Exploring the invariance of the Wellbeing Literacy 6-item (Well-Lit 6) Scale between Brazilian and French-Canadian populations
Bibliographic record
Abstract
Abstract | Introduction/Objective: Wellbeing literacy refers to the ability to understand, communicate, and apply knowledge related to wellbeing. In a global context marked by increasing mental health challenges and social inequalities, measuring wellbeing literacy has become essential for identifying needs, guiding public policies, and developing effective interventions. Therefore, this study aimed to estimate the invariance of the Wellbeing Literacy 6-item (Well-Lit 6) Scale at the configural, metric, and scalar levels according to nationality and gender. Method: The Brazilian sample consisted of 323 participants aged between 18 and 67 years (M = 27.9, SD = 10.8), of different genders (58.8% cisgender women), while the French-Canadian sample included 1,134 participants aged between 18 and 64 years (M = 40.2, SD = 12.2), also of different genders (66.8% cisgender women). Participants completed a sociodemographic questionnaire and the Well-Lit 6 Scale. Multigroup confirmatory factor analysis was employed to assess measurement invariance across nationality and gender. Results: The confirmatory factor analysis results indicate that the unidimensional model is equivalent across both Brazilian and French-Canadian samples, as well as across gender groups, as the model fit indices were not negatively impacted by the imposed constraints. Conclusions: These findings support the cross-cultural validity of the Well-Lit 6 Scale, demonstrating its appropriateness for assessing wellbeing literacy in diverse populations. The invariance properties of the instrument reinforce its value for comparative research and practical application in multicultural contexts.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| 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".