民主倒退时期的福祉政治：党派归属与对政府行为的支持如何与幸福感和生活满意度相关联

Introduction

Political hostility in the United States has increased drastically in the last decade (Pew Research Center, 2022). This trend of political polarization has led to a widening gap in intergroup emotions, with both politicians and the public alike leaning more heavily on their ingroup political identity and feeling colder towards the political opposition (Loepp, 2022). This political divide not only affects elections, but also spills over into everyday life, and is associated with decreased mental health (Fraser et al., 2022). Along with the impacts of polarization, politics also directly impact individuals’ lives through government policies and actions, which dictate the distribution of resources, rights, protections, and opportunities, thereby influencing psychological well-being (Barrafrem et al., 2021; Helliwell & Huang, 2008; Sibley et al., 2020). Crucially, when such actions signal democratic backsliding—for instance, weakened institutional checks, executive overreach, or the erosion of individual rights (Shore et al., 2025; Yourish et al., 2025)—people’s support or opposition of these actions may have direct implications for their mental health.

Although extant research has mapped partisan differences in subjective well-being – the perception that one’s life is going well (Bock & Schnabel, 2022; Huppert, 2009; Napier & Jost, 2008; Schlenker et al., 2012; Wojcik et al., 2015) – it is important to re-examine this gap during a period of democratic decline in the United States, when individuals’ well-being may hinge on their support or opposition to new actions. The early months of President Trump’s second presidency represent such a period: one marked by rapid and, at times, overwhelming political change (Ball, 2025; Carrier & Carothers, 2025; Treisman, 2025; Yourish et al., 2025). In this context, in an intensive longitudinal study during a unique and critical timeframe, we examined whether Democrats and Republicans differed in life satisfaction and happiness over five weeks and considered how exposure to specific governmental actions, and (dis)approval of these actions, correlated with well-being.

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Politics and Well-Being

The impact of politics on well-being is well-documented. Given its profound influence on individuals’ life circumstances, personal identities, social relationships, and its near-constant presence in the media, politics can significantly shape mental health and overall well-being (Ford et al., 2023). Research also suggests that greater political engagement or awareness is often associated with lower well-being. For instance, national surveys conducted in the U.S. in 2017 and 2020 found that individuals who reported higher political interest also reported lower levels of well-being, which held after controlling for age, gender, race, and political partisanship (Smith, 2022). Similarly, daily diary studies and experiments found that both Democrats and Republicans who were prompted to think about politics experienced more negative emotions, which in turn predicted declines in well-being (Ford et al., 2023).

Studies also show that there are reliable partisan differences in well-being, with conservatives self-reporting greater well-being than liberals (e.g., Bock & Schnabel, 2022; Napier & Jost, 2008; Schlenker et al., 2012; Wojcik et al., 2015). While this political ‘happiness gap’ is well-documented, little work has examined whether this gap changes over time, whether one’s political affiliation predicts well-being over time, and how support for or opposition to government actions is associated with well-being, particularly during periods of democratic stress. Previous research that examined the impact of politics on changes in well-being over time has been within the context of election results. Specifically, past research suggests that winning or losing power has short-term well-being effects, with winners reporting increases and losers reporting decreases (Lench et al., 2019; Pierce et al., 2016; Toshkov & Mazepus, 2023). For example, in a longitudinal study of the 2016 U.S. presidential election (Lench et al., 2019), Clinton supporters reported decreased well-being immediately following the election but returned to baseline within six months, whereas Trump supporters initially increased but also returned to baseline by six months. Additionally, in this study, researchers also found that greater conservatism consistently predicted higher well-being over the span of six months (Lench et al., 2019). We extend on this prior literature by investigating how specific governmental actions during a time of democratic backsliding may play a role in individuals’ well-being.

In the present study, we examined how individuals’ political affiliation and support for government actions was associated with well-being during the early months of President Trump’s second term. This unique period (February–March 2025) was marked by unprecedented sweeping policy changes and institutional challenges that raised widespread concerns about democratic decline (Carrier & Carothers, 2025). Specifically, we examined whether Democrats and Republicans differed in life satisfaction and happiness during this period, whether these well-being outcomes changed over time, and whether support for new federal actions differed by political affiliation. Finally, we tested whether support for governmental actions — with Republicans generally favoring administration actions and Democrats favoring oppositional actions — was correlated with well-being, and whether these associations happened to persist above and beyond political affiliation and controlling for demographics.

Why Would Republicans Be Happier than Democrats? Considering System Justification, Motivated Social Cognition, and Person–Environment Fit

System Justification

One potential reason for the well-documented partisan gap in well-being could be system justification (Napier & Jost, 2008). According to system justification theory, people are psychologically motivated to defend, justify, and rationalize current social and political systems, even when those systems disadvantage them, because doing so reduces uncertainty, threat, and cognitive dissonance (Jost, 2017; Jost, 2019). System justification is seen as serving a palliative function, as it has been associated with greater well-being (Vargas-Salfate et al., 2018). Thus, conservatives may report greater subjective well-being because they hold stronger system-justifying beliefs than liberals (Napier & Jost, 2008). Applied to the U.S. context and the present study, Republicans’ greater support for the Trump administration’s actions may reflect this system-justifying tendency, which in turn contributes to higher well-being. Democrats, who reliably report lower system justification, may instead experience increased threat from these same actions. In the context of democratic backsliding, this could mean that disapproval of government actions may carry psychological costs.

Motivated Cognition

A second explanation is that political ideology functions as motivated social cognition (Jost et al., 2003; Jost & Amodio, 2012). People’s ideology serves epistemic, existential, and relational needs, shaping how they process political information (Jost et al., 2009, 2018). In the current context, Republicans may engage in motivated reasoning to interpret the Trump administration’s actions as beneficial — even if the material effects are mixed — in order to preserve a coherent worldview and affirm their group identity (Jost et al., 2022; Prior, 2013). Democrats, by contrast, may be motivated to view the administration’s actions as harmful, which can heighten emotional distress, identity threat, and ultimately reduce well-being (Krupenkin et al., 2019; Lench et al., 2019). This asymmetry helps explain why Republicans’ support with administration actions may be associated with greater well-being, while Democrats’ opposition may be linked to lower well-being during this period of democratic decline.

