Association of Perceived Xingfu With Health-Related and Socioeconomic Factors Among Hong Kong Chinese Adults: Cross-Sectional Study Using a Novel Single-Item Tool
Bibliographic record
Abstract
Background: Xingfu (), a Chinese term, holds meanings that transcend Western concepts of happiness; it is modern and highly valued in China. Despite its centrality to China's national discourse on xingfu, there are no validated tools for measuring perceived xingfu, particularly in Hong Kong's unique sociopolitical context. Postpandemic recovery efforts and widening socioeconomic disparities in Hong Kong highlight the urgency of understanding indicators such as perceived xingfu. Objective: This study aimed to develop and validate the first single-item measure of perceived xingfu and examine its association with health-related and socioeconomic factors among Hong Kong Chinese adults, addressing gaps in culturally tailored assessment. Methods: Our cross-sectional online survey included 5070 Hong Kong Chinese adults in 2023. Perceived xingfu was measured using a novel, single-item, 11-point scale from 0 to 10, with higher scores indicating better perceived xingfu. Two-week test-retest showed high reliability (intraclass correlation coefficient of 0.78). We used regression models to analyze associations between perceived xingfu score and high perceived xingfu (defined as ≥7) with mutually adjusted study variables; all estimates were weighted based on 2022 Hong Kong population data. Results: The mean perceived xingfu score was 6.3 (SD 2.2). Perceived xingfu score was associated with happiness (r=0.85), perceived mental health (r=0.65), and adversity coping capability (r=0.50) and negatively associated with perceived stress (r=-0.56), past 7-days loneliness (r=-0.52), anxiety symptoms (r=-0.45), and depressive symptoms (r=-0.52). Female sex (β=0.69, adjusted odds ratio [aOR] 2.11), older age (β=0.46, aOR 2.67), having post-secondary education or above (β=0.19, aOR 1.35), higher monthly household income (≥ HKD60,000: β=0.99, aOR 3.04), living in owned properties (β=0.27, aOR 1.57), being retired (β=0.56, aOR 1.18), and excellent versus poor self-rated health (β=3.84, aOR 40.72) were associated with higher perceived xingfu score or high perceived xingfu (all Ps or Pstrend<0.001). Conclusions: This study pioneers the perceived xingfu measurement in a Chinese population using a concise, validated tool. Significant socioeconomic disparities and health associations highlight perceived xingfu's relevance to policy priorities, including equitable resource allocation and health support. Our single-item perceived xingfu tool offers practical utility for population surveillance and cross-cultural comparisons. Future research should explore longitudinal trends and integrate perceived xingfu into public health frameworks.
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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 | 0.001 | 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 | 0.001 |
| 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".