OpenAI o1-Preview vs. ChatGPT in Healthcare: A New Frontier in Medical AI Reasoning.

This editorial explores the recent advancements in generative artificial intelligence with the newly-released OpenAI o1-Preview, comparing its capabilities to the traditional ChatGPT (GPT-4) model, particularly in the context of healthcare. While ChatGPT has shown many applications for general medical advice and patient interactions, OpenAI o1-Preview introduces new features with advanced reasoning skills using a chain of thought processes that could enable users to tackle more complex medical queries such as genetic disease discovery, multi-system or complex disease care, and medical research support. The article explores some of the new model's potential and other aspects that may affect its usage, like slower response times due to its extensive reasoning approach yet highlights its potential for reducing hallucinations and offering more accurate outputs for complex medical problems. Ethical challenges, data diversity, access equity, and transparency are also discussed, identifying key areas for future research, including optimizing the use of both models in tandem for healthcare applications. The editorial concludes by advocating for collaborative exploration of all large language models (LLMs), including the novel OpenAI o1-Preview, to fully utilize their transformative potential in medicine and healthcare delivery. This model, with its advanced reasoning capabilities, presents an opportunity to empower healthcare professionals, policymakers, and computer scientists to work together in transforming patient care, accelerating medical research, and enhancing healthcare outcomes. By optimizing the use of several LLM models in tandem, healthcare systems may enhance efficiency and precision, as well as mitigate previous LLM challenges, such as ethical concerns, access disparities, and technical limitations, steering to a new era of artificial intelligence (AI)-driven healthcare.

Reference Hallucination Score for Medical Artificial Intelligence Chatbots: Development and Usability Study.

BACKGROUND: Artificial intelligence (AI) chatbots have recently gained use in medical practice by health care practitioners. Interestingly, the output of these AI chatbots was found to have varying degrees of hallucination in content and references. Such hallucinations generate doubts about their output and their implementation. OBJECTIVE: The aim of our study was to propose a reference hallucination score (RHS) to evaluate the authenticity of AI chatbots' citations. METHODS: Six AI chatbots were challenged with the same 10 medical prompts, requesting 10 references per prompt. The RHS is composed of 6 bibliographic items and the reference's relevance to prompts' keywords. RHS was calculated for each reference, prompt, and type of prompt (basic vs complex). The average RHS was calculated for each AI chatbot and compared across the different types of prompts and AI chatbots. RESULTS: Bard failed to generate any references. ChatGPT 3.5 and Bing generated the highest RHS (score=11), while Elicit and SciSpace generated the lowest RHS (score=1), and Perplexity generated a middle RHS (score=7). The highest degree of hallucination was observed for reference relevancy to the prompt keywords (308/500, 61.6%), while the lowest was for reference titles (169/500, 33.8%). ChatGPT and Bing had comparable RHS (ß coefficient=-0.069; P=.32), while Perplexity had significantly lower RHS than ChatGPT (ß coefficient=-0.345; P<.001). AI chatbots generally had significantly higher RHS when prompted with scenarios or complex format prompts (ß coefficient=0.486; P<.001). CONCLUSIONS: The variation in RHS underscores the necessity for a robust reference evaluation tool to improve the authenticity of AI chatbots. Further, the variations highlight the importance of verifying their output and citations. Elicit and SciSpace had negligible hallucination, while ChatGPT and Bing had critical hallucination levels. The proposed AI chatbots' RHS could contribute to ongoing efforts to enhance AI's general reliability in medical research.

Transforming Virtual Healthcare: The Potentials of ChatGPT-4omni in Telemedicine.

The introduction of OpenAI's ChatGPT-4omni (GPT-4o) represents a potential advancement in virtual healthcare and telemedicine. GPT-4o excels in processing audio, visual, and textual data in real time, offering possible enhancements in understanding natural language in both English and non-English contexts. Furthermore, the new "Temporary Chat" feature may improve privacy and data confidentiality during interactions, potentially increasing integration with healthcare systems. These innovations promise to enhance communication clarity, facilitate the integration of medical images, and increase data privacy in online consultations. This editorial explores some future implications of these advancements for telemedicine, highlighting the necessity for further research on reliability and the integration of advanced language models with human expertise.

