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Record W4200291645 · doi:10.1093/geroni/igab046.3460

Age-related Changes in Ongoing Thought Relate to External Context and Individual Cognition

2021· article· en· W4200291645 on OpenAlexaff
Adam Turnbull, Giulia Poerio, Feng Lin, Jonathan Smallwood

Bibliographic record

VenueInnovation in Aging · 2021
Typearticle
Languageen
FieldHealth Professions
TopicNoise Effects and Management
Canadian institutionsQueen's University
Fundersnot available
KeywordsPsychologyCognitionContext (archaeology)Experience sampling methodSet (abstract data type)Developmental psychologyExploratory researchSimilarity (geometry)Episodic memoryCognitive psychologySocial psychology

Abstract

fetched live from OpenAlex

Abstract Understanding how age-related changes in cognition manifest in the real world is an important goal for aging research. One means of capturing these changes involves “experience sampling” participant’s self-reported thoughts as they go about their daily lives. Previous research using this method has shown age-related changes in ongoing thought: e.g., older adults have fewer thoughts unrelated to the here-and-now. However, it is currently unclear how these changes reflect cognitive aging or lifestyle changes. 78 younger adults and 35 older adults rated their thought contents along 20 dimensions and the difficulty of their current activity in their daily lives. They also performed cognitive tasks in the laboratory. In a set of exploratory analyses using Principal Component Analysis (PCA), we found that older adults spent more time thinking positive, wanted thoughts, particularly in demanding contexts, suggesting they may use different strategies to regulate their emotions. In line with previous research, older adults spent less time mind wandering about their future selves. Past-related thought related to episodic memory differently in older and younger adults. Additionally, PCA analyses performed separately in older and younger adults showed high similarity to an analysis performed on the combined sample, suggesting a similar structure to ongoing daily life thought in older and younger adults. These findings inform the use of experience sampling to understand cognitive aging, highlighting the need to consider content along multiple dimensions as well as the context in which thoughts are reported when analyzing aging ongoing thought.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.724
Threshold uncertainty score0.372

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.063
GPT teacher head0.382
Teacher spread0.319 · 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

Citations1
Published2021
Admission routes1
Has abstractyes

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