Jumping to conclusions in the less-delusion-prone? Preliminary evidence from a more reliable beads task

Associations of conservatism and jumping to conclusions biases with aberrant salience and default mode network

AIM

While conservatism bias refers to the human need for more evidence for decision-making than rational thinking expects, the jumping to conclusions (JTC) bias refers to the need for less evidence among individuals with schizophrenia/delusion compared to healthy people. Although the hippocampus-midbrain-striatal aberrant salience system and the salience, default mode (DMN), and frontoparietal networks ("triple networks") are implicated in delusion/schizophrenia pathophysiology, the associations between conservatism/JTC and these systems/networks are unclear.

METHODS

Thirty-seven patients with schizophrenia and 33 healthy controls performed the beads task, with large and small numbers of bead draws to decision (DTD) indicating conservatism and JTC, respectively. We performed independent component analysis (ICA) of resting functional magnetic resonance imaging (fMRI) data. For systems/networks above, we investigated interactions between diagnosis and DTD, and main effects of DTD. We similarly applied ICA to structural and diffusion MRI to explore the associations between DTD and gray/white matter.

RESULTS

We identified a significant main effect of DTD with functional connectivity between the striatum and DMN, which was negatively correlated with delusion severity in patients, indicating that the greater the anti-correlation between these networks, the stronger the JTC and delusion. We further observed the main effects of DTD on a gray matter network resembling the DMN, and a white matter network connecting the functional and gray matter networks (all P < 0.05, family-wise error [FWE] correction). Function and gray/white matter showed no significant interactions.

CONCLUSION

Our results support the novel association of conservatism and JTC biases with aberrant salience and default brain mode.

A Bayesian model of the jumping-to-conclusions bias and its relationship to psychopathology

The mechanisms by which delusion and anxiety affect the tendency to make hasty decisions (Jumping-to-Conclusions bias) remain unclear. This paper proposes a Bayesian computational model that explores the assignment of evidence weights as a potential explanation of the Jumping-to-Conclusions bias using the Beads Task. We also investigate the Beads Task as a repeated measure by varying the key aspects of the paradigm. The Bayesian model estimations from two online studies showed that higher delusional ideation promoted reduced belief updating but the impact of general and social anxiety on evidence weighting was inconsistent. The altered evidence weighting as a result of a psychopathological trait appeared insufficient in contributing to the Jumping-to-Conclusions bias. Variations in Beads Task aspects significantly affected subjective certainty at the point of decisions but not the number of draws to decisions. Repetitions of the Beads Task are feasible if one assesses the Jumping-to-Conclusions bias using number of draws to decisions.

Towards a neurocomputational account of social controllability: From models to mental health

Controllability, or the influence one has over their surroundings, is crucial for decision-making and mental health. Traditionally, controllability is operationalized in sensorimotor terms as one's ability to exercise their actions to achieve an intended outcome (also termed "agency"). However, recent social neuroscience research suggests that humans also assess if and how they can exert influence over other people (i.e., their actions, outcomes, beliefs) to achieve desired outcomes ("social controllability"). In this review, we will synthesize empirical findings and neurocomputational frameworks related to social controllability. We first introduce the concepts of contextual and perceived controllability and their respective relevance for decision-making. Then, we outline neurocomputational frameworks that can be used to model social controllability, with a focus on behavioral economic paradigms and reinforcement learning approaches. Finally, we discuss the implications of social controllability for computational psychiatry research, using delusion and obsession-compulsion as examples. Taken together, we propose that social controllability could be a key area of investigation in future social neuroscience and computational psychiatry research.

Reasoning biases and delusional ideation in the general population: A longitudinal study

BACKGROUND

Reasoning biases have been suggested as risk factors for delusional ideation in both patients and non-clinical individuals. Still, it is unclear how these biases are longitudinally related to delusions in the general population. We hence aimed to investigate longitudinal associations between reasoning biases and delusional ideation in the general population.

METHODS

We conducted an online cohort study with 1184 adults from the German and Swiss general population. Participants completed measures on reasoning biases (jumping-to-conclusion bias [JTC], liberal acceptance bias [LA], bias against disconfirmatory evidence [BADE], possibility of being mistaken [PM]) and delusional ideation at baseline, and delusional ideation 7 to 8 months later.