ChatGPT-3.5 System Usability Scale early assessment among Healthcare Workers: Horizons of adoption in medical practice.

Artificial intelligence (AI) chatbots, such as ChatGPT, have widely invaded all domains of human life. They have the potential to transform healthcare future. However, their effective implementation hinges on healthcare workers' (HCWs) adoption and perceptions. This study aimed to evaluate HCWs usability of ChatGPT three months post-launch in Saudi Arabia using the System Usability Scale (SUS). A total of 194 HCWs participated in the survey. Forty-seven percent were satisfied with their usage, 57 % expressed moderate to high trust in its ability to generate medical decisions. 58 % expected ChatGPT would improve patients' outcomes, even though 84 % were optimistic of its potential to improve the future of healthcare practice. They expressed possible concerns like recommending harmful medical decisions and medicolegal implications. The overall mean SUS score was 64.52, equivalent to 50 % percentile rank, indicating high marginal acceptability of the system. The strongest positive predictors of high SUS scores were participants' belief in AI chatbot's benefits in medical research, self-rated familiarity with ChatGPT and self-rated computer skills proficiency. Participants' learnability and ease of use score correlated positively but weakly. On the other hand, medical students and interns had significantly high learnability scores compared to others, while ease of use scores correlated very strongly with participants' perception of positive impact of ChatGPT on the future of healthcare practice. Our findings highlight the HCWs' perceived marginal acceptance of ChatGPT at the current stage and their optimism of its potential in supporting them in future practice, especially in the research domain, in addition to humble ambition of its potential to improve patients' outcomes particularly in regard of medical decisions. On the other end, it underscores the need for ongoing efforts to build trust and address ethical and legal concerns of AI implications in healthcare. The study contributes to the growing body of literature on AI chatbots in healthcare, especially addressing its future improvement strategies and provides insights for policymakers and healthcare providers about the potential benefits and challenges of implementing them in their practice.

Persistent Shortness of Breath in Post-COVID-19 Patients: Inducible Laryngeal Obstruction Can Be a Cause.

BACKGROUND: Inducible laryngeal obstruction (ILO) is the adduction of the true vocal folds during inspiration or, less frequently, expiration. Its etiology is unknown. PURPOSE: This study aimed to identify ILO as a possible cause of shortness of breath (SOB) in post-COVID-19 patients. METHODS: A retrospective study was conducted on 59 post-COVID-19 adults complaining of SOB. We collected the cases' clinical and chest imaging data, including demographic data, pulmonary function test (PFT), CT chest, and laryngeal endoscopic examination. A visual score was used to assign the severity of the glottic obstruction. The grades of this score ranged from 0 (complete patency) to 3 (almost complete closure). RESULTS: ILO was detected in 8 out of 59 cases (13.5%). Two cases out of eight had glottic closure grade 1, while five cases had glottic closure grade 2, and one had glottic closure grade 3. There was a positive correlation between ILO grades (the severity of glottic closure) and PFT results (the degree of upper airway restriction). PFTs in ILO have a specific pattern. It was typical for the expiratory loop to be normal and the inspiratory loop to be flattened. CONCLUSION: ILO is a possible cause of SOB in post-COVID-19 adult cases. It should be considered during evaluation and management.

Validity and Reliability of the Arabic Version of the Glottal Function Index in Dysphonic Patients.

