Validation of a New Family Values Scale Among Older Chinese Adults
Bibliographic record
Abstract
Abstract Objective To examine the reliability, validity, and factor structure of the Family Values Scale among older Chinese adults. Background Family values shape caregiving practices, intergenerational relationships, and health outcomes in later life. In China, rapid social change has transformed traditional filial norms, yet few validated instruments capture contemporary family values among older adults. Method We applied Dima’s six-step psychometric validation protocol using data from the 2018 China Longitudinal Ageing Social Survey (CLASS; N = 11,418). Exploratory and confirmatory factor analyses assessed dimensionality, while internal consistency, measurement invariance, and sensitivity analyses evaluated reliability and robustness. Results After removing two poorly performing items, the revised six-item scale demonstrated good internal consistency (Cronbach’s α = 0.80) and strong model fit in confirmatory factor analysis (CFI = 0.98; TLI = 0.96; RMSEA = 0.06). All factor loadings exceeded recommended thresholds, supporting a unidimensional structure that was invariant across key sociodemographic groups. Conclusion The six-item Family Values Scale is a reliable and valid instrument for measuring contemporary family values among older Chinese adults. Implications This parsimonious scale can be used in large population studies and policy evaluations to better understand family-based care and ageing in rapidly changing societies.
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".