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The Consequences of Oromandibular Dystonia on Communicative Participation: A Qualitative Study of the Insider's Experiences

2019· article· en· W2529450001 on OpenAlexaff
Allyson D. Page, Lauren Siegel, Carolyn Baylor, Scott Adams, Kathryn M. Yorkston

Bibliographic record

VenueAmerican Journal of Speech-Language Pathology · 2019
Typearticle
Languageen
FieldMedicine
TopicVoice and Speech Disorders
Canadian institutionsWestern University
Fundersnot available
KeywordsInsiderQualitative researchPsychologyDysarthriaPerspective (graphical)Semi-structured interviewMedicineSocial psychologySociology

Abstract

fetched live from OpenAlex

Purpose The purpose of this study was to obtain a self-reported account of the experience of living with oromandibular dystonia (OMD) to gain a better understanding of both the daily facilitators and barriers to communicative participation and the strategies used for adapting to life with OMD. Method Eight individuals with OMD and dysarthria participated in 1 face-to-face, semistructured interview. Interviews were audio-recorded and transcribed verbatim. Qualitative, phenomenological methods of coding, immersion, and emergence were used in the analysis of interview data. Results Three major themes and 7 subthemes emerged from the analysis of interview data. First, "speaking is different now" provided examples of how speech changes are manifested in various life situations. Second, "my roles have changed" addressed how OMD has impacted work, home, and social roles. Third, "I accept it and move on" involved finding strategies that help and adopting a different perspective. Conclusion We suggest that the management of OMD must take a more holistic approach by addressing consequences beyond the physical symptoms and be tailored to each individual based on his or her personal concerns and goals.

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)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.009
Threshold uncertainty score0.740

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.002
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 head0.019
GPT teacher head0.370
Teacher spread0.351 · 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

Citations4
Published2019
Admission routes1
Has abstractyes

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