T70. DUAL-PROCESS THEORY, CONFLICT PROCESSING, AND DELUSIONAL BELIEF
Bibliographic record
Abstract
Abstract Background Individuals endorsing delusions exhibit multiple reasoning biases, including a bias toward lower decision thresholds, a bias toward gathering less data before forming conclusions, and a bias toward discounting evidence against one’s beliefs. Although these biases have been repeatedly associated with delusions, it remains unclear how they might arise, how they might be interrelated, and whether any of them play a causal role in forming or maintaining delusions. Progress toward answering these questions may be made by examining delusion-related reasoning biases from the perspective of dual-process theories of reasoning. Dual-process theories posit that human reasoning proceeds via two systems: an intuitive system (which is autonomous, does not require working memory) and an analytic system (which relies on working memory, supports hypothetical thought). Importantly, when the outputs of one or both systems conflict with one another, successful detection of this conflict is thought to produce additional engagement in analytic reasoning. Thus, the detection of and ensuing neurocognitive response to conflict may modulate analytic reasoning engagement. Working from this dual-process perspective, recent theories have hypothesized that more limited engagement in analytic reasoning, perhaps resulting from conflict processing deficits, may engender delusion-inspiring reasoning biases in people with schizophrenia. Methods Given this hypothesis, a literature review (Bronstein et al., 2019, Clinical Psychology Review, 72, 101748) was conducted to critically evaluate whether impaired conflict processing might be a primary initiating deficit in pathways relevant to the generation of delusion-relevant reasoning biases and the formation and/or maintenance of delusions themselves. Results Research examined in this review suggested that in healthy people, successful conflict detection raises decision thresholds. Conflict-processing deficits in delusional individuals with schizophrenia might impair this process. Consistent with this possibility, delusional individuals with schizophrenia (vs. healthy controls) make more decisions when they perceive their favored choice to be only marginally better than alternatives. Lower decision thresholds in individuals who endorse delusions may limit analytic thinking (which takes time). Reductions in decision-making thresholds and in analytic reasoning engagement may encourage these individuals to jump to conclusions, potentially promoting delusion formation, and may also increase bias against disconfirmatory evidence, which may help delusions persist. Discussion Extant literature suggests that conflict processing deficits might encourage delusion-related cognitive biases, which is broadly consistent with the idea that these deficits may be causally primary in pathways leading to delusions. This conclusion lends credence to previous theories suggesting that reduced modulation toward analytic reasoning in the presence of conflict might promote delusions. Future research should attempt to more specifically determine the source of deficits related to analytic reasoning engagement in delusional individuals with schizophrenia. It is often unclear whether analytic-reasoning-related deficits observed in existing literature result from impairments in conflict detection, responsiveness to conflict, or both. Tasks used to study dual-process reasoning in the general population may be useful platforms for specifying the nature of analytic-reasoning-related deficits in delusional individuals with schizophrenia.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".