Long-term care staffs’ experience in facilitating the use of videoconferencing by cognitively impaired long-term care residents during the COVID-19 pandemic: a mixed-methods study
Bibliographic record
Abstract
BACKGROUND: During the COVID-19 pandemic, numerous long-term care (LTC) homes faced restrictions that prevented face-to-face visits. To address this challenge and maintain family connections, many LTC homes facilitated the use of electronic tablets to connect residents with their family caregivers. Our study sought to explore the acceptability of this practice among staff members and managers, focusing on their experiences with facilitating videoconferencing. METHODS: A convergent mixed method research was performed. Qualitative and quantitative data collection through semi-structured interviews to assess the acceptability of videoconferencing in long-term care homes and to explore the characteristics of these settings. Quantitative data on the acceptability of the intervention were collected using a questionnaire developed as part of the project. The study included a convenience sample of 17 staff members and four managers. RESULTS: Managers described LTC homes' characteristics, and the way videoconferencing was implemented within their institutions. Affective attitude, burden, ethicality, opportunity costs, perceived effectiveness, and self-efficacy are reported as per the constructs of the Theoretical Framework of Acceptability. The results suggest a favorable acceptability and a positive attitude of managers and staff members toward the use of videoconferencing in long-term care to preserve and promote contact between residents and their family caregivers. However, participants reported some challenges related to the burden and the costs regarding the invested time and staff shortage. CONCLUSIONS: LTC home staff reported a clear understanding of the acceptability and challenges regarding the facilitation of videoconferencing by residents to preserve their contact with family caregivers.
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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 | 0.011 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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 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".