Natural Occurrence of Subjective Aging Experiences in Community-Dwelling Older Adults
Bibliographic record
Abstract
OBJECTIVES: The subjective experience of aging is a relevant correlate of developmental outcomes. However, traditional approaches fall short of capturing the inherent multidimensionality of subjective aging experiences (SAEs). Based on the concept of Awareness of Age-Related Change (AARC; Diehl, M. K., & Wahl, H.-W. (2010). Awareness of age-related change: Examination of a (mostly) unexplored concept. Journals of Gerontology: Series B: Psychological Sciences and Social Sciences, 65, 340-350. doi:10.1093/geronb/gbp110), this study provides a description of SAEs that is facet rich, and based on their natural occurrence, analyzes interindividual differences and associations with well-being. METHOD: Data came from 225 participants (70-88 years) of the ongoing BEWOHNT study. Open-ended diary entries about age-related experiences were collected for more than 14 days and coded according to AARC domains and subdomains. RESULTS: Seventy percent of all participants had SAEs about physical functioning. About half of the sample reported experiences in the domains interpersonal relations, social-emotional and social-cognitive functioning (COGN-EMOT), and lifestyle. Thirty percent experienced aging in terms of changes in cognitive functioning. Contents of SAEs varied by gender, age group, and functional status. SAEs about COGN-EMOT were most consistently related to affective components of subjective well-being. DISCUSSION: Our results demonstrate the benefits of an open-ended approach to a multidimensional understanding of SAEs. Content-related, social-cognitive and social-emotional changes more than functional age-related changes were most important for well-being.
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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 | 0.005 |
| 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 | 0.000 | 0.000 |
| 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".