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Exploring UK Public Attitudes Towards Stateless People: A Network Analysis

Published online by Cambridge University Press:  03 December 2025

Ellie Oppenheim ,
Ciarán O’Driscoll  and
Francesca Brady Open the ORCID record for Francesca Brady [Opens in a new window]
Ellie Oppenheim
Affiliation:
Research Department of Clinical, Educational, and Health Psychology, UCL , London, UK
Ciarán O’Driscoll
Affiliation:
Research Department of Clinical, Educational, and Health Psychology, CORE Data Lab, Centre for Outcomes Research and Effectiveness (CORE), UCL, London, UK
Francesca Brady*
Affiliation:
Research Department of Clinical, Educational, and Health Psychology, UCL , London, UK Woodfield Trauma Service, Central and North West London NHS Foundation Trust , London, UK
*
Corresponding author: Francesca Brady; Email: f.brady@ucl.ac.uk
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Abstract

This study provides quantitative evidence on UK public attitudes towards stateless people, comparing them with attitudes towards refugees and asylum seekers. A cross-sectional UK survey (n = 385) was conducted. Network analysis modelled associations between social policy attitudes and prejudice towards stateless people, refugees, and asylum seekers, alongside other variables, including political orientation and perceived threat. Social policy attitudes were more restrictive towards stateless people than refugees, but less restrictive than towards asylum seekers. Prejudice towards stateless people was not significantly different to that towards refugees or asylum seekers. Prejudice and social policy attitudes were highly interrelated between all three groups, with political orientation and perceived threat the strongest predictors. Findings demonstrate similarities in UK public attitudes towards stateless people, refugees, and asylum seekers. Awareness-raising interventions and interventions addressing political and threat-based narratives may be most effective in reducing discrimination and fostering inclusion of stateless people.

Keywords

statelessprejudicesocial policy attitudesrefugeeasylum seeker

Information

Type
Article
Information
Social Policy and Society , First View , pp. 1 - 19
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited.
Copyright
© The Author(s), 2025. Published by Cambridge University Press

Introduction

A person affected by statelessness is someone who is ‘not considered as a national by any State under the operation of its law’ (United Nations (UN) General Assembly, 1954). A person is stateless either where they are unable to acquire any nationality at birth or where they have lost or been deprived of the nationality they once held, without acquiring another one (The Institute of Statelessness and Inclusion (ISI), 2014). Although refugees, asylum seekers, and stateless persons are distinct legal categories, some refugees can also be stateless, and statelessness may be relevant to the determination process for some asylum applications. Stateless people share many experiences with asylum seekers and refugees, such as exposure to trauma, persecution, discrimination from governments and the public, being subject to immigration control, and being unable to access key public services before obtaining leave to remain in a host country (Liebling et al., Reference Liebling, Goodman, Burke and Zasada2014; Küey, Reference Küey2017; United Nations High Commissioner for Refugees (UNHCR), 2017; Schlaudt et al., Reference Schlaudt, Bosson, Williams, German, Hooper, Frazier, Carrico and Ramirez2020; Home Office, 2021).

UNHCR estimates there are over four million stateless people globally, with the actual figure likely much higher due to a lack of reporting on statelessness in approximately one half of the world’s countries (UNHCR, 2025). Despite this, little research has been conducted relating to the mental wellbeing of stateless people. Evidence identifies discrimination as a major stressor for asylum seekers and refugees (Hatch et al., Reference Hatch, Gazard, Williams, Frissa, Goodwin and Hotopf2016; Chen et al., Reference Chen, Hall, Ling and Renzaho2017; Tinghög et al., Reference Tinghög, Malm, Arwidson, Sigvardsdotter, Lundin and Saboonchi2017; Brunnet et al., Reference Brunnet, Bolaséll, Weber and Kristensen2018; Gkiouleka et al., Reference Gkiouleka, Avrami, Kostaki, Huijts, Eikemo and Stathopoulou2018; Ziersch et al., Reference Ziersch, Due and Walsh2020; Mougenot et al., Reference Mougenot, Amaya, Mezones-Holguin, Rodriguez-Morales and Cabieses2021), contributing to difficulties accessing adequate education, housing, and employment, and difficulties socially integrating within their host country (Bakker et al., Reference Bakker, Dagevos and Engbersen2014; Quinn, Reference Quinn2014; Borsch et al., Reference Borsch, de Montgomery, Gauffin, Eide, Heikkilä and Smith Jervelund2019; Lee et al., Reference Lee, Szkudlarek, Nguyen and Nardon2020; Ziersch et al., Reference Ziersch, Due and Walsh2020). These findings highlight the relevance of understanding public attitudes towards stateless people, who may encounter similar stressors. While some research has explored public perceptions of specific stateless populations, notably the Rohingya (e.g. Jerin and Mozumder, Reference Jerin and Mozumder2019; Kamruzzaman et al., Reference Kamruzzaman, Siddiqi and Ahmed2024), no research has been conducted that explores public attitudes towards stateless people more broadly. As such, this study aims to understand public attitudes towards stateless people as a general category, and to understand which factors may underpin these attitudes.

Attitudes toward stateless individuals, asylum seekers, and refugees

This article operationalises attitudes toward stateless people, asylum seekers, and refugees using two measures: (i) social policy attitudes, defined as support for policies that provide rights, protections, or assistance to these groups, and (ii) prejudice, reflecting negative feelings or biases toward the groups.

