Rising tide of stress: Global trends and structural predictors over 18 years
Bibliographic record
Abstract
• Across 146 countries, the odds of stress report increased by twofold in 18 years. • Existing disparities across gender, age, and income escalated over the years. • The rise in stress is particularly evident in countries becoming more fragile. Mounting evidence points to stress being a transdiagnostic contributing factor to health conditions. Given the health significance of stress, characterizing macro-level spatiotemporal trends and disparities of stress is necessary to understanding stress and its potential health burden across populations. The need to investigate structural factors contributing to stress is further underscored by the escalating instability worldwide over the past decade, which can trigger a stress response and lead to adverse health outcomes if left unaddressed. This study used nationally representative surveys ( N = 2461,226; 146 countries) in 2006–2023 and the Fragile State Index ( N = 137 countries) to i) describe global stress trends varied by world regions and demographic groups, and ii) examine whether nation-level state fragility, a summative measure that aggregates 12 economic, social, and political indicators to assess a state’s risk of collapse or conflict, predicts steeper increases in stress over time. A state’s level of fragility may contribute to individuals’ perceived stress and in turn have profound consequences for population physical and mental health. The current study reveals an alarming increase in stress globally and calls for prioritizing structural approaches to reverse this trend. By doing so, we not only reduce stress but also its related disease burden.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| 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 | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".