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Abstract

Background:

Insights from mental health stigma research indicate the importance of societal and political views on mental health perceptions. Most studies originate from typical Western neo-liberal settings and focus on generic mental health issues. Our research explores these associations in Hungary, an understudied post-communist context with significant stigma levels, examining a broad range of stigmas related to both general and three specific mental illnesses: schizophrenia, depression, and alcohol use disorder (AUD).

Aims:

The study aims to connect a wide array of political dispositions to stigma associated with both general and specific mental illnesses, exploring both attitudes and behavioral intentions.

Methods:

We surveyed 492 participants (147 males, 342 females) on their political dispositions, including Right-Wing Authoritarianism (RWA), Social Dominance Orientation (SDO), general and economic system justification, and conservative political ideology, and their attitudes toward general and specific mental illnesses. Regression analyses identified key political dispositions influencing stigma.

Results:

RWA was significantly linked to most stigma outcomes, while conservative political ideology showed a selective impact. Other predictors had minimal influence on stigma outcomes.

Conclusion:

Our findings suggest that perceptions of danger, threat, and unconventionality, as indicated by RWA, are crucial for mental health stigmatization in Hungary. Intervention programs should target these factors, particularly in similar contexts.

Keywords

Right-wing authoritarianism social dominance orientation system justification conservatism mental health stigma

The existing literature on the stigmatization of mental illness is predominantly based on studies from Western countries, with only 14.6% of all papers including data from low- or middle-income countries (Angermeyer & Schomerus, 2017). The almost exclusive reliance on data from typical Western neo-liberal contexts is particularly problematic given that one of the crucial insights of stigma research is that what people think regarding political and social questions – what is a fair society, who should yield power and why, who is the ‘other’ – matters for how people think of mental health. We will refer to such individual-level differences in worldview or ideology as political dispositions. Most research in this field, particularly on how political conservatism correlates with stigmatization, originates from the US (DeLuca & Yanos, 2016; Ragsdale, 2022). The only exception may be a Swedish study that reported similar findings to those found in the US (Löve et al., 2019).

Our research focuses on Hungary, a country with notable mental health challenges, including high rates of alcohol consumption (Mihailovic et al., 2020) and suicide (Balint et al., 2020). A recent Eurobarometer survey revealed that perceived stigma is widespread among Hungarians, with those displaying symptoms of mental illness being the least likely in Europe to seek or receive professional help (European Commission, 2023). Besides providing results from a new and understudied context, we extend on existing research by (i) comparing various conceptualizations and measures of political dispositions (ii) assessing stigma multidimensionally, and (iii) assessing stigma in the context of three distinct mental disorders – depression, schizophrenia, and alcohol use disorder (AUD).

Previous research on political dispositions has often relied on simple measures like ideological left-right self-placement or vote choice. While convenient for large-scale surveys, ideological self-placement has severe limitations as a measure. Education, cultural background, and individual differences in morals and values all matter for how people understand scales such as the left-right scale (Bauer et al., 2017; Kivikangas et al., 2021; Piurko et al., 2011). On the other hand, vote choice depends on what is on offer on the ideological menu – on how political entities (e.g. party elites) in a specific cultural and historical context package economic and cultural views under specific ideological banners into particular bundles of attitudes for voters to choose from (Sniderman & Bullock, 2004). This is especially true in the Hungarian context, where the political choice for more than a decade has been between the one-party rule of an increasingly authoritarian governing party, Fidesz, and an ideologically fragmented opposition that attempted to form a fragile coalition in the last two national elections (Lönnqvist et al., 2021). The Hungarian political system is characterized by democratic backsliding and a populist turn (Krekó & Enyedi, 2018; Wunsch & Gessler, 2023). The degree of power concentration on the government side is exceptional (Krekó & Enyedi, 2018), leading to a desperate alliance of social democratic, liberal, far-right, and green parties, and diminishing the significance of traditional political ideology measures such as vote choice and ideological left-right self-placement, which, in this context, wouldnot be face-valid indicators of individual’s actual beliefs.

We focused on Right-Wing Authoritarianism (RWA), Social Dominance Orientation (SDO), and system justification (SJ) – previous stigma research that has moved beyond ideological self-placement and vote choice has focused on RWA and SDO, and we argue that system justification could also be relevant. RWA outlines a conservative worldview characterized by aggressiveness toward outgroups, submission to authorities, and adherence to traditional values (Altemeyer, 2006). In the US, RWA has been correlated with various dimensions of stigma, including negative stereotypes, negative attributions and affect, and social distance toward generic mental illness (DeLuca & Yanos, 2016; DeLuca et al., 2018). In France and Greece, RWA predicted social distance from schizophrenia (Lampropoulos et al., 2021), and in Australia, it was associated with negative attitudes (e.g. blame, perceived dangerousness) and low social acceptance toward schizophrenia and depression (Kvaale & Haslam, 2016).

RWA is included in dual-process models of prejudice, in which it is complemented by Social Dominance Orientation (SDO). SDO refers to the extent to which individuals endorse a hierarchical perspective of society, desire intergroup dominance, and oppose equality (Duckitt et al., 2002; Pratto et al., 1994) – it reflects a motivation to distance oneself from subordinated groups (Hadarics & Kende, 2018). Two of the above-referred studies on RWA and mental health stigma have been conducted within the framework of the dual-process model. In France, Greece, and Australia, SDO, as compared to RWA, appears to be a somewhat weaker predictor of mental health stigma toward schizophrenia and depression (Kvaale & Haslam, 2016; Lampropoulos et al., 2021).

Both SDO and RWA can be interpreted as part of a family of psychological dispositions – a need for security and certainty, mental rigidity and inflexibility, preference for familiarity, order and structure – that underlie political conservatism (e.g. Jost, 2021; Jost et al., 2009). System justification theory suggests that the social and psychological need to defend, bolster, and justify prevailing social, economic, and political arrangements—that is, to see the status quo as good, fair, natural, desirable, and even inevitable is a unifying theme that defines conservatism (Jost, 2021). People who believe in a system that strongly stigmatizes mental illness could be expected to also stigmatize those with mental illness themselves. Besides general system justification beliefs (GSJ), economic system justification (ESJ) – the tendency to legitimize economic inequality (Jost & Thompson, 2000) – could be relevant. A general aversion to economic egalitarianism (ESJ) could motivate mental health stigma – in cultures dominated by capitalist values, individuals struggling with mental health issues are often viewed as burdens on society due to their limited economic productivity and are blamed for this shortfall (Scheff, 2017; Yang et al., 2014).

