A scoping review: Sensory interventions for older adults living with dementia
Bibliographic record
Abstract
This scoping review focused on the existing scholarly literature exploring sensory interventions and immersive environments developed for, and used by, older adults living with dementia. The purpose of the scoping review is 1) to understand the various sensory interventions that have been developed, used, and have provided data to show how such interventions are expected to impact the lives of individuals living with dementia; and 2) to understand how the field is moving forward. We chose to map the literature to understand the types of interventions, the types of outcomes measured, and the contexts of their implementation. Our search was constrained to references from 1990 to 1 June 2019 in the following databases: Academic Search Complete, CINAHL Complete, MEDLINE, PsycINFO databases, and Summon Search discovery layer. We screened 2305 articles based on their titles and abstracts, and 465 were sent to full text review, of which 170 were included in our full text extraction. Once the data were extracted, we created emic categories, which emerged from the data, for data that were amenable to categorization (e.g., study setting, intervention type, and outcome type). We developed ten different categories of interventions: art, aromatics, light, multi-component interventions, multisensory rooms, multisensory, music, nature, touch, and taste. Sensory interventions are a standard psychosocial approach to managing the personal expressions commonly experienced by people living with dementia. Our findings can help providers, caregivers, and researchers better design interventions for those living with dementia, to help them selectively choose interventions for particular outcomes and settings. Two areas emerging in the field are nature interventions (replacing traditional "multisensory rooms" with natural environments that are inherently multisensory and engaging) and multi-component interventions (where cognitive training programs are enhanced by adding sensory components).
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 teacher head, 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".