Although there is no data relating to public attitudes towards stateless people in the United Kingdom (UK), data demonstrates that attitudes towards asylum seekers and refugees are divided both in the UK and globally. Data suggests that the UK public has more social policy restrictive attitudes towards asylum seekers compared to other migrant groups, as measured by a desire to make it more difficult to migrate to the UK (The Migration Observatory, 2023). In contrast, attitudes towards refugees appear more positive, with the UK public tending to support social policies aimed at providing assistance to them (Amnesty International, 2016). Higher levels of public support for refugees may be related to refugees having legally recognised status as a protected group of people who have involuntarily left their home country (UN General Assembly, 1951), with qualitative findings from the UK (Lynn and Lea, Reference Lynn and Lea2003) and Australia (Hartley and Pedersen, Reference Hartley and Pedersen2015) finding that the public show more positive attitudes towards migrants perceived as ‘authorised’, ‘legal’, or ‘genuine’ than those perceived as ‘unauthorised’, ‘illegal’, or ‘bogus’. This is supported by findings from the United States that undergraduate students reported greater prejudice, perceived threat, and intergroup anxiety towards ‘unauthorised migrants’ compared with ‘authorised migrants’ (Murray and Marx, Reference Murray and Marx2013). Findings also demonstrate stronger support for social policies aimed at supporting those perceived as involuntarily leaving their home country (Verkuyten et al., Reference Verkuyten, Mepham and Kros2018). Many asylum seekers and stateless people struggle to gain legal recognition of involuntarily leaving their homes and are therefore less likely to be perceived as ‘authorised’ relative to refugees (UK Government, 2021; European Union Agency for Asylum, 2022).

Variables associated with attitudes towards refugees, asylum seekers, and other migrant groups

There are several variables that may be associated with public attitudes towards stateless individuals. As limited literature can be identified examining public attitudes towards stateless individuals, this study draws on the literature relating to variables associated with public attitudes towards asylum seekers and refugees, as well as other migrant groups. Research indicates that individuals who define themselves as politically conservative or right-wing are more likely to express greater prejudice and more restrictive social policy attitudes towards asylum seekers (Haslam and Holland, Reference Haslam, Holland, Bretherton and Balvin2012; Hartley and Pedersen, Reference Hartley and Pedersen2015; Canetti et al., Reference Canetti, Snider, Pedersen and Hall2016; Anderson and Ferguson, Reference Anderson and Ferguson2018; Hartley et al., Reference Hartley, Anderson and Pedersen2019), as well as anti-immigration sentiment more broadly (Gallego and Pardos-Prado, Reference Gallego and Pardos-Prado2014; Plener et al., Reference Plener, Groschwitz, Brähler, Sukale and Fegert2017; Anderson and Ferguson, Reference Anderson and Ferguson2018; Cowling et al., Reference Cowling, Anderson and Ferguson2019). This may partly reflect the greater emphasis right-wing ideologies place on tradition and conservation – values associated with preserving the past, resisting social change, and protecting the ‘in-group’ and its way of life (Schwartz, Reference Schwartz2012). Research has shown that right-wing populist attitudes are similarly shaped by perceived threats to social order, a desire for conservation, and preference for a past in which their group held greater centrality in society (Norris and Inglehart, Reference Norris and Inglehart2019; Lammers and Baldwin, Reference Lammers and Baldwin2020; Jami, Reference Jami2025). Another explanatory factor may be differences in empathy: research indicates those who identify as left–wing or liberal score higher on empathy measures than their conservative counterparts, which may contribute to more inclusive or supportive attitudes towards migrants (Hasson et al., Reference Hasson, Tamir, Brahms, Cohrs and Halperin2018; Zebarjadi et al., Reference Zebarjadi, Adler, Kluge, Sams and Levy2023).

Although political orientation may provide some explanation of social policy attitudes and prejudice, other predictors, such as personal contact with migrants and personal experience of migration are also valuable to consider. Intergroup contact theory (Allport, Reference Allport1954) suggests that attitudes towards an outgroup tend to be more favourable if the member of the ingroup has contact with an individual from the outgroup. Although meta-analytic review suggests that approximately 94 per cent of previous studies found a negative association between contact and prejudice, some qualifying factors are relevant. For example, Allport’s original idea that the ‘wrong kind’ of contact can increase negative emotions and stereotypes should be noted, and a significant body of research highlights the importance of the context of the contact, such as whether it is observed in an experimental or natural setting, the power dynamics between the groups engaging in the contact, common goals of the groups, and its duration, frequency and directness (McKeown and Dixon, Reference McKeown and Dixon2017; Vezzali et al., Reference Vezzali, Hewstone, Capozza, Giovannini and Wölfer2017). Despite these caveats, available literature across multiple settings and contexts suggests that intergroup contact between the public and migrants tends to be a significant predictor of pro-immigrant attitudes (McLaren, Reference McLaren2003; Escandell and Ceobanu, Reference Escandell and Ceobanu2009; Ghosn et al., Reference Ghosn, Braithwaite and Chu2019; Kotzur et al., Reference Kotzur, Schäfer and Wagner2019; De Coninck et al., Reference De Coninck, Rodríguez-de-Dios and d’Haenens2021). Personal experience of migration is also shown to foster pro-immigrant attitudes, including more favourable social policy attitudes (Just and Anderson, Reference Just and Anderson2015). This may be to avoid cognitive dissonance (Festinger, Reference Festinger1957) or because the shared processes of moving to another country, such as acculturation and physical and psychological uprooting, create solidarity and kinship between migrants (Just & Anderson, Reference Just and Anderson2015).

