A Study to Assess the Knowledge regarding Alzheimer's Disease among people above 45 years of age in selected areas at kollam
Bibliographic record
Abstract
The research project undertook was “study to assess the knowledge regarding Alzheimer’s disease among people above 45 years of age in selected areas at Kollam”. The objectives of the study were to assess the knowledge regarding Alzheimer’s disease among people above 45 years of age selected areas at Kollam, to find out the association between knowledge regarding Alzheimer’s disease among people above 45 years of age and selected demographic variables such as age, sex, educational qualification, occupation economic status, nutritional status. Non experimental survey design was adopted for this study. The study was conducted among 60 people above 45 years of age in selected areas at kollam. In order to assess the knowledge regarding alzhemiers disease, the study sample was selected by non-probability convenient sampling technique. The tool used for the data collection consisted of demographic performa and structured questionnaire, basic information of the study was given to subjects. The analysis of the data was based on objectives of the study using descriptive and inferential statistics. The findings of the study revealed that there was no significant association between knowledge and demographic variables like age, sex, educational qualification, occupation, economic status, Nutritional status. Based on the findings investigator has drawn implications which were of vital concerns in the field of nursing practice, nursing administration, nursing pattern, nursing education for the future development.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".