OBJECTIVES/HYPOTHESIS: The Glottal Function Index (GFI) is a four-item self-administered survey suitable for the evaluation and treatment of patients with glottal dysfunction. To date, it has been translated into Lithuanian, Persian, and Hebrew. This study is intended to translate and cross-culturally adapt the GFI for use in Arabic-speaking patients with dysphonia. STUDY DESIGN: This work is a cross-sectional study involving the administration of the GFI to participants with dysphonia (cases) and patients without dysphonia (controls). The validation process included reliability and validity assessments. METHODS: The GFI was translated using forward and backward translation methods from English into Arabic. The questionnaire's reliability was assessed using Cronbach's alpha and test-retest reliability (intraclass correlation coefficient, ICC). The Mann-Whitney test evaluated validity by comparing cases and controls. Finally, the Kruskal-Wallis test examined differences in the GFI across various pathologies. RESULTS: The GFI demonstrated favorable internal consistency (Cronbach's alpha = 0.848) and excellent test-retest reliability (ICC = 0.993). Significant differences in the A-GFI score between the cases and controls were also observed (P < 0.001), supporting the instrument's validity. However, no statistically significant differences were found in A-GFI across different diagnoses (P = 0.712). CONCLUSIONS: The A-GFI is a valid and reliable screening tool for clinicians to assess dysphonia and voice impairment in patients in Arabic-speaking countries. The tool is easy to administer in daily clinical practice given its brevity and self-administration.

Translation and Validation of an Arabic Version of the Voice Disability Coping Questionnaire.

OBJECTIVES/HYPOTHESES: Voice disorders can significantly affect the quality of life. This study aimed to translate, culturally adapt, and validate an Arabic version of the voice disability coping questionnaire (A-VDCQ) for use in Arabic-speaking populations with dysphonia. STUDY DESIGN: This was a cross-sectional study involving the translation and cultural adaptation of the VDCQ into Arabic. The validation process included reliability and validity assessments. Participants were categorized into cases (individuals with dysphonia) and controls (individuals without dysphonia) to compare coping strategies between the two groups. METHODS: ccccccccThe 15-item VDCQ was translated from English into Arabic using the forward and backward translation methods. The questionnaire's reliability was assessed using Cronbach's alpha and test-retest reliability (intraclass correlation coefficient, ICC). Validity was evaluated by comparing cases and controls using the Mann-Whitney test. Differences in coping strategies across different diagnoses were examined using the Kruskal-Wallis test. RESULTS: The A-VDCQ demonstrated satisfactory internal consistency (Cronbach's alpha = 0.769) and excellent test-retest reliability (ICC = 0.993). Significant differences in coping strategies between the cases and controls were also observed (P < 0.001), supporting the instrument's validity. Notably, item 4, which is related to information seeking, had the highest impact score among the cases. However, no statistically significant differences were found in coping strategies across different diagnoses (P = 0.249). CONCLUSIONS: The A-VDCQ demonstrated robust psychometric properties for assessing coping strategies in individuals with voice disorders and such strategies' potential implications for clinical practice and research.

Validity and Reliability of the Arabic Thyroidectomy-Related Voice and Symptom Questionnaire (A-TVSQ) for Assessing Post-Thyroidectomy Patients.

OBJECTIVE: Post-thyroidectomy patients commonly experience voice changes, swallowing symptoms, and neck discomfort, a condition known as post-thyroidectomy syndrome. The Thyroidectomy-Related Voice and Symptom Questionnaire (TVSQ) is a validated tool showing strong correlations with established tools with a potential predictive value for post-thyroidectomy voice outcomes. Our study aims to translate and validate the TVSQ into Arabic. METHODS: This validation study was conducted at King Abdulaziz University Hospital and King Khalid University Hospital in Riyadh, Saudi Arabia. Forward and backward translations ensured the conceptual equivalence of the Arabic TVSQ (A-TVSQ) and were reviewed by an expert panel. A pilot test assessed the A-TVSQ's face validity and clarity, leading to necessary cultural adjustments. The final A-TVSQ was preoperatively and postoperatively administered to thyroidectomy patients to evaluate its test-retest reliability. RESULTS: Data were collected from 116 participants (53 cases [45.6%] and 63 controls [54.3%]). The internal consistency analysis showed strong intercorrelation among the A-TVSQ items, with Cronbach's alpha coefficients (0.951) indicating excellent estimated internal consistency within both domains. Test-retest reliability showed a moderate level of reliability with an intraclass correlation coefficient of 0.696. A-TVSQ item discrimination analysis showed significant associations between the total and domain scores pre- and post-thyroidectomy. External validity analysis showed significant changes in A-TVSQ voice change (P < 0.010) and neck discomfort (P = 0.011) domains and total scores (P < 0.010) between before and 2 weeks after thyroidectomy. However, no significant changes were observed between 2 and 4 weeks after thyroidectomy. CONCLUSIONS: The translated and validated A-TVSQ showed excellent internal consistency and moderate test-retest reliability, comparable to the original version. Voice change significantly worsened after thyroidectomy, highlighting the need for continued monitoring and management strategies for this complication.