Research suggests that social policy attitudes and prejudice are associated. A substantial body of literature has demonstrated that prejudice towards asylum seekers, refugees and other migrant groups is associated with discriminatory or negative attitudes, including restrictive social policy preferences (Escandell and Ceobanu, Reference Escandell and Ceobanu2009; Pereira et al., Reference Pereira, Vala and Costa-Lopes2010; Gallego and Pardos-Prado, Reference Gallego and Pardos-Prado2014; Hartley and Pedersen, Reference Hartley and Pedersen2015; Just and Anderson, Reference Just and Anderson2015; Plener et al., Reference Plener, Groschwitz, Brähler, Sukale and Fegert2017; Anderson and Ferguson, Reference Anderson and Ferguson2018; Cowling et al., Reference Cowling, Anderson and Ferguson2019; Hartley et al., 2019; De Coninck et al., Reference De Coninck, Rodríguez-de-Dios and d’Haenens2021). A large body of research identifies perceived threat as a key predictor of prejudice and social policy attitude towards outgroups (Stephan and Stephan, Reference Stephan and Stephan1996; Bizman and Yinon, Reference Bizman and Yinon2001; Pereira et al., Reference Pereira, Vala and Costa-Lopes2010), including towards asylum seekers (Pattison and Davidson, Reference Pattison and Davidson2019) and refugees (Hartley and Pedersen, Reference Hartley and Pedersen2015).

Other psychological factors that could predict social policy attitudes and prejudice towards stateless people include personality traits, such as interpersonal style. The Inventory of Interpersonal skills (IIP) (Horowitz et al., Reference Horowitz, Alden, Wiggins and Pincus2000) assesses difficulties that people experience in their interpersonal relationships, organising these difficulties across the dimensions of ‘affiliation’ and ‘dominance’ (Lo Coco et al., Reference Lo Coco, Mannino, Salerno, Oieni, Di Fratello, Profita and Gullo2018). Affiliation entails high warmth/friendliness and correlates positively with is strongly related to the Big Five Trait of Agreeableness (Nysæter et al., Reference Nysæter, Langvik, Berthelsen and Nordvik2009). The opposite is true for high dominance (Nysæter et al., Reference Nysæter, Langvik, Berthelsen and Nordvik2009), with high dominance individuals more sensitive to cues signalling opportunities and threats to power (McClelland, Reference McClelland1985; Winter, Reference Winter and Smith1992). Research indicates agreeableness is associated with positive attitudes towards migrants (Dinesen et al., Reference Dinesen, Klemmensen and Nørgaard2014; Ackermann and Ackermann, Reference Ackermann and Ackermann2015; Freitag and Rapp, Reference Freitag and Rapp2015; Talay and De Coninck, Reference Talay and De Coninck2020).

Aims and hypotheses

This study aims to examine the social policy attitudes and prejudice levels of the UK public towards stateless people and to capture variables associated these attitudes. It aims to compare these findings to those relating to asylum seekers and refugees.

We hypothesised that: (i) more affiliative and less dominant interpersonal styles will be associated with more positive attitudes towards stateless people, as measured by less restrictive social policy attitudes and lower prejudice towards stateless people; (ii) more right-wing political orientation will be associated with more negative attitudes towards stateless people, as measured by restrictive social policy attitudes and greater prejudice towards stateless people, (iii) participants who have personal migration experience and/or previous contact with stateless people, asylum seekers or refugees will show more positive attitudes towards stateless people, as measured by less-restrictive social policy attitudes and lower prejudice towards stateless people; (iv) greater perceived threat will be associated with more negative attitudes towards stateless people, as measured by restrictive social policy attitudes and greater prejudice towards stateless people; (v) social policy attitudes towards asylum seekers and stateless people will be more restrictive than those towards refugees; and (vi) prejudice towards asylum seekers and stateless people will be greater than prejudice towards refugees.

Methods

Ethical approval

Ethical approval was obtained via the University College London Research Ethics Committee to undertake this project (Reference Number: 22223/001).

Design

The study used a cross-sectional design. Key variables captured included measures of attitude (prejudice and social policy attitude); demographic variables; and other variables including, perceived threat, interpersonal style, political orientation, previous contact with refugees, asylum seekers and stateless people, and personal migration experience. The study was pre-registered (https://aspredicted.org/k9bz4.pdf). There was a deviation from the pre-registered analytic plan, which made a hypothesis around personality traits. This was removed given overlap with interpersonal styles.

Participants

A total of 385 UK residents aged eighteen or above participated in this study. Participants who skipped more than or equal to 10 per cent of the questionnaire (n = 29) were excluded from analysis, leaving 356 participants. The sample (n = 356) comprised 48.9 per cent men, 49.7 per cent women, and 1.4 per cent non-binary people. The sample was 86.8 per cent White, with Asian and Asian UK the next most common ethnicity (6.2 per cent). Also, 44.4 per cent of the sample had secondary level or no formal education, and 40.4 per cent had university-level qualifications. 66 per cent were in employment. Full demographic information is outlined in the supplementary materials. Participants were recruited through Prolific (https://www.prolific.co), an online, quality-checked platform that recruits research participants in return for a fee. Participants were offered £6.94 per hour in line with Prolific’s suggested renumeration. The study excluded individuals not resident in the UK, not proficient in English, or under age eighteen.

Procedures

All data was collected in May 2022 across one day. Participants were recruited via Prolific. The listing on Prolific provided a link to an information sheet and consent form. Participants who provided consent were then able to access the survey via Qualtrics. All participants were given the same questionnaire in the same order. The questionnaire began with a section collecting demographic information and political orientation. Following this, participants were asked if they had personal experience of migration and whether they have previously or currently had any contact with stateless people, asylum seekers or refugees. The measures for these initial items are outlined below. Participants were then asked if they understood the term ‘stateless’. Following this, the questionnaire provided written definitions of the terms ‘asylum seeker’ and ‘refugee’, which were based on the 1951 Refugee Convention definitions (UN General Assembly, 1951). Participants were asked to watch a two-minute video (see supplementary materials) explaining statelessness. As statelessness is a less familiar concept to the public, a video was provided rather than a written definition, as it was anticipated this would help generate more comprehensive understanding. This video included a simplified version of the international legal definition of statelessness (UN General Assembly, 1954), and examples of reasons individuals might become stateless. Participants could rewatch the video as needed. All participants were required to confirm that they had read and understood the definitions of asylum seeker, refugee, and stateless person before they could move onto the next part of the questionnaire. Participants then completed the measures outlined below.

