BACKGROUND: Prep-4-RT is a co-designed stepped-care multimodal prehabilitation program for people scheduled to receive radiotherapy for head and neck cancer (HNC). Prehabilitation, which occurs between diagnosis and treatment commencement, aims to improve a patient\'s health to reduce the incidence and severity of current and future impairments. HNC treatment can be distressing and has detrimental impacts on function and quality of life. HNC patients have increased social vulnerabilities including higher rates of socio-economic disadvantage and engagement in lifestyle habits which increase cancer risk. High levels of physical and psychological impacts of HNC treatment and increased social vulnerabilities of this population warrant investigation of optimal pathways of care, such as prehabilitation. This paper describes a research protocol to evaluate the feasibility of Prep-4-RT, which was designed to prepare HNC patients for the physical and psychological impacts of radiotherapy.
METHODS: At least sixty adult HNC patients, scheduled to receive radiotherapy (with or without chemotherapy), will be recruited over a five-month period. All participants will receive access to Prep-4-RT self-management resources. Participants identified through screening as high-risk will also be offered individualised interventions with relevant allied health professionals prior to the commencement of radiotherapy (psychologists, dietitians, speech pathologists and physiotherapists). Participants will complete evaluation surveys assessing their experiences with Prep-4-RT resources and interventions. Clinicians will also complete program evaluation surveys. Primary feasibility outcomes include adoption (uptake and intention to try) and fidelity (adherence to the specialist prehabilitation pathway). Secondary feasibility outcomes include acceptability (patient and clinician) of and satisfaction (patient) with Prep-4-RT as well as operational costs. Feasibility outcome data will be analysed using exact binomial and one-sample t tests, as appropriate.
BACKGROUND: Ethics approval has been obtained at the Peter MacCallum Cancer Centre in Melbourne, Australia. Results will be presented at national conferences and published in peer-reviewed journal(s) so that it can be accessed by clinicians involved in the care of HNC patients receiving radiotherapy. If the model of care is found to be feasible and acceptable, the transferability and scalability to other cancer centres, or for other cancer types, may be investigated.
BACKGROUND: ANZCTA (Australian New Zealand Clinical Trials Registry) ACTRN12623000770662.

BACKGROUND: Many allied health services now provide both telehealth and in-person services following a rapid integration of telehealth as a response to the COVID-19 pandemic. However, little is known about how decisions are made about which clinical appointments to provide via telehealth versus in person.
OBJECTIVE: The aim of this study is to explore clinicians\' decision-making when contemplating telehealth for their clients, including the factors they consider and how they weigh up these different factors, and the clinicians\' perceptions of telehealth utility beyond COVID-19 lockdowns.
METHODS: We used reflexive thematic analysis with data collected from focus groups with 16 pediatric community-based allied health clinicians from the disciplines of speech-language pathology, occupational therapy, social work, psychology, and counseling.
RESULTS: The findings indicated that decision-making was complex with interactions across 4 broad categories: technology, clients and families, clinical services, and clinicians. Three themes described their perceptions of telehealth use beyond COVID-19 lockdowns: \"flexible telehealth use,\" \"telehealth can be superior to in-person therapy,\" and \"fear that in-person services may be replaced.\"
CONCLUSIONS: The findings highlight the complexity of decision-making in a community-allied health setting and the challenges experienced by clinicians when reconciling empirical evidence with their own clinical experience.

BACKGROUND: The term primary progressive aphasia (PPA) describes a group of language-led dementias. Disease-modifying treatments that delay, slow or reverse progression of PPA are currently lacking, though a number of interventions to manage the symptoms of PPA have been developed in recent years. Unfortunately, studies exploring the effectiveness of these interventions have used a variety of different outcome measures, limiting comparability. There are more constructs, apart from word retrieval, that are important for people with PPA that have not received much attention in the research literature. Existing core outcome sets (COS) for dementia and non-progressive aphasia do not meet the needs of people with PPA, highlighting a need to develop a specific COS for PPA.
METHODS: This protocol describes a three-stage study to identify a COS for PPA interventions in research and clinical practice. The stage 1 systematic review will identify existing speech, language and communication measures used to examine the effectiveness of interventions for PPA in the research literature. Employing a nominal group technique, stage 2 will identify the most important outcomes for people with PPA and their families. The data collected in stages 1 and 2 will be jointly analysed with the project PPI group and will inform the stage 2 modified Delphi consensus study to identify a core outcome measurement set for PPA among a range of research disciplines undertaking intervention studies for people with PPA.
BACKGROUND: Ethical approval for stage 2 of the study has been sought individually in each country at collaborating institutions and is stated in detail in the manuscript. Stage 3 has been granted ethical approval by the Chairs of UCL Language and Cognition Department Ethics, Project ID LCD-2023-06. Work undertaken at stages 1, 2 and 3 will be published in open-access peer-reviewed journal articles and presented at international scientific conferences.
UNASSIGNED: CRD42022367565.

