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Feeding/Swallowing Disorders: Maintaining Quality of Life in Persons with Intellectual Disability

2016· article· en· W2475641250 on OpenAlexvenueno aff
Luis F. Riquelme, Rebecca D. Benjamin, Hannah J. Tahhan, Gracelynn K. Sandoval, Naga Alomari, Alexandra Soyfer

Bibliographic record

VenueJournal of Intellectual Disability - Diagnosis and Treatment · 2016
Typearticle
Languageen
FieldHealth Professions
TopicDysphagia Assessment and Management
Canadian institutionsnot available
Fundersnot available
KeywordsChokingSwallowingIntellectual disabilityLife expectancyPopulationMedicineQuality of life (healthcare)Health careEtiologyPsychologyGerontologyPhysical therapyPsychiatryNursingEnvironmental health

Abstract

fetched live from OpenAlex

Persons with intellectual disability (ID) have received little attention in systematic studies of healthcare and quality of life. Less attention has been provided to specific disorders, such as those impacting the swallowing mechanism. In comparison to the general population, persons with ID experience noticeably greater healthcare inequalities and despite greater life expectancy, it is still lower than the general population. This paper serves as an introduction to healthcare colleagues regarding the risks involved in choking and swallowing disorders in persons with ID, how to evaluate these potential risks and possible treatments. Associated etiologies are presented. A discussion on feeding disorders versus swallowing disorders is also introduced. The inadequacy of swallowing assessment services to persons with ID may be related to the lack of professionals with specialized training in working with this population, reduced funding for research to explore options for improved nutrition and reduced risk of choking and minimal research on changes in feeding skills and/or swallow physiology in this select group of individuals

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)0.007
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.050
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0020.000

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 head0.084
GPT teacher head0.397
Teacher spread0.313 · 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.

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

Citations6
Published2016
Admission routes1
Has abstractyes

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