Embodied and embedded mindfulness: a mindful path to well-being
Bibliographic record
Abstract
While there is a growing interest in mindfulness as an intrapersonal trait, only a limited number of studies have investigated interpersonal mindfulness, and no study has examined the interaction between both concepts. This paper aims to evaluate a path model that depicts the role of both intrapersonal and interpersonal mindfulness in facilitating emotion regulation and improving well-being by mitigating the effects of psychological symptoms and enhancing social connectedness and safeness. Additionally, this study aims to compare the results obtained using different measures of intrapersonal and interpersonal mindfulness. Moreover, the study evaluates an alternative path model. A sample of 353 participants completed various measures of intrapersonal and interpersonal mindfulness, emotion dysregulation, psychological symptoms (stress, anxiety, and depression), social connectedness, social safeness, satisfaction with life, and happiness. The findings supported the proposed path model, indicating that emotion regulation mediated the relationship between intrapersonal and interpersonal mindfulness on one side and psychological symptoms and social connectedness and social safeness on the other side. Furthermore, the findings suggested that psychological symptoms and social related measures mediated the associations between emotion regulation and well-being. The same path model was supported when using different sets of mindfulness measures. The alternative path was not supported. This study enhances our understanding of how intrapersonal and interpersonal mindfulness interact together to promote emotion regulation, improve well-being, mitigate psychological symptoms, and foster social relatedness and safeness. The findings highlight the importance of training both intrapersonal and interpersonal mindfulness skills to enhance well-being. Implications and limitations are thoroughly discussed.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".