Self‐Transcendence as a Risk and Resilience Factor in Individuals at Clinical High Risk for Psychosis
Bibliographic record
Abstract
AIM: Self-transcendence is a personality feature and psychological resource that involves feelings of connectedness with the universe, all of humanity, and the individual self. Self-transcendence has been positively associated with both positive psychotic symptoms and clinical high risk for developing psychosis status, but studies reporting these findings focus solely on the connectedness-with-universe aspect of self-transcendence. The broader self-transcendence literature, which also includes connection with humanity and oneself, robustly supports self-transcendence as an indicator of well-being. Given this discrepancy, we sought to understand whether self-transcendence should be considered a risk or resilience factor for youth at clinical high risk. METHODS: We operationalised self-transcendence using two more holistic measures novel to the clinical high risk population. Clinical high risk participants (n = 42) and healthy controls (n = 44) completed the Adult Self-Transcendence Inventory and participated in narrative life story interviews which were coded for self-transcendence themes. RESULTS AND DISCUSSION: Clinical high risk individuals scored lower than healthy controls on measures of self-transcendence, functioning, and life satisfaction. However, there were no group differences in the relationships between self-transcendence and measures of well-being. CONCLUSION: Our findings suggest self-transcendence is a part of healthy personality development that may be impacted in clinical high risk individuals yet may still function as a psychological resource for this population, pointing toward new avenues for intervention in clinical high risk and other mental health populations.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".