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Record W4292822917 · doi:10.1080/13825585.2022.2110562

The impact of retirement on executive functions and processing speed: findings from the Canadian Longitudinal Study on Aging

2022· article· en· W4292822917 on OpenAlexafffundabout
Catherine Gosselin, Benjamin Boller

Bibliographic record

VenueAging Neuropsychology and Cognition · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicRetirement, Disability, and Employment
Canadian institutionsUniversité du Québec à Trois-RivièresInstitut Universitaire de Gériatrie de Montréal
FundersCanadian Institutes of Health ResearchSocial Sciences and Humanities Research Council of CanadaGovernment of Canada
KeywordsStroop effectPropensity score matchingPsychologySample size determinationLongitudinal studyCohortPost-hoc analysisSample (material)CognitionGerontologyDemographyMedicinePsychiatryStatisticsSociology

Abstract

fetched live from OpenAlex

= 1442), 45-85 years of age at baseline. Speed processing and executive functioning were assessed using standardized assessment tools at baseline and at follow-up, measured 3 years later. Retirees and workers were matched for age, sex, and education using the nearest neighbor propensity score method with a caliper of 0.02. Mixed ANOVA and post hoc analyses were conducted separately for the English- and French-speaking samples. Results for the English-speaking sample showed a significant decline on both the Stroop and the Mental Alternation tasks for retirees compared to workers from baseline to follow-up. These results support previous cross-sectional studies that have demonstrated a negative effect of retirement on executive functioning. The absence of significant results in the French-speaking sample are discussed in terms of sample size and professional occupation.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0040.000
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 head0.217
GPT teacher head0.439
Teacher spread0.223 · 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.

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

Citations5
Published2022
Admission routes3
Has abstractyes

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