RESULTS

A greater JTC bias was associated with a greater increase in delusional ideation over the following months. This association was better described by a positive quadratic relationship. Neither BADE, LA nor PM were associated with subsequent changes in delusional ideation.

CONCLUSIONS

This study suggests that jumping-to-conclusions predicts delusional ideation in the general population but that this association may follow a quadratic trajectory. While no other associations turned significant, future studies with shorter temporal distances may shed further light on the role of reasoning biases as risk factors for delusional ideation in non-clinical samples.

Whodunit - A novel video-based task for the measurement of jumping to conclusions in the schizophrenia spectrum

Jumping to conclusions (JTC) is implicated in the formation and maintenance of the positive symptoms of psychosis and over the years has become a prominent treatment target. Yet, measures designed to detect JTC are compromised by a number of limitations. We aimed to address some of these shortcomings with a new video-based "Whodunit task" among participants scoring high and low on the Community Assessment of Psychic Experiences (CAPE). We recruited a large sample (N = 979) from the general population who were divided into subgroups high vs. low on psychotic-like experiences (PLE), matched for depression and background characteristics. In the Whodunit task, participants were asked to rate the likelihood that one out of six suspects was the perpetrator of a crime (deliberately ambiguous with no clear clues until the end). The primary measure was the number of sequences-to-decision (STD). In line with the hypothesis, participants scoring high on the CAPE positive subscale displayed significantly lower STD and a higher rate of JTC. Response confidence in the assessments was elevated in the PLE-High group. The number of overall decisions was also significantly elevated for the PLE-High group. No group differences were found when comparing those scoring high versus low on depression. The STD index correlated significantly with a corresponding index from another JTC task. The study presents a new paradigm for the measurement of data gathering in the schizophrenia spectrum. Speaking to its validity, the Whodunit task was correlated with another JTC measure. Future research should test abbreviated versions of the paradigm, preferably using multiple trials with differing topics/emotional themes.

Computational mechanisms underlying illusion of control in delusional individuals

Humans navigate complex situations that require the accurate estimation of the controllability of the environment. Aberrant controllability computation might lead to maladaptive behaviors and poor mental health outcomes. Illusion of control, which refers to a heightened sense of control while the environment is uncontrollable, is one such manifestation and has been conceptually associated with delusional ideation. Nevertheless, this association has not yet been formally characterized in a computational framework. To address this, we used a computational psychiatry approach to quantify illusion of control in human participants with high (n = 125) or low (n = 126) trait delusion. Participants played a two-party exchange game in which their choices either did ("Controllable condition") or did not ("Uncontrollable condition") influence the future monetary offers made by simulated partners. We found that the two groups behaved similarly in model-agnostic measures (i.e., offer size, rejection rate). However, computational modeling revealed that compared to the low trait delusion group, the high delusion group overestimated their influence ("expected influence" parameter) over the offers made by their partners under the Uncontrollable condition. Highly delusional individuals also reported a stronger sense of control than those with low trait delusion in the Uncontrollable condition. Furthermore, the expected influence parameter and self-reported beliefs about controllability were significantly correlated in the Controllable condition in individuals with low trait delusion, whereas this relationship was diminished in those with high trait delusion. Collectively, these findings demonstrate that delusional ideation is associated with aberrant computation of and belief about environmental controllability, as well as a belief-behavior disconnect.

Rethinking delusions: A selective review of delusion research through a computational lens

Delusions are rigid beliefs held with high certainty despite contradictory evidence. Notwithstanding decades of research, we still have a limited understanding of the computational and neurobiological alterations giving rise to delusions. In this review, we highlight a selection of recent work in computational psychiatry aimed at developing quantitative models of inference and its alterations, with the goal of providing an explanatory account for the form of delusional beliefs in psychosis. First, we assess and evaluate the experimental paradigms most often used to study inferential alterations in delusions. Based on our review of the literature and theoretical considerations, we contend that classic draws-to-decision paradigms are not well-suited to isolate inferential processes, further arguing that the commonly cited 'jumping-to-conclusion' bias may reflect neither delusion-specific nor inferential alterations. Second, we discuss several enhancements to standard paradigms that show promise in more effectively isolating inferential processes and delusion-related alterations therein. We further draw on our recent work to build an argument for a specific failure mode for delusions consisting of prior overweighting in high-level causal inferences about partially observable hidden states. Finally, we assess plausible neurobiological implementations for this candidate failure mode of delusional beliefs and outline promising future directions in this area.