Person–Environment Fit

A third explanation comes from the concept of person–environment fit, which describes how well individuals’ values align with their broader sociopolitical context (Van Vianen, 2018). Greater similarity between individuals and their environments has been associated with better well-being and satisfaction (Hanel et al., 2020). In the U.S., conservatives report higher happiness and life satisfaction when the national climate is more conservative (Stavrova & Luhmann, 2016). Applied to the present context, Republicans may experience better well-being because their ideology aligns with the administration’s actions, creating a sense of fit. Democrats, in contrast, may report lower well-being because the policy environment is fundamentally misaligned with their values. Under conditions of democratic backsliding, this poor fit can be especially acute, as opposition to anti-democratic actions may generate political alienation but also psychological strain.

Together, these perspectives highlight how periods of democratic backsliding can have asymmetric consequences for people’s well-being. Republicans, whose stronger system-justifying tendencies, motivated reasoning, and ideological alignment with the administration may foster a better sense of fit, may report feeling higher well-being under such conditions. Democrats, by contrast, face increased psychological strain due to lower system justification making government actions appear more threatening, motivated cognition amplifying harm perceptions, and poor person–environment fit exacerbating distress. Thus, support for a backsliding regime may bring short-term psychological benefits, while disapproval may come at the cost of diminished well-being. This framework guided our investigation into how partisanship, support for governmental actions, and democratic decline intersect with people’s happiness and life satisfaction.

The Present Study: The Unique Context of the Second Trump Presidency

In summary, individuals’ political preferences have been consistently linked to their self-reports of well-being. Prior work has shown that conservatives typically report greater subjective well-being than liberals (e.g., Burton et al., 2015; Garner et al., 2021; Napier & Jost, 2008; Okulicz-Kozaryn et al., 2014; Stavrova & Luhmann, 2016). In the present study, we extend this literature by examining whether political partisanship predicted well-being during the early months of President Trump’s second presidency, a period when a conservative-led federal government issued sweeping policy changes at an unprecedented pace. During this period, concerns about democratic decline were especially pronounced. We specifically recruited those who identified with one of the two major political parties, as we were interested in differences between members of opposing parties during this highly partisan, polarized time. Additionally, we investigated whether constituents’ reported support for these new federal actions were associated with their subjective well-being, with particular attention to partisan differences in support.

This setting provides a unique opportunity to examine well-being during a period widely described as democratic backsliding. The first few months of President Trump’s second term were characterized by upheaval, including a surge of executive orders and hundreds of lawsuits (Ball, 2025; Treisman, 2025; Yourish et al., 2025). These actions affected both domestic and foreign policy, spanning immigration enforcement, birthright citizenship, tariffs, revoking education funding, mass federal firings, and U.S. involvement in the Ukraine–Russia and Gaza–Israel conflicts (Yourish et al., 2025). During this period, scholars warned of increasing authoritarianism, diminished institutional checks on executive power, and declining trust in democratic institutions (Cummings & Wilkins, 2025; Shore et al., 2025).

Accordingly, we examined partisan well-being between February and March 2025, surveying Democrats and Republicans weekly across five timepoints. Participants reported on their life satisfaction and happiness, as well as their support for ongoing government actions. We addressed three central questions and present our hypotheses:

Are Democrats more unhappy and dissatisfied, as well as less supportive of the current administration’s actions, in comparison to Republicans? At each timepoint, we examined whether there were mean differences in Democrats’ and Republicans’ life satisfaction and happiness the past week at each timepoint (T1-T5) and in their support for governmental actions and actions taken against the administration (presented using three news stories at each timepoint in T2-T5). Due to higher system justification, motivated cognition, and person-environment fit to the current administration, we hypothesized that at each timepoint, Republicans would report higher happiness, life satisfaction, and support for all of the Trump administration’s actions, in comparison to Democrats. Additionally, we anticipated that Democrats would report higher support for the actions taken against the Trump administration, compared to Republicans.

Second, does well-being change over time during this period of rapid political upheaval? Given prior work showing evidence that greater system justification and perceived person-environment fit are associated with greater well-being and that election wins and losses are accompanied by increased and decreased well-being, respectively, we predicted that Democrats would decrease in their well-being over time, whereas Republicans would increase.

Third, does support for governmental actions correspond with participants’ well-being during this period? Based on system justification, motivated cognition, and person-environment fit research, we also anticipated that greater support for each governmental action would be associated with higher well-being. On the other hand, we hypothesized that those who report greater support for actions taken against the administration would also have lower well-being. We explored whether these associations held even after accounting for political affiliation and demographic factors, thereby assessing whether dissatisfaction with government actions carries psychological consequences regardless of group identity.

Method

Transparency and Openness

Research materials and data are available at the Open Science Framework (OSF; https://osf.io/gyk74/). The measures, analyses and sample size were pre-registered, https://aspredicted.org/xwjs-3dcq.pdf. As noted in our pre-registration, we collected the data before pre-registering our analyses; however, we did not conduct any analyses on the data, the exception being descriptive analyses to identify how many participants we had in our sample and how many identified with each party. Data collection procedures were approved by Arizona State University’s Institutional Review Board (STUDY00021701).

Participants

We surveyed 601 participants (306 Democrats and 295 Republicans) across five timepoints, once per week, from February 22, 2025 to March 24, 2025. We recruited adults who lived in the U.S. during the time of data collection and had specified that they identified as Democrat or Republican on Prolific. We did not have any data exclusions, as Qualtrics data checks revealed that none of our participants appeared to be a bot and none had an unusually fast response. Our sample comprised 302 men, 295 women, and 4 nonbinary participants. The average age was 42.44 years (SD_age = 14.26), with the range being 18-85 years. Our sample was 74% White, 10% Black, 5% Hispanic, 6% Asian, 0.5% Middle Eastern or North African, and 5.3% Multiracial. Our study was called Weekly Reactions, in which participants gave their reactions to news stories and completed questions regarding their own feelings and their perceptions of others’. We compensated participants $2.25 for completing surveys 1 and 2, and $2.75 for surveys 3-5. If participants completed all 5 surveys, they received a $2.00 bonus, bringing the potential total to $14.75.

