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Tutorial: Motor-Based Treatment Strategies for /r/ Distortions.

ABSTRACT: Purpose This tutorial summarizes current best practices in treating American English /r/ distortions in children with residual speech errors. Method To enhance the effectiveness of clinicians' cueing and feedback, the phonetics of /r/ production is reviewed. Principles of acquisition, which can inform how to practice /r/ in the early stages of therapy, are explained. Elements of therapy that lack scientific support are also mentioned. Results Although there is significant variability in /r/ production, the common articulatory requirements include an oral constriction, a pharyngeal constriction, tongue body lowering, lateral bracing, and slight lip rounding. Examples of phonetic cues and shaping strategies are provided to help clinicians elicit these movements to evoke correct /r/ productions. Principles of acquisition (e.g., blocked practice, frequent knowledge of performance feedback) are reviewed to help clinicians structure the earliest stages of treatment to establish /r/. Examples of approaches that currently lack scientific support include nonspeech oral motor exercises, tactile cues along the mylohyoid muscle, and heterogeneous groupings in group therapy. Conclusion Treatment strategies informed by phonetic science and motor learning theory can be implemented by all clinicians to enhance acquisition of /r/ for children with residual errors. Supplemental Material https://doi.org/10.23641/asha.12771329.

SUBMITTER: Preston JL

PROVIDER: S-EPMC7842851 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Tutorial: Speech Motor Chaining Treatment for School-Age Children With Speech Sound Disorders.

Project description:Purpose Operationalized treatments for school-age children with speech sound disorders may result in more replicable and evidence-based interventions. This tutorial describes Speech Motor Chaining (SMC) procedures, which are designed to build complex speech around core movements by incorporating several principles of motor learning. The procedures systematically manipulate factors such as feedback type and frequency, practice variability, and stimulus complexity based on the child's performance. Method The rationale and procedures for SMC are described. Examples are presented of how to design stimuli, deliver feedback, and adapt the approach. Free resources are provided to guide clinicians through implementation of the procedure. Data on fidelity of implementation and dose per session are presented. Clinical and research evidence is provided to illustrate likely outcomes with the procedure. Results SMC is a method that can result in successful acquisition of target speech patterns and generalization to untrained words. Most clinicians can implement the procedure with over 90% fidelity, and most children can achieve over 200 trials per session. Conclusion Clinicians and researchers can use or adapt the operationally defined SMC procedures to incorporate several principles of motor learning into treatment for school-age children with speech sound disorders. Supplemental Material https://osf.io/5jmf9/.

| S-EPMC6802861 | biostudies-literature

Intensive Treatment for Persisting Rhotic Distortions: A Case Series.

Project description:Purpose:The study explored changes in accuracy of American English rhotics as a result of an intensive 1-week therapy program for adolescents and young adults with residual speech sound errors that had not resolved with previous therapy. Method:Four case reports are presented of individuals aged 13, 17, 21, and 22 years with residual /?/ distortions. Each participant attended a 1-week intensive program consisting of pretreatment assessments, 14 hr of therapy, and posttreatment assessment. Treatment sessions included structured motor-based practice, ultrasound visual feedback of the tongue, and auditory speech perception training. To assess generalization, untreated words and sentences with rhotics were recorded before and after therapy; these were rated by listeners who were blind to when the recordings were taken. Results:All participants showed measurable and statistically significant improvement in speech sound accuracy. Averaged across the 4 participants, rhotic accuracy at the word level improved from 35% to 83%. At the sentence level, rhotic accuracy increased from 11% pretreatment to 66% posttreatment in 1 week. Conclusion:The promise of an intensive treatment program that includes motor-based practice, biofeedback, and auditory perception training is illustrated by the case presentations in which substantial improvements in speech sound accuracy were observed. Supplemental Materials:https://doi.org/10.23641/asha.5561254.

| S-EPMC5945059 | biostudies-literature

Chemoinformatics-based enumeration of chemical libraries: a tutorial.

