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Record W4403329549 · doi:10.1044/2024_ajslp-24-00186

A First-Person Account of Caring for a Parent With Dysphagia

2024· article· en· W4403329549 on OpenAlexaff
Amanda Ramkishun, Madeleine Faur, Ashwini Namasivayam‐MacDonald

Bibliographic record

VenueAmerican Journal of Speech-Language Pathology · 2024
Typearticle
Languageen
FieldHealth Professions
TopicDysphagia Assessment and Management
Canadian institutionsMcMaster University
Fundersnot available
KeywordsDysphagiaPsychologyPerceptionCaregiver burdenMedicineClinical psychologyDevelopmental psychologyDementiaDisease

Abstract

fetched live from OpenAlex

PURPOSE: Research has shown that caregiver burden is compounded by dysphagia experienced by the care recipient. However, little is known about the caregiver perception of the caregiving experience, highlighting both the positive and negative experiences. As such, the purpose of this clinical focus article was to provide a first-person account of an adult caregiver of an aging parent with dysphagia and relate their experiences to current literature to inform clinical practice. METHOD: The caregiver provided a detailed account of her experiences caring for her father with dysphagia. Her account was analyzed to identify recurring themes in the literature regarding the caregiving experience and to identify gaps in dysphagia-related caregiver support. The caregiver's story is organized into seven main sections: (a) life before dysphagia, (b) dysphagia onset and diagnosis, (c) dysphagia management and support, (d) community support, (e) impact on family relationships, (f) social and emotional health, and (g) current perspectives on the caregiving experience. CONCLUSIONS: The challenges associated with caregiving clearly impact the caregiver's overall well-being, but she received abundant support from her family, community-based speech-language pathologist, and caregiver support groups. The caregiver's experiences, while not applicable to every caregiver caring for a loved one with dysphagia, can offer valuable insights to clinicians and other caregivers facing similar situations.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.676
Threshold uncertainty score0.539

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.029
GPT teacher head0.384
Teacher spread0.355 · 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 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

Citations2
Published2024
Admission routes1
Has abstractyes

Explore more

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