The Influence of Resilience on Psychological Well-Being of Malaysian University Undergraduates
Bibliographic record
Abstract
Psychological well-being is fundamental to the overall health of undergraduates, particularly to enable them to address challenges at the university. A review of related literature showed that there are various factors influencing individual’s psychological well-being. The purpose of this study is to investigate the influence of resilience on the psychological well-being of university undergraduates. For this purpose, a total of 200 undergraduates from local public universities (male = 90, female = 110) participated in this exploratory study. Responses were analysed using Smart PLS 3.0 to model the influence of the two variables. Results demonstrated two significant findings. Firstly, reliable and valid adapted instruments measuring resilience and psychological well-being were established, and secondly, resilience is a significant predictor and it explained 48.2% variance in psychological well-being. The findings are discussed in relation to the development of a model that relates the two constructs.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".