The relationship between early symptom severity, improvement and remission in first episode psychosis with jumping to conclusions

It is suggested that Jumping To Conclusions (JTC) reasoning bias might contribute to the distortion of external reality. However, the association between psychotic manifestations and JTC is obscure, especially if general intelligence is considered as a mediator. The aim of this study is to investigate the relation between severity, early clinical improvement and remission of symptoms in First Episode Psychosis (FEP) with JTC as an explanatory factor. One hundred seventy-one FEP individuals were evaluated with the Positive and Negative Syndrome Scale (PANSS) at baseline and one month after treatment initiation. Clinical improvement was ascribed as symptom change one-month post-baseline measurements. Symptomatic remission was assessed with the Andreasen severity criteria and JTC with the Beads Task, operationalized through Draws To Decision (DTD) (the lower the number of DTD, the higher the JTC bias). Regarding symptoms severity, total psychotic, total positive psychotic, and hallucinations-item PANSS scores showed a negative association with JTC after controlling for IQ. Regarding early clinical improvement, the association with JTC was non-significant. No significant association was detected between one month remission status of FEP and JTC. Our findings indicate that severity of positive symptoms is not associated with hastiness in decision-making, but rather with a heightened conservatism in terms of increased data gathering. Further research is required to replicate the results and clarify the cognitive processes involved.

Taking others into account: combining directly experienced and indirect information in schizophrenia

An abnormality in inference, resulting in distorted internal models of the world, has been argued to be a common mechanism underlying the heterogeneous psychopathology in schizophrenia. However, findings have been mixed as to wherein the abnormality lies and have typically failed to find convincing relations to symptoms. The limited and inconsistent findings may have been due to methodological limitations of the experimental design, such as conflating other factors (e.g. comprehension) with the inferential process of interest, and a failure to adequately assess and model the key aspects of the inferential process. Here, we investigated probabilistic inference based on multiple sources of information using a new digital version of the beads task, framed in a social context. Thirty-five patients with schizophrenia or schizoaffective disorder with a wide range of symptoms and 40 matched healthy control subjects performed the task, where they guessed the colour of the next marble drawn from a jar based on a sample from the jar as well as the choices and the expressed confidence of four people, each with their own independent sample (which was hidden from participant view). We relied on theoretically motivated computational models to assess which model best captured the inferential process and investigated whether it could serve as a mechanistic model for both psychotic and negative symptoms. We found that 'circular inference' best described the inference process, where patients over-weighed and overcounted direct experience and under-weighed information from others. Crucially, overcounting of direct experience was uniquely associated with most psychotic and negative symptoms. In addition, patients with worse social cognitive function had more difficulties using others' confidence to inform their choices. This difficulty was related to worse real-world functioning. The findings could not be easily ascribed to differences in working memory, executive function, intelligence or antipsychotic medication. These results suggest hallucinations, delusions and negative symptoms could stem from a common underlying abnormality in inference, where directly experienced information is assigned an unreasonable weight and taken into account multiple times. By this, even unreliable first-hand experiences may gain disproportionate significance. The effect could lead to false perceptions (hallucinations), false beliefs (delusions) and deviant social behaviour (e.g. loss of interest in others, bizarre and inappropriate behaviour). This may be particularly problematic for patients with social cognitive deficits, as they may fail to make use of corrective information from others, ultimately leading to worse social functioning.

Coronavirus conspiracy beliefs in the German-speaking general population: endorsement rates and links to reasoning biases and paranoia

BACKGROUND

Coronavirus-related conspiracy theories (CT) have been found to be associated with fewer pandemic containment-focused behaviors. It is therefore important to evaluate associated cognitive factors. We aimed to obtain first endorsement rate estimates of coronavirus-related conspiracy beliefs in a German-speaking general population sample and investigate whether delusion-related reasoning biases and paranoid ideation are associated with such beliefs.

