I’M STILL HERE: THE EXPERIENCE OF LIVING WITH EARLY ONSET DEMENTIA
Bibliographic record
Abstract
Dementia is a growing social and health care concern in today’s world. Although dementia is most often associated with the aging process, younger people can also be diagnosed with the disease. Early onset dementia (EOD) is dementia onset before the age of 65. Dementia’s degenerative nature is particularly challenging for younger people, as the disease tends to occur during a phase of life occupied with and characterized by middle-age tasks. In effect, younger people with dementia are forced to navigate and live a health experience normally encountered later in life. This presentation will summarize a Master’s of Nursing research study that examined the EOD experience from the point of view of four adults under the age of 65 living with dementia, in particular examining how these individuals perceived their own personhood. Using Interpretative Phenomenological Analysis (IPA) as the research method, as well as integrating an arts-based approach, this qualitative study revealed that the EOD experience can be incorporated into six themes: A Personal Journey, Navigating the System, The Stigma of Dementia, Connecting to the World, A Story Worth Telling and I’m Still Here. The participants’ stories as presented via these six thematic threads show that despite the challenges of living with dementia, people with EOD can have a strong sense of personhood. Implications for practice and policy making, as well as recommendations for future dementia research will be discussed.
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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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.015 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.002 | 0.005 |
| 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".