ChatGPT and the Future of Digital Health: A Study on Healthcare Workers' Perceptions and Expectations.

This study aimed to assess the knowledge, attitudes, and intended practices of healthcare workers (HCWs) in Saudi Arabia towards ChatGPT, an artificial intelligence (AI) Chatbot, within the first three months after its launch. We also aimed to identify potential barriers to AI Chatbot adoption among healthcare professionals. A cross-sectional survey was conducted among 1057 HCWs in Saudi Arabia, distributed electronically via social media channels from 21 February to 6 March 2023. The survey evaluated HCWs' familiarity with ChatGPT-3.5, their satisfaction, intended future use, and perceived usefulness in healthcare practice. Of the respondents, 18.4% had used ChatGPT for healthcare purposes, while 84.1% of non-users expressed interest in utilizing AI Chatbots in the future. Most participants (75.1%) were comfortable with incorporating ChatGPT into their healthcare practice. HCWs perceived the Chatbot to be useful in various aspects of healthcare, such as medical decision-making (39.5%), patient and family support (44.7%), medical literature appraisal (48.5%), and medical research assistance (65.9%). A majority (76.7%) believed ChatGPT could positively impact the future of healthcare systems. Nevertheless, concerns about credibility and the source of information provided by AI Chatbots (46.9%) were identified as the main barriers. Although HCWs recognize ChatGPT as a valuable addition to digital health in the early stages of adoption, addressing concerns regarding accuracy, reliability, and medicolegal implications is crucial. Therefore, due to their unreliability, the current forms of ChatGPT and other Chatbots should not be used for diagnostic or treatment purposes without human expert oversight. Ensuring the trustworthiness and dependability of AI Chatbots is essential for successful implementation in healthcare settings. Future research should focus on evaluating the clinical outcomes of ChatGPT and benchmarking its performance against other AI Chatbots.

Enhancing Expert Panel Discussions in Pediatric Palliative Care: Innovative Scenario Development and Summarization With ChatGPT-4.

This study presents a novel approach to enhance expert panel discussions in a medical conference through the use of ChatGPT-4 (Generative Pre-trained Transformer version 4), a recently launched powerful artificial intelligence (AI) language model. We report on ChatGPT-4's ability to optimize and summarize the medical conference panel recommendations of the first Pan-Arab Pediatric Palliative Critical Care Hybrid Conference, held in Riyadh, Saudi Arabia. ChatGPT-4 was incorporated into the discussions in two sequential phases: first, scenarios were optimized by the AI model to stimulate in-depth conversations; second, the model identified, summarized, and contrasted key themes from the panel and audience discussions. The results suggest that ChatGPT-4 effectively facilitated complex do-not-resuscitate (DNR) conflict resolution by summarizing key themes such as effective communication, collaboration, patient and family-centered care, trust, and ethical considerations. The inclusion of ChatGPT-4 in pediatric palliative care panel discussions demonstrated potential benefits for enhancing critical thinking among medical professionals. Further research is warranted to validate and broaden these insights across various settings and cultures.

Overview of Early ChatGPT's Presence in Medical Literature: Insights From a Hybrid Literature Review by ChatGPT and Human Experts.

ChatGPT, an artificial intelligence chatbot, has rapidly gained prominence in various domains, including medical education and healthcare literature. This hybrid narrative review, conducted collaboratively by human authors and ChatGPT, aims to summarize and synthesize the current knowledge of ChatGPT in the indexed medical literature during its initial four months. A search strategy was employed in PubMed and EuropePMC databases, yielding 65 and 110 papers, respectively. These papers focused on ChatGPT's impact on medical education, scientific research, medical writing, ethical considerations, diagnostic decision-making, automation potential, and criticisms. The findings indicate a growing body of literature on ChatGPT's applications and implications in healthcare, highlighting the need for further research to assess its effectiveness and ethical concerns.