Besides being limited to Western samples, the current literature on political attitudes and mental health stigma suffers from its focus on generic mental health (Angermeyer & Schomerus, 2017). In the present research, we focused on three types of mental illness: schizophrenia, depression, and AUD. The first two are, we believe, the most studied mental health illnesses in the literature on stigma. AUD was included, in part, because of its high prevalence in the East-Central European context, and therefore its high relevance from a public health perspective (Mihailovic et al., 2020).

Not only the determinants of mental health stigma but also the concept of stigma itself is inherently complex and calls for a multidimensional understanding. There is no universally accepted single definition or measure of stigma. Despite this, most researchers have relied on one dimension or a global scale (Pescosolido & Martin, 2015). Given that we measured a wide variety of psychological motivations that could underlie stigma, and that we included three very different mental health illnesses, we found it important to also assess the different dimensions of stigma as specifically as possible. That is, besides traditional prejudice and negative stereotypes and attitudes, we also measured desired social distance in various interactions, specific attributions, support for discrimination, and categorical beliefs.

In summary, the purpose of the present research was to assess a wide array of political dispositions and connect these to three distinct mental illnesses, schizophrenia, depression, and AUD, as well as a wide variety of different types of stigmas, ranging from attitudes to behavioral intentions. Importantly, this was conducted in Hungary, an understudied post-communist context with high levels of stigma associated with mental illness.

We propose that RWA, SDO, and General and Economic System Justification, alongside Conservative Political Ideology, will predict mental health stigma, both generally and for specific mental illnesses like depression, schizophrenia, and AUD. However, previous empirical work does not allow for more specific predictions with regards to what political dispositions go with what type of stigma. One aim of the present study is to start filling this gap in the literature.

Methods

Participants and procedure

Initially, 551 participants completed the survey questionnaire, but after excluding those with over 10 missing responses or monotonic responses, the final sample included 492 respondents (147 males, 342 females; M_Age = 29.02, SD = 12.71). The majority were educated, with 297 having at least a high school diploma and 177 holding university degrees. The sample featured 255 university students, 210 employees, and 27 others (e.g. retired). In terms of subjective socioeconomic status (SES), the distribution was 27 very high (‘I do not have any financial problems’), 355 high (‘I do not have financial problems, but I have to live within my means’), 102 low (‘I can’t buy everything I want and usually run out of money before the end of the month’), 6 very low (‘I have serious financial troubles’), with 2 not responding.

The study aimed for a sample size capable of detecting small effect sizes A priori power analysis with G*Power 3.1.9.7. (Faul et al., 2009) suggested a minimum of 402 participants was needed for five predictors, a small effect size of 0.05, 95% power, and an alpha of 0.05. Aiming to include four demographic variables as covariates, the target was at least 481 participants.

Recruitment occurred through course credit for university students and voluntary participation via social media and personal contacts for others. A link to an anonymous online survey in Qualtrics was shared with university students who signed up for a research credit course. Other participants were reached through social media, where we posted the link to the anonymous survey and asked our acquaintances to fill out the survey and share the link. University students voluntarily helped us distribute the link, reaching a diverse audience. We also sent the link to some acquaintances in private messages.

After consenting, participants answered questions on political dispositions. Following this, participants responded to questions assessing their attitudes toward mental illnesses in general.

Subsequently, participants were asked to read three vignettes depicting a target person experiencing a specific mental health problem. The vignettes were adapted from Link et al.’s (1999) research. The vignettes depicted János, Mihály, and Zoltán who were described as experiencing the symptoms of major depression, schizophrenia, and AUD, respectively. The names of the three target persons were typical Hungarian male first names. Following each vignette, several measures were employed to assess stigma toward the respective target person.

Finally, participants were thanked and debriefed. University students who participated for course credit were able to provide their identification details through a separate link, with the assurance that their responses would remain anonymous. This procedure was approved by the ethics committee of [Anonymous] University.

Measures

Predictor variables: Political dispositions and political ideology

RWA was assessed using 10 items based on the Hungarian adaptation of the RWA Scale by Enyedi (2004) and Fábián (1999), originally developed by Altemeyer (1981). An example item is, ‘It is always better to trust the judgment of the proper authorities in government and religion than to listen to the noisy rabble-rousers in our society, who are trying to create doubt in people’s minds’.

SDO was assessed using the 16-item SDO7 scale (Ho et al., 2015), adapted to Hungarian by Faragó & Kende (2017). An example item is, ‘We should not push for group equality’.

GSJ was assessed using the eight-item GSJ Scale (Jost et al., 2003), adapted to Hungarian by Berkics (2009). An example item is ‘In general, you find the Hungarian society to be fair’.

ESJ was measured using the 17-item ESJ Scale (Jost & Thompson, 2000), translated into Hungarian by Jost and Kende (2020). An example item is ‘If people work hard, they almost always get what they want’.

Liberal-conservative ideological self-placement was assessed using three items: ‘In political/economic/societal-cultural matters, people sometimes talk about conservatives and liberals. How would you generally describe your views on this scale?’

Items for RWA, SDO, and liberal-conservative self-placement were rated on 7-point scales from ‘strongly disagree’/‘extremely liberal’ to ‘strongly agree’/‘extremely conservative’. For ESJ and GSJ, 9-point scales from ‘strongly disagree’ to ‘strongly agree’ were used. Indexes for these variables were calculated by averaging the scores of all respective items.

Outcome variables

Generic scales assessing mental illness-associated stigma

The Attitudes Toward Mental Illness (AMIS; Kobau et al., 2010) is a 7-item scale designed to measure two subscales of mental health stigma: negative stereotypes associated with mental illnesses (AMIS-1; ‘I believe a person with mental illness is a danger to others’), and beliefs about recovery (AMIS-2; ‘I believe a person with mental illness can eventually recover’).

Participants’ openness to future interactions with individuals who have mental health problems was assessed using a 4-item version of the Reported and Intended Behavior Scale (RIBS; Evans-Lacko et al., 2011). An example of an item is ‘In the future, I would be willing to work with someone with a mental health problem’.

Items were assessed using 5-point scales, ranging from ‘strongly disagree’ to ‘strongly agree’. Indexes for these variables were calculated by averaging the scores of all respective items. Positively worded items were recoded so that index scores reflect negative stereotypes and behavioral intentions.

Specific measures assessing stigma related to specific mental illnesses

After reading each vignette, participants’ attitudes toward the individuals depicted with a specific mental illness (namely schizophrenia, depression, and AUD) were assessed using various measures. These included assessments of social distance, support for structural discrimination, and the belief in a continuum of symptom experience.

Desire for social distance was assessed using five items based on Link et al. (1999). An example of an item is ‘How willing would you be to move next door to the person depicted in the vignette?’

