Shifting positivity ratios: emotions and psychological health in later life
Bibliographic record
Abstract
OBJECTIVE: A positivity ratio of approximately three positive emotions to one negative emotion has been found to distinguish between flourishing and languishing (optimal vs. poor psychological health). The current study assessed 2-year shifts (2008, 2010) in positivity ratios among 295 older adults and considered whether such shifts were associated with concurrent changes in psychological health (perceived stress, depressive symptoms, and perceived control). METHOD: Based on participants' reported positive and negative emotions, we identified two positivity ratio groups who were characterized by ratios that did not change, either remaining persistently optimal (above 2.9) or persistently suboptimal, and two groups that depicted shifts in ratios that either became optimal or became suboptimal. RESULTS: Most participants (67%) remained in their initial group, but shifts between categories did occur in both directions. Ratio groups and time (2008 vs. 2010) were predictor variables in 4 × 2 generalized estimating equations that were computed for each psychological health measure. The hypothesized positivity ratio group × time interaction emerged for each psychological health measure. Ratio shifts that 'became optimal' were associated with a significant concurrent decrease in stress and an increase in perceived control; ratio shifts that 'became suboptimal' were associated with a significant increase in depression. CONCLUSION: Although older adults who began with a suboptimal positivity ratio were unlikely to experience a shift to an optimal ratio, findings are more encouraging for those who began with an optimal positivity ratio. The majority of these older adults retained optimal positivity ratios over time and appeared to flourish.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".