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Record W3082981015 · doi:10.1044/2020_persp-20-00067

Dysphagia-Related Caregiver Burden: Moving Beyond the Physiological Impairment

2020· article· en· W3082981015 on OpenAlexaff
Samantha Shune, Ashwini Namasivayam‐MacDonald

Bibliographic record

VenuePerspectives of the ASHA Special Interest Groups · 2020
Typearticle
Languageen
FieldHealth Professions
TopicDysphagia Assessment and Management
Canadian institutionsMcMaster University
Fundersnot available
KeywordsDysphagiaBiopsychosocial modelMedicineFamily caregiversHealth careCaregiver burdenPsychologyNursingDementiaPsychiatryDiseasePathology

Abstract

fetched live from OpenAlex

Purpose The biopsychosocial ramifications of dysphagia are widespread. However, its influence on informal caregivers and families is often overlooked. Ultimately, the health and well-being of an entire family is central to care provision. This tutorial introduces readers to the current literature on dysphagia-related caregiver burden and third-party disability, illustrates the consequences of such burden on both caregivers and patients, and suggests strategies for better supporting patients' informal caregivers. Conclusions It is essential that speech-language pathologists recognize that the consequences of dysphagia are not limited to the impairment itself and acknowledge dysphagia's substantial impact on the entire family system. More general health care literature suggests that asking caregivers individual questions, modifying the language used to talk with them, providing them with targeted education and resources, and organizing support groups may all be beneficial for increased perceived support and self-efficacy. Ultimately, in order to best meet the needs of our patients with dysphagia, we must also better meet the needs of their families and other informal caregivers.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.353
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.002
Research integrity0.0000.001
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 head0.049
GPT teacher head0.351
Teacher spread0.302 · 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.

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

Citations30
Published2020
Admission routes1
Has abstractyes

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