Self-Transcendence as a Buffer Against COVID-19 Suffering: The Development and Validation of the Self-Transcendence Measure-B
Bibliographic record
Abstract
The age of COVID-19 calls for a different approach toward global well-being and flourishing through the transcendence suffering as advocated by existential positive psychology. In the present study, we primarily explained what self-transcendence is and why it represents the most promising path for human beings to flourish through the transformation of suffering in a difficult and uncertain world. After reviewing the literature on self-transcendence experiences, we concluded that the model of self-transcendence presented by Frankl is able to integrate both of the characteristics associated with self-transcendence. Afterward, we discussed how the self-transcendence paradigm proposed by Wong, an extension of the model by Frankl, may help awaken our innate capacity for connections with the true self, with others, and with God or something larger than oneself. We presented self-transcendence as a less-traveled but more promising route to achieve personal growth and mental health in troubled times. Finally, we presented the history of the development and psychometrics of the Self-Transcendence Measure-Brief (STM-B) and reported the empirical evidence that self-transcendence served as a buffer against COVID-19 suffering. The presented data in the current study suggested that the best way to overcome pandemic suffering and mental health crises is to cultivate self-transcendence.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 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".