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Record W3107747457 · doi:10.12688/hrbopenres.13077.2

COVID-19 IDD: A global survey exploring family members’ and paid staff’s perceptions of the impact of COVID-19 on individuals with intellectual and developmental disabilities and their caregivers.

2020· preprint· en· W3107747457 on OpenAlexaff
Christine Linehan, Tal Araten‐Bergman, Jennifer Baumbusch, Julie Beadle‐Brown, Christine Bigby, Gail Birkbeck, Valerie J. Bradley, Michael Brown, Femmianne Bredewold, Masauso Chirwa, Jialiang Cui, Marta Godoy Gimenez, Tiziano Gomiero, Thilo Kroll, Malcolm MacLachlan, Brigit Mirfin‐Veitch, Jayanthi Narayan, Finiki Nearchou, Adam Nolan, Mary-Ann O’Donovan, Flávia H. Santos, Jan Šiška, Tim Stainton, Magnus Tideman, Jan Tøssebro

Bibliographic record

VenueHRB Open Research · 2020
Typepreprint
Languageen
FieldMedicine
TopicDown syndrome and intellectual disability research
Canadian institutionsQueen's UniversityUniversity of British ColumbiaCanadian Institute for Advanced Research
FundersHealth Research Board
KeywordsIntellectual disabilityPopulationPsychologyMedical educationMedicinePublic relationsPolitical sciencePsychiatry

Abstract

fetched live from OpenAlex

Background : This protocol outlines research to explore family members’ and paid staff’s perceptions of the impact of COVID-19 on individuals with intellectual and developmental disabilities and their caregivers. Evidence suggests that people with intellectual and developmental disabilities experience disparities in healthcare access and utilisation. This disparity was evident early in the pandemic when discussions arose regarding the potential exclusion of this population to critical care. Methods : An anonymous online survey will be conducted with caregivers, both family members and paid staff, to explore their perceptions of the impact of COVID-19 in terms of demographics, living arrangements, access to services, social distancing, and carer wellbeing. The survey will be developed by the research team, many of whom are experts in intellectual disability within their own jurisdictions. Using back-translation our team will translate the survey for distribution in 18 countries worldwide for international comparison. The survey team have extensive personal and professional networks and will promote the survey widely on social media with the support of local disability and advocacy agencies. Statistical descriptive and comparative analyses will be conducted. Ethical approval has been obtained for this study from University College Dublin’s Human Research Ethics Committee (HS-20-28-Linehan). Dissemination : Study findings will be prepared in a number of formats in order to meet the needs of different audiences. Outputs will include academic papers, lessons learned paper, practice guidelines, reports, infographics and video content. These outputs will be directed to families, frontline and management delivering disability services, national-level policy makers, healthcare quality and delivery authorities, national pandemic organisations and international bodies.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.008
metaresearch head score (Gemma)0.015
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.022
Threshold uncertainty score0.045

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.015
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0020.001
Scholarly communication0.0010.002
Open science0.0010.005
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0110.002

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 head0.428
GPT teacher head0.468
Teacher spread0.040 · 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 source (direct Gemma or distilled Codex), 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

Citations28
Published2020
Admission routes1
Has abstractyes

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