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Record W4409623493 · doi:10.1111/1460-6984.70042

Translation and Validation of the TOR‐BSST Into Turkish for Stroke Patients

2025· article· en· W4409623493 on OpenAlexaffabout
Serkan Bengisu, Özlem Öge‐Daşdöğen, Rosemary Martino

Bibliographic record

VenueInternational Journal of Language & Communication Disorders · 2025
Typearticle
Languageen
FieldHealth Professions
TopicDysphagia Assessment and Management
Canadian institutionsToronto Rehabilitation InstituteUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsDysphagiaSwallowingTurkishStroke (engine)MedicineContext (archaeology)Gold standard (test)Physical therapySurgeryInternal medicine

Abstract

fetched live from OpenAlex

PURPOSE: The most common cause of death in Turkey is attributed to vascular diseases, including stroke. Dysphagia stands out as one of the prevalent and life-threatening complications that often follow a stroke. Within the Turkish context, the availability of validated bedside screening tests for assessing dysphagia remains limited. The primary objective of this study was to undertake the translation of the TOR-BSST into Turkish and subsequently validate this newly translated Turkish version. METHOD: Once the translation of the TOR-BSST into Turkish was accomplished, 60 stroke patients were consecutively enroled in the validation process. The enroled patients were evaluated using the TOR-BSST-TR, administered by a speech and language pathologist (SLP) trained in TOR-BSST screener training. On the screening day, each patient underwent a videofluoroscopic swallowing study (VFSS), administered by another SLP blinded to the patient's medical information and TOR-BSST-TR results. The VFSS images were recorded for independent analysis by the second SLP who conducted the VFSS, and a third SLP, also blinded to the TOR-BSST-TR findings, using the Penetration Aspiration Scale (PAS) to measure airway invasion severity, and Dysphagia Severity Rating Scale (DSRS) to measure overall dysphagia severity. The reliability of the gold standard VFSS ratings was assessed using the intra-class correlation coefficient (ICC). The accuracy of the new TOR-BSST-TR was assessed using sensitivity, specificity, predictive values and likelihood ratios. RESULTS: Of all the 60 patients, 35 (58.3%) failed the TOR-BSST-TR, and 33 (55%) were identified with some degree of dysphagia from VFSS imaging scores. The overall inter-rater reliability (in ICC, 95% CI) for the gold standard ratings were as follows: PAS semi-solids (0.98, 0.95-0.99), PAS liquids (0.75, 0.58-0.85) and overall DSRS (0.70, 0.32-0.85). Based on the total screening score of the TOR-BSST-TR, the sensitivity, specificity, positive and negative predictive values along with positive likelihood ratio were as follows: 93.9%, 85.2%, 90.5%, 90.4% and 6.34, respectively. CONCLUSION: The TOR-BSST was successfully translated into Turkish, and the resulting TOR-BSST-TR demonstrated high accuracy in the acute stroke phase using videofluoroscopy as the gold standard. Specifically, the new TOR-BSST-TR screening tool yielded excellent sensitivity, specificity and predictive values in this patient population. The clinical implementation of this validated screening tool has the potential to enhance early detection of dysphagia, thereby triggering early management and ultimately improving patient outcomes and reducing the burden of complications from vascular diseases, such as stroke. Further research and widespread adoption of the TOR-BSST-TR could contribute to more standardized and effective dysphagia assessment protocols in clinical practice. WHAT THIS PAPER ADDS: What is already known on the subject Dysphagia, prevalent in over half of stroke survivors, poses severe complications, including aspiration pneumonia. While Turkey faces high stroke mortality, limited validated dysphagia screening tools exist. Recent cultural adaptation studies focus on tools like The Barnes-Jewish Hospital Stroke Dysphagia Screen, The Gugging Swallowing Screen Test and The Mann Assessment of Swallowing Ability. The Toronto Bedside Swallow Screening Test (TOR-BSST), a water-swallowing test for stroke patients, demonstrates accuracy. Adapting it to Turkish is crucial for effective bedside screening and managing dysphagia, offering significant benefits. This study translated TOR-BSST into Turkish, aiming to evaluate its validity and reliability in acute stroke patients, addressing a critical need in the Turkish stroke population. What this paper adds to the existing knowledge This study addresses the pressing issue of dysphagia, a life-threatening complication following strokes in Turkey, where validated bedside screening tests are limited. The research translates and validates the TOR-BSST into Turkish, involving 60 stroke patients. The TOR-BSST-TR form, administered by trained speech-language pathologists, demonstrated high sensitivity (93.9%) and good specificity (85.2%) in comparison to videofluoroscopy, the gold standard. Inter-rater reliability was satisfactory, showcasing the tool's effectiveness in identifying dysphagia. The study contributes valuable insights into dysphagia assessment, offering a reliable and culturally adapted screening tool for stroke patients in Turkey. What are the potential or actual clinical implications of this work? The clinical implications of this study are significant for stroke patients in Turkey facing dysphagia. The successful translation and validation of the TOR-BSST into Turkish offer healthcare professionals a culturally adapted and reliable bedside screening tool. This tool demonstrates high sensitivity and good specificity in identifying dysphagia, providing a valuable resource for early detection and effective management. The study's findings imply that the TOR-BSST-TR can be a practical and accurate instrument for clinicians, aiding in timely intervention, reducing complications and improving patient outcomes. Incorporating this tool into routine clinical practice may enhance dysphagia screening, leading to better patient care and quality of life.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.399
Threshold uncertainty score0.192

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 studies0.0000.000
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 head0.020
GPT teacher head0.413
Teacher spread0.392 · 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".

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Citations1
Published2025
Admission routes2
Has abstractyes

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