Health care experiences of people with dementia and their caregivers: a meta-ethnographic analysis of qualitative studies
Bibliographic record
Abstract
BACKGROUND: Understanding the health care experience of people with dementia and their caregivers is becoming increasingly important given the growing number of affected individuals. We conducted a systematic review of qualitative studies that examined aspects of the health care experience of people with dementia and their caregivers to better understand ways to improve care for this population. METHODS: We searched the electronic databases MEDLINE, Embase, PsychINFO and CINAHL to identify relevant articles. We extracted key study characteristics and methods from the included studies. We also extracted direct quotes from the primary studies, along with the interpretations provided by authors of the studies. We used meta-ethnography to synthesize the extracted information into an overall framework. We evaluated the quality of the primary studies using the Consolidated Criteria for Reporting Qualitative Research (COREQ) checklist. RESULTS: In total, 46 studies met our inclusion criteria; these involved 1866 people with dementia and their caregivers. We identified 5 major themes: seeking a diagnosis; accessing supports and services; addressing information needs; disease management; and communication and attitudes of health care providers. We conceptualized the health care experience as progressing through phases of seeking understanding and information, identifying the problem, role transitions following diagnosis and living with change. INTERPRETATION: The health care experience of people with dementia and their caregivers is a complex and dynamic process, which could be improved for many people. Understanding these experiences provides insight into potential gaps in existing health services. Modifying existing services or implementing new models of care to address these gaps may lead to improved outcomes for people with dementia and their caregivers.
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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 | 0.096 | 0.170 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.004 | 0.007 |
| Bibliometrics | 0.016 | 0.016 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.004 | 0.007 |
| Open science | 0.002 | 0.006 |
| 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".