Support for structural discrimination of the target person was measured with two items: ‘If the person in the vignette does not consent to medical treatment, he should receive compulsory treatment’ and ‘The person in the vignette should not be allowed to have a driving license’ (Schomerus et al., 2019).

Belief in a continuum of symptom experience was assessed with two items: ‘Basically, we are all sometimes like the target person, it is just a question of how pronounced this state is’ and ‘To some extent, everyone experiences similar problems as the target person’ (Schomerus et al., 2013).

Each Likert item, following the vignettes, was rated on a 5-point scale, and responses were recoded so that higher values indicate a greater desire for social distance, more support for structural discrimination, and less belief in a continuum of symptom experience.

Control variables: Demographic variables

We collected demographic data, including age (continuous), gender (dichotomous: 0 for male, 1 for female), educational level (four response options from ‘unfinished primary school’ to ‘completed master’s/Ph.D.’), and SES (four response options from ‘serious financial troubles’ to ‘money for everything’). In the linear regression analyses, we controlled for the effects of age, gender, and SES (educational level was excluded due to high homogeneity). SES was simplified to a dichotomous variable, with 0 representing low and very low SES, and 1 representing high and very high SES.

Data analysis

The statistical analysis was conducted using IBM SPSS 25.00 (IBM Corporation, Chicago, 2017). Initially, we explored zero-order correlations between study variables. We then conducted multiple linear regression models, with political dispositions and ideology as predictors and indicators of mental health stigma as dependent variables.

We controlled for age, gender, and SES in our models. To address the risk of Type I error inflation from multiple comparisons, we applied the Bonferroni correction, adjusting our alpha level. This resulted in a corrected p-value threshold of .0008 (.05 divided by 60) for analyses without demographic covariates, and .0005 (.05 divided by 96) for analyses with demographic covariates.

Results

Descriptive analysis

Table 1 presents descriptive statistics, reliability estimates, and Pearson correlations for study variables.

Table 1.

Descriptive statistics, correlation coefficients, and reliability measures for study variables.

Variables	1.	2.	3.	4.	5.	6.	7.	8.	9.	10.	11.	12.	13.	14.	15.	16.	17.
1. RWA	–	0.49**	0.52**	0.39**	0.54**	0.28**	0.25**	0.42**	0.42**	0.44**	0.02	0.41**	0.27**	−0.06	0.35**	0.28**	−0.03
2. SDO		–	0.45**	0.67**	0.44**	0.22*	0.23**	0.33**	0.32**	0.27**	0.03	0.34**	0.23**	−0.06	0.27**	0.15**	−0.06
3. GSJ			–	0.57**	0.47**	0.13**	0.14**	0.20**	0.23**	0.21**	0.09*	0.17**	0.08	−0.06	0.10*	0.06	−0.05
4. ESJ				–	0.37**	0.23**	0.16**	0.21**	0.21**	0.23**	−0.01	0.22**	0.17**	−0.05	0.17**	0.07	−0.06
5. LibCons					–	0.32**	0.19**	0.35**	0.37**	0.27**	0.09*	0.32**	0.23**	−0.01	0.28**	0.18**	0.06
General mental health stigma
6. AMIS-1						–	0.30**	0.47**	0.33**	0.31**	0.05	0.43**	0.34**	0.21**	0.30**	0.20**	0.13**
7. AMIS-2							–	0.54**	0.40**	0.20**	0.12**	0.39**	0.16**	0.13**	0.31**	0.07	0.10*
8. RIBS								–	0.64**	0.34**	0.10*	0.66**	0.30**	0.12**	0.51**	0.21**	0.08
Vignette – Depression
9. Social distance									–	0.40**	0.28**	0.70**	0.25**	0.12**	0.55**	0.24**	0.11*
10. Structural disc										–	0.15**	0.34**	0.47**	−0.01	0.28**	0.49**	0.04
11. Continuum beliefs											–	0.14**	0.07	0.33**	0.11*	0.06	0.31**
Vignette – Schizophrenia
12. Social distance												–	0.46**	0.28**	0.65**	0.27**	0.15**
13. Structural disc													–	0.23**	0.27**	0.47**	0.04
14. Continuum beliefs														–	0.14**	0.03	0.44**
Vignette – alcohol use disorder
15. Social distance															–	0.43**	0.34**
16. Structural disc																–	0.18**
17. Continuum beliefs																	–
M	2.63	2.88	3.38	4.13	2.70	3.03	2.03	2.49	2.24	2.19	2.19	3.29	3.26	4.17	3.49	3.30	3.84
SD	1.09	1.02	1.50	1.08	0.86	0.85	0.71	0.96	0.92	0.97	0.99	1.08	1.07	0.98	1.00	1.06	1.07
Cronbach’s α	0.84	0.89	0.84	0.79	0.82	0.74	0.69	0.84	0.89	–	–	0.92	–	–	0.89	–	–

Notes. *p < .05. **p < .01. RWA = Right-Wing Authoritarianism; SDO = Social Dominance Orientation; GSJ = General System Justification; ESJ = Economic System Justification; LibCons = Liberal-Conservative Self-Placement; AMIS-1 = Attitudes Toward Mental Illness and its treatment scale negative stereotypes; AMIS-2 = Attitudes Toward Mental Illness and its Treatment Scale Recovery (reverse-coded); RIBS = openness to future interactions with individuals who have mental health problems (reverse-coded); Social Distance = desire for social distance; Structural Disc = support for structural discrimination; Continuum Beliefs = belief in a continuum of symptom experience (reverse-coded).

A moderate positive correlation exists among political dispositions and ideology measures, indicating they share a psychological basis but are distinct constructs. RWA, SDO, and conservatism were associated with stigma related to mental illnesses, except disbelief in a continuum of symptom experience. Higher scores on these scales were correlated with negative stereotypes, reduced optimism about recovery, and an increased desire for social distance, showing a pattern of reluctance to engage with individuals with mental health problems generally, and schizophrenia, depression, or AUD specifically. Additionally, there was a greater willingness to support structural discrimination.

The correlations between GSJ and ESJ with mental health stigma were less consistent. Although there were significant correlations with some stigma indicators, these were generally weak. Furthermore, many indicators of mental health stigma showed non-significant correlations with both forms of system justification.

Interestingly, the strengths of the correlations between various indices of mental health stigma varied considerably. Measures of social distance tended to be moderately or highly correlated with each other across mental health issues. Specifically, individuals who desired distance from one form of mental health issue also tended to desire distance from individuals with other types of mental health issues. However, measures of support for structural discrimination and (dis)belief in a continuum of symptom experience had lower correlations across different mental health issues and with measures of social distance.

