Experiences of loneliness among older people living alone. A qualitative study in Quebec (Canada)
Bibliographic record
Abstract
Abstract In this article, we analyse experiences of loneliness among older people living alone. Current knowledge suggests that loneliness is a significant social issue that can compromise health and wellbeing, and that seniors living alone are at a higher risk of loneliness. Based on a qualitative methodological approach and semi-structured interviews conducted with 43 people aged 65 or over living alone in Montreal (Quebec, Canada), this study sought to understand how they perceive, reflect on and react to loneliness. The results show that these seniors perceive loneliness as a dynamic, and rarely static, experience, which has a very different significance, depending on whether it is chosen or circumstantially imposed. The experience of loneliness recounted by the seniors we met is characterised by its heterogeneity, and involves, to varying degrees, their relationship to themselves (solitude), to others (family (and friends) lonelinessandloneliness in love) and/or to the world (existential lonelinessandaloneness). Lastly, our analyses highlight how social factors, such as age, gender, marital status, social network and socio-economic conditions, shape the experience of loneliness among seniors. These factors also influence the strategies that seniors develop to prevent or alleviate loneliness, strategies that yield very mixed results.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.017 | 0.005 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".