Subjective experience of paranoid ideation in a virtual reality social environment: A mixed methods cross‐sectional study

Riches, Simon; Bird, L.; Chan, Narelle; Rus-Calafell, Mar; Valmaggia, Lucia

doi:10.1002/cpp.2431

Cited by 19 publications

(9 citation statements)

References 31 publications

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“…This effect might arise from some form of familiarity -those who behave more like us inspire less vigilance. In one virtual reality study, unfamiliarity, feeling out of place and feeling like an outsider increased participants' perceptions of being judged by avatars, as well as increased perceptions of these avatars aiming to cause emotional distress (Riches et al, 2020). Likewise, epidemiological work has observed increased psychosis risk in those marginalised, and 'othered' in a community (el Bouhaddani et al, 2019;Kirkbride et al, 2017), and network approaches find that being socially withdrawn from a group increases paranoia in those with psychosis and those at familial risk for psychosis (Isvoranu et al, 2021).…”

Section: Discussionmentioning

confidence: 99%

Knowing me, knowing you: Interpersonal similarity improves predictive accuracy and reduces attributions of harmful intent

Barnby¹,

Raihani²,

Dayan³

2021

Preprint

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To benefit from social interactions, people need to predict how their social partners will behave. Such predictions arise through integrating prior expectations with evidence from observations, but where the priors come from and whether they influence the integration is not clear. Furthermore, this process can be affected by factors such as paranoia, in which the tendency to form biased impressions of others is common. Using a modified social value orientation (SVO) task in a large online sample (n=697), we showed that participants used a Bayesian inference process to learn about partners, with priors that were based on their own preferences. Paranoia was associated with preferences for earning more than a partner and less flexible beliefs regarding a partner’s social preferences. Alignment between the preferences of participants and their partners was associated with better predictions and with reduced attributions of harmful intent to partners.

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Section: Discussionmentioning

confidence: 99%

Knowing me, knowing you: Interpersonal similarity improves predictive accuracy and reduces attributions of harmful intent

Barnby¹,

Raihani²,

Dayan³

2021

Preprint

View full text Add to dashboard Cite

show abstract

“…While we partnered participants against genuine people, we cannot capture all social nuance that might be present in a real-world interaction. There may be a host of other social factors that may influence learning rates and uncertainty over inferred social intentions in paranoia such as eye contact and multiple social actors [ 35 ], and we feel this is an important topic for future research. Additionally, while not a substantial limitation for us to use Bayesian inference rather than its common approximations (e.g.…”

Section: Discussionmentioning

confidence: 99%

Reduction in social learning and increased policy uncertainty about harmful intent is associated with pre-existing paranoid beliefs: Evidence from modelling a modified serial dictator game

et al. 2020

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Current computational models suggest that paranoia may be explained by stronger higher-order beliefs about others and increased sensitivity to environments. However, it is unclear whether this applies to social contexts, and whether it is specific to harmful intent attributions, the live expression of paranoia. We sought to fill this gap by fitting a computational model to data (n = 1754) from a modified serial dictator game, to explore whether pre-existing paranoia could be accounted by specific alterations to cognitive parameters characterising harmful intent attributions. We constructed a ‘Bayesian brain’ model of others’ intent, which we fitted to harmful intent and self-interest attributions made over 18 trials, across three different partners. We found that pre-existing paranoia was associated with greater uncertainty about other’s actions. It moderated the relationship between learning rates and harmful intent attributions, making harmful intent attributions less reliant on prior interactions. Overall, the magnitude of harmful intent attributions was directly related to their uncertainty, and importantly, the opposite was true for self-interest attributions. Our results explain how pre-existing paranoia may be the result of an increased need to attend to immediate experiences in determining intentional threat, at the expense of what is already known, and more broadly, they suggest that environments that induce greater probabilities of harmful intent attributions may also induce states of uncertainty, potentially as an adaptive mechanism to better detect threatening others. Importantly, we suggest that if paranoia were able to be explained exclusively by core domain-general alterations we would not observe differential parameter estimates underlying harmful-intent and self-interest attributions.

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“…While we partnered participants against genuine people, we cannot capture all social nuance that might be present in a real-world interaction. There may be a host of other social factors that may influence learning rates and uncertainty over inferred social intentions in paranoia such as eye contact and multiple social actors (Riches et al, 2020), and we feel this is an important topic for future research. Additionally, while not a substantial limitation for us to use Bayesian inference rather than its common approximations (e.g.…”

Section: Discussionmentioning

confidence: 99%

Reduction in social learning and increased policy uncertainty about harmful intent is associated with pre-existing paranoid beliefs: evidence from modelling a modified serial dictator game.

Barnby¹,

Bell²,

Mehta³

et al. 2020

Preprint

View full text Add to dashboard Cite

Current computational models suggest that paranoia may be explained by stronger higher-order beliefs about others and increased sensitivity to environments. However, it is unclear whether this applies to social contexts, and whether it is specific to harmful intent attributions, the live expression of paranoia. We sought to fill this gap this by fitting a computational model to data (n = 1754) from a modified serial dictator game, to explore whether pre-existing paranoia could be accounted by specific alterations to cognitive parameters characterising harmful intent attributions. We constructed a ‘Bayesian brain’ model of others’ intent, which we fitted to harmful intent and self-interest attributions made over 18 trials, across three different partners. We found that pre-existing paranoia was associated with greater uncertainty about other’s actions. It moderated the relationship between learning rates and harmful intent attributions, making harmful intent attributions less reliant on prior interactions. Overall, the magnitude of harmful intent attributions was directly related to their uncertainty, and importantly, the opposite was true for self-interest attributions. Our results explain how pre-existing paranoia may be the result of an increased need to attend to immediate experiences in determining intentional threat, at the expense of what is already known, and more broadly, they suggest that environments that induce greater probabilities of harmful intent attributions may also induce states of uncertainty, potentially as an adaptive mechanism to better detect threatening others. Importantly, we suggest that if paranoia were able to be explained exclusively by core domain-general alterations we wouldn’t observe differential parameter estimates underlying harmful-intent and self-interest attributions.

show abstract

Subjective experience of paranoid ideation in a virtual reality social environment: A mixed methods cross‐sectional study

Cited by 19 publications

References 31 publications

Knowing me, knowing you: Interpersonal similarity improves predictive accuracy and reduces attributions of harmful intent

Knowing me, knowing you: Interpersonal similarity improves predictive accuracy and reduces attributions of harmful intent

Reduction in social learning and increased policy uncertainty about harmful intent is associated with pre-existing paranoid beliefs: Evidence from modelling a modified serial dictator game

Reduction in social learning and increased policy uncertainty about harmful intent is associated with pre-existing paranoid beliefs: evidence from modelling a modified serial dictator game.

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