The Relationship between Mindful Attention Awareness and Parenting Stress among Chinese Parents
Bibliographic record
Abstract
This study aimed to examine the relationship between parents' mindful attention awareness and their parenting stress. A survey was conducted with 461 parents from various provinces in China, and both correlation and regression analyses were applied to the data. The findings revealed a significant negative correlation between mindful attention awareness and parenting stress (r = -0.235, p < 0.001). Even after controlling for demographic variables such as parent gender, number of children, educational attainment, and socioeconomic status, mindful attention awareness remained a significant negative predictor of parenting stress (β = -0.232, t = -5.061, p < 0.001). Moreover, socioeconomic status was also found to have a significant influence on parenting stress. These results suggest that enhancing parents' mindful attention awareness may help alleviate parenting stress, improve parent–child relationships, and foster overall family functioning. Theoretically, this study expands the cross-cultural understanding of the relationship between mindful attention awareness and parenting stress, while practically, it provides valuable insights for developing targeted interventions to support parents. Future research should consider employing longitudinal designs and incorporating multiple measurement methods to further explore the mechanisms underlying mindful attention awareness in diverse parenting contexts.
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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 | 0.002 |
| 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) | 0.001 | 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".