METHODS

We conducted a cross-sectional non-probability online study, quota-sampled for age and gender, with 1684 adults from Germany and German-speaking Switzerland. We assessed general and specific coronavirus conspiracy beliefs, reasoning biases [jumping-to-conclusions bias (JTC), liberal acceptance bias (LA), bias against disconfirmatory evidence (BADE), possibility of being mistaken (PM)], and paranoid ideation, using established experimental paradigms and self-report questionnaires.

RESULTS

Around 10% of our sample endorsed coronavirus-related CT beliefs at least strongly, and another 20% to some degree. Overall endorsement was similar to levels observed in a UK-based study (Freeman et al., 2020b). Higher levels of conspiracy belief endorsement were associated with greater JTC, greater LA, greater BADE, higher PM, and greater paranoid ideation. Associations were mostly small to moderate and best described by non-linear relationships.

CONCLUSIONS

A noticeable proportion of our sample recruited in Germany and German-speaking Switzerland endorsed coronavirus conspiracy beliefs strongly or to some degree. These beliefs are associated with reasoning biases studied in delusion research. The non-probability sampling approach limits the generalizability of findings. Future longitudinal and experimental studies investigating conspiracy beliefs along the lines of reasoning are encouraged to validate reasoning aberrations as risk factors.

Prolonged rather than hasty decision-making in schizophrenia using the box task. Must we rethink the jumping to conclusions account of paranoia?

Jumping to conclusions (JTC) is the best established cognitive bias in schizophrenia and is increasingly targeted in interventions aimed to improve positive symptoms. To address shortcomings of the standard measure to capture JTC, the beads task, we developed a new variant-the box task-which was subsequently validated in people with elevated psychotic-like experiences. For the first time, the box task was administered in a sample of individuals with manifest schizophrenia. We hypothesized that patients with schizophrenia would display an elevated JTC bias relative to controls.

METHOD

We recruited a large sample of 101 patients with schizophrenia and matched them to an online sample recruited from the general population. In the box task, participants must decide which of two kinds of colored balls are presented more often. Participants are told that the task may end prematurely, and that task performance will be counted as an error if no decision had been made before that point. The primary measure was the number of draws to decision (DTD), where fewer DTD corresponds to greater JTC.

RESULTS

In contrast to expectations, participants with schizophrenia showed significantly higher DTD (i.e., reduced JTC). Consistent with our previous findings, patients also displayed a lowered decision threshold compared to controls. Response confidence for the final decision was lower in patients and correlated with self-esteem and positive symptoms. While there was evidence that previous knowledge of the box task lowered DTD, exclusion of participants with experience on the box task did not substantially change results.

DISCUSSION

The study fits a growing body of experiments casting doubt on the generalizability of the JTC effect in schizophrenia across different tasks. While the study tentatively supports a liberal acceptance account of psychosis, caution is warranted and we recommend that research should explore and control for potentially important mediators (e.g., task difficulty, stress, test-taking attitudes).

Jumping to conclusions in the less-delusion-prone? Further evidence from a more reliable beads task

BACKGROUND

A single meta-analysis has found that healthy people with higher delusion-proneness tend to gather less information (i.e., make fewer draws to decision, or DTD) on the beads task, although the findings of contributing studies were mixed, and the pooled effect size was small. However, using a new and more reliable "distractor sequences" beads task, we recently found a positive relationship between delusion-proneness and DTD in a healthy sample. In the current study, we re-tested this relationship in a new sample, and tested the possibility that the relationship is driven by participant's ability to understand and use odds or likelihood information ("odds literacy").

METHODS

Healthy participants (N = 167) completed the distractor sequences beads task, the Peters Delusions Inventory (PDI) which measures delusion-proneness, a measure of odds literacy, and the Depression, Anxiety, and Stress scale.

RESULTS

PDI and DTD were positively correlated, and comparing PDI quartiles on DTD confirmed a statistically significant trend of increasing DTD with PDI quartile. Odds literacy was positively rather than negatively associated with both DTD and PDI. Anxiety was positively correlated with PDI and DTD.

CONCLUSIONS

We replicated our earlier finding that DTD and delusion-proneness were positively related in a non-clinical sample, but found that increased odds-literacy did not drive lower PDI and DTD, and hence did not explain their covariance. It is possible however that anxiety and co-occurring risk aversion drive increased delusion-proneness and information-gathering, potentially accounting for the positive relationship between PDI and DTD.