MétaCan
Menu
Back to cohort
Record W2995686345 · doi:10.1177/2333721419895617

“At 80 I Know Myself”: Embodied Learning and Older Adults’ Experiences of Polypharmacy and Perceptions of Deprescribing

2019· article· en· W2995686345 on OpenAlexaff
Alison Ross, James Gillett

Bibliographic record

VenueGerontology and Geriatric Medicine · 2019
Typearticle
Languageen
FieldMedicine
TopicPharmaceutical Practices and Patient Outcomes
Canadian institutionsMcMaster University
Fundersnot available
KeywordsPolypharmacyDeprescribingEmbodied cognitionPerceptionPerspective (graphical)Aging in placeGerontologyOlder peopleMedicinePsychologyComputer scienceIntensive care medicine

Abstract

fetched live from OpenAlex

In response to the risks of polypharmacy for older adults, there are increasing calls for the development and implementation of deprescribing programs. This article examines the forms of expertise that inform older adults' decisions about how to use medications given concerns over polypharmacy and a clinical focus on deprescribing. In-depth interviews with older adults found that diverse knowledge sources underpin decisions regarding polypharmacy and deprescribing. Findings indicate that this knowledge is formed through a lifetime of embodied learning-the production of relevant knowledge through lived experiences of the body. By way of this embodied learning, older adults possess individualized knowledge bases that inform health and health care decisions, especially regarding the use of medications. If deprescribing programs are to be embedded into standard preventive medical care of older adults, then it is valuable for health care providers to be aware of and take seriously the contribution of embodied knowledge.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.122
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.038
GPT teacher head0.365
Teacher spread0.326 · 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

Citations8
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueGerontology and Geriatric MedicineSame topicPharmaceutical Practices and Patient OutcomesFrench-language works237,207