Growing old and being old: Emotional well-being across adulthood.
Bibliographic record
Abstract
The present study examines change in reports of daily, weekly, and monthly psychological distress over 20 years, and of negative and positive affect over 10 years, using data from the Midlife in the United States study. The study includes three waves of data collection on adults ranging from 22 to 95 years old. Cross-sectional findings reveal that older age is related to lower levels of psychological distress and negative affect and to higher levels of positive affect across each successive age group. Yet, longitudinal findings vary across younger, middle-aged, and older adults. Psychological distress decreases over time among younger adults (although only until age 33 for weekly reports), remains stable in midlife, and is stable (monthly) or slightly increases (daily and weekly) among older adults. For negative affect, levels decrease over time for younger and middle-aged adults, and only increase for the oldest adults for daily and monthly affect. Positive affect is stable over time among younger adults, but decreases in midlife starting in the mid-fifties. In conclusion, overall patterns of findings suggest that being old (assessed cross-sectionally) is related to higher levels of emotional well-being. Growing old (assessed longitudinally) is related to improvements in emotional well-being across younger and early middle adulthood, which mirrors cross-sectional findings. There is relative stability in later midlife, however, and continued stability or slight declines across older age. (PsycInfo Database Record (c) 2023 APA, all rights reserved).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".