Of the original 601 participants at T1, we retained 73% at T2 (March 1-3, 2025; N = 437; 216 Democrats and 221 Republicans), 74% at T3 (March 8-10, 2025; N = 445; 223 Democrats and 222 Republicans), 70% at T4 (March 15-17, 2025; N = 421; 211 Democrats and 210 Republicans), and 66% at T5 (March 22-24, 2025; N = 397; 206 Democrats and 191 Republicans). Sensitivity power analyses for independent t-tests revealed that for our smallest sample size (i.e., T5), we had >99% power to detect effect sizes as small as d = 0.43. For our growth models, we conducted posthoc Monte Carlo simulation analyses with 1,000 simulations for each effect, and we report power for each significant effect (ranging from 0.60 to 0.88). More details regarding completion rates and simulation analyses can be found in our Supplementary Materials.

Demographics at each timepoint can be found in Table 1. For our analyses for Questions 1 and 3, no participants were excluded from analyses; we also used all available data from participants across all timepoints. For Question 2, given that we examined participants’ change over time in longitudinal growth models, we excluded participants who only completed T1 (N = 79); thus, we retained 87% of our sample (N = 522; 260 Democrats and 262 Republicans).

Measures

Demographic Variables

At T1, participants reported their gender identity (man/woman/nonbinary) and age (open-ended). Participants also indicated their race/ethnicity (Black or African American/East Asian/Hispanic or Latinx/Indigenous American, American Indian, or Alaska Native/Middle Eastern or North African/Native Hawaiian or other Pacific Islander/South Asian/Southeast Asian/White), which were consolidated into 6 racial categories (see Table 1). For our analyses using race as a covariate, we created a dichotomous race variable by combining 5 racial categories into one category for our participants of color. Additionally, participants reported their subjective socioeconomic status in the U.S. from 1 (worst off) to 10 (best off) (M = 5.42, SD = 1.80).

Table 1

Demographic Information for Each Timepoint

Parameter	Time 1 (N = 601)	Time 2 (N = 437)	Time 3 (N = 445)	Time 4 (N = 421)	Time 5 (N = 397)
Political Affiliation
Democrat	49.1% (N = 295)	50.6% (N = 221)	49.9% (N = 222)	49.9% (N = 210)	48.1% (N = 191)
Republican	50.9% (N = 306)	49.4% (N = 216)	50.1% (N = 223)	50.1% (N = 211)	51.9% (N = 206)
Gender
Man	50.2% (N =302)	49.0 % (N = 214)	49.4% (N = 222)	48.7% (N = 205)	49.6% (N = 205)
Woman	49.1% (N = 295)	50.8 % (N = 222)	49.7% (N = 221)	50.8% (N = 214)	50.4% (N = 214)
Nonbinary	0.7% (N = 4)	0.2% (N = 1)	0.4% (N = 2)	0.5% (N = 2)	0.0% (N = 0)
Race
White American	73.7% (N = 443)	75.5% (N = 330)	73.7% (N = 328)	73.9% (N = 311)	73.3% (N = 291)
Black or African American	10.0% (N = 60)	6.6% (N = 29)	9.7% (N = 43)	9.7% (N = 41)	8.6% (N = 34)
Hispanic or Latinx	4.8% (N = 29)	4.8% (N = 21)	4.3% (N = 19)	3.3% (N = 14)	4.0% (N = 16)
Asian	5.7% (N = 34)	6.2% (N = 27)	5.4% (N = 24)	6.2% (N = 26)	6.8% (N = 27)
MENA	0.5% (N = 3)	0.7% (N = 3)	0.7% (N = 3)	0.7% (N = 3)	0.5% (N = 2)
Multiracial	5.3% (N = 32)	6.2% (N = 27)	6.3% (N = 28)	6.2% (N = 26)	6.8% (N = 27)
Age
Mean (SD)	42.44 (14.26)	43.87 (14.38)	43.84 (14.14)	44.13 (14.20)	44.24 (13.96)
Range	18 to 85	18 to 85	18 to 85	18 to 85	19 to 79

Political Affiliation

At T1, participants reported whether they considered themselves to be a Republican (N = 284), Democrat (N = 295), Independent (N = 19), or Something else (N = 3). For those who identified as an independent or something else, we asked them to choose whether they considered themselves to be closer to Republicans (N = 11) or Democrats (N = 11).

Life Satisfaction

At each timepoint, participants answered the following single-item question to measure their satisfaction with their life (adapted from Cheung & Lucas, 2014) over the past week: “On average how satisfied were you with your life over this past week?” from a 1 (very dissatisfied) to 7 (very satisfied) Likert scale (T1: M = 4.74, SD = 1.62; T2: M = 4.67, SD = 1.64; T3: M = 4.72, SD = 1.63; T4: M = 4.87, SD = 1.54; T5: M = 4.88, SD = 1.56).

Happiness

Participants completed a single-item question to measure their past week’s happiness: “Taking all things together, on average how would you say you felt over this past week?” from a 1 (very unhappy) to 7 (very happy) Likert scale (T1: M = 4.64, SD = 1.60; T2: M = 4.51, SD = 1.72; T3: M = 4.60, SD = 1.64; T4: M = 4.77, SD = 1.56; T5: M = 4.81, SD = 1.62).

Support for Federal Actions

Starting with T2, we provided participants with three news topics that took place in the prior week in each survey for them to read and respond to. We selected articles to cover a variety of issues, including both foreign and domestic policy, federal cuts, immigration, as well as court cases. These news articles can be found in the Supplementary Materials. After each story, participants reported how much they supported each of these decisions or proposals, on Likert scales of 1 (not at all) to 7 (very much).

In T2, participants reported how much they supported 1) the Trump administration views towards Ukraine (M = 3.25, SD = 2.39), 2) Trump’s proposal to acquire and develop the Gaza strip (M = 2.56, SD = 2.02, and 3) the House of Representatives passing a budget bill that would lead to large tax cuts and reductions in federal spending (M = 3.18, SD = 2.25). In T3, participants reported how much they supported 1) the Trump administration’s tariff actions toward Canada (M = 2.93, SD = 2.24), 2) Trump’s proposal to increase logging in national forests (M = 2.78, SD = 2.09), and 3) the termination of hundreds of active National Institute of Health (NIH) research grants (M = 3.30, SD = 2.46). In T4, participants reported their approval of 1) the Trump administration’s decision to try and deport U.S. permanent resident Mahmoud Khalil (M = 2.85, SD = 2.24), 2) the Trump administration’s decision to pull federal funding from higher education institutions (M = 3.21, SD = 2.40), and 3) a federal judge’s order to rehire thousands of fired government workers (M = 5.31, SD = 2.15). Finally, in T5, participants reported their support of 1) the decision to deny entry to a French scientist because of his phone messages that criticized the Trump administration (M = 2.42, SD = 2.00), 2) Chief Justice Roberts rebuking Trump for calling for impeachment of a federal judge (M = 5.16, SD = 2.21), and 3) a federal judge’s order blocking DOGE from accessing Social Security information (M = 5.43, SD = 2.23).

