Attitude to Ageing As a Predictor of Subjective Health and Quality of Life Among Older People in Delta State, Nigeria
Bibliographic record
Abstract
OBJECTIVE: The study investigated attitude to ageing as a predictor of subjective health and quality of life among the older people in Ika South Local Government Area, Delta State. Three research questions guided the study. METHOD: The population of the study comprised 6,670 older people 3,323 males and 3347 females in Ika South Local Government Area of Delta State. The sample size of the study is 667 older people in Ika South Local Government Area of Delta State. A multi-stage random sampling technique was used to get the sample size for the study. Two stages of selection were used in order to draw the sample for the study. For the first stage, simple sampling technique was used to draw 11 communities out of 22 communities in the study area. In second stage 10% of the study population was used. The questionnaires were validated by two experts from guidance and counselling and one from measurement and evaluation. Reliability of the instrument was determined using Cronbach Alpha method reliability estimate. Copies of the questionnaire were administered directly to the respondents. Linear regression was used for the data analysis. RESULTS: The finding of the study revealed that older people of Ika South Local Government Area maintains positive attitude to ageing, that attitude to ageing is not a predictor of subjective health among older people of Ika South Local Government Area and attitude to ageing does not significantly predict quality of life among people of Ika South Local Government Area. CONCLUSION: Based on the finding of the study, government and professional guidance counsellors should make use of the information generated from the study to organize workshop training for older people on what constitute subjective health quality of life and what constitute positive attitude to ageing. 
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".