind the incumbent DPP. The effect of anger aligns with the classic rally-\u0026rsquo;round-the-flag hypothesis (Mueller \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e1970\u003c/span\u003e; Lambert, Schott, and Scherer \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Falc\u0026oacute;-Gimeno, Mu\u0026ntilde;oz, and Pannico \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2025\u003c/span\u003e), whereas the impact of anxiety\u0026mdash;reducing incumbent support under external pressure\u0026mdash;offers an important corrective to existing theories.\u003c/p\u003e \u003cp\u003eBased on the results shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e and two figures, the primary implication is that anxiety acts as a salience booster, making voters more sensitive to the incumbent's policy failures. Anger and anxiety have distinct, and even opposite, interactive effects on political behavior (voting for the DPP), depending on a voter's evaluation of Taiwan's international status. For a country under external pressure, the results suggest that mobilizing a resistant public requires leaders to successfully convert fear and uncertainty into actionable anger and defiance. If unmanaged anxiety subsumes anger, political fragmentation or a preference for non-confrontational change may take center stage.\u003c/p\u003e \u003cp\u003eThe key theoretical implication is that the power of AIT in a cross-national, security context is validated. This emotional\u0026ndash;cognitive dynamic underscores that democratic accountability operates not only through reasoned judgment but also through affective reactions. The emotional logic of democratic survival has broader implications for other democracies facing security challenges, such as South Korea or Japan. Both countries are facing pressure from North Korea, China, and Russia. Korean and Japanese people have expressed their anger on street and place their hope on new leadership, respectively.\u003ca class=\"FNLink\" href=\"#Fn5\" id=\"#FNLinkFn5\"\u003e\u003c/a\u003e Recognizing the emotional dimension of threat perception enriches theories of political behavior and democratic resilience under stress.\u003c/p\u003e \u003cp\u003eThe third implication concerns polarization. Previous polarization literature that emphasizes anger that result from conflict in identity between in-group and out-group (e.g. Achen and Bartels \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Hetherington and Weiler \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Iyengar and Westwood \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Whereas anger can generate defensive solidarity, anxiety tends to heighten uncertainty and blame, potentially widening partisan divides. Thus, external threats can either unify or fragment public opinion depending on which emotion dominates.\u003c/p\u003e \u003cp\u003eThis research confirms the function of two core psychological mechanisms\u0026mdash;anxiety and anger\u0026mdash;in shaping political behavior under security threat. Importantly, these mechanisms are not confined to wartime or international crises. \u0026ldquo;Peacetime\u0026rdquo; issues can also be understood as alternative forms of threat that activate the same emotional systems of appraisal and response. For example, voters anxious about an economic downturn prioritized the economy in the 2008 U.S. presidential election, contributing to Barack Obama\u0026rsquo;s decisive victory amid the financial crisis (Singer \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). Similarly, receiving negative information can trigger individuals\u0026rsquo; anxiety toward a policy issue, which in turn motivates political participation such as voting in a referendum (Tsai \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Rising anger during domestic political conflict can also heighten motivation for aggressive or punitive action (Schnakenberg and Wayne 2024), while feelings of humiliation\u0026mdash;appraising oneself as unjustly demeaned\u0026mdash;may fuel risk-taking behavior aimed at restoring honor or autonomy (Barnhart \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). These examples reveal a coherent emotional logic across contexts: whether the perceived threat stems from foreign coercion, economic instability, or political confrontation.\u003c/p\u003e \u003cp\u003eIn the future, this study of emotional\u0026ndash;cognitive dynamic can be improved by measuring people\u0026rsquo;s cognition and emotion before and after important events occur (Ladd and Lenz \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). It is also necessary to consider experimental design, making causal inference about the sequencing between cognition and emotion. Moreover, while Taiwan provides a compelling case, its unique geopolitical environment may limit external validity. Future research could employ panel or experimental designs across multiple democracies\u0026mdash;such as South Korea or Japan\u0026mdash;to test the generalizability of emotion-based voting under different types of threats. Certainly, we should expand our scope of research to the source and behavioral responses of both positive and negative emotion.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eThis research received no external funding.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eThe author prepares the whole manuscript alone.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eData analyzed in this article were from \"Taiwan's Election and Democratization Study, 2024-2028\". The document code for this study is TEDS2024. \"Taiwan's Election and Democratization Study\" (TEDS) was an inter-university research project initiated by Professor Chi Huang in 2000. The principal investigator from 2024 to 2028 is Research Fellow Lu-huei Chen (Election Study Center, National Chengchi University). More information is on TEDS website (http://www.tedsnet.org). The author appreciates the assistance in providing data by the institute and individuals aforementioned. The author is alone responsible for views expressed herein. The author also wants to extends his gratitude to Chi Huang for his extraordinary leadership of data collection for more than two decades, and to Lu-huei Chen for continuing this crucial effort.