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Record W2107063745 · doi:10.1017/s1041610207004966

The measuring, meaning and importance of activities of daily living (ADLs) as an outcome

2007· article· en· W2107063745 on OpenAlexafffund
Kenneth Rockwood

Bibliographic record

VenueInternational Psychogeriatrics · 2007
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHealth Systems, Economic Evaluations, Quality of Life
Canadian institutionsDalhousie University
FundersDalhousie Medical Research Foundation
KeywordsDementiaActivities of daily livingCognitionCognitive impairmentPsychologyMeaning (existential)Physical medicine and rehabilitationFunctional impairmentClinical trialMedicineClinical psychologyGerontologyCognitive psychologyPsychiatryPsychotherapistDisease

Abstract

fetched live from OpenAlex

Dementia is defined as global cognitive impairment that interferes with function; however, function has been less well measured than cognition in anti-dementia drug trials. In the modern era of anti-dementia clinical trials, measurement of function has improved by differentiating between the aspects of function that have been impaired--for example, impaired initiative versus ineffective performance, as is evaluated by the Disability Assessment for Dementia. Obstacles remain, including how best to distinguish the concepts of functional impairment and disability, how broad to make the range of functional impairment (e.g. whether it should include impaired performance of hobbies, or withdrawal from leisure activities) to individualize assessment, and to distinguish cognitive from non-cognitive causes of impaired function. Even though it appears that improved function is commonly related to improved executive function, and that the latter, more than other aspects of improved cognition, is the effect most prized by patients, families and physicians, functional assessment measures are often less sensitive to change than other outcome measures. How best to improve sensitivity to change of functional measurements is controversial, but it is necessary to do so in order to evaluate the full effects of treatment.

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)0.016
metaresearch head score (Gemma)0.003
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 score0.188
Threshold uncertainty score0.541

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0160.003
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 head0.231
GPT teacher head0.438
Teacher spread0.207 · 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

Citations36
Published2007
Admission routes2
Has abstractyes

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