OBJECTIVE: Speech sound disorder (SSD) describes a \'persistent difficulty with speech sound production that interferes with speech intelligibility or prevents verbal communication\'. There is a need to establish which care pathways are most effective and efficient for children with SSD. Comparison of care pathways requires clearly defined, evidence-based, interventions and agreement on how to measure the outcomes. At present, no definitive list of assessments, interventions or outcomes exists. The objective of this umbrella review paper is to provide a rigorous and detailed list of assessments, interventions and outcomes which target SSD in children.
METHODS: In December 2022, a systematic search of Ovid Medline, OVID Embase, CINAHL, PsycInfo and Cochrane and a number of grey literature platforms were undertaken. 18 reviews were included, and subsequently 415 primary research articles were assessed for data related to assessments, interventions or outcomes. The AMSTAR (Assessing the Methodological Quality of Systematic Reviews) framework was used to assess the quality of the retained reviews.
METHODS: Reviews were retained which took place in any setting.
METHODS: The population is children of any age with a diagnosis of SSD of unknown origin.
METHODS: Reviews reporting outcomes, assessment and interventions for children with SSD.
RESULTS: Extraction and analysis identified 37 assessments, 46 interventions and 30 outcome measures used in research reporting of SSD. Not all of the listed outcomes were linked to specific outcome measurement tools, but these were measurable through the use of one or more of the assessments extracted from the retained reviews.
CONCLUSIONS: The findings of this review will be used to develop a Core Outcome Set for children with SSD. The findings are part of a rigorous process essential for advancing healthcare research and practice in the specific area of speech and language therapy for children with SSD.
UNASSIGNED: CRD42022316284.

UNASSIGNED: Automatic recognition of stutters (ARS) from speech recordings can facilitate objective assessment and intervention for people who stutter. However, the performance of ARS systems may depend on how the speech data are segmented and labelled for training and testing. This study compared two segmentation methods: event-based, which delimits speech segments by their fluency status, and interval-based, which uses fixed-length segments regardless of fluency.
UNASSIGNED: Machine learning models were trained and evaluated on interval-based and event-based stuttered speech corpora. The models used acoustic and linguistic features extracted from the speech signal and the transcriptions generated by a state-of-the-art automatic speech recognition system.
UNASSIGNED: The results showed that event-based segmentation led to better ARS performance than interval-based segmentation, as measured by the area under the curve (AUC) of the receiver operating characteristic. The results suggest differences in the quality and quantity of the data because of segmentation method. The inclusion of linguistic features improved the detection of whole-word repetitions, but not other types of stutters.
UNASSIGNED: The findings suggest that event-based segmentation is more suitable for ARS than interval-based segmentation, as it preserves the exact boundaries and types of stutters. The linguistic features provide useful information for separating supra-lexical disfluencies from fluent speech but may not capture the acoustic characteristics of stutters. Future work should explore more robust and diverse features, as well as larger and more representative datasets, for developing effective ARS systems.

Speech and language therapists (SLTs) worldwide report challenges with providing recommended, evidence-based intervention intensity for children with speech sound disorder (SSD). Challenges such as service constraints and/or family contexts impact on access to optimal therapy intensity. Existing research indicates that empowering and training parents to deliver intervention at home, alongside SLT support, offers one possible solution to increasing the intensity of intervention children with SSD receive. Digital health could increase accessibility to intensive home practice and help sustain engagement with therapy activities. Further exploration is needed around what makes parent-implemented interventions for children with SSD effective, for who and in which situations. This paper outlines the protocol for a realist review which aims to explore the active ingredients and contextual factors of effective digital parent-led interventions.
A realist review will explore the research question, following six stages. The scope of the review will be determined, and initial programme theories will be developed about what works in digital parent-implemented interventions for SSD, for whom, how, why and in what circumstances. Relevant secondary data, identified through a formal search strategy, will be selected, appraised, analysed and synthesised using realist principles to test and further refine the initial programme theories. This process will develop refined underpinning explanatory theories which capture the interaction between contexts, mechanisms and outcomes of the intervention. An expert steering group will provide insight to inform explanatory theories, searches, and dissemination.
Ethical approval is not required for this review. The refined programme theories from the review will inform the next stages of a wider study. A subsequent realist evaluation will test and further refine theories with key stakeholders. Following this, the underpinning programme theory will be used to coproduce a digital tool, to support parents to deliver home intervention alongside SLT support.

