Depression, Anxiety, Stress, and Adjustments among Malaysian Gifted Learners: Implication towards School Counseling Provision
Bibliographic record
Abstract
Gifted learners have special characteristics which make them unique individuals. However, just like their normative group, gifted learners experience some psychological issues that hinder their ability to adjust in new environments. This study aims to examine levels of depression, anxiety, stress, and adjustments (psychological, social and emotional) faced by Malaysian gifted learners in school. It also investigates the relationship between all these variables under study. A total of 112 students aged 16 years old were involved in the study. The study employs a cross-sectional survey design, and the data was collected using two sets of questionnaires namely, the Depression, Anxiety, and Stress Scales (DASS), and the Social Well-Being Questionnaire (SWBQ). Data shows that local gifted learners experienced some form of depression, anxiety and stress. It is also found that the participants have high levels of psychological, social and emotional adjustments. Strong positive correlations were found between depression with anxiety and stress, whereas negative correlation was found between depressions with all forms of adjustment. The findings of this research provided a fundamental basis to be used in the future development of counseling provision for gifted educational programs in local school context.
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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 | 0.000 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".