Adaptation to Spanish of the “Relational Needs Satisfaction Scale”: Translation and psychometric testing
Bibliographic record
Abstract
This article aims to adapt to Spanish the Relational Needs Satisfaction Scale (RNSS) and to test the factor structure with a clinical and a non-clinical sample. A total of 459 individuals completed the RNSS, a measure of life satisfaction and of psychological wellbeing. Results showed that the translation was adequate. An exploratory and confirmatory factor analysis was conducted followed by the test of three models that confirmed the five-factor structure and the second-order global factor proposed in the original study, and in adaptations to other languages. The advantages and disadvantages of these models are discussed. Correlations of the RNSS with life satisfaction and psychological wellbeing measures were in the expected direction, providing evidence of convergent validity. The Spanish version of the RNSS is a valid and reliable measure of the construct it was intended to measure, though some improvements in item wording could be incorporated and tested (for instance, item 18 should be positively worded as the rest of the items in order to avoid the effect of negative wording).
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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 | 0.006 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".