Predictors of Canadians’ Psychological Well-Being in Retirement: A Mixed Methods Approach
Bibliographic record
Abstract
In prior decades, retirement research focused on the negative effects of the life transition—such as negative psychological well-being caused by factors such as difficulties adjusting to retirement, feelings of a role loss, or the financial effects of retirement. However, there is considerable agreement across recent research studies that post-retirement years are marked by positive psychological well-being due to a variety of factors. For example, retirees often spend more time in roles (such as volunteer positions) that provide life satisfaction. The present study uses both quantitative and qualitative methods to examine factors related to well-being in retirement among individuals living in Canada. A sample of 136 participants between the ages of 54 and 86 years old was recruited to complete a survey that measured psychological well-being using Center for Epidemiologic Studies Short Depression Scale (CES-D10; Radloff, 1977) and Positive and Negative Affect Schedule (PANAS; Watson & Clark, 1992) and measured life satisfaction using Satisfaction with Life Scale (SWLS; Diener, et al., 1985). In addition, the quantitative portion of the survey targeted other aspects of life in relation to well-being including physical health, satisfaction with roles (e.g., marital), financial security, and the social role of volunteering. Of the 136 participants, 113 participants completed an optional phone interview. Phone interview responses were coded for future time perspective (FTP) with the hypothesis that FTP is correlated with overall well-being in retirement. The mixed methods approach supported by several theoretical approaches explored in this proposal is novel in retirement study data in that very few studies pertinent to retirees living in Canada examine psychological well-being during retirement with in-depth analyses of qualitative data in conjunction with quantitative data. Qualitative data was utilized to examine the experience of retired Canadians by detailing their “deeper thoughts and behaviours that governed their [quantitative] responses” (Creswell & Poth, 2018, p. 46), specifically investigating gender differences and differences in the experience of a planned versus unplanned retirement on the impact of their well-being. Quantitatively, results indicate that: an unplanned retirement still provides challenges for retirees as seen through reports of lower levels of life satisfaction and family satisfaction, retirees are cognizant of the importance of physical health, volunteering is positively correlated to psychological well-being, and financial income predicts satisfaction with life regardless of an unplanned or planned retirement. Qualitative results indicate that retirees are resilient even with a forced/unplanned retirement, retirees are extremely active and conscious of preventative physical and mental healthcare, and for the most part, retirees’ expectations of retirement met their reality.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".