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Record W1516765900 · doi:10.1002/acp.2946

The Use and Benefits of External Memory Aids in Older and Younger Adults

2013· article· en· W1516765900 on OpenAlexaff
Emily Schryer, Michael G. Ross

Bibliographic record

VenueApplied Cognitive Psychology · 2013
Typearticle
Languageen
FieldPsychology
TopicAging and Gerontology Research
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsPsychologyRecallTask (project management)Young adultMemory impairmentCognitionDevelopmental psychologyCognitive psychologyPsychiatry

Abstract

fetched live from OpenAlex

Summary We examined the spontaneous use and benefits of external memory aids in older (aged 60–85 years) and younger (aged 17–31 years) adults. In Study 1, participants were or were not given the opportunity to use a memory aid in a phone message recall task. In Study 2, a memory aid was available for one of two similar tasks. Participants' spontaneous use of external memory aids was measured. On the Memory Compensation Questionnaire, older adults reported using external memory aids more frequently but were no more likely than younger adults to take notes on the messages. Older adults benefitted from the availability of notes in both studies; younger adults benefitted when the memory task was more challenging. The results illustrate the value of external memory aids and suggest that older adults may underutilize them. The findings also raise questions about the relation between self‐reported and actual use of strategies in everyday life. Copyright © 2013 John Wiley & Sons, Ltd.

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)0.001
metaresearch head score (Gemma)0.006
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 score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.050
GPT teacher head0.344
Teacher spread0.295 · 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

Citations29
Published2013
Admission routes1
Has abstractyes

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