This cross-sectional comparative study aimed to analyse and compare the story-grammar components in Tamil-speaking children with and without hearing impairment (HI) narratives.
The study used a cross-sectional, comparative design to assess and compare narrative structures.
Data were collected at the Sri Ramachandra Institute of Higher Education and Research in Chennai, India.
30 children participated in the study, including 15 children with severe to profound hearing loss who used cochlear implants and 15 with normal hearing. The participants were language-age-matched children aged 3-5 years, proficient in Tamil.
No specific interventions were implemented in this study.
The primary outcome measures focused on story-grammar components, including settings, characters, initiating events, internal plans, attempts, outcomes, and resolution. These components were evaluated through narrative retellings by the children.
Analysis of the narratives revealed significant differences between the two groups. Children with normal hearing demonstrated a higher representation of story-grammar elements than children with HI.
The findings suggest that children with normal hearing exhibit a more proficient understanding and utilisation of story structure in their story-telling than children with HI. This study highlights the importance of narrative analysis in language assessment, particularly for children with HI. Tailored interventions incorporating appropriate language stimulation techniques are needed to enhance children\'s narrative skills with HI. Further research in this area is warranted.

The primary objective of the present systematic review is to: (1) identify the current vocal tasks being used for acoustic and/or auditory perceptual analysis to differentiate between individuals with and without voice disorders. The secondary objectives are to: (2) evaluate the evidence of the sensitivity, specificity and accuracy of those vocal tasks for acoustic and/or auditory perceptual analysis in discriminating the individuals with voice disorders from those without; and (3) compare the values between the vocal tasks in discriminating individuals with voice disorders from those without.
We search the following electronic databases: MEDLINE, EMBASE, CINAHL, Scopus, Web of Science Core Collection, PubMed Central and Google Scholar. Grey literature searches will include ProQuest Dissertations and Theses, ClinicalTrials.gov and the Cochrane Register of Controlled Trials. Websites of professional organisations and textbooks will be hand searched for relevant information related to the research question. Study screening, selection and data extraction will be conducted independently by two reviewers. Any disagreements will be resolved by discussion or by involving a third reviewer.The methodological quality of the included studies will be appraised using the relevant Critical Appraisal Tools by JBI. The clinical guidelines and recommendations for voice assessment by professional bodies will be appraised using the Reporting Items for practice Guidelines in HealThcare (RIGHT) checklist. The findings will be presented in the form of an information matrix with the tasks identified tabulated against the nature of the task, dimensions being tested, and their accuracy, sensitivity, and specificity in identifying individuals with voice problems.
Formal ethics approval is not required. The findings will be presented at national and international conferences and published in a peer-reviewed journal.
CRD42023431634.

Parkinson\'s disease (PD) is the second most prevalent neurodegenerative disorder in the world after Alzheimer\'s disease. Early diagnosing PD is challenging as it evolved slowly, and its symptoms eventuate gradually. Recent studies have demonstrated that changes in speech may be utilized as an excellent biomarker for the early diagnosis of PD. In this study, we have proposed a Chirplet transform (CT) based novel approach for diagnosing PD using speech signals. We employed CT to get the time-frequency matrix (TFM) of each speech recording, and we extracted time-frequency based entropy (TFE) features from the TFM. The statistical analysis demonstrates that the TFE features reflect the changes in speech that occurs in the speech due to PD, hence can be used for classifying the PD and healthy control (HC) individuals. The effectiveness of the proposed framework is validated using the vowels and words from the PC-GITA database. The genetic algorithm is utilized to select the optimum features subset, while a support vector machine (SVM), decision tree (DT), K-Nearest Neighbor (KNN), and Naïve Bayes (NB) classifiers are employed for classification. The TFE features outperform the breathiness and Mel frequency cepstral coefficients (MFCC) features. The SVM classifier is most effective compared to other machine-learning classifiers. The highest classification accuracy rates of 98% and 99% are achieved using the vowel /a/ and word /atleta/, respectively. The results reveal that the proposed CT-based entropy features effectively diagnose PD using the speech of a person.

Chronic cough is a common problem that can be refractory to medical treatment. Nonpharmaceutical management of chronic cough has an important role in well selected patients. This review article outlines the history of chronic cough management, current approaches to speech pathology management of the condition and new modalities of nonpharmaceutical treatment. There is a need for further research into nonpharmaceutical options with well described randomised control trials.