Measures

Demographic variables included gender, age, ethnicity, employment status, and education level.

Interpersonal functioning was assessed using the Inventory of Interpersonal Problems (IIP-32) (Horowitz et al., Reference Horowitz, Alden, Wiggins and Pincus2000). The IIP-32 is a 32-item inventory of distressing interpersonal behaviours. Items are scored on a five-point Likert scale in response to the stem: “how much have you been distressed by this problem?”. The dimensions of dominance and affiliation are considered in this study. The range of affiliation includes friendly to hostile behaviour, while the range of dominance goes from dominating to submissive behaviour. Studies of the IIP-32 show satisfactory validity and internal reliability in both clinical and non-clinical populations (Barkham et al., Reference Barkham, Hardy and Startup1996; McEvoy et al., Reference McEvoy, Burgess, Page, Nathan and Fursland2013; Lo Coco et al., Reference Lo Coco, Mannino, Salerno, Oieni, Di Fratello, Profita and Gullo2018), and good reliability in this sample (McDonald’s ω = 0.924). An R package was used to calculate the dominance and affiliation scores (Girard et al., Reference Girard, Zimmerman and Wright2021).

Perceived threat was assessed using a single item measure adapted from Escandell and Ceobanu (Reference Escandell and Ceobanu2009). This single item measure read: ‘in general terms, are there too many migrants who live in our country?’. Participants selected either ‘yes, there are too many’ (scored 1) or ‘no, there are not too many’ (scored 0).

Prejudice was assessed using a single item measure for stateless people, asylum seekers, and refugees separately using a measure based on Hartley and Pedersen (Reference Hartley and Pedersen2015). Participants were asked ‘in general how positive or favourable do you feel about (stateless people/asylum seekers/refugees)?’. Participants responded using a seven-point Likert scale ranging from ‘extremely unfavourable’ to ‘extremely favourable’. The question was repeated for each group. Scores were reversed to measure prejudice, rather than positivity.

Understanding of statelessness was measured using the following binary question ‘Do you know what it means to be a stateless person?’.

Political orientation was measured on a scale from zero to one hundred where zero was left-wing and one hundred was right-wing. Scores were equal to the number the individual chose on the scale.

Personal migration experience was measured by participants providing a binary response as to whether they had ever lived in a country other than their home country.

Contact was measured by participants providing a binary response to the question ‘have you ever had any friends, relatives, or acquaintances who were or are asylum seekers, refugees or stateless?’.

Social policy attitudes towards stateless people, asylum seekers, and refugees were separately assessed using measures based on Hartley and Pedersen (Reference Hartley and Pedersen2015). Participants rated their level of support for policies aimed at each group on a seven-point Likert scale. Three policy statements were given for each group separately, and were as follows: ‘[stateless people/asylum seekers/refugees] should have immediate access to all social services such as education, housing and healthcare’; ‘[stateless people/asylum seekers/refugees] should have the right to work as soon as they enter the UK’; ‘there is too much effort put into the care and support of [stateless people/asylum seekers/refugees] in the community’ (reverse scored). A mean score of the three policy items was calculated with higher scores reflecting more restrictive social policy attitudes. Reliability analysis yielded McDonald’s ω of .86, .89 and .87 for social policy attitudes towards stateless people, asylum seekers, and refugees, respectively.

Data analysis

Preliminary analyses included calculating means, standard deviations, Spearman’s correlations, and difference tests between groups.

Mixed graphical network analysis

Mixed Graphical Modelling (MGM), i.e. network modelling, was used to explore the relationship between the study variables and social policy attitudes and prejudice towards all three groups. MGMs offer several advantages over hierarchical regression models. MGMs excel in handling diverse data types simultaneously, capturing complex and bidirectional relationships between variables, and providing a comprehensive network structure (Haslbeck et al., Reference Haslbeck, Borsboom and Waldorp2021). They perform automatic variable selection and handle missing data more effectively. MGMs are particularly useful for exploratory analysis, revealing unexpected connections and reducing dimensionality in high-dimensional datasets. Whilst hierarchical regression models focus on linear relationships and unidirectional influences, MGMs offer a more flexible and holistic approach to modelling complex systems, making them better suited for understanding intricate relationships and interdependencies among variables. While a nested structure is defined within a hierarchical regression, within network models, the structure emerges from the data. This provides useful insights into how the variables used in this study may work independently and together to inform social policy attitudes and prejudice.

We estimated MGMs, in which measures were added as either continuous or categorical. In estimating the network, an elastic net regularisation reduces the inclusion of spurious edges, resulting in a sparse network with higher specificity (Epskamp et al., Reference Epskamp, Borsboom and Fried2018). The regularisation parameter was selected with 10-fold cross-validation and specified that estimates across neighbourhood regressions should be combined (AND rule). As the regression on social policy attitudes and prejudice towards stateless individuals includes many terms, this renders the AND-rule very conservative (Haslbeck and Waldorp, Reference Haslbeck and Waldorp2020).