Voice Problems Among School Teachers employing the Tele-teaching Modality.

OBJECTIVES: To assess the prevalence of voice problems among teachers in Riyadh during tele-teaching and examine the relationship between the Voice Handicap Index 10 (VHI10) scores and a variety of risk factors believed to be related to voice problems. We also assessed awareness of voice hygiene and therapy among teachers. STUDY DESIGN: An observational cross-sectional study conducted using a multistage random sampling method among Riyadh school teachers who taught by tele-teaching for a minimum of one year. METHODS: A self-assessment questionnaire which included demographic information about teachers, factors related to their teaching backgrounds, tele-teaching settings, effects of tele-teaching on the voice, medical and social histories, reports of voice and reflux symptoms, VHI10, and general knowledge about voice hygiene. This was distributed to school teachers using an SMS link through the Ministry of Education's IT department. RESULTS: A total 495 were included in the study after exclusions. The prevalence of teachers who had significant voice problems during tele-teaching (VHI10>11) was 21.6%. Multiple risk factors significantly increased the risk of voice problems during tele-teaching. These factors included being female, teacher age, the presence of background noise from both teachers and students, loud voices, using an open camera during the teaching, stress and anxiety, allergies, respiratory disease, reflux, hearing problems, and a family history of voice problems. Only 4.6% of respondents were familiar with voice hygiene and voice therapy, but 65% believe that it is important for teachers to be knowledgeable about them. CONCLUSIONS: Due to the lower prevalence of voice disorders among tele-teaching compared to traditional teaching methods, tele-teaching may be a viable option for teachers who have voice problems. There are still several factors influencing voice problems among tele-teachers. To attenuate potential risks, it is crucial that teachers are aware of the concepts of voice hygiene and voice therapy.

Validation and Cultural Adaptation of the Arabic Version of the Aging Voice Index.

BACKGROUND: The aging voice index (AVI) is a 23-item self-administered, patient-reported outcome measure. It was developed in the English language to assess the impact of voice disorders on the elderly population. OBJECTIVES: This study aimed to develop an Arabic version of the AVI (A-AVI), test its reliability and validity, and assess its psychometric aspects in Arabic-speaking elderly persons with voice disorders. STUDY DESIGN/METHODS: This was an observational, cross-sectional study involving elderly patients aged ≥60 years. Eighty-two patients with voice disorders were included in the dysphonia group and 77 patients without voice disorders were included in the vocally healthy group. The translated A-AVI and Arabic voice handicap index 10 (A-VHI10) were distributed to the study groups. The A-AVI was tested for its reliability (test-retest reliability and internal consistency) and validity (content, construct, and concurrent with A-VHI10). RESULTS: The A-AVI showed excellent test-retest reliability and internal consistency (intraclass correlation coefficient = 0.987 and Cronbach's alpha = 0.954, respectively). There was a significant difference in A-AVI scores between the elderly in the dysphonia and vocally healthy groups (P < 0.001). In addition, a significant correlation was demonstrated between A-AVI and A-VHI10 (r = 0.89). Unilateral vocal fold immobility and inflammatory laryngeal disorders were most frequently reported by the dysphonia group (28%). CONCLUSIONS: A-AVI has excellent validity and reliability in Arab-speaking elderly patients with voice disorders. It can be considered in the assessment of the effect of voice disorders on the quality of life of the elderly.

Development of the Arabic Voice Pathology Database and Its Evaluation by Using Speech Features and Machine Learning Algorithms.

A voice disorder database is an essential element in doing research on automatic voice disorder detection and classification. Ethnicity affects the voice characteristics of a person, and so it is necessary to develop a database by collecting the voice samples of the targeted ethnic group. This will enhance the chances of arriving at a global solution for the accurate and reliable diagnosis of voice disorders by understanding the characteristics of a local group. Motivated by such idea, an Arabic voice pathology database (AVPD) is designed and developed in this study by recording three vowels, running speech, and isolated words. For each recorded samples, the perceptual severity is also provided which is a unique aspect of the AVPD. During the development of the AVPD, the shortcomings of different voice disorder databases were identified so that they could be avoided in the AVPD. In addition, the AVPD is evaluated by using six different types of speech features and four types of machine learning algorithms. The results of detection and classification of voice disorders obtained with the sustained vowel and the running speech are also compared with the results of an English-language disorder database, the Massachusetts Eye and Ear Infirmary (MEEI) database.

