O2–05–01: The social experiences of spouses of persons with young‐onset dementia (YOD): Social change, support and resiliency
Bibliographic record
Abstract
Young-onset dementia (YOD; onset before 65) accounts for approximately 5–9% of the total dementia population. The majority of caregiving is provided on an informal basis, often by the affected person's spouse. There is little qualitative interview research that has focused specifically on the social experiences of YOD spousal caregivers, and none within the Canadian context. The purpose of this study was to explore the social experiences of spouses of persons with YOD within the Canadian context. In this descriptive, qualitative study, semi-structured, face-to-face interviews were conducted to explore the nature of spouses' social experiences. Participants were recruited through Alzheimer Society Chapters in Ontario. Ten YOD spousal caregivers living in Ontario participated. Interviews included open-ended questions on social experiences such as recreational activities and social change. Interview transcripts were coded using NVivo 9 and analyzed using inductive content analysis. Participants (6 females, 4 males) had a mean age of 55 (sd=6.45), and all were currently employed. Persons with YOD had a mean age of 61 (sd=4.33). One spouse was currently working, and three were living in a long-term care home. Qualitative analysis revealed four emergent themes relevant to social experiences: giving up activities in favour of new activities, sources of social support, adapting and maintaining social and recreational activities, and social spaces as safe spaces. Participants frequently described giving up social and recreational activities due to fear of leaving their spouse home alone. Participants discussed adapting social and recreational activities in order to include their spouse, or simply to accommodate their caregiving obligations. Additionally, many participants cited experiences where their friends and family had avoided them and their spouse, or treated their spouse with YOD as though they were non-existent. New themes included giving up activities in favour of new activities and social spaces as safe spaces. Results highlight the complex nature of these social experiences, and ultimately challenge our theoretical understanding of the dementia caregiver experience. Additionally, these findings carry practical significance; results provide specific suggestions for improvement of social services focused on caregiver support.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.008 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 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".