Rapid and sound assessment of well-being within a multi-dimensional approach: The Well-being Numerical Rating Scales (WB-NRSs)
Bibliographic record
Abstract
The assessment of well-being remains an important topic for many disciplines including medical, psychological, social, educational, and economic fields. The present study assesses the reliability and validity of a five-item instrument for evaluating physical, psychological, spiritual, relational, and general well-being. This measure uniquely utilizes a segmented numeric version of the visual analog scale in which a respondent selects a whole number that best reflects the intensity of the investigated characteristic. In study one, 939 clinical (i.e., diagnosed with cancer and liver disease with cirrhosis) and non-clinical (i.e., undergraduate students and their family and acquaintances) participants between the ages of 18 to 87 years (M = 47.20 years, SD = 19.62, 54% males) were recruited. Results showed items have strong discriminant ability and the spread of threshold parameters attests to the appropriateness of the response categories. Moreover, convergent and discriminant validity were found with other self-report measures (e.g., depression, anxiety, optimism, well-being) and the measure showed responsiveness to two separate interventions for clinical populations. In study two, 287 Canadian (ages ranged from 18 to 30 years; M = 20.78, SD = 3.32; 23% males) and 342 Italian undergraduate psychology students (age ranged from 18 to 29 years, M = 21.21 years, SD = 1.73, 38% males) were recruited to complete self-report questionnaires. IRT-based differential item functioning analyses provided evidence that the item properties were similar for the Italian and English versions of the scale. Additionally, the validity results obtained in study one were replicated and similar relationships between criterion variables were found when comparing the Italian- and the English-speaking samples. Overall, the current study provides evidence that the Italian and English versions of the WB-NRSs offer added value in research focused on well-being and in assessing well-being changes prompted by intervention programs.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".