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Rural Residence and Prescription Medication Use by Community‐Dwelling Older Adults: A Review of the Literature

2008· review· en· W2020144852 on OpenAlex
Ruby Grymonpre, Pamela Hawranik

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueThe Journal of Rural Health · 2008
Typereview
Languageen
FieldMedicine
TopicPharmaceutical Practices and Patient Outcomes
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsCINAHLMedicineMedical prescriptionResidencePsycINFOContext (archaeology)MEDLINERural areaGerontologyFamily medicineEnvironmental healthDemographyPsychological interventionGeographyNursing

Abstract

fetched live from OpenAlex

CONTEXT: Due to various barriers to health care access in the rural setting, there is concern that rural older adults might have lower access to prescribed medications than their urban counterparts. PURPOSE: To review published research reports to determine prevalence and mean medication use in rural, noninstitutionalized older adults and assess whether rural-urban differences exist. METHODS: PubMed, Ageline, Cinahl, PsycInfo, International Pharmaceutical Abstracts, Agricola, and Institute for Scientific Information Web of Science - Social Science Index were searched. English-language articles through May 2005 involving a sample of rural, noninstitutionalized older adults and analyses of overall medication prevalence and/or intensity were included. Review articles, conference abstracts, dissertations, books, and articles targeting nonprescription or specific therapeutic categories were excluded. A total of 206 citations were identified and 26 met the inclusion criteria. FINDINGS: Reported prevalence of prescription medication use by rural older adults varied between 62% and 96%, with 2-6 prescriptions per person. Multivariate analyses results were equally inconsistent. Controlling for insurance, most US studies suggest there is no rural-urban difference in access to prescribed medications. However, this finding may not be generalizable across all regions in the United States or other countries. CONCLUSIONS: Geographic location may not be as important a variable for medication usage as for other health services utilization.

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.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesResearch integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.692
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
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 integrity0.0000.002
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 head0.140
GPT teacher head0.451
Teacher spread0.311 · 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