Supporting the needs of people with intellectual and developmental disabilities 1 year into the <scp>COVID</scp>‐19 pandemic: An international, mixed methods study of nurses' perspectives
Bibliographic record
Abstract
As the largest public health crisis within a century, the COVID-19 pandemic has caused long-term disruption in the support systems of people with intellectual and developmental disabilities (IDD) across the globe. The purpose of this study was to investigate challenges and ameliorative strategies to supporting the basic care needs of people with IDD 1 year into the pandemic, as experienced by nurses who specialize in IDD nursing. We surveyed a convenience sample of 369 nurses from across North America, Europe, and Australasia using a 52-item online questionnaire. Descriptive statistics were used to rank the greatest challenges and the degree of support available to nurses, and manifest content analysis was used to analyze open-ended responses related to ongoing challenges and ameliorative strategies. Results of descriptive analyses revealed consistent findings across global regions in terms of the challenges faced by nurses; the greatest challenges related to supporting or enabling socialization with family/friends, ensuring adequate day programming or educational services, identifying/planning alternative entertainment activities, ensuring adequate staffing of familiar support workers and caregivers, and managing challenging behaviors related to change in daily routine and activities. Nurses described a considerable degree of support offered by their organizations in terms of flexibility in scheduling related to family obligations and paid time off for COVID-19-related isolation and quarantine. Content analysis of open-ended survey responses revealed numerous challenges related to: (1) client socialization, meaningful activity, and mental/behavioral health; (2) interpreting, keeping up with, and helping others to understand COVID-19 guidelines; (3) access to, quality of, and continuity of care; and (4) COVID-19 fatigue and the influence of time. Overall, our study highlights ongoing issues with access to care and support, exacerbated by the pandemic, and the importance of having meaningful activity and socialization for overall well-being of people with IDD during a long-term public health crisis.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.573 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".