Within the MGMs, we estimated all pairwise interactions. These interactions are conditional on all other variables (i.e. modelling the relationship between variables, while controlling for the influence of all other variables). This allows us to identify variables that are uniquely associated with social policy attitudes and prejudice. Estimating separate networks for each group in MGMs allows for the identification of group-specific patterns, detection of differential relationships across groups, and generation of group-specific hypotheses. On the other hand, estimating all data within one graphical model provides increases statistical power, reveals overall patterns, and controls for the influence of social policy attitudes and prejudice between groups, highlighting moderation effects. As such, we estimated both as they are complementary in nature, allowing us to draw more robust conclusions about group similarities and differences in the data. This meant that we estimated a model for stateless people, termed the Stateless Focal Network model, with separate focal models for refugees and asylum seekers for comparison. A second network, termed the Integrated Network model models all the data to control for social policy attitudes and prejudice towards asylum seekers and refugees. Edges with categorical variables can be interpreted in terms of (averaged) regression coefficients, while edges between continuous variables can be interpreted as partial correlations.

Open data and transparency

Raw data and r code to reproduce the analysis and additional supplementary material are available: https://osf.io/n3wky/ (O’Driscoll, Reference O’Driscoll2025).

Results

Preliminary analysis

Descriptive statistics are displayed in Table 1. Zero order correlations are shown in Table 2. Notably, 32.3 per cent of the sample reported not understanding what it meant to be stateless prior to watching the definition video, highlighting a lack of awareness about this group.

Table 1.

Descriptive statistics of measured variables

Higher scores indicate more right-wing political orientation.

Table 2.

Zero order Spearman’s correlations between key study variables

Note: *** Correlation is significant at p<.001; **Correlation is significant at p<.01 level; *Correlation is significant at p<.05 level.

Mixed graphical network

The Stateless Focal Network model (Figure 1) estimates associations between social policy attitudes and prejudice towards stateless people, and the other study variables, without including social policy attitudes and prejudice towards either asylum seekers or refugees in the network. Separate network models for social policy attitudes and prejudice towards asylum seekers and refugees are displayed alongside the Stateless Focal Network Model for comparison.

Figure 1.

Stateless Focal Network model (stateless focal network model with refugee and asylum seeker focal networks for comparison). The thicker and darker the edge, the larger the edge weight and stronger the unique association between two variables. The colour of the edges indicates the relationship sign (i.e. positive = green, negative = red). Continuous variables are represented as circles and categorical as squares. Variables are as follows: 1. Dominance, 2. Affiliation, 3. Age, 4. Political Orientation, 5. Prejudice, 6. Social Policy Attitude, 7. Personal Migration Experience, 8. Contact, 9. Perceived Threat, 10. Gender, 11. Ethnicity, 12. Education Level, 13. Employment.

An Integrated Network model (Figure 2) was also modelled. The Integrated Network modelled the prejudice and social policy attitudes towards all three groups in one network. The partial correlation matrices modelled by the networks are provided in the supplementary material.

Figure 2.

Integrated Network model including measurement of prejudice and social policy attitudes towards stateless people, refugees, and asylum seekers in one network together. The thicker and darker the edge, the larger the edge weight and stronger the unique association between two variables. The colour of the edges indicates the relationship sign (i.e. positive = green, negative = red). Continuous variables are represented as circles and categorical as squares. Variables are as follows: 1. Dominance, 2. Affiliation, 3. Age, 4. Political Orientation, 5. Asylum Seeker Prejudice, 6. Stateless Prejudice, 7. Refugee Prejudice 8. Refugee Social Policy, 9. Asylum Seeker Social Policy, 10. Stateless Social Policy, 11. Personal Migration Experience, 12. Contact, 13. Perceived Threat, 14. Gender, 15. Ethnicity, 16. Education Level, 17. Employment.

Analysis

Hypothesis i: more affiliative and less dominant interpersonal styles will be associated with more positive attitudes towards stateless people, as measured by less-restrictive social policy attitudes and lower prejudice towards stateless people.

Zero order correlations indicate no significant association between affiliative interpersonal styles and either social policy attitudes towards stateless people (rs(354) = .049, p = .352) or prejudice towards stateless people (rs(354) = −.006, p = .914). Dominant interpersonal styles also showed no significant relationships to social policy attitude towards stateless people (rs(354) = .103, p = .051) or prejudice towards stateless people (rs(354) = . 087, p = .101).

Hypothesis ii: more right-wing political orientation will be associated with more negative attitudes towards stateless people, as measured by restrictive social policy attitudes and greater prejudice towards stateless people.

Zero order correlations indicate a moderate to strong positive correlation between right-wing political orientation and more restrictive social policy attitudes towards stateless people (rs(354) = .590, p<.001), as well as higher prejudice towards stateless people (rs(354) = .518, p<.001).

In the Stateless Focal Network model, which controls for the influence of all other variables except attitude measures towards refugees and asylum seekers, the partial correlations between these variables were still significant, and right-wing political orientation remained directly associated with more restrictive social policy attitudes towards stateless people (r =.230) and prejudice (r = .054).

Finally, in the Integrated Network model, which models the social policy attitudes and prejudice towards stateless people, refugees, and asylum seekers in one network together, political orientation was no longer directly associated with either social policy attitudes or prejudice towards stateless people. Instead, more right-wing political orientation was directly associated with greater perceived threat (r = .209), which then was indirectly associated with more restrictive social policy attitudes and greater prejudice towards stateless people through prejudice and social policy attitudes towards both asylum seekers and refugees.

Hypothesis iii: participants who have personal migration experience and/or previous contact with stateless people, asylum seekers or refugees will show more positive attitudes towards stateless people, as measured by less restrictive social policy attitudes and lower prejudice towards stateless people.

