“The Government Is Keeping Me From My Mother”: Impacts of Visitation Restrictions as Reported by Family Members
Bibliographic record
Abstract
Abstract The Ohio Nursing Home Family Satisfaction Survey (FSS) is a self-administered mailed questionnaire with an online option conducted every two years per state mandate. Data collection for the tenth implementation of the FSS occurred between August 2021 and May 2022, while some nursing facilities in the state were still restricting visitation based on occurrences of COVID-19 infections. While the 2021-22 FSS questionnaire did not ask about family members’ experiences with visitation restrictions during COVID-19, respondents were provided the opportunity to leave general comments at the end of the survey and to participate in a separate, online COVID-19 survey where they could provide input about their experiences during the pandemic. A total of 13,010 family members of nursing facility residents responded to the 2021-22 FSS and 764 nursing home family members responded to the COVID-19 survey. Using content analysis, researchers from Scripps Gerontology Center at Miami University analyzed 2,890 open-ended comments from the FSS and COVID-19 surveys and identified 269 comments pertaining to visitation restrictions, which were then coded and analyzed for themes. While some family members reported appreciation or neutrality regarding visitation restrictions, the majority of commenters reported negative social and emotional impacts on both residents and family members and negative physical and cognitive impacts on residents, particularly those living with dementia. This session will share findings from the qualitative analysis and considerations for policy makers in the event of future infectious disease outbreaks.
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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 | 0.005 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".