Results

Analytical Plan

To address Question 1, we conducted independent t-tests at each timepoint to examine whether there were mean differences in life satisfaction, happiness, and governmental action support between Democrats and Republicans. For Question 2, to test whether Democrats and Republicans changed in their life satisfaction and happiness over time, we conducted longitudinal growth models for all participants who completed at least two surveys, utilizing the full information maximum likelihood (FIML; Allison, 2010; Preacher et al., 2008) estimator to handle missing data. Each model had two levels. Level 1 represented within-participant variables (life satisfaction, happiness) that were measured across five timepoints, while Level 2 represented political affiliation, a between-participant variable. In Level 1, life satisfaction and happiness were regressed on time (on a weekly basis), creating a slope representing change over time for each of these variables. Time was centered at the first timepoint. Random effects were created for intercepts (T1 responses) and slopes and were allowed to covary. At Level 2, the intercepts and slopes were regressed on political party, measuring whether slopes for Democrats and Republicans significantly changed over time and whether these slopes significantly varied between party.

For Question 3, we examined whether participants’ support for federal actions were associated with their life satisfaction and happiness, conducting correlations at T2-T5 between action support and life satisfaction/happiness. Additionally, we conducted regressions controlling for political party, age, gender, SES, and race to isolate the unique variance in life satisfaction/happiness explained by action support.

Mean Differences in Well-Being

All means and standard deviations can be found in Figure 1 and Table 2. Consistent with our hypotheses, at all timepoints, Republicans reported greater life satisfaction over the past week, in comparison to Democrats (ts ≥ 5.36, ps ≤ .001, ds ≥ 0.50). Additionally, Republicans also reported feeling greater happiness at all timepoints, compared to Democrats (ts ≥ 6.07, ps ≤ .001, ds ≥ 0.59).

Figure 1

Differences by Political Affiliation in Life Satisfaction and Happiness Across Timepoints

Table 2

Mean Differences by Political Affiliation in Life Satisfaction and Happiness

	Democrats M (SD)	Republicans M (SD)	Mean Comparison	95% CI of Difference
Life Satisfaction
Time 1	4.36 (1.62)	5.14 (1.53)	t(598.75) = 6.12, p < .001, d = 0.50	[.53, 1.04]
Time 2	4.19 (1.69)	5.15 (1.45)	t(421.89) = 6.40, p < .001, d = 0.61	[.67, 1.26]
Time 3	4.24 (1.57)	5.21 (1.54)	t(442.87) = 6.62, p < .001, d = 0.57	[.69, 1.26]
Time 4	4.48 (1.49)	5.27 (1.49)	t(417) = 5.41, p < .001, d = 0.63	[.50, 1.07]
Time 5	4.50 (1.55)	5.30 (1.55)	t(394.90) = 5.36, p < .001, d = 0.53	[.51, 1.11]
Happiness
Time 1	4.14 (1.56)	5.16 (1.47)	t(598.58) = 8.21, p < .001, d = 0.67	[.77, 1.26]
Time 2	3.88 (1.74)	5.12 (1.45)	t(417.63) = 8.06, p < .001, d = 0.77	[.94, 1.54]
Time 3	4.01 (1.55)	5.20 (1.52)	t(442.90) = 8.18, p < .001, d = 0.78	[.90, 1.48]
Time 4	4.33 (1.52)	5.22 (1.47)	t(416.56) = 6.07, p < .001, d = 0.59	[.60, 1.17]
Time 5	4.29 (1.64)	5.37 (1.40)	t(392.49) = 7.02, p < .001, d = 0.71	[.78, 1.38]

Mean Differences in Federal Action Support

Consistent with hypotheses, Republicans reported greater support than Democrats for all actions taken by the Trump administration and Republican lawmakers, whereas Democrats reported greater support than Republicans for all actions taken against the Trump administration (ts ≥ 12.61, ps < .001, ds ≥ 1.29). Means and standard deviations for each issue can be found in Table 3.

Table 3

Mean Differences by Political Affiliation in Support for Federal Actions

Topic of Agreement	Democrats M (SD)	Republicans M (SD)	Mean Comparison	95% CI of Difference
T2
aTrump Administration’s Views Towards Ukraine	1.43 (1.11)	5.04 (1.91)	t(353.77) = 24.18, p < .001, d = 2.30	[3.31, 3.90]
aTrump’s Proposal to Acquire and Develop Gaza Strip	1.39 (1.17)	3.71 (2.01)	t(356.05) = 14.81, p < .001, d = 1.41	[2.01, 2.63]
aHouse of Representatives Passing Budget Bill	1.52 (1.17)	4.80 (1.84)	t(374.88) = 22.27, p < .001, d = 2.12	[2.99, 3.67]
T3
aTrump Administration’s Tariff Actions Towards Canada	1.40 (1.09)	4.46 (2.05)	t(335.55) = 19.66, p < .001, d = 1.87	[2.76, 3.37]
aTrump’s Logging Proposal in National Forests	1.46 (1.06)	4.11 (2.03)	t(332.09) = 17.30, p < .001, d = 1.64	[2.35, 2.94]
aTermination of Active National Institute of Health (NIH) Grants	1.47 (1.14)	5.14 (2.01)	t(349.59) = 23.69, p < .001, d = 2.25	[3.37, 3.98]
T4
aTrump Administration’s Attempt to Deport Mahmoud Khalil	1.44 (1.15)	4.26 (2.18)	t(315.75) = 16.59, p < .001, d = 1.62	[2.49, 3.16]
aTrump Administration’s Decision to Pull Higher Education Funding	1.48 (1.19)	4.96 (2.01)	t(337.90) = 21.53, p < .001, d = 2.11	[3.16, 3.79]
bFederal Judge Order to Rehire Government Workers	6.59 (0.99)	4.03 (2.24)	t(287.31) = 15.17, p < .001, d = 1.48	[-2.89, -2.23]
T5
aDecision to Deny Entry to French Scientist due to Trump Criticism	1.37 (1.14)	3.55 (2.12)	t(286.66) = 12.61, p < .001, d = 1.29	[1.84, 2.51]
bChief Roberts’ Rebuke of Trump for Calling for Judge Impeachment	6.35 (1.34)	3.87 (2.24)	t(304.99) = 13.30, p < .001, d = 1.36	[-2.85, -2.12]
bFederal Judge Order Blocking DOGE from Accessing Social Security	6.79 (0.59)	3.96 (2.40)	t(211.49) = 15.88, p < .001, d = 1.65	[-3.17, -2.49]