Zero order correlations showed no significant relationship between contact and social policy attitudes towards stateless people (rs(354) = −.086, p = .105). In contrast, a significant zero order correlation was found between contact and lower prejudice towards stateless people (rs(354) = −.144, p<.010). Similarly, no significant relationship was found between personal migration experience and social policy attitude towards stateless people (rs(354) = −.006, p = .230). However, a significant association was found between personal migration experience and lower prejudice towards stateless people (rs(354) = −.145, p<.010).

In the Stateless Focal Network model, personal migration experience remained associated with prejudice towards stateless people (r = −.135). However, contact was no longer directly associated with prejudice and was instead associated with perceived threat (r = .077, odds ratio: 1.112), which was in turn associated with prejudice indirectly through other variables in the network.

In the Integrated Network model, the association between personal migration experience and prejudice was no longer present and was instead indirectly associated through other variables in the network. Contact remained associated with perceived threat (r = .321, odds ratio: 1.417) in the Integrated Network model, which was then indirectly associated with social policy attitudes and prejudice towards stateless people.

Hypothesis iv: perceived threat will be associated with more negative attitudes towards stateless people, as measured by restrictive social policy attitudes and greater prejudice towards stateless people.

Zero order correlations showed a significant correlation between greater perceived threat and more restrictive social policy attitudes (rs(354) = .514, p<.001) and greater prejudice towards stateless people (rs(354) = .419, p<.001).

In the Stateless Focal Network model, greater perceived threat was directly associated with more restrictive social policy attitudes towards stateless people (r = .378). Greater perceived threat was indirectly associated with greater prejudice towards stateless people through more restrictive social policy attitudes towards stateless people and to a lesser degree right-wing political orientation.

In the Integrated Network model, perceived threat was indirectly associated with more restrictive social policy attitudes and greater prejudice towards stateless people.

Hypothesis v: social policy attitudes towards asylum seekers and stateless people will be more restrictive than those towards refugees.

A significant difference was found in social policy attitudes towards stateless people, asylum seekers and refugees (F(1.813, 643.670) = 26.552, p<.001, ηp2 = 0.070) (Greenhouse-Geisser corrected). Social policy attitudes towards asylum seekers (M = 3.341, SD = 1.683) were significantly more restrictive than those towards refugees (M = 2.995, SD = 1.547), t(355) = 8.694, p<.001. Social policy attitudes towards stateless people (M = 3.224, SD = 1.513) were also significantly more restrictive than those towards refugees, t(355) = 4.411, p<.001). A significant difference was found between social policy attitudes towards stateless people and asylum seekers, t(355) = 2.246, p=.025.

Hypothesis vi: prejudice towards asylum seekers and stateless people will be greater than prejudice towards refugees.

A significant difference was found in prejudice towards stateless people, asylum seekers and refugees (F(1.872, 664.574) = 8.215, p<.001, ηp2 = .023 (Greenhouse–Geisser corrected). Pairwise comparisons showed that prejudice towards asylum seekers (M = 3.287, SD = 1.611) was significantly higher than towards refugees (M = 3.073, SD = 1.461), t(355) = 4.691, p<.001). No significant difference was found between prejudice towards stateless people (M = 3.169, SD = 1.406) and asylum seekers, t(355) = 2.064, p=.080), or between stateless people and refugees, t(355) = 1.740, p=.083).

Further analysis of the focal network models

Following analysis relating to the hypotheses set out above, further exploration of the data was conducted.

In the Stateless Focal Network model, greater prejudice towards stateless people was directly associated with more right-wing political orientation (r = .053), more restrictive social policy attitudes towards stateless people (r = .620), lack of personal migration experience (r = .134), gender (r = .023), ethnicity (r = .057), and employment (r = .047). All other variables in the network were indirectly associated through these variables. Social policy attitude towards stateless people was directly associated with fewer variables, and direct associations were only found with political orientation (r = .230), prejudice (r = .620), and perceived threat (r = .378). All other variables in the network were indirectly associated to social policy attitudes towards stateless people through these variables. Being of older age and being more educated was associated with more right-wing political orientation.

Focal network models for refugees and asylum seekers revealed significant direct associations between social policy attitudes and perceived threat (r = .344 for asylum seekers, r = .553 for refugees), prejudice (r = .629 for asylum seekers, r = .551 for refugees), and political orientation (r = .147 for asylum seekers, r = .222 for refugees). For refugees and stateless people, no direct association was found between prejudice and perceived threat; instead, this relationship was mediated through other variables, most notably social policy attitudes. In contrast, prejudice towards asylum seekers showed a direct association with perceived threat.

Further analysis of the Integrated Network model

Within the Integrated Network model, social policy attitudes towards stateless people were associated directly with prejudice towards stateless people (r = .483) and social policy attitudes towards asylum seekers (r = .367). All other variables were associated with social policy attitudes towards stateless people through these two variables. Within this model, prejudice towards stateless people was directly associated with prejudice towards asylum seekers (r = .283), prejudice towards refugees (r = .235), social policy attitudes towards asylum seekers (r = .182), and social policy attitudes towards stateless people (r = .483). All other variables were associated with prejudice towards stateless people through these variables.

Discussion

This study explored UK public attitudes towards stateless people, operationalised as prejudice and social policy attitudes towards this group. Variables associated with these attitudes were also explored, and attitudes towards stateless people were compared to those towards asylum seekers and refugees.

