Emotional impact of dementia diagnosis: Exploring persons with dementia and caregivers’ perspectives
Bibliographic record
Abstract
This paper examined the emotional impact of diagnosis disclosure on recently diagnosed people with dementia. Thirty patient/caregiver dyads attending a Geriatric Day Hospital Program in Ottawa, Canada participated in this qualitative exploratory study. Data sources included: (a) audio-tapes of diagnosis disclosure meeting, (b) in-depth interviews with patients and caregivers within one week of disclosure, and (c) focus group interviews with caregivers within one month. Patients exhibited a range of emotional responses which can be divided into three broad categories: (a) responses suggesting a lack of insight and/or an active denial of the diagnosis, (b) grief reactions/emotional crisis related to the experience of actual or anticipated losses associated with dementia, and (c) positive coping responses to maximize the disease outcome. Participants went through stages of emotional response to their diagnosis: not noticing symptoms, noticing & covering up, or noticing & revealing; diagnostic process & disclosure; confirming or shock; denial, crisis, or maximizing; disorganization or adaptation. There is a need to develop a better understanding of the experience of people with dementia at the critical point of diagnosis disclosure in order to design supportive interventions to maximize adaptive coping responses.
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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 | 0.006 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.005 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".