Main analysis

We conducted regression analyses to identify the key political dispositions and ideologies underlying mental health-related stigma. The dependent variables were regressed on political and demographic measures. Results, presented without covariates in Table 2 and with covariates in Supplemental Table S1, show RWA’s significant association with most outcomes, highlighting its critical role in shaping mental health stigma.

Table 2.

Results of regression analysis with political dispositions and ideologies as predictors and mental health-related stigma as outcomes.

General mental health stigma
Variables	DV1: AMIS-1				DV2: AMIS-2				DV3: RIBS
	B	SE	B 95% CI	p	B	SE	B 95% CI	p	B	SE	B 95% CI	p
RWA	0.15	0.04	0.07, 0.24	.0006	0.11	0.04	0.04, 0.19	.0037	0.27	0.05	0.17, 0.36	<.0001
SDO	−0.04	0.05	−0.14, 0.06	.4239	0.10	0.05	0.01, 0.19	.0255	0.16	0.06	0.05, 0.27	.0055
GSJ	−0.10	0.03	−0.17, −0.04	.0021	−0.02	0.03	−0.07, 0.04	.5399	−0.06	0.04	−0.13, 0.01	.0944
ESJ	0.16	0.05	0.06, 0.26	.0014	0.00	0.04	−0.09, 0.08	.9666	−0.03	0.05	−0.14, 0.08	.5789
Ideology	0.25	0.05	0.14, 0.35	<.0001	0.05	0.05	−0.04, 0.14	.3063	0.20	0.06	0.08, 0.31	.0006
Model	R² = 0.15, F (5, 478) = 16.705, p < .0001				R² = 0.08, F (5, 478) = 8.600, p < .0001				R² = 0.22, F (5, 478) = 26.142, p < .0001
Vignette – Depression
	DV4: Social distance				DV5: Structural discrimination				DV6: Continuum beliefs
	B	SE	B 95% CI	p	B	SE	B 95% CI	p	B	SE	B 95% CI	p
RWA	0.25	0.05	0.16, 0.34	<.0001	0.39	0.05	0.29, 0.48	<.0001	−0.09	0.06	−0.20, 0.02	.1206
SDO	0.13	0.05	0.02, 0.23	.0201	0.00	0.06	−0.11, 0.11	.9635	0.05	0.07	−0.07, 0.18	.4099
GSJ	−0.04	0.03	−0.10, 0.03	.2825	−0.06	0.04	−0.13, 0.01	.0800	0.09	0.04	0.01, 0.17	.0275
ESJ	−0.03	0.05	−0.13, 0.08	.6137	0.10	0.05	−0.01, 0.21	.0607	−0.11	0.06	−0.24, 0.01	.0665
Ideology	0.20	0.06	0.09, 0.30	.0004	0.04	0.06	−0.08, 0.15	.5158	0.12	0.07	−0.01, 0.25	.0705
Model	R² = 0.22, F (5, 478) = 26.279, p < .0001				R² = 0.21, F (5, 478) = 25.593, p < .0001				R² = 0.02, F (5, 478) = 2.274, p = .0462
Vignette – Schizophrenia
	DV7: Social distance				DV8: Structural discrimination				DV9: Continuum beliefs
	B	SE	B 95% CI	p	B	SE	B 95% CI	p	B	SE	B 95% CI	p
RWA	0.31	0.05	0.20, 0.41	<.0001	0.21	0.06	0.10, 0.32	.0002	−0.06	0.06	−0.16, 0.05	.3136
SDO	0.22	0.06	0.09, 0.34	.0006	0.12	0.07	−0.02, 0.25	.0837	−0.04	0.06	−0.17, 0.09	.5277
GSJ	−0.11	0.04	−0.19, −0.04	.0043	−0.13	0.04	−0.22, −0.05	.0016	−0.03	0.04	−0.11, 0.05	.4534
ESJ	0.00	0.06	−0.12, 0.12	.9722	0.07	0.06	−0.06, 0.20	.2734	0.01	0.07	−0.06, 0.19	.8192
Ideology	0.18	0.06	0.05, 0.30	.0062	0.15	0.07	0.02, 0.28	.0244	0.06	0.07	−0.06, 0.19	.3345
Model	R² = 0.21, F (5, 478) = 26.099, p < .0001				R² = 0.11, F (5, 478) = 11.590, p < .0001				R² = 0.01, F (5, 478) = 0.811, p = .5424
Vignette – Alcoholism
	DV10: Social distance				DV11: Structural discrimination				DV12: Continuum beliefs
	B	SE	B 95% CI	p	B	SE	B 95% CI	p	B	SE	B 95% CI	p
RWA	0.26	0.05	0.16, 0.36	<.0001	0.30	0.06	0.18, 0.41	<.0001	−0.04	0.06	−0.16, 0.08	.4742
SDO	0.14	0.06	0.03, 0.26	.0181	0.04	0.07	−0.09, 0.17	.5147	−0.06	0.07	−0.20, 0.08	.3768
GSJ	−0.14	0.04	−0.21, −0.07	.0003	−0.11	0.04	−0.19, −0.02	.0116	−0.05	0.04	−0.13, 0.04	.2809
ESJ	0.02	0.06	−0.10, 0.13	.7587	−0.02	0.06	−0.14, 0.11	.8010	−0.02	0.07	−0.15, 0.11	.7891
Ideology	0.18	0.06	0.06, 0.30	.0036	0.09	0.07	−0.05, 0.22	.1986	0.19	0.07	0.05, 0.33	.0080
Model	R² = 0.16, F (5, 478) = 18.80, p < .0001				R² = 0.09, F (5, 478) = 9.853, p < .0001				R² = 0.02, F (5, 478) = 1.866, p = .0987

Notes. B: Unstandardized regression coefficient. Bonferroni-corrected p = .0008. RWA = Right-Wing Authoritarianism; SDO = Social Dominance Orientation; GSJ = General System Justification; ESJ = Economic System Justification; Ideology = liberal-conservative self-placement; AMIS-1 = Attitudes Toward Mental Illness and its treatment scale negative stereotypes; AMIS-2 = Attitudes Toward Mental Illness and its treatment scale recovery (reverse-coded); RIBS = openness to future interactions with individuals who have mental health problems (reverse-coded); Social Distance = desire for social distance; Structural Disc = support for structural discrimination; Continuation = belief in a continuum of symptom experience (reverse-coded). The results are virtually identical when controlling for demographic variables (gender, age, SES, see Supplemental Table S1).