Well-Being Over Time

Linear Growth Models

As hypothesized, over the five weeks, Republicans increased in their life satisfaction, b = 0.04, SE = 0.02, p = .029, power = 0.61. However, contrary to our hypotheses, Democrats also increased in their life satisfaction over time, b = 0.05, SE = 0.02, p = .013, power = 0.71. The change trajectories of Republicans and Democrats did not significantly differ, b = 0.01, SE = 0.03, p = .849. The results for happiness mirrored those for life satisfaction, as both Republicans (b = 0.04, SE = 0.02, p = .023, power = 0.60) and Democrats (b = 0.05, SE = 0.02, p = .008, power = 0.72) increased in their happiness over time. Again, for happiness, change trajectories did not significantly differ, b = 0.01, SE = 0.03, p = .818.

Quadratic Growth Models and Model Comparison

Upon examining the data and based on reviewer feedback, we also conducted alternative models. Specifically, we conducted quadratic growth models, separately for life satisfaction and happiness, separately for Democrats and Republicans, which tested whether there was both quadratic and linear change in Democrats’ and Republicans’ well-being. We also conducted model comparison tests which compared each quadratic model to their corresponding linear model. In contrast to our linear growth models, Republicans did not have significant linear (life satisfaction: b = 0.04, SE = 0.07, p = .580; happiness: b = -0.03, SE = 0.06, p = .591) or quadratic change (life satisfaction: b = 0.001, SE = 0.02, p = .924; happiness: b = 0.02, SE = 0.01, p = .171) in the quadratic models. However, model fit indices showed that the linear models, in which Republicans reported increased life satisfaction and happiness, were a better fit to the data, in comparison to the quadratic models. Specifically, likelihood ratio tests indicated that the quadratic models were not significantly a better fit than the linear models (life satisfaction: χ²(4) = 7.26, p = .124; happiness: χ²(4) = 2.10, p = .717), in which case we retain the simpler, more parsimonious model, which are the linear models. Additionally, the linear models had lower AICs (life satisfaction: 3303.34 < 3304.08; happiness: 3228.90 < 3234.49) and BICs (life satisfaction: 3333.38 < 3354.14; happiness: 3258.64 < 3284.56), indicating that the linear models are a better fit to the data for Republicans.

In contrast, Democrats, showed evidence of both linear and quadratic change in their well-being. For linear change, Democrats marginally declined in their life satisfaction over time (b = -0.14, SE = 0.07, p = .054, power = 0.52) and significantly declined in happiness (b = -0.16, SE = 0.07, p = .024, power = 0.65). Additionally, Democrats also showed positive quadratic change for both satisfaction (b = 0.05, SE = 0.02, p = .005, power = 0.81) and happiness (b = 0.06, SE = 0.02, p = .002, power = 0.88), such that well-being decreased at first then increased. Model fit comparisons indicated that for the likelihood ratio tests, the quadratic models were a significantly better fit than the linear models (life satisfaction: χ²(4) = 10.13, p = .038; happiness: χ²(4) = 10.12, p = .038). The quadratic models’ AICs were also lower than the linear models’ (life satisfaction: 3651.772 < 3653.91; happiness: 3574.85 < 3576.97), suggesting the quadratic models were a better fit. However, the linear models’ BICs were lower (life satisfaction: 3701.94 > 3684.01; happiness: 3625.01 > 3607.07), indicating better fit on this metric.

Taken together, we believe that linear models best fit the data for Republicans’ well-being, while quadratic models best fit Democrats’ data. Thus, while Republicans reported an overall linear increase in well-being over this timespan, Democrats demonstrated negative linear change, though rebounded positively.

Action Support and Well-Being

Consistent with our predictions, support for the Trump administration’s and Republican lawmakers’ actions was positively correlated with well-being across all timepoints, rs ≥ .20, ps < .001. Additionally, greater support for actions taken against the Trump administration was associated with decreased well-being, rs ≤ -.14, ps ≤ .006.

For our exploratory analyses, we conducted linear regressions in which we controlled for political party, age, gender, race, and subjective socioeconomic status. Adding political party was a deviation from our exploratory analyses mentioned in our preregistration. In analyses that did not include political party, all associations were significant, bs ≥ |.11|, ps ≤ .001. We elected to include political party in our exploratory regressions, in order to investigate whether these associations between support and well-being held above and beyond political party. After controlling for these variables, the associations between satisfaction with the Trump administration’s actions and well-being were weaker. Nevertheless, we still found that satisfaction with 8 of the 12 actions was significantly correlated with happiness and/or life satisfaction, suggesting that support and well-being are related beyond their shared variance with partisanship alone. Regression weights for each of these associations can be found in Table 4. Mirroring mean differences between Democrats’ and Republicans’ well-being, political affiliation remained a consistent and robust predictor of well-being, such that Republicans reported higher well-being at each timepoint, while accounting for support and other demographics. We also found that higher SES was reliably associated with well-being.

