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Record W4394694278 · doi:10.32920/25569735.v1

Effects of mindfulness training on cognition and wellbeing in healthy older adults

2024· preprint· en· W4394694278 on OpenAlexaboutno aff
Sasha Mallya, Alexandra Fiocco

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldPsychology
TopicHealth and Well-being Studies
Canadian institutionsnot available
Fundersnot available
KeywordsMindfulnessCognitionPsychologyTraining (meteorology)Cognitive trainingGerontologyClinical psychologyMedicinePsychiatry

Abstract

fetched live from OpenAlex

Adults over the age of 65 years are now the fastest growing segment of the Canadian population. Although individual differences exist, aging is commonly associated with impairments in executive function and episodic memory. Previous studies have shown that mindfulness-based stress reduction (MBSR) can improve cognitive function in healthy younger adults, but no studies have yet examined this effect in older adults. The present study investigated the effectiveness of MBSR on improving executive function and episodic memory in older adult as well as its effectiveness in improving perceived stress and well-being. Ninety-seven healthy older adults were randomly assigned to either MBSR (n = 57) or an active control group (n = 40). It was hypothesized that compared with the control group, the MBSR group would display significant improvements in measures of executive function, episodic memory, mindfulness, mood, self-esteem, and quality of life. No clinically meaningful changes were found on any variable. In light of these results, the value of MBSR for this population is discussed.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.021
GPT teacher head0.339
Teacher spread0.318 · 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 designNon-randomized trial
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 routes1
Has abstractyes

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