Psychological Stress and Antibody Response to Influenza Vaccination: When Is the Critical Period for Stress, and How Does It Get Inside the Body?
Bibliographic record
Abstract
OBJECTIVES: This study attempted to determine whether stress of moderate intensity could modulate the antibody response to an influenza vaccination in healthy young adults, identify critical periods during which stress could influence antibody response, and delineate behavioral and biological pathways that might explain relations between stress and antibody. METHODS: A cohort of 83 healthy young adults underwent 13 days of ambulatory monitoring before, during, and after vaccination. Four times daily, subjects reported the extent to which they felt stressed and overwhelmed and collected a saliva sample that was later used to measure cortisol. A battery of health practices (cigarette smoking, alcohol use, physical activity, sleep hygiene) was assessed daily. Antibody titers to the vaccine components were measured at baseline and at 1-month and 4-month follow-up assessments. RESULTS AND CONCLUSIONS: To the extent that they reported higher levels of stress across the monitoring period, subjects exhibited poorer antibody responses to the New Caledonia strain of the vaccine. Stress ratings on the 2 days before the vaccine and the day it was given were not associated with antibody response. However, the 10 days afterward appeared to be a window of opportunity during which stress could shape the long-term antibody response to varying degrees. With respect to potential mediating pathways, little evidence emerged in favor of cortisol secretion, alcohol consumption, physical activity, or cigarette smoking. However, analyses were consistent with a pattern in which feelings of stress and loss of sleep become locked into a feed-forward circuit that ultimately diminishes the humoral immune response. These findings may shed light on the mechanisms through which stress increase vulnerability to infectious disease.
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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 | 0.000 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".