Conservative political ideology had a more selective impact, significantly predicting negative stereotypes related to mental illnesses in general, as well as the desire for social distance from individuals exhibiting symptoms of mental illness in general and specifically from those with symptoms of depression, schizophrenia, and AUD. The other predictors – GSJ, ESJ, and SDO – largely failed to predict outcomes, suggesting minimal contributions beyond RWA to mental health stigma.

Discussion

Our study aimed to conceptually replicate and extend research on the role of political dispositions and ideology in mental health stigma. First, we sought to replicate findings from the U.S. and Sweden indicating that RWA predicts mental health stigma (DeLuca & Yanos, 2016; DeLuca et al., 2018; Löve et al., 2019). Secondly, we aimed to expand upon these findings. Previous research in this context has focused mainly on RWA and self-reported political ideology or affiliation. By including a wider array of measures, we intended to explore whether other belief systems associated with a politically conservative ideology could add to our understanding of the processes underlying mental health stigma.

The concepts that we studied, RWA, SDO, and system as well economic justification, could, in theory, have been expected to be associated with mental health stigma through different processes. An association between RWA and stigma could be due to the perceived dangers associated with mental health issues. On the other hand, an association between SDO and stigma would indicate the importance of distancing oneself from perceived subordinate groups. In turn, those who believe in the (economic) system could be expected to blame individuals for their misfortunes. Finally, those who identify as conservative, with its emphasis on the status quo, norms, uniformity, and homogeneity, may dislike those who deviate from and thereby perhaps question standards of ‘normality’.

Our study compared the above dispositions and ideologies as predictors of various types of mental health stigma in Hungary, a novel context for this type of research. Hungary’s high prevalence of mental illness, significant stigma against mental health patients (Buchman-Wildbaum et al., 2018; European Commission, 2023; Krupchanka & Winkler, 2016), and the dominance of right-wing ideologies (Bíró-Nagy et al., 2022; Lönnqvist et al., 2021; Várnagy, 2023) present a unique backdrop for examining how individual political orientations influence mental health stigma. Given both the strength of mental health stigma and right-wing ideologies, one could have expected stigma to be normalized to the degree that there would be little if any room for the explanatory power of individual differences. Hungary was, in this respect, a setting that allowed for a hard test of the notion that what people think regarding political and social questions can help understand mental health stigma. Our results suggest that even in this context, individual differences in political dispositions, RWA in particular, can help understand a wide range of stigmas associated with various mental health issues. These findings corroborate previous research from the U.S. and Sweden, providing evidence for the replicability of these results across very different types of national contexts.

Although individual-level results cannot be generalized to explain group (or country) level phenomena, our results suggest that a political leadership that has built its electoral success on protecting the normative Hungarian way of life from, for instance, the liberal financial elite and foreign intelligence agencies, who have allegedly tried to impose for instance, forced immigration and an LGBQT agenda (Szabó, 2020), may have created a mass public that fears everything ‘other’, including people with mental health issues, Hungary has very low levels of help-seeking behavior, inadequate professional support for mental health issues, and the pervasive perception of differential treatment of mental health patients (European Commission, 2023). If, as our results suggest, RWA –characterized by fear of the dangerous other – influences mental health stigma, then the Hungarian leadership may have successfully cultivated an electorate fearful of all that is not ‘normal’.

Concepts like ‘Otherness’ and ‘Othering’ have become influential in explaining not only stigma and racism but also the perpetuation of social injustices. The governing party’s framing of the majority ingroup as hegemonically normative and minority outgroups as alien (Bhugra et al., 2023) can embed harmful institutional patterns within policies, laws, and social practices (Akbulut & Razum, 2022). Othering legitimizes disadvantageous institutional structures and social practices and is structurally embedded in power and representation discourse (Akbulut & Razum, 2022). Discrimination and stigmatization of individuals with mental health issues may be by-products of constructing the ‘Other’ (Bhugra et al., 2023). Such social identity formulations and related national policies significantly influence beliefs about people with mental illnesses, such as perceived dangerousness, as evidenced by a study of U.S. public view trends from 1996 to 2018 (Pescosolido et al., 2019).

Understanding the role of perceived threat in mental health stigma is key to developing effective interventions in Hungary. This perception may explain why individuals with symptoms of schizophrenia and AUD, often linked to danger, face greater stigma than those with depression, seen as less threatening (Kilian et al., 2021; Mannarini & Boffo, 2015; Marie & Miles, 2008; Penn et al., 1999). Although similar differences were found in a study employing U.S. samples (Pescosolido et al., 2019), depression may also be seen as more normative in Eastern Europe where general life satisfaction is lower (Djankov et al., 2016).

Mental health stigma reduction programs often focus, understandably, on the targets of stigma, and concentrate on micro-level factors to improve conditions for people living with mental illness. These interventions typically employ strategies of education contact, or a combination of both, to mitigate stigma, both among those directly and indirectly affected (Corrigan et al., 2001; Gronholm et al., 2017; Morgan et al., 2018). Recent research, however, has expanded our understanding of stigma, with Tyler and Slater (2018) emphasizing its use as a tool for social control through political and cultural power, and Kapadia (2023) advocating for recognizing its structural dimensions. Our findings support the notion that interventions should not only focus on those directly experiencing stigma but also address individuals and the broader context that perpetuates it. While acknowledging the benefit of education and social contact, our research, in conjunction with other studies (Kapadia, 2023; Kohrt et al., 2018; Tyler & Slater, 2018), highlights the complex connections between macro-level political ideologies and micro-level perceptions of threat. This complex web of influences suggests that stigma reduction efforts need to be multifaceted, addressing both individual attributes and the larger societal and political structures that sustain them.

While advocating for broad societal changes in response to mental health issues might seem overly ambitious, acknowledging the influence of political dispositions and ideologies on mental health stigma is crucial. Interventions should target the core concerns of those stigmatizing others, including the perceived threats posed by mental illnesses. Future research should aim to identify exactly ‘what is at stake’ (Yang et al., 2014); that is, why do people feel threatened, and explore ways to alleviate perceived threats posed by non-conventional identities.

Limitations and strengths

The study has several limitations. First, the study does not allow for causal inferences. Causal pathways are seldom if ever possible to identify in survey studies (for an excellent discussion on the role that colliders, confounders, and mediators can play in any results, see Wysocki et al., 2022). Secondly, our sample, being relatively well-educated and middle-class, might not accurately represent the general Hungarian population, possibly affecting the generalizability of our findings. The impact of SDO and system justification could vary across different socioeconomic groups. Thirdly, all vignette subjects were male. Some research has shown that gender-typical disorders (e.g. a male with AUD) might be targets of harsher stigma; such cases may be less likely to be perceived as genuine mental disturbances (Wirth & Bodenhausen, 2009). Future research should collect a more diverse sample in terms of education and socioeconomic status and consider the target person’s gender as a potential moderator in the associations between political ideology and stigma.

