Accessibility of Virtual Primary Care for Adults With Intellectual and Developmental Disabilities During the COVID-19 Pandemic: Qualitative Study
Bibliographic record
Abstract
BACKGROUND: The COVID-19 pandemic has led to an unprecedented increase in the delivery of virtual primary care. Adults with intellectual and developmental disabilities (IDDs) have complex health care needs, and little is known about the value and appropriateness of virtual care for this patient population. OBJECTIVE: The aim of this study was to explore the accessibility of virtual primary care for patients with IDDs during the pandemic. METHODS: We conducted semistructured interviews with 38 participants in Ontario, Canada between March and November 2021. A maximum variation sampling strategy was used to achieve a diverse sample including 11 adults with IDDs, 13 family caregivers, 5 IDD support staff members, and 9 primary care physicians. An iterative mixed inductive and deductive thematic analysis approach was used to code the data and synthesize higher-level themes. The analysis was informed by the Levesque Patient-Centered Access to Health Care Framework. RESULTS: We identified themes related to 4 of 5 access-to-care dimensions that highlighted both the benefits and challenges of virtual care for adults with IDDs. The benefits included saving time spent traveling and waiting; avoiding anxiety and challenging behavior for patients who struggle to attend in-person visits; allowing caregivers who live far away from their loved ones to participate; reducing illness transmission; and allowing health care providers to see patients in their home environments. The challenges included lack of access to necessary technology, lack of comfort or skill using technology, and lack of nonverbal communication; difficulty engaging and establishing rapport; patient exclusion from the health care encounter; and concerns about privacy and confidentiality. An overarching theme was that "one size does not fit all," and the accessibility of virtual care was dependent on the interaction between the following 5 categories of factors: patient characteristics, patient context, caregiver characteristics, service context, and reason for a particular primary care visit. Though virtual care was not always appropriate, in some cases, it dramatically improved patients' abilities to access necessary health care. CONCLUSIONS: This study suggests that a flexible patient-centered system including multiple delivery modalities is needed to ensure all patients have access to primary care. Implementing this system will require improved virtual care platforms, access to technology for patients and caregivers, training for primary care providers, and appropriately aligned primary care funding models.
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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 | 0.004 | 0.005 |
| 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 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".