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Record W4392714779 · doi:10.1080/09638288.2024.2326185

A qualitative study of clinicians’ and individuals’ with lower limb loss perspectives on the development of a novel online self-management program

2024· article· en· W4392714779 on OpenAlexaff
Elham Esfandiari, William C. Miller, Sheena King, Maureen C. Ashe, W. Ben Mortenson

Bibliographic record

VenueDisability and Rehabilitation · 2024
Typearticle
Languageen
FieldEngineering
TopicProsthetics and Rehabilitation Robotics
Canadian institutionsInternational Collaboration On Repair DiscoveriesVancouver Coastal HealthGF Strong Rehabilitation CentreUniversity of British Columbia
Fundersnot available
KeywordsRehabilitationSelf-managementQualitative researchPsychologyLimb lossPhysical therapyPhysical medicine and rehabilitationMedicineMedical educationComputer scienceAmputationPsychiatry

Abstract

fetched live from OpenAlex

PURPOSE: To explore the rehabilitation preferences and experiences of clinicians and patients for education after lower limb loss to facilitate the development of an online self-management program. METHODS: A qualitative descriptive approach was used. Thirty-one clinicians (physiotherapists, occupational therapists, and prosthetists), and 26 patients with lower limb loss (transtibial and transfemoral amputation; mean age (SD) of 63.3 (9.1), years) were recruited. We used semi-structured focus groups and one-on-one interviews, and audio recorded the interviews. Data were analyzed using conventional content analysis. RESULTS: Three themes were identified: (1) Needing education in rehabilitation described the education in current practice as one-on-one discussion and booklets and highlighted the limitations of education such as its length, static nature, and inaccessible for patients living in remote areas. (2) Getting back to activities prior to amputation emphasized how goal setting and social support could assist patients and facilitate self-management. (3) Augmenting learning highlighted the need for an accessible complementary source for education and potential solutions to overcome the barriers of online delivery. CONCLUSIONS: Our findings underscore the importance of education in the rehabilitation of patients to help them get back to their activities. An online accessible tool may improve education by providing information and peer support.

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)0.001
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 score0.113
Threshold uncertainty score0.388

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.020
GPT teacher head0.325
Teacher spread0.305 · 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

Citations1
Published2024
Admission routes1
Has abstractyes

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