Resilience: A psychobiological construct for psychiatric disorders
Bibliographic record
Abstract
Understanding of psychopathology of mental disorder is evolving, particularly with availability of newer insight from the field of genetics, epigenetics, social, and environmental pathology. It is now becoming clear how biological factors are contributing to development of an illness in the face of a number of psychosocial factors. Resilience is a psychobiological factor which determines individual's response to adverse life events. Resilience is a human capacity to adapt swiftly and successfully to stressful/traumatic events and manage to revert to a positive state. It is fundamental for growth of positive psychology which deals with satisfaction, adaptability, contentment, and optimism in people's life. Of late, there has been a paradigm shift in the understanding of resilience in context of stress risk vulnerability dimension. It is a neurobiological construct with significant neurobehavioral and emotional features which plays important role in deconstructing mechanism of biopsychosocial model of mental disorders. Resilience is a protective factor against development of mental disorder and a risk factor for a number of clinical conditions, e.g. suicide. Available information from scientific studies points out that resilience is modifiable factor which opens up avenues for a number of newer psychosocial as well as biological therapies. Early identification of vulnerable candidates and effectiveness of resilience-based intervention may offer more clarity in possibility of prevention. Future research may be crucial for preventive psychiatry. In this study, we aim to examine whether resilience is a psychopathological construct for mental disorder.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".