The Role of Grit and Zest for Life in Enhancing Work Engagement: A Cross-Sectional Study
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Bibliographic record
Abstract
This study aims to investigate the relationships between work engagement, grit, and zest for life among working adults. Specifically, it examines how grit and zest for life predict work engagement, providing insights into the psychological traits that foster employee motivation and productivity. A cross-sectional design was employed, involving 153 participants selected based on the Morgan and Krejcie table. Data were collected using three standardized tools: the Utrecht Work Engagement Scale (UWES) for measuring work engagement, the Grit Scale (Grit-O) for assessing grit, and the Zest for Life subscale from the Values in Action Inventory of Strengths (VIA-IS). Pearson correlation coefficients were calculated to examine relationships between variables, and linear regression analysis was used to determine the predictive power of grit and zest for life on work engagement. Analyses were conducted using IBM SPSS Statistics version 27. Descriptive statistics indicated moderate to high levels of work engagement (M = 4.52, SD = 1.12), grit (M = 3.84, SD = 0.76), and zest for life (M = 4.11, SD = 0.89). Correlation analysis revealed significant positive relationships between work engagement and grit (r = 0.62, p < .001) and zest for life (r = 0.58, p < .001). Regression analysis showed that grit (B = 0.45, p < .001) and zest for life (B = 0.39, p < .001) significantly predict work engagement, explaining 53% of its variance (R² = 0.53, F(2, 150) = 83.56, p < .001). The study demonstrates that both grit and zest for life are significant predictors of work engagement. These findings suggest that fostering perseverance and enthusiasm among employees can significantly enhance their engagement at work. The results have practical implications for organizational leaders and HR practitioners aiming to improve employee motivation and productivity.
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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 | 0.000 |
| 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 | 0.000 |
| 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