Table 4

Regression Weights between Governmental Action Support and Well-Being Without Controls and While Controlling for Political Party, Age, Gender, Race, and SES

	Support (without controls)		Support (with controls)		Political Party	Age	Gender	Race	SES
Outcomes at timepoint	R2	b [95% C.I.]	R2	b [95% C.I.]	b[95% C.I.]	b [95% C.I.]	b[95% C.I.]	b[95% C.I.]	b [95% C.I.]
T2 Life Satisfaction (N = 436)
aTrump Administration’s Views Towards Ukraine	0.10	0.21***[.15, .28]	0.22	0.16***[.07, .25]	-0.25[-.68, .17]	0.001 [-.01, .01]	0.20[-.08, .47]	-0.29[-.63, .04]	0.29***[.22, .37]
aTrump’s Proposal to Acquire and Develop Gaza Strip	0.06	0.20***[.13, .28]	0.20	0.09*[.01, .18]	-0.62***[-.97, -.28]	0.001 [-.01, .01]	0.19[-.09, .47]	-0.27[-.61, .06]	0.29***[.21, .36]
aHouse of Representatives Passing Budget Bill	0.12	0.25***[.19, .31]	0.22	0.16***[.07, .26]	-0.30[-.71, .11]	0.00 [-.01, .01]	0.20[-.07, .48]	-0.28[-.61, .05]	0.27***[.19, .35]
T2 Happiness (N = 436)
aTrump Administration’s Views Towards Ukraine	0.12	0.25***[.19, .32]	0.23	0.15**[.06, .24]	-0.60**[-1.04, -.16]	-0.001 [-.01, .01]	0.20[-.09, .49]	-0.20[-.54, .15]	0.27***[.19, .35]
aTrump’s Proposal to Acquire and Develop Gaza Strip	0.07	0.23***[.15, .31]	0.22	0.08[-01, .17]	-0.95***[-1.31, -.60]	-0.001 [-.01, .01]	0.19[-.10, .48]	-0.18[-.53, .17]	0.26***[.18, .34]
aHouse of Representatives Passing Budget Bill	0.17	0.31***[.25, .38]	0.25	0.21***[.12, .31]	-0.44*[-.86, -.03]	-0.001 [-.01, .01]	0.22[-.06, .51]	-0.17[-.51, .17]	0.24***[.16, .32]
T3 Life Satisfaction (N = 445)
aTrump Administration’s Tariff Actions Towards Canada	0.08	0.21***[.14, .27]	0.18	0.10*[.02, .19]	-0.59**[-.97, -.21]	0.01 [-.004, .02]	0.18[-.10, .46]	-0.02[-.34, .31]	0.24***[.17, .32]
aTrump’s Logging Proposal in National Forests	0.10	0.24***[.18, .31]	0.19	0.13**[.05, .22]	-0.57**[-.93, -.21]	0.004 [-.01, .01]	0.21[-.07, .48]	-0.04[-.36, .29]	0.23***[.15, .31]
aTermination of Active National Institute of Health (NIH) Grants	0.07	0.17***[.11, .23]	0.17	0.05[-.04, .13]	-0.75***[-1.18, -.33]	0.01 [-.004, .02]	0.17[-.11, .45]	-0.04[-.37, .29]	0.25***[.17, .32]
T3 Happiness (N = 445)
aTrump Administration’s Tariff Actions Towards Canada	0.11	0.25***[.18, .31]	0.20	0.12**[.03, .20]	-0.77***[-1.15, -.39]	-0.001 [-.01, .01]	0.16[-.12, .43]	-0.12[-.44, .21]	0.20***[.12, .28]
aTrump’s Logging Proposal in National Forests	0.13	0.28***[.21, .35]	0.20	0.15***[.07, .24]	-0.72***[-1.08, -.35]	-0.004 [-.01, .01]	0.19[-.09, .47]	-0.14[-.46, .19]	0.19***[.11, .26]
aTermination of Active National Institute of Health (NIH) Grants	0.10	0.21***[.15, .27]	0.19	0.07[-.01, .16]	-0.85***[-1.28, -.43]	-0.002 [-.01, .01]	0.16[-.12, .43]	-0.15[-.47, .18]	0.20***[.12, .28]
T4 Life Satisfaction (N = 419)
aTrump Administration’s Attempt to Deport Mahmoud Khalil	0.04	0.14***[.08, .21]	0.15	0.06[-.02, .14]	-0.59**[-.95, -.22]	0.002 [-.01, .01]	0.23[-.05, .50]	-0.002[-.33, .32]	0.23***[.16, .31]
aTrump Administration’s Decision to Pull Higher Education Funding	0.04	0.13***[.07, .20]	0.15	0.05[-.04, .14]	-0.58**[-.99, -.16]	0.002 [-.01, .01]	0.23[-.04, .51]	-0.01[-.33, .32]	0.24***[.16, .31]
bFederal Judge Order to Rehire Government Workers	0.03	-0.12***[-.19, -.05]	0.15	-0.06[-.14, .02]	-0.61***[-.96, -.26]	0.002 [-.01, .01]	0.24[-.04, .51]	-0.003[-.33, .32]	0.24***[.16, .32]
T4 Happiness (N = 419)
aTrump Administration’s Attempt to Deport Mahmoud Khalil	0.06	0.16***[.10, .23]	0.17	0.08*[.003, .17]	-0.59***[-.96, -.23]	-0.01 [-.02, .004]	0.35*[.07, .62]	-0.15[-.48, .18]	0.22***[.15, .30]
aTrump Administration’s Decision to Pull Higher Education Funding	0.06	0.16***[.10, .23]	0.17	0.10*[.02, .19]	-0.47*[-.88, -.05]	-0.01 [-.02, .004]	0.37**[.10, .65]	-0.16[-.48, .17]	0.23***[.15, .31]
bFederal Judge Order to Rehire Government Workers	0.02	-0.11**[-.18, -.04]	0.16	-0.03[-.11, .05]	-0.75***[-1.11, -.40]	-0.01 [-.02, .01]	0.33*[.06, .61]	-0.16[-.48, .17]	0.22***[.15, .30]
T5 Life Satisfaction (N = 397)
aDecision to Deny Entry to French Scientist due to Trump Criticism	0.06	0.19***[.11, .26]	0.17	0.10*[.02, .19]	-0.53**[-.87, -.20]	0.001 [-.01, .01]	0.19[-.10, .48]	-0.22[-.55, .12]	0.25***[.17, .33]
bChief Roberts’ Rebuke of Trump for Calling for Judge Impeachment	0.02	-0.11**[-.18, -04]	0.16	-0.04[-.12, .04]	-0.65***[-.99, -.30]	0.001 [-.01, .01]	0.21[-.08, .50]	-0.26[-.59, .08]	0.26***[.18, .34]
bFederal Judge Order Blocking DOGE from Accessing Social Security	0.02	-0.10**[-.17, -.03]	0.16	-0.003[-.09, .08]	-0.74***[-1.12, -.37]	0.001 [-.01, .01]	0.19[-.10, .49]	-0.26[-.59, .08]	0.25***[.17, .33]
T5 Happiness (N = 397)
aDecision to Deny Entry to French Scientist due to Trump Criticism	0.07	0.22***[.14, .30]	0.20	0.09*[.01, .18]	-0.82***[-1.16, -.47]	-0.004 [-.01, .01]	0.14[-.15, .43]	-0.29[-.63, .06]	0.24***[.16, .32]
bChief Roberts’ Rebuke of Trump for Calling for Judge Impeachment	0.03	-0.13***[-.20, -.06]	0.19	-0.03[-.11, .05]	-0.95***[-1.31, -.59]	-0.004 [-.01, .01]	0.15[-.15, .45]	-0.32[-.66, .02]	0.24***[.16, .33]
bFederal Judge Order Blocking DOGE from Accessing Social Security	0.03	-0.13***[-.20, -.06]	0.19	0.01[-.07, .10]	-1.05***[-1.44, -.67]	-0.004 [-.01, .01]	0.13[-.17, .43]	-0.32[-.66, .02]	0.24***[.16, .32]

