The Social Construction of Dementia: Implications for Healthcare Experiences of Caregivers and People Living with Dementia
Bibliographic record
Abstract
Globally, systems have invested in a variety of dementia care programs in response to the aging population and those who have been diagnosed with dementia. This study is a qualitative secondary analysis of interview data from a larger study investigating stakeholder perceptions of programs that support caregivers and people living with an Alzheimer's Disease or Alzheimer's Disease-related dementia (AD/ADRD) in five North American jurisdictions. This study analyzed interviews with individuals living with an AD/ADRD and caregivers of individuals living with an AD/ADRD (n = 11). Thematic analysis was conducted to understand how the perception of dementia may have shaped their engagement and experience with healthcare systems. Our analysis resulted in three main themes of care users' experience: (i) undesirable experience owing to the overarching negative shared understanding and stereotyping of dementia; (ii) dismissal throughout disease progression when seeking health and social care support; and (iii) dehumanization during care interactions. The findings carry critical social and clinical implications, for example, in informing person-centered approaches to care, and communication tools clinicians can use to enhance provider, patient, and caregiver well-being.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.011 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.016 | 0.018 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.001 | 0.013 |
| Research integrity | 0.002 | 0.003 |
| 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".