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Record W4285385992 · doi:10.1007/s10826-022-02336-8

A Qualitative Examination of the Impact of the COVID-19 Pandemic on Individuals with Neuro-developmental Disabilities and their Families

2022· article· en· W4285385992 on OpenAlexafffund
David Nicholas, Wendy Mitchell, Jill Ciesielski, Arisha Khan, Lucyna Lach

Bibliographic record

VenueJournal of Child and Family Studies · 2022
Typearticle
Languageen
FieldPsychology
TopicFamily and Disability Support Research
Canadian institutionsMcGill UniversityMcGill University Health CentreUniversity of CalgaryUniversity of Alberta
FundersKids Brain Health NetworkAzrieli Foundation
KeywordsPandemicPsychologyPsychological resilienceFlexibility (engineering)PopulationMental healthFocus groupCoronavirus disease 2019 (COVID-19)Service providerResilience (materials science)Qualitative researchDevelopmental psychologyService (business)MedicinePsychiatryBusinessEnvironmental healthSocial psychologySociologyDisease

Abstract

fetched live from OpenAlex

Individuals with neuro-developmental disabilities (NDD) have been profoundly affected by the COVID-19 pandemic. Based on focus groups with 24 service providers supporting this population, using an Interpretive Description approach, we examined perceived impacts of the pandemic on individuals with NDD and their families. The results highlight pandemic-related experiences which include: service reduction, the need for financial supports, relying on natural supports, and school-related challenges. Interruptions in services have resulted in intensified mental health issues for individuals with NDD and family caregivers, with particular concern for those with added social determinants of health-related barriers. Mitigating factors have also emerged, such as resilience and technology utilization to facilitate communication. Recommendations for resource flexibility and sufficiency as well as navigational support are offered.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.134
Threshold uncertainty score0.521

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.135
GPT teacher head0.418
Teacher spread0.282 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations16
Published2022
Admission routes2
Has abstractyes

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