Facilitators and barriers to using smart TV among older adults in care settings: a scoping review protocol
Bibliographic record
Abstract
INTRODUCTION: The objective of the scoping review is to understand what has been reported in the literature regarding facilitators and barriers to using smart television (smart TV) among older adults in care settings. METHODS AND ANALYSIS: The scoping review will adopt the Joanna Briggs Institute scoping review methodology. It will occur between March and August 2022. It will consider literature on using smart TV with older adults in care settings. A three-step search strategy will be applied: (1) to identify keywords and index terms from MEDLINE and CINAHL; (2) to do a search using identified keywords and index terms across chosen databases (MEDLINE, CINAHL, Embase, Web of Science, Scopus, AgeLine, PsycINFO, Web of Science, ProQuest and Google) and (3) to hand search the reference lists of all selected literature for additional literature. Further, we will search using Google for grey literature. Two research assistants will independently screen the titles and abstracts by referring to the inclusion criteria. After that, two researchers will independently assess the full text of selected literature by referring to the inclusion criteria. We will present the data in a table with narratives that answer the questions of the scoping review. ETHICS AND DISSEMINATION: The scoping review does not require ethics approval because it collects data from the publicly available literature. The findings will offer insights to inform the use of smart TV among older adults in care settings for education, practice, policy and future research. The scoping review results will also be disseminated through conference presentations and an open-access publication in a peer-reviewed journal.
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 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 | 0.158 | 0.107 |
| Meta-epidemiology (narrow) | 0.005 | 0.007 |
| Meta-epidemiology (broad) | 0.011 | 0.012 |
| Bibliometrics | 0.017 | 0.012 |
| Science and technology studies | 0.007 | 0.006 |
| Scholarly communication | 0.009 | 0.011 |
| Open science | 0.007 | 0.009 |
| Research integrity | 0.013 | 0.008 |
| Insufficient payload (model declined to judge) | 0.067 | 0.020 |
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".