Facilitators and barriers to using telepresence robots in aged care settings: a scoping review protocol
Bibliographic record
Abstract
INTRODUCTION: Social isolation is a significant issue in aged care settings (eg, long-term care (LTC) and hospital) and is associated with adverse outcomes such as reduced well-being and loneliness. Loneliness is linked with depression, anxiety, cognitive decline, weakened immune system, poor physical health, poor quality of life and mortality. The use of robotic assistance may help mitigate social isolation and loneliness. Although telepresence robots have been used in healthcare settings, a comprehensive review of studies focusing on their use in aged care for reducing social isolation requires further investigation. This scoping review will focus on the use of telepresence robots to support social connection of older people in care settings. METHODS AND ANALYSIS: This scoping review will follow Joanna Briggs Institute scoping review methodology. The review team consists of patient partners and family partners, a nurse researcher and a group of students. In the scoping review, we will search the following databases: MEDLINE (Ovid), CINAHL, PsycINFO (EBSCO), Web of Science and ProQuest Dissertations & Theses Global. Google and Google Scholar will be used to search for additional literature. A handsearch will be conducted using the reference lists of included studies to identify additional relevant articles. The scoping review will consider studies of using a telepresence robotic technology with older adults in care settings (ie, LTC and hospital), published in English. ETHICS AND DISSEMINATION: Since the methodology of the study consists of collecting data from publicly available articles, it does not require ethics approval. By examining the current state of using telepresence to support older people in care settings, this scoping review can offer useful insight into users' needs (eg, patients' and care providers' needs) and inform future research and practice. We will share the scoping review results through conference presentations and an open access publication in a peer-reviewed journal.
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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 | 0.081 | 0.065 |
| Meta-epidemiology (narrow) | 0.004 | 0.005 |
| Meta-epidemiology (broad) | 0.014 | 0.014 |
| Bibliometrics | 0.016 | 0.010 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.007 | 0.008 |
| Open science | 0.006 | 0.007 |
| Research integrity | 0.008 | 0.006 |
| Insufficient payload (model declined to judge) | 0.064 | 0.011 |
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".