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Record W2170012663

What influences seniors' choice of medications for osteoarthritis? Qualitative inquiry.

2006· article· en· W2170012663 on OpenAlexaffabout
Kelly Nicol Bower, Dawn Frail, Peter L. Twohig, Wayne Putnam

Bibliographic record

VenuePubMed · 2006
Typearticle
Languageen
FieldMedicine
TopicMedication Adherence and Compliance
Canadian institutionsDalhousie University
Fundersnot available
KeywordsOsteoarthritisQualitative researchNova scotiaMedicineGrounded theoryFamily medicineQuality (philosophy)Alternative medicinePsychologyPathologySociology
DOInot available

Abstract

fetched live from OpenAlex

OBJECTIVE: To explore with seniors what influences their choice of medication for osteoarthritis. DESIGN: Qualitative study using semistructured in-depth interviews. SETTING: Interviews were conducted in patients' homes in two cities in Nova Scotia. PARTICIPANTS: Seniors with a physician-confirmed diagnosis of osteoarthritis. METHOD: Interviews were audiotaped and transcribed verbatim. A grounded-theory approach was used. Key words and phrases were identified independently by all members of the research team who then collectively grouped the data into conceptual categories. MAIN FINDINGS: Four themes emerged from discussions about medication choices: the role of family physicians in influencing use of cyclooxygenase-2 inhibitors, the effect of fear of making medication choices, the reasons for discontinuing cyclooxygenase-2 inhibitors, and views on other information sources. Distribution of free samples, family physicians' recommendations, and fear of side effects influenced seniors' choices of osteoarthritis medications. They claimed not to be influenced by direct-to-consumer advertising or the fact that cyclooxygenase-2 inhibitors are more expensive than other classes of drugs for osteoarthritis. CONCLUSION: Because seniors' choice of medications for osteoarthritis is often influenced by physicians' recommendations and distribution of free samples, further research into how distribution of free samples affects medication choices in family practice is needed.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.815
Threshold uncertainty score0.306

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0000.000

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 head0.092
GPT teacher head0.382
Teacher spread0.290 · 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.

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

Citations11
Published2006
Admission routes2
Has abstractyes

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