The Impact of the COVID-19 pandemic on adults with visual impairments in canada
Bibliographic record
Abstract
Purpose : The COVID-19 pandemic has had a substantial impact on society but has disproportionately affected the disability population. The CNIB COVID-19 Impact Survey was distributed throughout Canada in May 2020 to gather information on the experiences of adults with visual impairments during the pandemic. This cross-sectional study identified key aspects in which those with vision loss have been impacted by the pandemic and associated policies and procedures. Methods : Analyses were conducted using IBM SPSS version 22 statistical software. Conventional descriptive statistics were used to describe the sample. Data were crosstabulated by age, age of sight loss onset, severity of sight loss, other disability or health condition, employment status, and education. Results : Approximately half (51%) of the sample had concerns about their healthcare, and just over half (58%) said they did not know where to get tested for SARS-CoV2. Key concerns reported by respondents included: 1. Touching things in public such as elevator panels, self-serve kiosks, or restroom doors to check signage (68% agreed). 2. Due to social distancing, they feel more depressed, sad, and lonely (64% agreed). 3. Because the individual does not drive, they will not be able to get themselves or a family member to a COVID-19 test centre or to a hospital or healthcare facility if they present with severe COVID-19 symptoms (61% agreed). 4. Getting access to accurate and current information about those who may be infected in their area (59% agreed). 5. Concern about accessing emergency medical services (50% agreed). 6. Unsure how to maintain appropriate social distance in public (48% agreed). Conclusions : The COVID-19 pandemic has impacted those with sight loss in many ways and in many different aspects of their lives. This study gave key insights into barriers affecting the societal participation of those with sight loss. While the findings of this study may have evolved over the course of the pandemic, these concerns are important for all levels of policy and advocacy leads to take into account while developing and revising existing policies. This study has provided evidence for the development of new policies and procedures, and the evaluation of existing policies and public health procedures to ensure those with sight loss are not put at an even greater disadvantage during these times and are able to receive the necessary supports.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".