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Record W4404919516 · doi:10.5770/cgj.27.771

New Disability in a Cohort Study of Older Men—The Manitoba Follow-Up Study

2024· article· en· W4404919516 on OpenAlexafffundvenueabout
Philip D. St. John, Scott Nowicki, Robert B. Tate

Bibliographic record

VenueCanadian Geriatrics Journal · 2024
Typearticle
Languageen
FieldMedicine
TopicFrailty in Older Adults
Canadian institutionsUniversity of WinnipegUniversity of ManitobaManitoba HealthHealth Sciences Centre
FundersCanadian Institutes of Health Research
KeywordsMedicineIncidence (geometry)CohortCohort studyGerontologyProspective cohort studyDemographyPhysical therapyInternal medicine

Abstract

fetched live from OpenAlex

Background: There is a large literature on the prevalence of disability in older men, but less data on the incidence of new disability. Objectives: 1. To determine the incidence of moderate-to-severe disability in a prospective cohort study of aging men; and 2. To determine predisposing risk factors for new moderate to severe disability. Design & Setting: The Manitoba Follow-up Study is a closed cohort study. In 1948, the initial sample was 3,983 men who qualified for air crew training in the Royal Canadian Air Force. In 2004, there were 796 men who were still alive and responded to the annual questionnaire with no missing data, and who did not have disability. The mean age at that time was 84. Methods: We calculated the incidence of new moderate-to-severe disability from 2004 to 2017, calculated the time to disability, and constructed survival analysis models to determine factors which predicted disability. Results: The incidence of disability increased with the aging of the cohort and ranged from 4% to 12% per year. In unadjusted models, poor self-rated health (SRH), low life satisfaction, a low score on the Physical Component Score (PCS) of the Short Form-36, and the number of chronic conditions were all associated with new disability. In adjusted models, SRH, the PCS, and the number of chronic conditions were associated with new disability. Conclusions: Global measures of well-being, as well as multimorbidity, predict new disability.

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)0.001
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 score0.583
Threshold uncertainty score0.748

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.019
GPT teacher head0.278
Teacher spread0.259 · 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

Citations0
Published2024
Admission routes4
Has abstractyes

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