Development of successful ageing multidimensional assessment scale and its reliability and validity
Bibliographic record
Abstract
Objective According to the theoretic framework of successful ageing,this study developed a multidimensional Successful Ageing Assessment Scale and tested its reliability and validity.Methods Through literature review,the study determined evaluative dimension,structure and scoring method.Then,the Successful Ageing Multidimensional Assessment Scale(SAMAS) was developed and was optimized by the expert consultation,semi-structured interview and twice tests.The predicted sample was conducted with item analysis,and testing of reliability and validity; the formal tested sample was conducted with item analysis,conformance testing and testing of reliability and validity.Then the formal tested sample was tested and retested two weeks later.The intestine emendatory Activities of Daily Living Scale (ADL),Mini Mental State Examination Scale (MMSE),Social Disability Screening Schedule (SDSS) and Memorial University of Newfoundland Scale of Happiness(MUNSH) were used to test its criteri-on validity.Results SAMAS consisted of 5 dimensions,including chronic disease state,physical perfor-mance,cognitive function,social function,subjective well-being.Item analysis showed the dimensions of scale and total scale scores had positive correlation.In conformance testing,the Kappa value was 0.65～0.86,test-retest reliability was 0.66～0.85 and the internal consistency reliability was 0.88.The correl-ative coefficient of the physical performance and social function scores were negatively correlated with ADL scores and SSDS scores,the correlative coefficient of the cognitive function and subjective well-being scores were positively correlated with MMSE scores and MUNSH scores.Conclusions SAMAS suggested good reliability,validity and could well evaluate comprehensive health for the elderly,at the same time could distinguish between SA and non SA group. Key words: Successful ageing; Multidimensional health measurement; Scale 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 | 0.009 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".