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Record W2339851178

THE FUNCTIONAL AUTONOMY MEASUREMENT SYSTEM (SMAF): A CLINICAL-BASED INSTRUMENT FOR MEASUR- ING DISABILITIES AND HANDICAPS IN OLDER PEOPLE

2001· article· en· W2339851178 on OpenAlexaff
Réjean Hébert, Johanne Guilbault, Nicole Dubuc

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMedicine
TopicCerebral Palsy and Movement Disorders
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsActivities of daily livingAutonomyPsychological interventionScale (ratio)PsychologyReliability (semiconductor)Independent livingPatient-Reported Outcomes Measurement Information SystemApplied psychologyGerontologyMedicineClinical psychologyPsychometricsComputerized adaptive testingPsychiatry
DOInot available

Abstract

fetched live from OpenAlex

The SMAF (Functional Autonomy Measurement System) is a 29-item scale developed according to the WHO classification of disabilities.It measures functional ability in 5 areas: activities of daily living (ADL) [7 items], mobility [6 items], communication [3 items], mental functions [5 items] and instrumental activities of daily living (IADL) [8 items]. For each item,the disability is scored on a 5-point scale:0 (independent), -0.5 (with difficulty), -1 (needs supervision), -2 (needs help), -3 (dependent). Resources available to compensate the disability are also evaluated, and a handicap score is deducted. Stability of the resources is also assessed. A disability score (on -87) can be calculated, together with sub-scores for each dimension. SMAF must be administered by a health professional (nurse or social worker) who scores the subject after obtaining the information, either by questioning the subject and proxies, or by observing and even testing the subject.This instrument was submitted to many validity and reliability studies. It is responsive to interventions, and a change of 5 points or more should be considered the minimal metrically d e t e c t a ble ch a n ge and cl i n i c a l ly significant. Correspondence of the SMAF score with the required nursing-care time and the cost of long-term care, either at home or in different institutional settings,has been established.It has been utilized in many epidemiological and evaluative studies.It is also used in the clinical setting for assessment and follow-up of elderly disabled patients in the institution, in the community and in rehabilitation programs.

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)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.054
Threshold uncertainty score0.371

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.076
GPT teacher head0.294
Teacher spread0.218 · 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.

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

Citations64
Published2001
Admission routes1
Has abstractyes

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