Item-specific overlap between hallucinatory experiences and cognition in the general population: A three-step multivariate analysis of international multi-site data
Why this work is in the frame
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Bibliographic record
Abstract
Hallucinatory experiences (HEs) can be pronounced in psychosis, but similar experiences also occur in nonclinical populations. Cognitive mechanisms hypothesized to underpin HEs include dysfunctional source monitoring, heightened signal detection, and impaired attentional processes. Using data from an international multisite study on non-clinical participants (N = 419), we described the overlap between two sets of variables - one measuring cognition and the other HEs - at the level of individual items. We used a three-step method to extract and examine item-specific signal, which is typically obscured when summary scores are analyzed using traditional methodologies. The three-step method involved: (1) constraining variance in cognition variables to that which is predictable from HE variables, followed by dimension reduction, (2) determining reliable HE items using split-halves and permutation tests, and (3) selecting cognition items for interpretation using a leave-one-out procedure followed by repetition of Steps 1 and 2. The results showed that the overlap between HEs and cognition variables can be conceptualized as bi-dimensional, with two distinct mechanisms emerging as candidates for separate pathways to the development of HEs: HEs involving perceptual distortions on one hand (including voices), underpinned by a low threshold for signal detection in cognition, and HEs involving sensory overload on the other hand, underpinned by reduced laterality in cognition. We propose that these two dimensions of HEs involving distortions/liberal signal detection, and sensation overload/reduced laterality may map onto psychosis-spectrum and dissociation-spectrum anomalous experiences, respectively.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it