The study’s strengths include the simultaneous investigation of multiple indicators of political ideology as determinants of a broad spectrum of stigma outcomes. Conducted in an understudied context in which mental health stigma is both very prevalent and a significant barrier to utilizing professional mental health services, this research may offer both theoretical and practical insights. Importantly, our findings indicate that perceived danger, threat, and unconventionality, as indicated by RWA – not derogation indicated by SDO nor belief in an (economically) just system – are key in mental health stigmatization. This is what intervention programs should target. This research is particularly relevant for researchers and practitioners in contexts with dominant right-wing conservative ideologies and strong hostility toward non-conventional identities.

Supplemental Material

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Supplemental material, sj-docx-2-isp-10.1177_00207640241267803 for Right-wing authoritarianism, social dominance, system justification, and conservative political ideology as predictors of mental health stigma: The Hungarian case by Zsolt Péter Szabó, Jan-Erik Lönnqvist, Nóra Anna Lantos and Jussi Valtonen in International Journal of Social Psychiatry

Research Data

sj-sav-1-isp-10.1177_00207640241267803 – for Right-wing authoritarianism, social dominance, system justification, and conservative political ideology as predictors of mental health stigma: The Hungarian case

sj-sav-1-isp-10.1177_00207640241267803 for Right-wing authoritarianism, social dominance, system justification, and conservative political ideology as predictors of mental health stigma: The Hungarian case by Zsolt Péter Szabó, Jan-Erik Lönnqvist, Nóra Anna Lantos and Jussi Valtonen in International Journal of Social Psychiatry

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Footnotes

Acknowledgements

The authors would like to thank all participants involved in the study.

Conflict of interest

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

Compliance with ethical standards

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional research committee and with the 1964 Declaration of Helsinki and its later amendments or comparable ethical standards.

ORCID iD

Zsolt Péter Szabó

Data availability statement

The data analyzed in this study are included with the manuscript.

Supplemental material

Supplemental material for this article is available online.

References

Akbulut

Razum

(2022). Why Othering should be considered in research on health inequalities: Theoretical perspectives and research needs. SSM – Population Health, 20, 101286. https://doi.org/10.1016/j.ssmph.2022.101286

Altemeyer

(1981). Right-wing authoritarianism. Winnipeg: University of Manitoba Press.

Altemeyer

R. A.

(2006). The authoritarians. Winnipeg, Canada: University of Manitoba Press.

Angermeyer

M. C.

Schomerus

(2017). State of the art of population-based attitude research on mental health: A systematic review. Epidemiology and Psychiatric Sciences, 26, 252–264. https://doi.org/10.1017/S2045796016000627

Balint

Fuzer

Gonda

Dome

(2020). Estimation of the relationship between the persistent decrease of the suicide rate and the changes in sociodemographic composition in Hungary between 1990 and 2011. PLos One, 15, e0241314. https://doi.org/10.1371/journal.pone.0241314

Bauer

P. C.

Barberá

Ackermann

Venetz

(2017). Is the left-right scale a valid measure of ideology? Individual-level variation in associations with ‘left’ and ‘right’ and left-right self-placement. Political Behavior, 39, 553–583. https://doi.org/10.1007/s11109-016-9368-2

Berkics

(2009). A disztributív igazságosság észlelése és a rendszerigazolás: kultúrközi összehasonlítás két volt szocialista országban. [Perceptions of distributive justice and system justification: A cross-cultural comparison of two post-socialist countries.] Magyar Pszichológiai Szemle, 64, 229–252.

Bhugra

Smith

Liebrenz

Ventriglio

Gnanapragasam

S. N.

Buadze

Pemberton

Poulter

(2023). ‘Otherness’, otherism, discrimination, and health inequalities: Entrenched challenges for modern psychiatric disciplines. International Review of Psychiatry, 35, 234–241. https://doi.org/10.1080/09540261.2023.2192275

Bíró-Nagy

Szászi

Á.

Varga

(2022). Divided Hungary: Political polarization of the Hungarian society. Policy Solutions. https://www.policysolutions.hu/userfiles/Polcy_Solutions_Divided_Hungary_2022_EN.pdf

10.

Buchman-Wildbaum

Paksi

Sebestyén

Kun

Felvinczi

Schmelowszky

Á.

Griffiths

M. D.

Demetrovics

Urbán

(2018). Social rejection towards mentally ill people in Hungary between 2001 and 2015: Has there been any change?. Psychiatry Research, 267, 73–79.

11.

Corrigan

P. W.

River

L. P.

Lundin

R. K.

Penn

D. L.

Uphoff-Wasowski

Campion

Mathisen

Gagnon

Bergman

Goldstein

Kubiak

M. A.

(2001). Three strategies for changing attributions about severe mental illness. Schizophrenia Bulletin, 27, 189–195. https://doi.org/10.1093/oxfordjournals.schbul.a006865

12.

DeLuca

J. S.

Yanos

P. T.

(2016). Managing the terror of a dangerous world: Political attitudes as predictors of mental health stigma. International Journal of Social Psychiatry, 62, 21–30. https://doi.org/10.1177/0020764015589131

13.

DeLuca

J. S.

Vaccaro

Seda

Yanos

P. T.

(2018). Political attitudes as predictors of the multiple dimensions of mental health stigma. International Journal of Social Psychiatry, 64, 459–469. https://doi.org/10.1177/00207640187763

14.

Djankov

Nikolova

Zilinsky

(2016). The happiness gap in Eastern Europe. Journal of Comparative Economics, 44, 108–124. https://doi.org/10.1016/j.jce.2015.10.006

15.

Duckitt

Wagner

Du Plessis

Birum

(2002). The psychological bases of ideology and prejudice: Testing a dual process model. Journal of Personality and Social Psychology, 83, 75–93. https://doi.org/10.1037/0022-3514.83.1.75

16.

Enyedi

(2004). A voluntarizmus tere: A pártok szerepe a törésvonalak kialakulásában. [The field of voluntarism: The role of parties in the formation of cleavages]. Századvég, 33, 3–27.

17.

Enyedi

Krekó

(2018). Explaining Eastern Europe: Orbán’s laboratory of illiberalism. Journal of Democracy, 29, 39–51. https://doi.org/10.1353/jod.2018.0043

18.

European Commission. (2023). Flash Eurobarometer 530. Mental health report. https://www.europa.eu/eurobarometer/surveys/detail/3032

19.

