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Record W1526656226 · doi:10.5334/ijic.1076

Communicating during care transitions for older hip fracture patients: family caregiver and health care provider's perspectives

2013· article· en· W1526656226 on OpenAlexafffund
Christine Glenny, Paul Stolee, Linda Sheiban, Susan Jaglal

Bibliographic record

VenueInternational Journal of Integrated Care · 2013
Typearticle
Languageen
FieldMedicine
TopicHip and Femur Fractures
Canadian institutionsCanada Research ChairsUniversity of WaterlooUniversity of Toronto
FundersCanadian Institutes of Health ResearchUniversity of Toronto
KeywordsPsychological interventionHealth careMedicineNursingInformation sharingFamily caregiversFocus groupFamily medicineBusiness

Abstract

fetched live from OpenAlex

INTRODUCTION: Older hip fracture patients frequently require care across a variety of settings, from multiple individuals, including their family caregivers. We explored issues related to information sharing during transitional care for older hip fracture patients through the perspectives of both health care providers and family caregivers. METHODS: Thirty-five semi-structured interviews were conducted with family caregivers (n = 9) and health care providers (n = 26) of six hip fracture patients to gather perspectives on information sharing at each care transition, beginning with post-surgical discharge from acute care. Data were analysed using conventional qualitative content analysis methods using NVivo8 software. RESULTS: Both family caregivers and health care providers recognise that family caregivers' involvement has important benefits for patients, but this involvement is frequently limited by poor information sharing. Barriers include limited staff time, patient privacy regulations and lack of a clear structure to guide information sharing. Receiving, not offering, information was the focus of information sharing by both family caregivers and health care providers. CONCLUSIONS: Specific barriers that lead to poor information sharing between family caregivers and health care providers have been identified in this study. Possible interventions to improve information sharing include encouraging communication with family caregivers as standard care practice, educational strategies and more effective use of health information systems and technologies.

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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.097
Threshold uncertainty score0.621

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 integrity0.0000.001
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 head0.011
GPT teacher head0.299
Teacher spread0.288 · 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

Citations51
Published2013
Admission routes2
Has abstractyes

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