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Record W2141962341 · doi:10.1177/1049732312457467

Patient Perceptions of the Path to Osteoporosis Care Following a Fragility Fracture

2012· article· en· W2141962341 on OpenAlexafffundabout
Dorcas Beaton, R. Sujic, Kristin McIlroy Beaton, Joanna E. M. Sale, Victoria Elliot‐Gibson, Earl R. Bogoch

Bibliographic record

VenueQualitative Health Research · 2012
Typearticle
Languageen
FieldMedicine
TopicBone health and osteoporosis research
Canadian institutionsUniversity of Toronto
FundersMerck Sharp and DohmeOntario Ministry of Health and Long-Term CareEli Lilly and Company
KeywordsFragility fractureFragilityFocus groupOsteoporosisMedicineAction (physics)Orthopedic surgerySurgeryInternal medicineBone mineral

Abstract

fetched live from OpenAlex

Coordinator-based osteoporosis (OP) screening programs for fragility-fracture patients in orthopedic environments improve rates of OP testing and care, but there are still gaps in care. The purpose of this study was to understand the process by which patients decided whether to proceed with OP testing or care within these programs. Twenty-four fragility-fracture patients in the OP screening program at a large, urban, university hospital in Canada participated in one of five focus groups. Focus group transcripts were sorted and coded. Links between themes were developed to generate a description of the process leading to successful initiation of OP care after a fragility fracture. To initiate OP testing and care, patients had to both comprehend the link between their fragility fracture and OP, and make an action-oriented appraisal of what action to take. Several modifiable facilitators and barriers influenced the process between screening and undergoing OP testing and initiating treatment.

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)0.009
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation 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 score0.380
Threshold uncertainty score0.775

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
Science and technology studies0.0010.000
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 head0.166
GPT teacher head0.541
Teacher spread0.374 · 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 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

Citations31
Published2012
Admission routes3
Has abstractyes

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