Evans-Lacko

Rose

Little

Flach

Rhydderch

Henderson

Thornicroft

(2011). Development and psychometric properties of the Reported and Intended Behaviour Scale (RIBS): A stigma-related behaviour measure. Epidemiology and Psychiatric Sciences, 20, 263–271. https://doi.org/10.1017/S2045796011000308

20.

Fábián

(1999). Tekintélyelvűség és előítéletek. [Authoritarianism and prejudice]. Budapest: Új Mandátum.

21.

Faragó

Kende

(2017). Az elnyomás támogatása vagy az egyenlőség ellenzése? Az Új Szociális Dominancia Orientáció Skála (SDO7) vizsgálata. [Support for dominance or opposition to equality? The examination of the new Social Dominance Orientation Scale (SD7)]. Alkalmazott Pszichológia, 17, 115–135.

22.

Faul

Erdfelder

Buchner

Lang

A.-G.

(2009). Statistical power analyses using G*Power 3.1: Tests for correlation and regression analyses. Behavior Research Methods, 41, 1149–1160. https://doi.org/10.3758/BRM.41.4.1149

23.

Gronholm

P. C.

Henderson

Deb

Thornicroft

(2017). Interventions to reduce discrimination and stigma: The state of the art. Social Psychiatry and Psychiatric Epidemiology, 52, 249–258. https://doi.org/10.1007/s00127-017-1341-9

24.

Hadarics

Kende

(2018). The dimensions of generalized prejudice within the dual-process model: The mediating role of moral foundation. Current Psychology: A Journal for Diverse Perspectives on Diverse Psychological Issues, 37, 731–739. https://doi.org/10.1007/s12144-016-9544-x

25.

A. K.

Sidanius

Kteily

Sheehy-Sheffington

Pratto

Henkel

K. E.

Foels

Stewart

A. L.

(2015). The nature of social dominance orientation: Theorizing and measuring preferences for intergroup inequality using the new SDO7 scale. Journal of Personality and Social Psychology, 109, 1003–1028. https://doi.org/10.1037/pspi0000033

26.

Jost

J. T.

(2021). Left and right: The psychological significance of a political distinction. New York: Oxford University Press.

27.

Jost

J. T.

Federico

C. M.

Napier

J. L.

(2009). Political ideology: Its structure, functions, and elective affinities. Annual Review of Psychology, 60, 307–333. https://doi.org/10.1146/annurev.psych.60.110707.163600

28.

Jost

J. T.

Glaser

Kruglanski

A. W.

Sulloway

F. J.

(2003). Political conservatism as motivated social cognition. Psychological Bulletin, 129, 339–375. https://doi.org/10.1037/0033-2909.129.3.339

29.

Jost

J. T.

Kende

(2020). Setting the record straight: System justification and rigidity-of-the-right in contemporary Hungarian politics. International Journal of Psychology, 55, 96–115. https://doi.org/10.1002/ijop.12631

30.

Jost

J. T.

Thompson

E. P.

(2000). Group-based dominance and opposition to equality as independent predictors of self-esteem. Ethnocentrism, and social policy attitudes among African Americans and European Americans. Journal of Experimental Social Psychology, 36, 209–232. https://doi.org/10.1006/jesp.1999.1403

31.

Kapadia

(2023). Stigma, mental illness & ethnicity: Time to centre racism and structural stigma. Sociology of Health & Illness, 45, 855–871. https://doi.org/10.1111/1467-9566.13615

32.

Kilian

Manthey

Carr

Hanschmidt

Rehm

Speerforck

Schomerus

(2021). Stigmatization of people with alcohol use disorders: An updated systematic review of population studies. Alcoholism: Clinical and Experimental Research, 45, 899–911. https://doi.org/10.1111/acer.14598

33.

Kivikangas

J. M.

Fernández-Castilla

Järvelä

Ravaja

Lönnqvist

J.-E.

(2021). Moral foundations and political orientation: Systematic review and meta-analysis. Psychological Bulletin, 147, 55–94. https://doi.org/10.1037/bul0000308

34.

Kobau

Dilorio

Chapman

Delvecchio

; SAMHSA/CDC Mental Illness Stigma Panel Members. (2010). Attitudes about mental illness and its treatment: Validation of a generic scale for public health surveillance of mental illness associated stigma. Community Mental Health Journal, 46, 164–176. https://doi.org/10.1007/s10597-009-9191-x

35.

Kohrt

B. A.

Jordans

M. J. D.

Turner

E. L.

Sikkema

K. J.

Luitel

N. P.

Rai

Singla

D. R.

Lamichhane

Lund

Patel

(2018). Reducing stigma among healthcare providers to improve mental health services (RESHAPE): Protocol for a pilot cluster randomized controlled trial of a stigma reduction intervention for training primary healthcare workers in Nepal. Pilot and Feasibility Studies, 4, 36. https://doi.org/10.1186/40814-018-0234-3

36.

Krupchanka

Winkler

(2016). State of mental healthcare systems in Eastern Europe: Do we really understand what is going on? BJPsych International, 13, 96–99. https://doi.org/10.1192/S2056474000001446

37.

Kvaale

E. P.

Haslam

(2016). Motivational orientations and psychiatric stigma: Social motives influence how causal explanations relate to stigmatizing attitudes. Personality and Individual Differences, 89, 111–116. https://doi.org/10.1016/j.paid.2015.09.044

38.

Lampropoulos

Chatzigianni

Chryssochoou

Apostolidis

(2021). Ideology and the stigma of schizophrenia: Applying the dual-process motivational model in the French and Greek contexts. Journal of Community & Applied Social Psychology, 31, 326–340. https://doi.org/10.1002/casp.2503

39.

Link

B. G.

Phelan

Bresnahan

Stueve

Pescosolido

B. A.

(1999). Public conceptions of mental illness: Labels, causes, dangerousness, and social distance. American Journal of Public Health, 89, 1328–1333. https://doi.org/10.2105/ajph.89.9.1328

40.

Lönnqvist

J.-E.

Szabó

Z. P.

Kelemen

(2021). ‘The new state that we are building’: Authoritarianism and system-justification in an illiberal democracy. Frontiers in Psychology, 12, 703280. https://doi.org/10.3389/fpsyg.2021.703280

41.

Löve

Bertilsson

Martinsson

Wängnerud

Hensing

(2019). Political ideology and stigmatizing attitudes toward depression: The Swedish case. International Journal of Health Policy and Management, 8, 365–274. https://doi:10.15171/ijhpm.2019.15

42.

