Induction of acute stress through an internet-delivered Trier Social Stress Test as assessed by photoplethysmography on a smartphone
Bibliographic record
Abstract
Recent studies have demonstrated the feasibility of administering the Trier Social Stress Test (TSST) through the internet, with major implications for promoting inclusivity in research participation. However, online TSST studies to date are limited by a lack of control groups and the need for biological measures of stress reactivity that can be fully implemented online. Here, we test smartphone-based photoplethysmography as a measure of heart rate reactivity to an online variant of the TSST. Results demonstrate significant acceleration in heart rate and heightened self-reported stress and anxiety in the TSST condition relative to a placebo version of the TSST. The placebo condition led to a significant increase in self-reported stress and anxiety relative to baseline levels, but this increase was smaller in magnitude than that observed in the TSST condition. These findings highlight the potential for smartphone-based photoplethysmography in internet-delivered studies of cardiac reactivity and demonstrate that it is critical to utilize random assignment to a control or stressor condition when administering acute stress online.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".