Unraveling the Pathways from Mindfulness to Wellbeing: Mediating Role of Self Compassion and Caring for Bliss in Adults
Bibliographic record
Abstract
Mindfulness which was an area of scientific study has developed as a field of research and growth and attracts people and therapists who wish to possess more knowledge on how it can enhance people’s lives. This research therefore aims at identifying the influence of mindfulness on the two aspects of wellbeing “Caring for Bliss” and “Self-Compassion” during the developmental phase referred to as emerging adulthood. This research shall be a survey study in which the nature is correlational. The technique used to select the sample will be convenience sampling. Thus, a sample (N= 219) is selected with age from 18 to 29 using 4 instruments of collection. Namely, the instruments are; the Toronto Mindfulness Scale (TMS), the Caring for Bliss Scale (CBS), the Self compassion Scale Short Form (SCS-SF), WHO-5 Wellbeing Index. After collecting the data, Correlation and Regression analysis are run for the existence of the relationship and its consequences on the identified members of the population by employing Statistical Package for Social Sciences (SPSS). Besides, in Haye’s model 5, the macro process of the chain mediation and gender as moderator is applied to establish. It was also noted that although the impact of mindfulness on the respondents’ wellbeing could be ascertained, it was only possible to estimate the influence of the intermediate variable ‘caring for bliss’ as moderate. Therefore, chain mediation was not present in the given scenario; however, gender influenced it greatly. Hence, this inconsistency in the findings of the study may be attributed to self-report.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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".