Stress, Resilience, and the Immune System: A Health Psychology Analysis
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
To investigate the relationship between stress resilience and immune system functionality, emphasizing the psychological mechanisms that contribute to immune regulation and the potential for resilience-building interventions to enhance immune responses. This comprehensive review synthesizes existing research from psychological, immunological, and epidemiological studies. It examines the impact of acute and chronic stress on immune function, explores the role of psychological resilience as a mediator, and evaluates the effectiveness of various stress management and resilience-building strategies. Evidence indicates a significant link between psychological resilience and stronger immune function. Individuals with higher resilience levels exhibit better immune responses, likely due to the effective management of stress and its physiological consequences. Additionally, interventions aimed at increasing resilience, such as mindfulness practices, cognitive-behavioral therapy, and lifestyle changes, have shown promise in bolstering immune health. Strengthening psychological resilience holds substantial potential for improving immune system outcomes, suggesting a need for holistic health approaches that incorporate mental, physical, and social well-being components. Future research should focus on identifying specific mechanisms through which resilience affects immune function and developing targeted interventions to enhance both psychological well-being and immune health.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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 | 0.000 | 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