Intra- and Inter-database Study for Arabic, English, and German Databases: Do Conventional Speech Features Detect Voice Pathology?

A large population around the world has voice complications. Various approaches for subjective and objective evaluations have been suggested in the literature. The subjective approach strongly depends on the experience and area of expertise of a clinician, and human error cannot be neglected. On the other hand, the objective or automatic approach is noninvasive. Automatic developed systems can provide complementary information that may be helpful for a clinician in the early screening of a voice disorder. At the same time, automatic systems can be deployed in remote areas where a general practitioner can use them and may refer the patient to a specialist to avoid complications that may be life threatening. Many automatic systems for disorder detection have been developed by applying different types of conventional speech features such as the linear prediction coefficients, linear prediction cepstral coefficients, and Mel-frequency cepstral coefficients (MFCCs). This study aims to ascertain whether conventional speech features detect voice pathology reliably, and whether they can be correlated with voice quality. To investigate this, an automatic detection system based on MFCC was developed, and three different voice disorder databases were used in this study. The experimental results suggest that the accuracy of the MFCC-based system varies from database to database. The detection rate for the intra-database ranges from 72% to 95%, and that for the inter-database is from 47% to 82%. The results conclude that conventional speech features are not correlated with voice, and hence are not reliable in pathology detection.

An Investigation of Multidimensional Voice Program Parameters in Three Different Databases for Voice Pathology Detection and Classification.

BACKGROUND AND OBJECTIVE: Automatic voice-pathology detection and classification systems may help clinicians to detect the existence of any voice pathologies and the type of pathology from which patients suffer in the early stages. The main aim of this paper is to investigate Multidimensional Voice Program (MDVP) parameters to automatically detect and classify the voice pathologies in multiple databases, and then to find out which parameters performed well in these two processes. MATERIALS AND METHODS: Samples of the sustained vowel /a/ of normal and pathological voices were extracted from three different databases, which have three voice pathologies in common. The selected databases in this study represent three distinct languages: (1) the Arabic voice pathology database; (2) the Massachusetts Eye and Ear Infirmary database (English database); and (3) the Saarbruecken Voice Database (German database). A computerized speech lab program was used to extract MDVP parameters as features, and an acoustical analysis was performed. The Fisher discrimination ratio was applied to rank the parameters. A t test was performed to highlight any significant differences in the means of the normal and pathological samples. RESULTS: The experimental results demonstrate a clear difference in the performance of the MDVP parameters using these databases. The highly ranked parameters also differed from one database to another. The best accuracies were obtained by using the three highest ranked MDVP parameters arranged according to the Fisher discrimination ratio: these accuracies were 99.68%, 88.21%, and 72.53% for the Saarbruecken Voice Database, the Massachusetts Eye and Ear Infirmary database, and the Arabic voice pathology database, respectively.

Studying the Psychological Profile of Patients with Laryngopharyngeal Reflux.

BACKGROUND/AIMS: Psychological factors have been claimed to play a role in the predisposition for laryngopharyngeal reflux (LPR) symptoms. The aims of this work were to study the relationship between psychological disorders and LPR and to investigate the effect of potential psychological disorders on patients' self-perception of reflux-related problems. METHODS: Forty-two patients with symptoms suggestive of LPR were psychologically evaluated using the Social Readjustment Rating Scale, the Symptom Checklist-90 Revised, the Manifest Anxiety Scale of Taylor, the Minnesota Multiphasic Personality Inventory, and the Zung Self-Rating Depression Scale. Oropharyngeal 24-hour pH monitoring was used to diagnose LPR. LPR-related symptoms were assessed using the reflux symptom index (RSI) and the voice handicap index-10 (VHI-10). Patients were divided into groups based on psychiatric evaluation and pH results. Correlations between psychological profile characteristics and LPR-related parameters were also investigated. RESULTS: No significant difference was found between the positive and negative LPR group for any of the assessed psychological disorders. Also, no significant difference was detected between the positive and negative psychological disorder groups regarding RSI, VHI-10, and pH results. Correlations between psychological profile parameters and LPR-related measures were also nonsignificant. CONCLUSION: It appears that there is no association between psychological disorders and LPR. The psychological background of the LPR patients had no influence on patients' self-perception of their reflux-related problems.

