Validation of the PANAS: A Measure of Positive and Negative Affect for Use with Cross-National Older Adults
Bibliographic record
Abstract
Objectives: Positive and negative affect is a relevant facet of well-being for community-dwelling older adults. This article reports the validation of the Positive And Negative Affect Scale (PANAS), by means of confirmatory analysis.Methods: A community-dwelling cross-national sample of 1291 older adults aged 75 years-old and older voluntarily completed the PANAS. The relations between variables in the model were evaluated using structural equation based on maximum likelihood estimation. The distributional properties, cross-sample stability, internal reliability, and convergent, external and criterion-related validities of the PANAS were analyzed and found to be psychometrically acceptable.Results: Our results outcomes support for the hypothesis that the PANAS is valid and reliable in the two 10-item mood scales, hence fit for use with older adults, within a culturally diverse view of well-being.Conclusions: The psychometric properties of the PANAS are satisfactory in this older sample, and according to those of its early version. Taken together, these results substantiate the validity of this measure when applied to an older community cross-national population.
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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 | 0.009 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| 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".