Re-thinking the nature of day programs for people with dementia: Implications for research
Bibliographic record
Abstract
Day programs are commonly identified in dementia strategies as a solution for keeping people with dementia home for as long as possible. Limited research evidence is available to support these policy approaches, and much of what exists demonstrates equivocal results. While key day program researchers have called for improvements in methodological and theoretical efforts, we argue that basic assumptions concerning what a day program is, and how the effects of day programs should be studied, also require reconsideration. Problematization is a systematic review strategy used to identify and critique assumptions guiding research practices and knowledge development in a field of study. The approach entails a broad overview of a field of research alongside a close reading of key texts to identify prevailing assumptions about the object of study and how it can be known. The intent is to discern how these assumptions are influencing research practices and thus knowledge development. A review of historical texts and research literature reviews was used (1) to identify trends in day program research between 1990 and 2018 and (2) to support identification of influential and typical studies for closer analysis ( n = 36). The outcome of our analysis of the research literature suggests three sets of assumptions that guide much of the day program research literature: dementia is mainly treated as a problem of the individual; day programs are treated as stand-alone units of substitute care; and the space of day programs is seen as a simple background to care. We argue that the assumptions regarding care and space have narrowed the field of research and contributed to the production of equivocal findings. We suggest alternative framings of notions of care and space, informed by a Science and Technology Studies’ approach to care practices, to generate knowledge about day programs that can usefully inform policy and practice.
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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 | 0.130 | 0.209 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.007 | 0.010 |
| Science and technology studies | 0.007 | 0.026 |
| Scholarly communication | 0.023 | 0.054 |
| Open science | 0.008 | 0.011 |
| Research integrity | 0.007 | 0.016 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".