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Record W3163251614 · doi:10.1136/bmjopen-2020-040116

Role of physiotherapy in supporting recovery from breast cancer treatment: a qualitative study embedded within the UK PROSPER trial

2021· article· en· W3163251614 on OpenAlexaff
Sophie Rees, Bruno Mazuquin, Helen Richmond, Esther Williamson, Julie Bruce

Bibliographic record

VenueBMJ Open · 2021
Typearticle
Languageen
FieldMedicine
TopicCancer survivorship and care
Canadian institutionsMemorial University of Newfoundland
FundersNational Institute for Health and Care Research Applied Research Collaboration Oxford and Thames ValleyHealth Technology Assessment ProgrammeUniversity Hospitals Coventry and Warwickshire NHS TrustNational Institute for Health and Care Research
KeywordsMedicineBreast cancerQualitative researchPhysical therapyAlternative medicineCancerFamily medicineInternal medicinePathology

Abstract

fetched live from OpenAlex

Objectives To explore the experiences of women with breast cancer taking part in an early physiotherapy-led exercise intervention compared with the experiences of those receiving usual care. To understand physiotherapists’ experience of delivering the trial intervention. To explore acceptability of the intervention and issues related to the implementation of the Prevention Of Shoulder Problems (PROSPER) programme from participant and physiotherapist perspective. Design Qualitative semistructured interviews with thematic analysis. Setting UK National Health Service. Participants Twenty participants at high risk of shoulder problems after breast cancer surgery recruited to the UK PROSPER trial (10 each from the intervention arm and control arm), and 11 physiotherapists who delivered the intervention. Trial participants were sampled using convenience sampling. Physiotherapists were purposively sampled from high and low recruiting sites. Results Participants described that the PROSPER exercise intervention helped them feel confident in what their body could do and helped them regain a sense of control in the context of cancer treatment, which was largely disempowering. Control arm participants expressed less of a sense of control over their well-being. Physiotherapists found the exercise intervention enjoyable to deliver and felt it was valuable to their patients. The extra time allocated for appointments during intervention delivery made physiotherapists feel they were providing optimal care, being the ‘perfect physio’. Lessons were learnt about the implementation of a complex exercise intervention for women with breast cancer, and the issues raised will inform the development of a future implementation strategy. Conclusions A physiotherapist-delivered early supported exercise intervention with integrated behavioural strategies helped women at risk of shoulder problems following breast cancer treatment to feel more confident in their ability to mobilise their arm post-surgery. A physiotherapist-delivered early supported exercise intervention with integrated behavioural strategies may address the sense of powerlessness that many women experience during breast cancer treatment. Trial registration number ISRCTN35358984 .

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)0.031
metaresearch head score (Gemma)0.039
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.031
Threshold uncertainty score0.164

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0310.039
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0070.009
Scholarly communication0.0040.004
Open science0.0020.007
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0040.000

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 head0.064
GPT teacher head0.469
Teacher spread0.405 · 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 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

Citations16
Published2021
Admission routes1
Has abstractyes

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