Identity Processes, Depression, and the Aging Self<br/>—A Norwegian Study
Bibliographic record
Abstract
The Identity Process Theory is a theory of how people adapt to aging. According to this theory, older people attribute their physical functioning to a more variable state of health or to their age. Health attributions per se help older people avoid negative thoughts and feelings about themselves and their own process of aging. We explored health versus age attributions, and their effects upon depressive symptoms and negativity toward aging among 359 older Norwegians (age range = 60 - 91 years of age). Aging pertained to psychosocial loss, physical change, and psychological growth. Data collected in the 2004 WHOQOL-OLD Norwegian Field Study were analyzed by using a MANOVA and a validatory path analysis. Our findings consistently supported health attributions in relation to psychosocial loss (X2 = 20.37, df = 10, p = 0.03; GFI = 0.98, AGFI = 0.95, RMSEA = 0.05), physical change (X2 = 35.03, df = 14, p = 0.000; GFI = 0.97, AGFI = 0.94, RMSEA = 0.06), and psychological growth (X2 = 22.22, df = 13, p = 0.05; GFI = 0.98, AGFI = 0.96, RMSEA = 0.04). Health attributions increased participants’ depressive symptoms and negativity toward aging, especially toward psychosocial loss (β= - 0.45, p = 0.000) and physical change (β= - 0.48, p = 0.000). We relate these theoretically contradictory findings to Norwegian cultural beliefs and values. We make recommendations for research, including normalizing depressive symptoms and cross-cultural investigations.
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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 | 0.003 | 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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".