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Record W2992293802 · doi:10.1044/2020_ajslp-20-00124

Exploring the Psychosocial Impact of Botulinum Toxin Type A Injections for Individuals With Oromandibular Dystonia: A Qualitative Study of Patients' Experiences

2021· article· en· W2992293802 on OpenAlexaff
Allyson D. Page, Nada Elhayek, Carolyn Baylor, Scott Adams, Mandar Jog, Kathryn M. Yorkston

Bibliographic record

VenueAmerican Journal of Speech-Language Pathology · 2021
Typearticle
Languageen
FieldMedicine
TopicBotulinum Toxin and Related Neurological Disorders
Canadian institutionsWestern University
Fundersnot available
KeywordsPsychosocialBotulinum toxinMedicineQualitative researchQuality of life (healthcare)Focal dystoniaPsychologyClinical psychologyNursingPsychiatrySurgery

Abstract

fetched live from OpenAlex

Purpose The purpose of this study was to explore the psychosocial impact of botulinum toxin (BoNT) injections for oromandibular dystonia (OMD) and to gain a better understanding of how participants judge the success of this treatment. Method Eight individuals with OMD and dysarthria participated in one 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 Two major themes and six subthemes emerged from the analysis of interview data. The first theme, Botox has changed me and my experiences , explored the participants' perspective of receiving BoNT injections and its psychosocial impact. The second theme, What communication is like for me , explored the psychosocial impact of BoNT on speech production and participation. Conclusions Our results suggest that BoNT has a variable impact on domains related to quality of life, satisfaction with treatment, speech production, and communicative participation. This study adds novel information related to the psychosocial consequences of BoNT treatment in the management of OMD and builds on a literature that studies the consequences and experiences of living with OMD.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.071
Threshold uncertainty score0.347

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
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 head0.036
GPT teacher head0.363
Teacher spread0.327 · 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
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueAmerican Journal of Speech-Language PathologySame topicBotulinum Toxin and Related Neurological DisordersFrench-language works237,207