MétaCan
Menu
Back to cohort
Record W2731832053 · doi:10.1093/geroni/igx004.3899

PSYCHOSOCIAL STRESS AND RESPONSE TIME INCONSISTENCY IN OLD AGE: A MEASUREMENT BURST APPROACH

2017· article· en· W2731832053 on OpenAlexaff
Robert S. Stawski, Stuart MacDonald

Bibliographic record

VenueInnovation in Aging · 2017
Typearticle
Languageen
FieldPsychology
TopicAging and Gerontology Research
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsPsychosocialStressorPsychologyCognitionStress (linguistics)Clinical psychologyCognitive agingAffect (linguistics)Developmental psychologyPsychiatry

Abstract

fetched live from OpenAlex

Psychosocial stress has been identified as an important modifiable risk factor for normal and pathological cognitive aging. Evidence exists showing psychosocial stress predicting poorer performance across multiple cognitive domains (e.g., working memory), with limited research considering stress effects on response time inconsistency (RTI). Using data from a measurement burst design, 111 older adults (Mage=80, Range=66–95) completed a processing speed task on 6 occasions over a 14-day period, repeating this protocol every 6 months for 2.5 years. Participants also completed measures of daily and perceived stress. Results from multilevel models revealed that individual differences in emotional (affect) and psychosomatic (pain) reactions to daily stressors and global perceptions of stress were associated with greater RTI (ps<.001). Additionally, these associations increased with age (p<.01). Discussion will focus on the importance of different dimensions of psychosocial stress for understanding cognitive aging, and the utility of measurement burst designs for examining stress-RTI links.

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)0.018
metaresearch head score (Gemma)0.028
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.018
Threshold uncertainty score0.093

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0180.028
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.107
GPT teacher head0.395
Teacher spread0.289 · 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 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
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueInnovation in AgingSame topicAging and Gerontology ResearchFrench-language works237,207