Twenty-five years later: How consistent are studies using the Trier Social Stress Test protocol - A Systematic Review of its methodology
Bibliographic record
Abstract
Since its development in 1993, the Trier Social Stress Test (TSST) has been used widely as a psychosocial stress paradigm to activate the sympathetic nervous system and hypothalamic-pituitary-adrenal axis (HPAA) stress systems, stimulating physiological functions (e.g. heart rate) and cortisol secretion. Several methodological variations introduced over the years have led the scientific community to question replication between studies. In this systematic review, we used the Preferred Reporting Items of Systematic Reviews and Meta-Analysis (PRISMA) to synthesize procedure-related data available about the TSST protocol to highlight commonalities and differences across studies. We noted significant discrepancies across studies in how researchers applied the TSST protocol. In particular, we highlight variations in testing procedures (e.g., number of judges, initial number in the arithmetic task, time of the collected saliva samples for cortisol) and discuss possible misinterpretation in comparing findings from studies failing to control for variables or using a modified version from the original protocol. Further, we recommend that researchers use a standardized background questionnaire when using the TSST to identify factors that may influence physiological measurements in tandem with a summary of this review as a protocol guide. More systematic implementation and detailed reporting of TSST methodology will promote study replication, optimize comparison of findings, and foster an informed understanding of factors affecting responses to social stressors in healthy people and those with pathological conditions. Keywords: Trier Social Stress Test, Stress paradigm, Protocol, Systematic Review, Standardization
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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 | 0.220 | 0.516 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.014 | 0.017 |
| Bibliometrics | 0.018 | 0.013 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.012 | 0.016 |
| Open science | 0.005 | 0.006 |
| Research integrity | 0.007 | 0.005 |
| Insufficient payload (model declined to judge) | 0.006 | 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".