Association Between Wisdom and Psychotic-Like Experiences in the General Population: A Cross-Sectional Study
Bibliographic record
Abstract
Introduction Wisdom has been empirically researched as a complex psychological characteristic that is associated with many mental health outcomes. However, its association with psychotic-like experiences (PLEs) remains unclear. This is the first work to assess wisdom, explore its association with PLEs, and test its moderating effect on the relation between the frequency of PLEs and their associated distress in the general population. Methods From January 29th to February 5th, 2021, our online self-administered survey recruited 927 participants (ages 14 to 65) from thirteen Chinese provinces. Convenience sampling was employed. We measured wisdom with the 12-item three-dimensional wisdom scale (3D-WS-12) and PLEs with the 15-item positive subscale of the Community Assessment of Psychic Experiences (CAPE-P15). Results Using the cut-off value of 1.47 in the mean frequency score, we divided our participants into high-PLEs group (188, 22.1%) and low-PLEs group (663, 77.9%). Three-dimensional wisdom score was decreased in the high-PLEs group compared to the low-PLEs group (Kruskal-Wallis t = 59.9, p < 0.001). Wisdom was associated with less frequent PLEs (Spearman’s rho = −0.21, p < 0.01) and lower distress related to PLEs (Spearman’s rho = −0.28) in the high-PLEs group (all above p < 0.001), which were replicated in the low-PLEs group. Notably, wisdom significantly attenuated the distress associated with PLEs [coefficient = −0.018, Bootstrap 95% CI (−0.029, −0.008)], but only in the low-PLEs group. Conclusion Our results implicated that wisdom could protect individuals from distressful subclinical psychotic symptoms and wiser individuals have better general mental health.
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How this classification was reachedexpand
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 | 0.002 | 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 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".