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eTaiwan\u0026rsquo;s Election and Democratization Study, 2020\u0026ndash;2024 (IV): The Survey of Presidential and Legislative Elections, 2024 (TEDS2024) were deposited into the Survey Research Data Archive, Academia Sinica, and are available at the following URL: https://doi.org/10.6141/TW-SRDA-D00260-1\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAbelson, R. P., Kinder, D. R., Peters, M. D., \u0026amp; Fiske, S. T. (1982). 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Lawrence Erlbaum Associates,.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Footnotes","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003etails about Taiwan\u0026rsquo;s 2024 presidential election, see Appendix A.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e Due to the fact that only 357 cases fall in the group of voting for KMT or PFP, the estimates of binary logit regression model are not reliable. Therefore, I only report the results from the model for people the voted for the DPP in 2020.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e I control for gender, age (20 to 29 years old, 30 to 39 years old, 40 to 49 years old, 50 to 59 years old, and more than 60 years old), and education (elementary school, high school, and university) in every regression models. For convenience of interpretation, those coefficients are not shown in the tables.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e Predicted probabilities were calculated using the fitted values from the logistic regression model. For each combination of anxiety level (1\u0026ndash;4) and perception of international status (\u0026ldquo;About the same\u0026rdquo; and \u0026ldquo;Worse\u0026rdquo;), I set all other covariates to their observed means (for continuous variables) or modal categories (for categorical variables). I then used the estimated coefficients to compute the linear predictor (log-odds), which was transformed into a probability using the logistic function. 95% confidence intervals were derived using simulation from the variance\u0026ndash;covariance matrix of the model. The\u0026nbsp;datagrid()\u0026nbsp;and\u0026nbsp;predictions()\u0026nbsp;functions in the marginaleffects package in R were used to generate predicted values and their 95% confidence intervals.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e China\u0026rsquo;s aggregation gets Korean and Japanese people\u0026rsquo;s nerve. In Korea, an increasing number of anti-China rallies not only mark escalation of anti-Chinese tourism but also reflect tensions with China (Lee, 2025; Rashid, \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). In a 2024 opinion poll, 90 percent of Japanese respondents had a negative view of China, citing the Senkaku Island and Taiwan issues (Japan Times, 2024). The newly-elected Japan\u0026rsquo;s prime minister, Takaichi Senae, is well-known for her hawkish on China. As for Russia, Japan and Korea have joined Western sanctions after the invasion of Ukraine.\u0026nbsp;The growing embrace of Russia and North-Korea also increases the tensions between Russia and these two countries.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"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":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-8291322/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8291322/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003ePolitical behavior research often separates cognitive evaluations from emotional reactions, treating voters as either rational performance evaluators or emotionally driven decision makers. This study advances an integrated cognition\u0026ndash;emotion model in which broad political evaluation (e.g., retrospective judgment) and discrete emotional response\u0026mdash;anxiety and anger\u0026mdash;operate as distinct but interacting pathways shaping electoral choice. Using post-election survey data from Taiwan\u0026rsquo;s 2024 presidential contest and controlling for lagged vote choice and feelings toward candidates, I show that negative assessments of Taiwan\u0026rsquo;s international status and cross-Strait relations significantly reduce support for the incumbent. Anxiety about potential conflict independently lowers incumbent support and amplifies the electoral penalty associated with negative evaluations. Anger toward external coercion, by contrast, increases support for the incumbent but does not strengthen the effect of cognitive judgments. Across all robustness checks, the core findings remain substantively identical. These findings offer a framework for understanding how citizens interpret political conditions and how these interpretations\u0026mdash;cognition and emotions\u0026ndash;shape their vote choices.\u003c/p\u003e","manuscriptTitle":"An Integrated Model of Cognition, Emotion, and Vote Choice: Evidence from Taiwan","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-01-13 19:37:35","doi":"10.21203/rs.3.rs-8291322/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"be45e1b0-1d44-4724-a4e7-ac49ea90c6ff","owner":[],"postedDate":"January 13th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-01-13T19:37:35+00:00","versionOfRecord":[],"versionCreatedAt":"2026-01-13 19:37:35","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8291322","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8291322","identity":"rs-8291322","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}