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There is always Sorrow: Risk Factors Faced by Parents of Children Presenting with Severe Intellectual Disabilities

2024· article· en· W4397005343 on OpenAlexvenueno aff
Sandisiwe Buthelezi, Daphney Mawila

Bibliographic record

VenueJournal of Intellectual Disability - Diagnosis and Treatment · 2024
Typearticle
Languageen
FieldPsychology
TopicFamily and Disability Support Research
Canadian institutionsnot available
Fundersnot available
KeywordsThematic analysisPsychologyFocus groupIntellectual disabilityQualitative researchMultidisciplinary approachDevelopmental psychologyClinical psychologyMedicinePsychiatry

Abstract

fetched live from OpenAlex

Background: This study investigates the risk factors faced by parents of children with Severe Intellectual Disabilities. Methods: This study used a phenomenological research design within a qualitative research approach. Six parents of children diagnosed with Severe Intellectual Disability at Learners with Special Educational Needs schools were purposively selected to participate in this study. Data were collected through semi-structured interviews and a focus group. Thematic data analysis was used to analyze data. Results: The findings of this study revealed that parents of children with Severe Intellectual Disabilities faced risks that exacerbated negative outcomes. Psychological distress, social exclusion and isolation, financial burdens, and lack of access to formal education were risk factors that hindered their ability to care for and support their children. Conclusions: Based on these findings, the study concluded that parents need access to multidisciplinary teams of healthcare professionals to support them in combatting the risk factors they face.

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)0.002
metaresearch head score (Gemma)0.012
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 score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0030.002
Scholarly communication0.0020.001
Open science0.0000.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0010.000

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 head0.045
GPT teacher head0.325
Teacher spread0.281 · 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

Citations4
Published2024
Admission routes1
Has abstractyes

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