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Record W4379536106 · doi:10.1186/s12877-023-03990-3

Barriers and facilitators to participation in exercise prehabilitation before cancer surgery for older adults with frailty: a qualitative study

2023· article· en· W4379536106 on OpenAlexafffund
Keely Barnes, Emily Hladkowicz, Kristin Dorrance, Gregory L. Bryson, Alan J. Forster, Sylvain Gagné, Allen Huang, Manoj M. Lalu, Luke T. Lavallée, Chelsey Saunders, Hussein Moloo, Julie Nantel, Barbara Power, Celena Scheede‐Bergdahl, Monica Taljaard, Carl van Walraven, Colin J. L. McCartney, Daniel I. McIsaac

Bibliographic record

VenueBMC Geriatrics · 2023
Typearticle
Languageen
FieldMedicine
TopicFrailty in Older Adults
Canadian institutionsUniversity of OttawaMcGill UniversityOttawa Hospital
FundersInternational Anesthesia Research SocietyCanadian Frailty NetworkUniversity of Ottawa
KeywordsPrehabilitationMedicineRandomized controlled trialPhysical therapyRehabilitationQualitative researchIntervention (counseling)GerontologyNursingSurgery

Abstract

fetched live from OpenAlex

BACKGROUND: Older adults with frailty are at an increased risk of adverse outcomes after surgery. Exercise before surgery (exercise prehabilitation) may reduce adverse events and improve recovery after surgery. However, adherence with exercise therapy is often low, especially in older populations. The purpose of this study was to qualitatively assess the barriers and facilitators to participating in exercise prehabilitation from the perspective of older people with frailty participating in the intervention arm of a randomized trial. METHODS: This was a research ethics approved, nested descriptive qualitative study within a randomized controlled trial of home-based exercise prehabilitation vs. standard care with older patients (≥ 60 years) having elective cancer surgery, and who were living with frailty (Clinical Frailty Scale ≥ 4). The intervention was a home-based prehabilitation program for at least 3 weeks before surgery that involved aerobic activity, strength and stretching, and nutritional advice. After completing the prehabilitation program, participants were asked to partake in a semi-structured interview informed by the Theoretical Domains Framework (TDF). Qualitative analysis was guided by the TDF. RESULTS: Fifteen qualitative interviews were completed. Facilitators included: 1) the program being manageable and suitable to older adults with frailty, 2) adequate resources to support engagement, 3) support from others, 4) a sense of control, intrinsic value, noticing progress and improving health outcomes and 5) the program was enjoyable and facilitated by previous experience. Barriers included: 1) pre-existing conditions, fatigue and baseline fitness, 2) weather, and 3) guilt and frustration when unable to exercise. A need for individualization and variety was offered as a suggestion by participants and was therefore described as both a barrier and facilitator. CONCLUSIONS: Home-based exercise prehabilitation is feasible and acceptable to older people with frailty preparing for cancer surgery. Participants identified that a home-based program was manageable, easy to follow with helpful resources, included valuable support from the research team, and they reported self-perceived health benefits and a sense of control over their health. Future studies and implementation should consider increased personalization based on health and fitness, psychosocial support and modifications to aerobic exercises in response to adverse weather conditions.

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)0.020
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 score0.017
Threshold uncertainty score0.090

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0170.020
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0060.005
Scholarly communication0.0020.003
Open science0.0020.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.035
GPT teacher head0.367
Teacher spread0.333 · 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

Citations81
Published2023
Admission routes2
Has abstractyes

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