Cross-Cultural Psychometric Analysis of the Mature Happiness Scale-Revised: Mature Happiness, Psychological Inflexibility, and the PERMA Model
Bibliographic record
Abstract
Abstract The present study aimed to evaluate the psychometric properties of the Mature Happiness Scale, a measure focused on inner harmony. Mature happiness is achieved when a person can live in balance between both positive and negative aspects of their life. A total sample of 2,130 participants from five countries (Canada: n = 390, United States: n = 223, United Kingdom: n = 512, Spain: n = 724, and Hungary: n = 281) responded to an online survey including the original Mature Happiness Scale, the PERMA-Profiler, and the Acceptance and Action Questionnaire-II. Exploratory and confirmatory factor analyses yielded a one-factor solution with seven positive items (non-reversed). We called this new version of the questionnaire the Mature Happiness Scale-Revised (MHS-R). Measurement invariance was found across countries, age groups, gender, and mental disorder diagnosis. Internal consistency and test–retest reliability were high. Older people, males, and people without a mental disorder diagnosis scored higher in mature happiness than younger ones, females, and those with a mental health disorder diagnosis, respectively. Mature happiness showed strong positive associations with various subscales of the PERMA-Profiler, specifically with positive emotions and meaning in life. In addition, mature happiness was strongly correlated with less negative affect and inner conflict and lower psychological inflexibility, whereas it was moderately correlated with lower loneliness. This validity evidence supports the cross-cultural use of the MHS-R in the aforementioned countries to reliably measure happiness among adults. With its holistic approach, the MHS-R may be a unique complement to other well-being measures, particularly to better predict mental health problems.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.007 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".