Development and Validation of Retirement Anxiety Scale for Secondary School Teachers in Osun State, Nigeria
Bibliographic record
Abstract
The study conducted a factor analysis of Retirement Anxiety Scale (RAS) for secondary school teachers. It developed a set of appropriate and homogeneous items on retirement anxiety suitable for Nigerian school teachers. It also determined the reliability indices of the scale and established its factor structure. The study population comprised all secondary school teachers in Osun state. Teachers that had less than ten years to retire from the service were the targeted population. A sample size of 204 teachers was purposively selected from four randomly selected local government of the state, based on the years left in service. The selected teachers completed the Retirement Anxiety Scale (RAS). The result was subjected to Principal Component Analysis with varimax rotation (PCA). The results of the PCA revealed that the communality h2 of each item was more than 0.5, which implied a satisfactory quality. The KMO > 0.8 showed that the data were sufficiently enough to undergo factor analysis, while the Barlett sign p < 0.001 revealed a sensible PCA. The reliability coefficient Cronbach α was statistically significant (0.863) indicating a high degree of internal consistency. The study concluded that the RAS instrument was valid and reliable for measuring retirement anxiety among secondary school teachers and also found suitable for Nigerian schools. The six-components released by the PCA could be used as a guide for school counsellors in pre-retirement counselling of secondary school teachers.
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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".