11 Exploring the Impact of COVID-19 on Families of Children with Developmental Disabilities: A Community-Based Formative Study
Bibliographic record
Abstract
Abstract Primary Subject area Developmental Paediatrics Background The COVID-19 pandemic has impacted every facet of society but has been particularly disastrous for families of children with developmental disabilities (DD) living on the margins. The unprecedented repercussions of COVID-19, including quarantine, social distancing, and service restrictions, continue to disproportionately impact these families. This is a pattern observed in previous humanitarian crises, where there has been a lack of response for children with DD. There is an urgent need to understand the experiences of families of children with DD in order to develop a community-driven model of service provision. Objectives This study aims to identify the experienced impact of COVID-19 on families of children with DD who have significant needs and social barriers. Design/Methods This was a community-based participatory study using a formative research framework in accordance with COREQ guidelines. In-depth interviews (IDIs) were conducted with caregivers and care providers of children with DD. Data were recorded, transcribed, and coded using deductive and inductive coding methods by three independent coders. A peer debriefing strategy was used to verify the coding approach and interpretation of findings in accordance with the RATS (relevancy, appropriateness, transparency, and soundness) guidelines for qualitative research. Perceived parental stress and social support were explored using the Perceived Stress Scale (PSS-10) and Multidimensional Scale of Perceived Social Support (MSPSS). Results A total of 25 IDIs were conducted. Of the 15 caregivers interviewed, five were new to Canada. Results suggested both newcomer and non-newcomer families of children with DD are in crisis, reporting high stress and low social support, with increased difficulties navigating and accessing therapies and programs, including those offered virtually. Participants reported behavioural regressions and increased anxiety among their children with DD, as well as caregiver mental health challenges. Providers reported having to change their service delivery model in accordance with public health recommendations, but caregivers said that they were not included in these decisions. Conclusion Families of children with DD face extraordinary barriers to care, which may be further compounded by the COVID-19 pandemic. Our study demonstrates the value of community-informed design, particularly in the setting of the COVID-19 pandemic. To deliver truly patient-centred services during the pandemic, there is an urgent need for responsive programming that is built with patients, for patients.
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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 | 0.017 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.012 | 0.005 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".