Assistive technologies that support social interaction in long-term care homes
Bibliographic record
Abstract
OBJECTIVE: The objective of this scoping review is to chart the literature on assistive technologies that support social interaction (excluding robots) used with older adults in long-term care (LTC). INTRODUCTION: The need for LTC in institutional settings is in high demand. Loneliness and social isolation are common in these settings. Technology holds potential to contribute to mitigation of loneliness. As there are no systematic reviews examining forms of assistive technologies to support social interaction other than robots, used within LTC settings, there is a need to categorize the current research regarding such technologies to inform practice, policy and any need for further research. INCLUSION CRITERIA: The review will consider studies based in LTC institutional settings with participants (≥65 years), institutional staff and visiting family members METHODS:: The JBI methodology for scoping reviews will be employed. This includes a three-step search strategy: i) identify keywords from CINAHL and PsycINFO, ii) conduct a second search using all identified keywords across select databases, and iii) screen the reference lists of all included articles and reports for additional studies. Titles and abstracts will be screened by two independent reviewers. Full text of selected citations will be assessed against inclusion criteria by two independent reviewers. A data extraction tool will be used, and extracted data will be presented in a narrative accompanied by diagrams or tables that reflect the objective of the review.
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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.008 | 0.004 |
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; both teacher heads agree on what is shown here.
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".