This study identified that social policy attitudes towards stateless people were significantly more restrictive than those towards refugees, but significantly less restrictive than those towards asylum seekers. In contrast, no significant difference was identified between prejudice levels towards stateless people and refugees or stateless people and asylum seekers. This finding suggests that the UK public views refugees as most legitimately deserving social policy support, and asylum seekers as least legitimately deserving of policy support. Our findings suggest that social policy attitudes may be more cognitively complex than prejudice, involving additional considerations beyond basic intergroup bias, such as perceived ‘legitimacy’ of the group. Our interpretation aligns with the findings of an Australian study, where participants reported feelings of anger towards asylum seekers, and perceptions of them as ‘illegals’ and ‘queue jumpers’ (Hartley and Pedersen, Reference Hartley and Pedersen2015). This is consistent with other studies which suggest that the public are likely to express more favourable attitudes towards ‘authorised’ migrants (such as legally recognised refugees) than those viewed as ‘unauthorised’ migrants (Murray and Marx, Reference Murray and Marx2013). Given our findings, it is possible that stateless people were viewed as less ‘unauthorised’ than asylum seekers, but more ‘unauthorised’ than refugees, hence the different social policy attitudes, despite similar levels of prejudice towards stateless people and both other groups.

When refugee and asylum seeker attitudes were incorporated into the Integrated Network model, complex interrelationships emerged among prejudice and social policy attitudes across all three groups, and the other study variables. Notably, associations between social policy attitudes towards stateless people and other study variables were mediated through attitudes towards asylum seekers, while prejudice towards stateless people was linked to the wider network through prejudice towards asylum seekers and refugees. This pattern suggests that public attitudes towards stateless people may, in part, be formed indirectly through their perceptions of refugees and asylum seekers. One possible interpretation is that this is due to a lack of public awareness of statelessness, meaning people need to draw on their impressions of refugees and asylum seekers to form attitudes towards stateless people.

Our findings underscore the interconnected nature of attitudes towards asylum seekers, refugees, and stateless people. This, combined with the similarities in prejudice levels and the common predictors of attitudes identified across groups (discussed below), suggests that policies and interventions designed to reduce discrimination against asylum seekers and refugees are also likely to benefit stateless people. Similarly, interventions aimed at supporting asylum seekers and refugees to cope with the effects of negative public attitudes are likely to be supportive for stateless people. Although therapies targeting public attitudes and discrimination are relatively understudied, evidence-based interventions that currently exist for asylum seekers and refugees (e.g. Kira and Tummala-Narra, Reference Kira and Tummala-Narra2014; Pedersen and Hartley, Reference Pedersen and Hartley2015; van Heemstra et al., Reference van Heemstra, Scholte, Haagen and Boelen2019) should be considered for stateless individuals.

Focal Network models showed similar associations across each group, with social policy attitudes towards all three groups showing direct associations with the three same variables – prejudice, perceived threat, and political orientation. The similar patterns of association found across the Focal Network Models for each group suggest that social policy attitude formation operates in broadly similar ways across the three groups, with political orientation, prejudice and perceived threat acting as mediators.

Focal Network models showed that for refugees and stateless people, prejudice was indirectly associated with perceived threat through other variables, most notably social policy attitude towards the respective groups. In contrast, prejudice towards asylum seekers showed a direct association with perceived threat. This suggests that prejudicial attitudes towards asylum seekers may be more readily accessible in situations where people feel under threat, whereas for refugees and stateless people, threat perceptions may first be filtered through considerations about social policy before forming prejudicial attitudes towards these two groups. More right-wing political orientation was directly associated with more prejudicial attitudes towards all three groups in Focal Network models.

Analysis from Integrated Network modelling showed that perceived threat appeared to act as a psychological mediator between both social policy attitudes and prejudice towards all three groups and the other study variables. Combined with findings from the Focal Network models relating to the importance of political orientation as a mediator, it is likely that interventions and policies targeting political and threat-based narratives will have the greatest success in changing attitudes towards all three groups. No significant associations emerged between either social policy attitudes or prejudice towards stateless people and interpersonal style (dominance vs. affiliation), suggesting that interventions designed to target interpersonal style are unlikely to be effective.

Focal Network models also found associations between personal migration experience and prejudice towards both stateless people and refugees, but no significant relationship with prejudice towards asylum seekers. Additionally, whilst no significant associations were found between prejudice towards stateless people and prior contact, prejudice towards refugees and asylum seekers was associated with prior contact. This suggests that although the key associations were consistent across all three groups, there were small but significant differences in how attitudes are likely formed, with contact and personal migration experience showing variable associations with prejudice towards the three groups. These differences, alongside some differences in mean prejudice and social policy attitudes towards groups, indicate that while interventions aimed at reducing negative attitudes or supporting individuals in coping with their effects are likely to be broadly applicable across groups, it remains important to account for the finer distinctions in how public attitudes toward stateless people, asylum seekers, and refugees may diverge. Given this, it may also be helpful to consider designing new policies and interventions for stateless people that attend to the differences identified between public attitudes towards the three groups.

Nearly a third of participants indicated unfamiliarity with the concept of statelessness. Research suggests that public knowledge plays a crucial role in shaping public attitudes (Sinnott, Reference Sinnott2000). For example, Pedersen et al. (Reference Pedersen, Paradies, Hartley and Dunn2011) demonstrated that that teaching cross-cultural issues in university significantly increased positive attitudes towards asylum seekers. Educational interventions could target issues linked to perceived threat and political orientation, which, given our finding that these variables have the strongest direct associations with higher prejudice and more restrictive social policy attitudes towards stateless people, may reduce discriminatory attitudes or behaviour (see Pedersen and Hartley, Reference Pedersen and Hartley2015 for suggested intervention approaches). As media has been shown to influence prejudice, perceived threat, and political orientation (Vliegenthart et al., Reference Vliegenthart, Boomgaarden and Van Spanje2012; Sheets et al., Reference Sheets, Bos and Boomgaarden2016), interventions targeting inaccurate or sensationalist media reporting of migration and statelessness-related issues, may also be effective in reducing discrimination.

