How to be happy from east to west: social and flexible pursuit of happiness is associated with positive effects of valuing happiness on well-being
Bibliographic record
Abstract
Abstract Recent evidence has suggested that valuing happiness to an extreme degree has a potential downside in Western but not in East Asian countries. We tested how valuing happiness relates to well-being in mainland China (N = 721) and Western countries (UK, US, and Canada) (N = 349) in two online survey studies. We predicted that pursuing happiness in a socially engaged yet flexible (i.e., feasible and achievable) way underlies a positive association between valuing happiness and well-being. Indeed, in study 1, a socially engaged definition of happiness mediated the relationship between valuing happiness and well-being in a Chinese sample. Specifically, increased valuing happiness was associated with a higher socially engaged definition of happiness, which in turn was related to higher well-being. Demonstrating the role of flexibility in pursuing happiness, Chinese participants reported more items overall and more feasible items to achieve happiness, though not more social items than participants in the Western sample). In study 2, we repeated the study during the Covid-19 lockdown in Chinese (N = 308) and Western (N = 185) samples and also tested if participants were able to adopt a mindset of flexibly pursuing happiness by adding a survey with social actions that were still feasible (e.g., a call instead of meeting in-person). We found the association holds in times of emotional stress and social restrictions in both samples, suggesting that people flexibly pursue social activities that relate to happiness. We propose that a socially engaged but also feasible and flexible way to pursue happiness is associated with higher well-being.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".