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Record W3003735931 · doi:10.1017/s0714980819000758

Operationalizing the Disablement Process for Research on Older Adults: A Critical Review

2020· review· en· W3003735931 on OpenAlexafffund
Natasha E. Lane, Cynthia M. Boyd, Thérèse A. Stukel, Walter P. Wodchis

Bibliographic record

VenueCanadian Journal on Aging / La Revue canadienne du vieillissement · 2020
Typereview
Languageen
FieldSocial Sciences
TopicRetirement, Disability, and Employment
Canadian institutionsInstitute for Clinical Evaluative SciencesTrillium Health CentreToronto Rehabilitation InstituteUniversity of Toronto
FundersNational Institute on AgingCanadian Institutes of Health Research
KeywordsOperationalizationProcess (computing)PsychologyProcess managementComputer scienceEngineeringEpistemologyPhilosophy

Abstract

fetched live from OpenAlex

Self-care disability is difficulty with or dependence on others to perform activities of daily living, such as eating and dressing. Disablement is worsening self-care disability measured over time. The disablement process model (DPM) is often used to conceptualize gerontology research on self-care disability and disablement; however, no summary of variables that align with person-level DPM constructs exists. This review summarizes the results of 88 studies to identify the nature and role of variables associated with disability and disablement in older adults according to the person-level constructs (e.g., demographic characteristics, chronic pathologies) in the DPM. It also examines the evidence for cross-sectional applications of the DPM and identifies common limitations in extant literature to address in future research. Researchers can apply these results to guide theory-driven disability and disablement research using routinely collected health data from older adults.

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)0.020
metaresearch head score (Gemma)0.053
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.020
Threshold uncertainty score0.107

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0200.053
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0050.004
Bibliometrics0.0110.010
Science and technology studies0.0010.002
Scholarly communication0.0040.005
Open science0.0030.002
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0030.001

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 head0.293
GPT teacher head0.480
Teacher spread0.187 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations10
Published2020
Admission routes2
Has abstractyes

Explore more

Same venueCanadian Journal on Aging / La Revue canadienne du vieillissementSame topicRetirement, Disability, and EmploymentFrench-language works237,207