The Relative Contribution of Mindfulness and Gratitude in Predicting Happiness among University Students
Why this work is in the frame
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Bibliographic record
Abstract
The present study aims at identifying the separate and interactive contribution of gratitude and mindfulness in predicting happiness; examining the relationship between these variables; identifying differences between students with high happiness and students with low happiness in gratitude and mindfulness; and identifying the levels of gratitude, mindfulness, and happiness among the students of Princess Nourah Bint Abdulrahman University. The research sample consisted of 447 female students aged 18-25 years. The research instruments included the Toronto Mindfulness Scale, the Oxford Happiness Questionnaire, as well as the Gratitude, Resentment, and Appreciation Test-Short form. The study found out that gratitude and mindfulness had a significant contribution in predicting happiness among university students (31% and 41.5%, respectively). The interaction between the total scores of mindfulness and gratitude contributed 51.5% of the variance in happiness among university students. The interaction between mindfulness, sense of abundance, and simple appreciation contributed 54.4% of the variance in happiness among university students. The study found a positive correlation between mindfulness, gratitude (sense of abundance, simple appreciation, appreciation of others), and happiness. Additionally, it was found that students at Nourah Bint Abdulrahman University had moderate levels of mindfulness and moderate to high levels of gratitude and happiness. The sense of abundance domain was moderate, the simple appreciation domain was high, and the appreciation of others domain was moderate. Mindfulness, gratitude, sense of abundance, simple appreciation, and appreciation of others increased among the students with high happiness. Received: 8 March 2021 / Accepted: 22 June 2021 / Published: 8 July 2021
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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 | 0.002 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it