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Record W2970326862 · doi:10.1177/1049732319868981

Confronting Medicine’s Dichotomies: Older Adults’ Use of Interpretative Repertoires in Negotiating the Paradoxes of Polypharmacy and Deprescribing

2019· article· en· W2970326862 on OpenAlexaff
Alison Ross, James Gillett

Bibliographic record

VenueQualitative Health Research · 2019
Typearticle
Languageen
FieldMedicine
TopicPharmaceutical Practices and Patient Outcomes
Canadian institutionsMcMaster University
Fundersnot available
KeywordsPolypharmacyDeprescribingNarrativeNegotiationDichotomyQualitative researchMedicineNarrative inquiryOlder peopleHealth careGeriatricsGerontologyPsychologyPsychiatrySociologyPolitical science

Abstract

fetched live from OpenAlex

To address the risks associated with polypharmacy, health care providers are investigating the feasibility of deprescribing programs as part of routine medical care to reduce medication burden to older adults. As older adults are enrolled in these programs, they are confronted with two dominant and legitimate accounts of medications, labeled the medication paradox: medications keep you healthy but they might be making you sick. We investigated how the medication paradox operates in the lives of older adults. In-depth qualitative interviews were conducted and analyzed with older adults aged 70+ to identify the various paradoxes that seniors live through regarding their medications and the narratives that they engage to negotiate these contradictions. Older adults were found to have established interpretative repertoires to make sense of the incongruent narratives of the medication paradox. In this article, we demonstrate older adults’ efforts to carve out their unique place in the dichotomized institution of medicine.

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)0.042
metaresearch head score (Gemma)0.037
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.042
Threshold uncertainty score0.220

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0420.037
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.001
Science and technology studies0.0090.030
Scholarly communication0.0080.012
Open science0.0020.013
Research integrity0.0020.004
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 head0.573
GPT teacher head0.612
Teacher spread0.039 · 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 designQualitative
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

Citations9
Published2019
Admission routes1
Has abstractyes

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