Mannarini

Boffo

(2015). Anxiety, bulimia, drug and alcohol addiction, depression, and schizophrenia: What do you think about their aetiology, dangerousness, social distance, and treatment? A latent class analysis approach. Social Psychiatry and Psychiatric Epidemiology, 50, 27–37. https://doi.org/10.1007/00127-014-0925-x

43.

Marie

Miles

(2008). Social distance and perceived dangerousness across four diagnostic categories of mental disorder. Australian & New Zealand Journal of Psychiatry, 42, 126–133. https://doi.org/10.1080/00048670701787545

44.

Mihailovic

Szöllősi

G. J.

Rancic

János

Boruzs

Nagy

A. C.

Timofeyev

Dragojevic-Simic

Antunovic

Reshetnikov

Ádány

Jakovljevic

(2020). Alcohol consumption among the elderly citizens in Hungary and Serbia – comparative assessment. International Journal of Environmental Research and Public Health, 17, 1289. https://doi.org/10.3390/ijerph17041289

45.

Morgan

A. J.

Reavley

N. J.

Ross

Too

L. S.

Jorm

A. F.

(2018). Interventions to reduce stigma towards people with severe mental illness: Systematic review and meta-analysis. Journal of Psychiatric Research, 103, 120–133. https://doi.org/10.1016/j.jpsychires.2018.05.017

46.

Penn

D. L.

Kommana

Mansfield

Link

B. G.

(1999). Dispelling the stigma of schizophrenia: II. The impact of information on dangerousness. Schizophrenia Bulletin, 25, 437–466. https://doi.org/10.1093/oxfordjournals.schbul.a033391

47.

Pescosolido

B. A.

Manago

Monahan

(2019). Evolving public views on the likelihood of violence from people with mental illness: Stigma and its consequences. Health Affairs, 38, 1735–1743. https://doi.org/10.1377/hlthaff.2019.00702

48.

Pescosolido

B. A.

Martin

J. K.

(2015). The stigma complex. Annual Review of Sociology, 41, 2201–2230. https://doi:10.1146/annurev-soc-071312-145702

49.

Piurko

Schwartz

S. H.

Davidov

(2011). Basic personal values and the meaning of left-right political orientations in 20 countries. Political Psychology, 32, 537–561. https://doi.org/10.1111/j.1467-9221.2011.00828.x

50.

Pratto

Sidanius

Stallworth

L. M.

Malle

B. F.

(1994). Social dominance orientation: A personality variable predicting social and political attitudes. Journal of Personality and Social Psychology, 67, 741–763. https://doi.org/10.1037/0022-3514.67.4.741

51.

Ragsdale

J. M.

Elliott

(2022). Opioid addiction, attributions, and stigma: An online vignette experimental study. Stigma and Health, 7, 205–213. https://doi.org/10.1037/sah0000374

52.

Scheff

T. J.

(2017). Being mentally ill: A sociological study. Routledge.

53.

Schomerus

Matschinger

Angermeyer

M. C.

(2013). Continuum beliefs and stigmatizing attitudes towards persons with schizophrenia, depression and alcohol dependence. Psychiatry Research, 209, 665–669. https://doi.org/10.1016/j.psychres.2013.02.006

54.

Schomerus

Stolzenburg

Freitag

Speerfock

Janowitz

Evans-Lacko

Muehlan

Schmidt

(2019). Stigma as a barrier to recognizing personal mental illness and seeking help: A prospective study among untreated persons with mental illness. European Archives of Psychiatry and Clinical Neuroscience, 269, 469–479. https://doi.org/10.1007/s00406-018-0896-0

55.

Sniderman

P. M.

Bullock

(2004). A consistency theory of public opinion and political choice: The hypothesis of menu dependence. In Saris

W. E.

Sniderman

P. M.

(Eds.), Studies in public opinion (pp. 337–357). Princeton University Press.

56.

Szabó

(2020). First as tragedy, then as farce: A comparative study of right-wing populism in Hungary and Poland. Journal of Comparative Politics, 13, 24–42. https://www.proquest.com/docview/2416506379?pq-origsite=gscholar&fromopenview=true

57.

Tyler

Slater

(2018). Rethinking the sociology of stigma. The Sociological Review, 66, 721–743. https://doi.org/10.1177/0038026118777425

58.

Várnagy

(2023). Hungary: Political developments and data in 2022: The tumultuous year of the status quo. European Journal of Political Research Political Data Yearbook, 62(1), 213–229. https://doi.org/10.1111/2047-8852.12426

59.

Wirth

J. H.

Bodenhausen

G. V

. (2009). The role of gender in mental-illness stigma: A national experiment. Psychological Science, 20(2), 169–173. https://doi.org/10.1111/j.1467-9280.2009.02282.x

60.

Wunsch

Gessler

(2023). Who tolerates democratic backsliding? A mosaic approach to voters’ response to authoritarian leadership in Hungary. Democratization, 5, 914–937. https://doi.org/10.1080/13510347.2023.2203918

61.

Wysocki

A. C.

Lawson

K. M.

Rhemtulla

(2022). Statistical control requires causal justification. Advances in Methods and Practices in Psychological Science, 5(2), 25152459221095823. https://doi.org/10.1177/25152459221095823

62.

Yang

L. H.

Chen

F. P.

Sia

K. J.

Lam

Ngo

Lee

Kleinman

Good

(2014). ‘What matters most:’ A cultural mechanism moderating structural vulnerability and moral experience of mental illness stigma. Social Science & Medicine, 103, 84–93. https://doi.org/10.1016/j.socscimed.2013.09.009

Supplementary Material

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Right-wing authoritarianism,social dominance,system justification,and conservative political ideology as predictors of mental health stigma: The Hungarian case

Abstract

Background:

Aims:

Methods:

Results:

Conclusion:

Keywords

Methods

Participants and procedure

Measures

Predictor variables: Political dispositions and political ideology

Outcome variables

Generic scales assessing mental illness-associated stigma

Specific measures assessing stigma related to specific mental illnesses

Control variables: Demographic variables

Data analysis

Results

Descriptive analysis

Main analysis

Discussion

Limitations and strengths

Supplemental Material

sj-docx-2-isp-10.1177_00207640241267803 – Supplemental material for Right-wing authoritarianism, social dominance, system justification, and conservative political ideology as predictors of mental health stigma: The Hungarian case

Research Data

sj-sav-1-isp-10.1177_00207640241267803 – for Right-wing authoritarianism, social dominance, system justification, and conservative political ideology as predictors of mental health stigma: The Hungarian case

Footnotes

Acknowledgements

Conflict of interest

Funding

Compliance with ethical standards

ORCID iD

Data availability statement

Supplemental material

References

Supplementary Material