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Record W3095703500 · doi:10.1111/jir.12791

Down syndrome caregivers' support needs: a mixed‐method participatory approach

2020· article· en· W3095703500 on OpenAlexafffund
Kristen Hart, Nicole Neil

Bibliographic record

VenueJournal of Intellectual Disability Research · 2020
Typearticle
Languageen
FieldPsychology
TopicFamily and Disability Support Research
Canadian institutionsWestern University
FundersWestern University
KeywordsCitizen journalismPsychologyNursingComputer scienceMedicineWorld Wide Web

Abstract

fetched live from OpenAlex

BACKGROUND: The purpose of the study was to explore the support needs of caregivers of children with Down syndrome from their perspective using a mixed-method participatory research approach. METHODS: Concept mapping methodology was used to obtain caregiver perspectives. Twenty-one caregivers answered the question 'Are parents of individuals with Down syndrome supported, why or why not?' Caregivers were involved in the analysis of the data through concept mapping procedures. RESULTS: Sorted data were analysed with multidimensional scaling and cluster analysis. Participants generated eight thematic clusters representing the support needs of caregivers of children with Down syndrome. The themes included online and social support, support system gaps, areas where support is lacking, Down syndrome community support, financial support, advocacy needs, educational support and concerns for community programming. CONCLUSIONS: Themes align with previous research on support needs of parents of children with developmental disabilities. The study highlights the need for more local organisations to offer support that is affordable and accessible for families. Results will support future programme planning for services for individuals caring for those with Down syndrome.

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)0.013
metaresearch head score (Gemma)0.017
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.575
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0130.017
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.003
Science and technology studies0.0000.003
Scholarly communication0.0000.000
Open science0.0020.001
Research integrity0.0000.004
Insufficient payload (model declined to judge)0.0280.002

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 head0.286
GPT teacher head0.458
Teacher spread0.172 · 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; both teacher heads agree on what is shown here.

Study designQualitative
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

Citations19
Published2020
Admission routes2
Has abstractyes

Explore more

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