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Record W2538032709 · doi:10.1002/rnj.298

Healthcare Professionals’ Attitudes to Rehabilitation Programming for Male Cancer Survivors

2016· article· en· W2538032709 on OpenAlexaff
Charlotte Handberg, Julie Midtgaard, Claus Vinther Nielsen, Sally Thorne, Kirsten Lomborg

Bibliographic record

VenueRehabilitation Nursing · 2016
Typearticle
Languageen
FieldMedicine
TopicCancer survivorship and care
Canadian institutionsUniversity of British Columbia
FundersSundhed, Region MidtjyllandKræftens BekæmpelseWorld Health Organization
KeywordsRehabilitationHealth professionalsHealth careMedicinePsychologyNursingFamily medicinePhysical therapyPolitical science

Abstract

fetched live from OpenAlex

PURPOSE: The purpose of this study is to describe and interpret the attitudes and conduct of hospital healthcare professionals (HCPs) in association with male cancer survivors and their municipal rehabilitation participation. DESIGN: Ethnographic fieldwork was conducted, consisting of participant observation and nine semistructured focus group interviews with 58 hospital HCPs. METHODS: Using interpretive description methodology with symbolic interaction as a theoretical framework, data were collected through fieldwork in three oncology wards in Denmark. FINDINGS: Attitudes about both gender and rehabilitation were identified as overarching obstructions within hospital HCP conduct toward promoting men's participation in cancer rehabilitation. CONCLUSIONS: Gender and rehabilitation perceptions formed barriers in this context, suggesting that male cancer survivors' rehabilitation outcomes may be compromised by HCP attitudes and conduct. CLINICAL RELEVANCE: These findings provide insight into approaches to guide HCPs to take responsibility for rehabilitation and to take gender into account in their work.

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)0.001
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 score0.700
Threshold uncertainty score0.561

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 head0.022
GPT teacher head0.385
Teacher spread0.363 · 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

Citations14
Published2016
Admission routes1
Has abstractyes

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