The Q-Life experience: An evaluation of an employee resilience program
Bibliographic record
Abstract
BACKGROUND: Many employers are turning to training programs to help them cope or flourish in life. Many programs on the market have not been validated. OBJECTIVE: The objective was to evaluate the effect building awareness and skill development can have on sustaining high resilience within a group of employees. METHODS: 524 participants completed the 44 itemed Q-Life assessment. A CFA model was conducted to determine whether the Q-Life score, adequately describes the data. 116 employees signed up to the Q-Life experience with 64 completing all requirements. RESULTS: The RMSEA index was less than 0.08, RMSEA = 0.07, 90%CI = [0.07, 0.07], which is indicative of a good model fit. The mean of score for resilience on the first test (M = 249.91) was significantly lower than the mean of post-test (M = 264.91). CONCLUSIONS: The results indicated that the model demonstrated acceptable fit to the data and can be used as an assessment tool for the Q-Life. The Q-Life experience showed significant improvement in resilience.
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How this classification was reachedexpand
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 | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".