The EvalUation of goal-diRected activities to prOmote well-beIng and heAlth (EUROIA) scale: Psychometric evaluation with Confirmatory Factor Analysis
Bibliographic record
Abstract
OBJECTIVES: While state-based models of health-related quality of life (HRQL) are well-established in providing clinically relevant descriptions of HRQL status, they do not provide information on how to maintain or improve HRQL. The EvalUation of goal-diRected activities to prOmote well-beIng and heAlth (EUROIA), rooted in a novel process-based model of HRQL, measures goal-directed activities that are self-reported to promote HRQL as part of an individual's process of adapting to dynamic changes in health status. Our objectives were to condense and summarize the psychometric properties of the EUROIA by (i) defining and confirming its factor structure, (ii) evaluating its construct validity, and (iii) examining its internal consistency. METHODS: Principal component analysis was performed on the 18-item EUROIA to explore the underlying factor structure and condense the scale. Confirmatory factor analysis was conducted on the revised 14-item, 4-factor structure EUROIA instrument to evaluate the model fit. Data was obtained from adult participants with a diagnosis of chronic heart failure or advanced chronic kidney disease from 3 hospitals in Toronto, Canada. RESULTS: The revised 14-item EUROIA demonstrated 4 dimensions-Social Affiliation, fulfillment of Social Roles and Responsibilities, Self-Affirmation, and Eudaimonic Well-being-with a Cronbach's alpha of 0.83, representing good internal consistency. Our confirmatory factor analysis final model achieved good overall model fit: (χ2 / df = 1.80; Tucker-Lewis index = 0.90; comparative fit index = 0.93; standardized root-mean-square residual = 0.06; root-mean-square error of approximation = 0.06). All items exhibited a factor loading greater than λ > 0.4 and p < 0.001. CONCLUSION: The EUROIA holds clinical potential in its ability to provide informed feedback to patients on how they might maintain or modify their use of goal-directed activities to maintain and optimize perceived well-being.
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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 | 0.016 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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".