Limitations and future research

Whilst this research elucidates several useful findings, there are methodological limitations to the study design. Quantitative surveys cannot capture nuances in participants’ attitudes or experiences. Future research could use a qualitative framework to supplement this article’s findings. The cross-sectional design is also a limitation, as causality cannot be established. Longitudinal or experimental research into the psychological and social processes by which different variables influence attitude formation towards stateless people, asylum seekers, and refugees is required.

In addition, the social policy attitudes disclosed by participants were likely informed by a specific understanding of statelessness based on the definition provided. Outside of this survey, UK residents might have different understanding, or express different attitudes towards stateless people. The definition of statelessness provided also did not summarise the legal status of stateless people. As such participants may have assumed that, unlike refugees, and similar to asylum seekers, stateless people may not have leave to remain in the UK. This might explain the finding that social policy attitudes towards stateless people were more restrictive than those towards refugees. Furthermore, the video definition for statelessness may have primed participants differently compared to the written definitions for asylum seekers and refugees. Response order effects could also have influenced results. The study’s sample also does not reflect the distribution of the UK population across different demographic characteristics. Future studies should try to replicate the findings of this study using a more representative sample, perhaps through more targeted recruitment.

There were also limitations to some of the measures used. To keep the survey short, single item measures were used to assess political orientation, contact, prejudice, and perceived threat. These may have lower construct validity than multiple item measures. For example, the use of a 0–100 scale for participants to rate their political orientation from left-wing (0) to right-wing (100) relies on individual interpretation of ‘left-wing’ and ‘right-wing’ (Bauer et al., Reference Bauer, Barberá, Ackermann and Venetz2017) and may conflate economic and cultural dimensions of political orientation. Similarly, construct validity may have been improved by utilising Pattison and Davidson’s (Reference Pattison and Davidson2019) measure of perceived threat, which assesses four dimensions of perceived threat, including realistic threat, symbolic threat, intergroup anxiety, and negative stereotypes. Moreover, given research suggesting that type and context of intergroup contact may be associated with differing attitudinal outcomes (McKeown and Dixon, Reference McKeown and Dixon2017; Vezzali et al., Reference Vezzali, Hewstone, Capozza, Giovannini and Wölfer2017), it would have been beneficial to use a more comprehensive measure of contact to test these associations in our sample. Additionally, our contact measure failed to differentiate between interactions with refugee, asylum seekers, or stateless persons. This may have influenced the contact and social policy association findings, as it is likely that most participants reporting contact had not interacted with a stateless person due their smaller numbers, which may explain why no association was found between contact and social policy attitude towards stateless people. Consequently, it remains unclear whether the absence of an association reflects a limitation of the measure or a genuine lack of relationship.

Conclusion

This study provides the first quantitative evidence on UK public attitudes towards stateless people and how these compare with attitudes towards asylum seekers and refugees. We engage with these conclusions cautiously, noting that ongoing research, replication, and systematic comparisons are essential. The findings of this study highlight that many members of the UK public potentially hold prejudicial or restrictive social policy attitudes towards stateless people. Given such attitudes can adversely affect the mental health of refugees and asylum seekers, our research underscores the importance of addressing discrimination as a key area for support for stateless people in the UK.

Supplementary material

Supplementary material available at: https://doi.org/10.17605/OSF.IO/N3WKY

Acknowledgements

We wish to thank all research participants for taking the time to share their views on this topic.

Author Contributions: CRediT Taxonomy

Ellie Oppenheim Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Project administration, Writing - original draft, Writing - review & editing

Ciarán O’Driscoll Conceptualization, Formal analysis, Investigation, Methodology, Supervision, Writing - review & editing

Francesca Brady Conceptualization, Methodology, Supervision, Writing - review & editing

Funding

No funding to declare.

Competing interests

No potential conflict of interest was reported by the author(s).

Ethical approval

This study was approved by the UCL Research Ethics Committee, with Project ID 2223.001.

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Figure 0

Table 1. Descriptive statistics of measured variables

Figure 1

Table 2. Zero order Spearman’s correlations between key study variables

Figure 2

Figure 1. Stateless Focal Network model (stateless focal network model with refugee and asylum seeker focal networks for comparison). The thicker and darker the edge, the larger the edge weight and stronger the unique association between two variables. The colour of the edges indicates the relationship sign (i.e. positive = green, negative = red). Continuous variables are represented as circles and categorical as squares. Variables are as follows: 1. Dominance, 2. Affiliation, 3. Age, 4. Political Orientation, 5. Prejudice, 6. Social Policy Attitude, 7. Personal Migration Experience, 8. Contact, 9. Perceived Threat, 10. Gender, 11. Ethnicity, 12. Education Level, 13. Employment.

Figure 3

Figure 2. Integrated Network model including measurement of prejudice and social policy attitudes towards stateless people, refugees, and asylum seekers in one network together. The thicker and darker the edge, the larger the edge weight and stronger the unique association between two variables. The colour of the edges indicates the relationship sign (i.e. positive = green, negative = red). Continuous variables are represented as circles and categorical as squares. Variables are as follows: 1. Dominance, 2. Affiliation, 3. Age, 4. Political Orientation, 5. Asylum Seeker Prejudice, 6. Stateless Prejudice, 7. Refugee Prejudice 8. Refugee Social Policy, 9. Asylum Seeker Social Policy, 10. Stateless Social Policy, 11. Personal Migration Experience, 12. Contact, 13. Perceived Threat, 14. Gender, 15. Ethnicity, 16. Education Level, 17. Employment.