Discussion

Our findings highlight the psychological consequences of political change during a period widely described as democratic backsliding. During the second month of President Trump’s second presidency, a period characterized by sweeping executive actions and warnings of democratic decline, Republicans consistently reported greater life satisfaction and happiness than Democrats. Republicans increased in their well-being over the course of five weeks. In contrast, and unexpectedly, while Democrats at first decreased in their well-being, they then showed increases in well-being during this period. Importantly, partisan differences in support for governmental actions mirrored our predictions: Republicans were more supportive of the Trump administration’s actions, whereas Democrats expressed greater support for actions taken against the administration. These differences were associated with well-being. Greater support for the administration’s actions was associated with higher well-being, whereas greater support for oppositional actions was correlated with lower well-being. Notably, several of these associations held even after accounting for political affiliation and demographic variables (age, race, gender, and socioeconomic status), suggesting that dissatisfaction with government actions carries psychological costs regardless of partisan identity.These findings both replicate and extend prior research on the partisan “happiness gap.” Consistent with past work, Republicans reported greater well-being than Democrats, but our results also complicate this story by showing that Democrats’ well-being increased modestly over time, suggesting resilience processes such as adaptation or solidarity. Importantly, support for governmental actions was associated with well-being above and beyond partisan identity, highlighting the psychological costs of political misfit. Taken together, this study provides new evidence that the well-being consequences of political change are predicted not only by group membership but are also linked to individuals’ alignment with government actions during this volatile period of democratic decline in the U.S.

Political Partisanship and Well-Being

Consistent with prior research documenting a “happiness gap” between conservatives and liberals (Bock & Schnabel, 2022; Napier & Jost, 2008; Schlenker et al., 2012; Wojcik et al., 2015), we found that Republicans reported greater happiness and life satisfaction than Democrats. This gap may reflect stronger system-justifying tendencies, motivated cognition, and greater person–environment fit among Republicans, whose ideology aligned more closely with the administration’s policies. In line with our hypotheses, we find that Republicans also reported a modest increase in their well-being over time. Additionally, although Democrats consistently reported lower well-being, their average scores hovered near the midpoint (i.e., somewhat satisfied or happy) and while decreasing at first, then increased modestly over time. Similar rebound patterns are documented in other contributions to this special issue, albeit with different outcomes (Lalot & Abrams, 2025; Marinthe et al., 2026), indicating that psychological responses to political stressors are dynamic. We suggest three possible reasons for this rebound effect: one based on our study design and the other two based on prior theory.

First, Democrats’ well-being may have reflected whether they were presented with news stories or the type of news stories. For instance, they may have declined in their well-being from T1 to T2, given that participants did not read any news stories during T1. After being reminded of the administration’s actions, they may have led to a decrease in well-being. In T4 and T5, they were also presented with some actions taken against the administration, which may have bolstered their well-being. However, we are also hesitant to conclude that the inclusion of these stories about anti-administration actions fully explained this increase in well-being, given that the associations between support for these anti-administration actions and well-being were weaker than the associations for support for the administration’s actions. Additionally, after controlling for other variables, these associations for anti-administration actions were no longer significant. Thus, we surmise that there may have been other theoretical mechanisms as to why Democrats displayed this increase in well-being.

Democrats may have adapted: theories of hedonic adaptation suggest that people often return to baseline levels of well-being even after significant life events (Brickman et al., 1978; Kahneman, 1999; Loewenstein & Ubel, 2008). Similar patterns have been observed following election losses, where initial declines in well-being eventually give way to recovery (Lench et al., 2019; Pierce et al., 2016). Therefore, while Democrats displayed a momentary decrease in well-being after being first presented with news stories, their well-being rebounded as time passed.

Additionally, Democrats may have experienced greater ingroup solidarity in the face of collective threat (Ball & Branscombe, 2019). Such solidarity can foster well-being through moral engagement, prosocial behavior, and strengthened moral identity (Goering et al., 2024; Waytz & Hofmann, 2020). Thus, in the current context, it is possible that the Trump administration’s pursuit of policies that Democrats perceived as immoral or unjust may have spurred them to engage in prosocial responses — such as collective action and social justice advocacy — that, in turn, bolstered well-being.

Political Partisanship and Action Support

We also found that partisan differences in support were robust and consistently linked to well-being. Republicans consistently reported greater support for administration actions, while Democrats consistently supported actions opposing the administration. Support for administration actions was associated with higher well-being, whereas opposition was correlated with lower well-being, even though average support for the administration’s actions among Republicans was modest (M = 4.27 on a 1–7 scale). Democrats, in contrast, overwhelmingly opposed these actions (M = 1.44). Thus, while both parties diverged sharply, neither expressed overwhelming enthusiasm for the administration’s agenda.

