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Relationship Between Mobility Limitations and the Places Where Older Adults With Intellectual Disabilities Live

2008· article· en· W2127273512 on OpenAlexaffabout
Shaun Cleaver, Hélène Ouellette‐Kuntz, Duncan Hunter

Bibliographic record

VenueJournal of Policy and Practice in Intellectual Disabilities · 2008
Typearticle
Languageen
FieldMedicine
TopicChronic Disease Management Strategies
Canadian institutionsChronic Disease Prevention Alliance of CanadaQueen's University
Fundersnot available
KeywordsResidenceProxy (statistics)GerontologyPsychologyPopulationDemographyMedicineSociology

Abstract

fetched live from OpenAlex

ABSTRACT As the population ages, mobility limitations are associated with increased mortality and negative health‐related states both in the general population and among people with intellectual disabilities. The influence of mobility limitations upon the lives and lifestyles of people with intellectual disabilities remains poorly understood. Specifically, the extent to which mobility limitations might limit residential options for individuals and families has not been evaluated. To determine the relationship between mobility limitations and place of residence for adults with intellectual disabilities, age 45 and older, a proxy‐response telephone survey was completed for 128 adults with intellectual disabilities in Southeastern Ontario. A participant's place of residence was categorized as being “high support” (group homes and nursing homes) or “low support” (living alone, with family, roommates, or host family). People with a score of 12 or less on the Rivermead Mobility Index were considered to have a mobility limitation. The relationship between mobility limitations and high‐support residential settings was analyzed using a multivariate logistic regression model. After adjusting for age, sex, and presence of cerebral palsy, communication problems and behavior problems, people with mobility problems had 3.6 times greater odds of living in high‐support settings. Authors concluded that mobility limitations are associated with residence in “high‐support” settings and that further investigation is needed to determine the direction of causality and to create programs and services that equalize opportunities.

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)0.000
metaresearch head score (Gemma)0.004
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 score0.112
Threshold uncertainty score0.222

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.099
GPT teacher head0.355
Teacher spread0.256 · 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

Citations9
Published2008
Admission routes2
Has abstractyes

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Same venueJournal of Policy and Practice in Intellectual DisabilitiesSame topicChronic Disease Management StrategiesFrench-language works237,207