Psychosocial Development and Well-being in Retirement: The Relationship Between Generativity, Ego Integrity, and Regret Among Canadian Retirees
Bibliographic record
Abstract
Transitions such as retirement may facilitate change in social and psychological dynamics, perhaps encouraging what Butler (2002) refers to as a life review: an introspective process encouraging reflection on the life course, potentially eliciting regret(s). Older adults may especially be tasked with coming to terms with the life they have lived given time constraints and perceivably less opportunity to rectify paths not taken. Drawing upon Erikson’s (1950) stages of generativity and ego integrity, the purpose of the present study is to understand the role of psychosocial development in the presence or absence of regret as well as to further understand which specific factors may contribute to well-being in retirement. Overall, results indicate relationships between generativity, ego integrity, and two types of well-being (satisfaction with life [SWL] and meaning in life [MIL]). Scores on generativity and MIL were not significantly different between those who expressed having regrets compared with those who did not have any regrets, whereas scores on ego integrity and SWL were significantly different. However, frequency analyses revealed that most retirees did not indicate having regrets and for those that did, career- and family-related regrets were expressed most frequently. Finally, generativity and ego integrity, but not regret, were predictors of both types of well-being. These findings highlight the impact of psychosocial factors on coming to terms with regret and well-being outcomes among retirees.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".