In exploratory analyses, we found that many of these support-well-being associations held after controlling for party and demographics, particularly those between support for administrative actions and well-being. This suggests that approval of these actions captures more than partisan identity: it reflects the degree of fit or misfit between individuals and their political environment. In contrast, associations between opposition to the administration’s actions and well-being were weaker and were no longer significant after controlling for demographic variables. We surmise that this may have occurred because these anti-administration actions were not perceived as effective checks on the administration. Although judges dissented or issued rulings against certain policies, participants may have viewed such pushback as temporary or ultimately insufficient (e.g., because the administration could appeal federal judge court orders). Consequently, this suggests that actions taken by the ruling party or administration itself may have more impact on individuals, in comparison to oppositional actions. In the context of democratic backsliding that is perpetuated by the government, well-being disparities may be exacerbated as they create an environment that aligns with one group’s values while alienating the other. In such contexts, disapproval of government actions—particularly in a backsliding context—may carry psychological costs in the form of reduced well-being.

While our findings illustrate how periods of democratic decline may contribute to links between support and well-being, they also raise new questions that future research must address.

Limitations and Future Directions

Despite the numerous strengths of the present investigation (e.g., pre-registered designs and hypotheses, longitudinal data), there are some limitations that invite further inquiry. First, due to our study design, we were unable to test for mechanisms from prior literature explaining the happiness gap between political parties (e.g., system justification), which opens a promising direction for future studies. Although we drew on established theoretical perspectives such as system justification, motivated cognition, and person–environment fit to frame our predictions, our design did not allow us to directly test these mechanisms. Future research should measure or experimentally manipulate these processes to more precisely identify the pathways through which support of government actions are associated with well-being.

Second, there were limitations to our longitudinal design. Because participants responded to different actions and proposed policies at each timepoint, we were unable to assess whether longitudinal changes in support for these actions tracked changes in well-being. We are also unable to rule out the possibility of reverse causality, such that individuals’ well-being may also influence their support for government actions. Future studies should more directly examine directionality, and investigate whether continued exposure to, and resistance against, specific government actions accumulate psychological costs over time. Additionally, while our aim was to capture the rapid flurry of political actions during this specific period, changes in well-being were modest for both Republicans and Democrats, which may have occurred due to the short period, thus these findings should be regarded with caution. Future work should examine longer periods of time, to investigate long-term changes in well-being.

Third, we used single-item measures of life satisfaction and happiness, and for personal support for each of the stories. While we are unable to test for reliability at each individual timepoint and are more susceptible to measurement error, correlations for our well-being measures between timepoints were moderate to high (rs ≥ .68). Additionally, previous work has found that that single-item measures of life satisfaction and happiness demonstrated criterion validity with longer, established measures (Abdel-Khalek, 2006; Cheung & Lucas, 2014) and studies investigating well-being within the context of politics have also used single-item measures of well-being (Napier & Jost, 2008; Schlenker et al., 2012). However, for best practices, future studies should examine these variables using established measures and/or measures with multiple items.

Fourth, we focused specifically on Democrats and Republicans, recruiting individuals who already identified with one of these parties on Prolific. Thus, we recognize that this limits the generalizability of our findings, given that an increasing proportion of Americans identify as Independents (Jones, 2024). Future research should examine whether Independents experience well-being patterns more similar to those of the dominant group, the opposition group, or somewhere in between.

Finally, other individual factors and processes may play a role in individuals’ well-being and support for government action during this time. Many of the Trump administration’s actions—including restrictions on immigration, revoking education funding, and cuts to research—disproportionately affect immigrants, people of color, and individuals with lower socioeconomic status. Given that our focus was on Democrats and Republicans, we did not focus on recruiting participants from various demographic backgrounds. However, we do report exploratory analyses for race and SES in our Supplementary Materials. Other individual factors may play a factor in well-being during this period (e.g., unemployment, trust in government institutions, amount of news consumption). Future work should investigate whether democratic backsliding imposes greater well-being costs on marginalized populations, who may both oppose such policies more strongly and bear their material consequences more directly, as well as examine other individual differences that may impact well-being. Additionally, building on related work in this special issue, future research could investigate how anxiety about democratic backsliding relates to well-being and support for government actions, consistent with evidence linking anxiety to support for democratic principles and political action (Borghi et al., 2025).

Conclusion

In sum, our findings illustrate asymmetric patterns of well-being for dominant and opposition groups during a period widely described as democratic backsliding. During the early months of President Trump’s second presidency, Republicans consistently reported greater happiness and life satisfaction than Democrats, as well as stronger support for administration actions. Democrats, by contrast, expressed greater support for oppositional actions. Greater support for administration actions was associated with higher well-being, whereas greater support for oppositional actions was correlated with lower well-being—even though both groups showed modest increases in well-being over time. Importantly, many of the support–well-being associations held even after accounting for political affiliation and demographics, suggesting that dissatisfaction with government actions carries psychological consequences regardless of group identity. More broadly, our findings underscore how the psychological costs of political misfit may become especially salient in times of democratic decline.

We consider the implications of these findings within the context of democratic backsliding. Democrats’ rebound in well-being may be an adaptive response to an adverse political environment. While this may be beneficial for individuals themselves, this could also reduce long-term engagement or resistance against future actions, which could facilitate further erosion of democratic norms. For Republicans, increased well-being over time could reinforce support that contribute to democratic backsliding and thus, continued system instability.

Finally, while our data reflect a unique time in the United States during the early months of President Trump’s second term, these findings may be relevant in other societies that are experiencing authoritarian shifts. Specifically, we may also find that constituents who oppose the party in power report lower well-being in comparison to those who support the party in power, and this difference may be associated with lower support for government actions. Future research should examine these questions in other countries, to test whether these findings generalize, and investigate which psychological mechanisms explain them. By doing so, scholars can better understand the personal toll of democratic decline and the resilience processes that enable people to resist it.

Conflicts of Interest

The authors declare no competing interests.

Acknowledgements

This study was funded through the first author’s startup funds from Arizona State University.

Data Availability Statement

Research materials and data are available at the Open Science Framework (OSF; https://osf.io/gyk74/).

Supplementary Materials

The supplementary materials can be found here.

Author Contributions

D.J.W., K.L., and S.S. designed the study and outlined the original draft. D.J.W. collected and analyzed the data and wrote the original draft. D.J.W., K.L., S.S., and S.P. provided critical revisions.

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