Standardization of nasalance scores in normal Saudi speakers.

OBJECTIVE: The aims of this study were to obtain normative nasalance scores for a normal Saudi population with different ages and genders, to develop nasometric Arabic speech materials, and to make cross-linguistic comparison. SUBJECTS: Participants included 219 normal Saudi native monolingual Arabic speakers of different ages. Subjects were classified into four groups according to age and gender. Subjects did not have any history of oral, nasal, or velopharyngeal abnormality. METHODS: Arabic speech samples were developed to evaluate nasalance scores, which included syllables repetition, three oral sentences, three oro-nasal sentences, and three nasal sentences. Nasalance data were obtained using Nasometer II-6400. RESULTS: Normative nasalance values were determined. Significant differences between the male and female children groups were noticed in many parameters. Nasalance scores were higher in adults, with significant differences between all groups. CONCLUSION: Normative nasalance scores for Saudi Arabic speakers have been developed for both adults and children. The Arabic speech materials developed in this study appear to be easy to use and applicable for different age groups.

Development of the Arabic Version of Dysphagia Handicap Index (DHI).

The Dysphagia Handicap Index (DHI) is a 25-item self-administered questionnaire. It is a noninvasive tool for measuring the handicapping effect of dysphagia on the physical, functional, and emotional aspects of people's lives. The purposes of the present study were to develop an Arabic version of the DHI and to evaluate its validity, consistency, and reliability in the normal Arabic population with oropharyngeal dysphagia. This was a prospective study that was carried out at the Communication and Swallowing Disorders Unit, King Saud University. The generated Arabic DHI was administered to 94 patients with oropharyngeal dysphagia and 98 control subjects. Internal consistency and test-retest reliability were evaluated. The results of the patients and the control group were compared. The Arabic DHI showed excellent internal consistency (Cronbach's α = 0.95). Also, good test-retest reliability was found for the total scores of the Arabic DHI (r = 0.9, p = 0.001). There was a significant difference between the DHI scores of the control group and those of the oropharyngeal dysphagia group (p < 0.001). This study demonstrated that the Arabic DHI is a valid tool for self-assessment of the handicapping effect of dysphagia on the physical, functional, and emotional aspects of patients and can be used by Arabic language speakers.

Voice problems among laryngopharyngeal reflux patients diagnosed with oropharyngeal pH monitoring.

BACKGROUND AND OBJECTIVES: There is a lack of consensus regarding the clinical presentation and diagnosis of laryngopharyngeal reflux (LPR). The aim of this study was to explore voice-related abnormalities in a group of LPR patients, diagnosed with a 24-hour oropharyngeal pH monitoring. PATIENTS AND METHODS: Eighty-two patients with voice-related problems participated in the study. Diagnosis of LPR was made using a 24-hour oropharyngeal pH monitoring. Patients were divided accordingly into positive and negative pH groups. Comparisons between the two groups were done, including results of clinical presentation, Voice Handicap Index-10 (VHI-10), reflux symptom index (RSI), reflux finding score (RFS), and acoustic measurements. The correlation was conducted between Ryan scores and other variables including VHI-10, RSI, and RFS. RESULTS: Significant differences were found between the two groups for RSI and VHI-10. No significant differences were found between the two groups regarding clinical presentation, RFS or acoustic measures. Significant positive correlations were found between the Ryan composite measurements and both severity ratings (VHI-10, RSI). CONCLUSION: LPR clinical presentation appears to be non-specific in terms of symptoms and laryngeal findings. LPR appears to have an effect on the patients' self-perception of voice problems. Further studies are needed to clarify the effect of LPR on acoustic measurements.