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Record W4414398655 · doi:10.1080/17549507.2025.2555248

The late paid price: The lived experience of late radiation associated dysphagia

2025· article· en· W4414398655 on OpenAlexaffabout
Hilary Cochrane, Camilla Dawson, Stacey A. Skoretz

Bibliographic record

VenueInternational Journal of Speech-Language Pathology · 2025
Typearticle
Languageen
FieldHealth Professions
TopicDysphagia Assessment and Management
Canadian institutionsUniversity of AlbertaUniversity of British Columbia
Fundersnot available
KeywordsLived experienceDysphagiaQuality of life (healthcare)Patient experienceHealth professionalsQuality (philosophy)

Abstract

fetched live from OpenAlex

PURPOSE: Late radiation-associated dysphagia is a rare side effect of radiation treatment for head and neck cancer. Arising over five years after treatment, it may profoundly impact survivors' health and quality of life. This study sought to gain insight into the lived experience of late radiation associated dysphagia. METHOD: This qualitative study utilised semi-structured phone interviews. Research assistants completed transcription using a consensus process with the first author for unclear speech segments. A patient partner was consulted at all study stages. Participants were purposively sampled from a single Canadian province, and an inductive thematic analysis was employed. RESULT: Twelve participants were enrolled between 9-33 years post cancer diagnosis. Four main themes were identified: a) Glad to be alive, but…, b) eating isn't the same, c) it changes everything, and d) a lot of gaps. CONCLUSION: We identified impacts beyond physiological changes. Social connection, daily logistics and eating related quality of life challenges were prevalent. Results highlight gaps in person-centred decision making and access to health care professionals who understand and recognise this complex condition. We recommend improved patient education, provider awareness, as well as monitoring and treatment for late effects.

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)0.002
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 score0.541
Threshold uncertainty score0.308

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
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 science0.0010.000
Research integrity0.0000.001
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 head0.023
GPT teacher head0.416
Teacher spread0.393 · 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

Citations0
Published2025
Admission routes2
Has abstractyes

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Same venueInternational Journal of Speech-Language PathologySame topicDysphagia Assessment and ManagementFrench-language works237,207