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Record W1872680692 · doi:10.2147/ppa.s86922

Back to the future – feasibility of recruitment and retention to patient education and telephone follow-up after hip fracture: a pilot randomized controlled trial

2015· article· en· W1872680692 on OpenAlexafffundabout
Dolores Langford, Maureen C. Ashe, Lena Fleig, Nancy Cho, Monique Ledoyen, Maeve Frost, Nina Sharpe, Jayne Lehn, Kristin Brown

Bibliographic record

VenuePatient Preference and Adherence · 2015
Typearticle
Languageen
FieldMedicine
TopicHip and Femur Fractures
Canadian institutionsUniversity of British ColumbiaVancouver Coastal HealthUniversity of British Columbia Hospital
FundersCanadian Institutes of Health ResearchVancouver Coastal Health Research InstituteUniversity of British ColumbiaMichael Smith Health Research BC
KeywordsMedicineCoachingRandomized controlled trialPhysical therapyPsychosocialPsychological interventionHealth coachingQuality of life (healthcare)AnxietyRandomizationHospital Anxiety and Depression ScaleNursingPsychiatryPsychology

Abstract

fetched live from OpenAlex

OBJECTIVES: Our primary aim of this pilot study was to test feasibility of the planned design, the interventions (education plus telephone coaching), and the outcome measures, and to facilitate a power calculation for a future randomized controlled trial to improve adherence to recovery goals following hip fracture. DESIGN: This is a parallel 1:1 randomized controlled feasibility study. SETTING: The study was conducted in a teaching hospital in Vancouver, BC, Canada. PARTICIPANTS: Participants were community-dwelling adults over 60 years of age with a recent hip fracture. They were recruited and assessed in hospital, and then randomized after hospital discharge to the intervention or control group by a web-based randomization service. Treatment allocation was concealed to the investigators, measurement team, and data entry assistants and analysts. Participants and the research physiotherapist were aware of treatment allocation. INTERVENTION: Intervention included usual care for hip fracture plus a 1-hour in-hospital educational session using a patient-centered educational manual and four videos, and up to five postdischarge telephone calls from a physiotherapist to provide recovery coaching. The control group received usual care plus a 1-hour in-hospital educational session using the educational manual and videos. MEASUREMENT: Our primary outcome was feasibility, specifically recruitment and retention of participants. We also collected selected health outcomes, including health-related quality of life (EQ5D-5L), gait speed, and psychosocial factors (ICEpop CAPability measure for Older people and the Hospital Anxiety and Depression Scale). RESULTS: Our pilot study results indicate that it is feasible to recruit, retain, and provide follow-up telephone coaching to older adults after hip fracture. We enrolled 30 older adults (mean age 81.5 years; range 61-97 years), representing a 42% recruitment rate. Participants excluded were those who were not community dwelling on admission, were discharged to a residential care facility, had physician-diagnosed dementia, and/or had medical contraindications to participation. There were 27 participants who completed the study: eleven in the intervention group, 15 in the control group, and one participant completed a qualitative interview only. There were no differences between groups for health measures. CONCLUSION: We highlight the feasibility of telephone coaching for older adults after hip fracture to improve adherence to mobility recovery goals.

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)0.017
metaresearch head score (Gemma)0.026
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.017
Threshold uncertainty score0.090

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0170.026
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0020.003
Open science0.0020.002
Research integrity0.0040.003
Insufficient payload (model declined to judge)0.0100.001

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 head0.105
GPT teacher head0.327
Teacher spread0.223 · 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 designRandomized trial
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

Citations38
Published2015
Admission routes3
Has abstractyes

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