Examining attitudes to uptake and sustainment of technology among care aides in the delivery of care: a scoping review protocol
Bibliographic record
Abstract
INTRODUCTION: Care aides are health workers who deliver hands-on care to patients across the healthcare continuum. The use of technology in healthcare delivery is increasing, and evidence regarding how care aides' attitudes may either facilitate or hinder the adoption of healthcare technologies is lacking.The aim of the proposed scoping review is to examine available evidence regarding care aides' attitudes towards the adoption of innovation and factors that may influence the sustainable use of technology in healthcare delivery. Published studies, grey literature and review articles that identify a method for the review, conference abstracts and website publications regarding the attitude, uptake and sustainable use of technology in care delivery by care aides will be included. For abstracts that have resulted in publications, the full publications will be included. The search for evidence commenced in June 2023 and will end in March 2024. METHODS AND ANALYSIS: The Joanna Briggs Institute (JBI) method will be used to conduct the review. The CINAHL, Cochrane Library, EMBASE, MEDLINE, ProQuest, PubMed, SCOPUS, PROSPERO, Web of Science and JBI Evidence Synthesis databases will be searched using keywords for publications within the last 20 years to examine trends in health technology and attitudes of care aides towards innovation over the last two decades. A search of grey literature and websites will be conducted. The reference list of the retrieved articles will be used to identify additional literature. The search results will be exported into a literature management tool for screening and analysis. Article screening will be performed by two authors and if a third is needed to resolve any differences. Data analysis will be guided by two theoretical frameworks. ETHICS AND DISSEMINATION: No ethics approval is required. The findings will be disseminated in a peer-reviewed journal and presented in conferences. REGISTRATION DETAILS: https://doi.org/10.17605/OSF.IO/CZQUP.
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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 | 0.096 | 0.067 |
| Meta-epidemiology (narrow) | 0.006 | 0.007 |
| Meta-epidemiology (broad) | 0.015 | 0.017 |
| Bibliometrics | 0.021 | 0.015 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.008 | 0.009 |
| Open science | 0.007 | 0.007 |
| Research integrity | 0.011 | 0.006 |
| Insufficient payload (model declined to judge) | 0.061 | 0.017 |
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".