The Golden Ticket: Gaining In-Person Access to Relatives in Long-Term Care Homes During the COVID-19 Pandemic
Bibliographic record
Abstract
Context: Governments made emergency declarations to restrict the presence of family carers in long-term care homes (LTCHs) as part of infection control measures during the pandemic. Within Canada, two visitor statuses were created: ‘essential’ to the health of the resident and ‘non-essential’ or ‘social visitor’, who were subject to additional restrictions. Objective: This study explored family carers’ experiences navigating in-person access to their relatives in LTCH during the pandemic. Methods: Using interpretive description, a sample of 14 family carers (nine daughters, five spouses) living in British Columbia, Canada, participated in in-depth interviews via video call about their experiences between March 2020 and June 2021. Findings: Analyses illustrated variability in carers’ visitor status across families and over time. Two key themes were identified: 1) “Fighting a Losing Battle” describes how reductionist attitudes and policies minimized the role of caregiving and resulted in traumatic disruptions in familial relationships; 2) “Who’s In and Who’s Out” captures inequities in how visitor status policies were applied. Limitations: Restrictions on conducting research during the pandemic resulted in a smaller sample of family carer participants. Implications: Findings highlight the patchwork implementation of visitor policies over the initial 17 months of the pandemic and the precarious space family carers continue to occupy within the LTC sector. Future research should focus on formalising support for family presence during public health emergencies.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.009 | 0.004 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| 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".