Project description:Virtual compound libraries are increasingly being used in computer-assisted drug discovery applications and have led to numerous successful cases. This paper aims to examine the fundamental concepts of library design and describe how to enumerate virtual libraries using open source tools. To exemplify the enumeration of chemical libraries, we emphasize the use of pre-validated or reported reactions and accessible chemical reagents. This tutorial shows a step-by-step procedure for anyone interested in designing and building chemical libraries with or without chemoinformatics experience. The aim is to explore various methodologies proposed by synthetic organic chemists and explore affordable chemical space using open-access chemoinformatics tools. As part of the tutorial, we discuss three examples of design: a Diversity-Oriented-Synthesis library based on lactams, a bis-heterocyclic combinatorial library, and a set of target-oriented molecules: isoindolinone based compounds as potential acetylcholinesterase inhibitors. This manuscript also seeks to contribute to the critical task of teaching and learning chemoinformatics.

| S-EPMC7590480 | biostudies-literature

Targeted maximum likelihood estimation for a binary treatment: A tutorial.

Project description:When estimating the average effect of a binary treatment (or exposure) on an outcome, methods that incorporate propensity scores, the G-formula, or targeted maximum likelihood estimation (TMLE) are preferred over naïve regression approaches, which are biased under misspecification of a parametric outcome model. In contrast propensity score methods require the correct specification of an exposure model. Double-robust methods only require correct specification of either the outcome or the exposure model. Targeted maximum likelihood estimation is a semiparametric double-robust method that improves the chances of correct model specification by allowing for flexible estimation using (nonparametric) machine-learning methods. It therefore requires weaker assumptions than its competitors. We provide a step-by-step guided implementation of TMLE and illustrate it in a realistic scenario based on cancer epidemiology where assumptions about correct model specification and positivity (ie, when a study participant had 0 probability of receiving the treatment) are nearly violated. This article provides a concise and reproducible educational introduction to TMLE for a binary outcome and exposure. The reader should gain sufficient understanding of TMLE from this introductory tutorial to be able to apply the method in practice. Extensive R-code is provided in easy-to-read boxes throughout the article for replicability. Stata users will find a testing implementation of TMLE and additional material in the Appendix S1 and at the following GitHub repository: https://github.com/migariane/SIM-TMLE-tutorial.

| S-EPMC6032875 | biostudies-literature

Promoting Therapists' Use of Motor Learning Strategies within Virtual Reality-Based Stroke Rehabilitation.

Project description:PurposeTherapists use motor learning strategies (MLSs) to structure practice conditions within stroke rehabilitation. Virtual reality (VR)-based rehabilitation is an MLS-oriented stroke intervention, yet little support exists to assist therapists in integrating MLSs with VR system use.MethodA pre-post design evaluated a knowledge translation (KT) intervention incorporating interactive e-learning and practice, in which 11 therapists learned how to integrate MLSs within VR-based therapy. Self-report and observer-rated outcome measures evaluated therapists' confidence, clinical reasoning and behaviour with respect to MLS use. A focus group captured therapists' perspectives on MLS use during VR-based therapy provision.ResultsThe intervention improved self-reported confidence about MLS use as measured by confidence ratings (p <0.001). Chart-Stimulated Recall indicated a moderate level of competency in therapists' clinical reasoning about MLSs following the intervention, with no changes following additional opportunities to use VR (p = .944). On the Motor Learning Strategy Rating Instrument, no behaviour change with respect to MLS use was noted (p = 0.092). Therapists favoured the strategy of transferring skills from VR to real-life tasks over employing a more comprehensive MLS approach.ConclusionThe KT intervention improved therapists' confidence but did not have an effect on clinical reasoning or behaviour with regard to MLS use during VR-based therapy.

| S-EPMC5167266 | biostudies-literature

Neurofeedback Training Based on Motor Imagery Strategies Increases EEG Complexity in Elderly Population.

Project description:Neurofeedback training (NFT) has shown promising results in recent years as a tool to address the effects of age-related cognitive decline in the elderly. Since previous studies have linked reduced complexity of electroencephalography (EEG) signal to the process of cognitive decline, we propose the use of non-linear methods to characterise changes in EEG complexity induced by NFT. In this study, we analyse the pre- and post-training EEG from 11 elderly subjects who performed an NFT based on motor imagery (MI-NFT). Spectral changes were studied using relative power (RP) from classical frequency bands (delta, theta, alpha, and beta), whilst multiscale entropy (MSE) was applied to assess EEG-induced complexity changes. Furthermore, we analysed the subject's scores from Luria tests performed before and after MI-NFT. We found that MI-NFT induced a power shift towards rapid frequencies, as well as an increase of EEG complexity in all channels, except for C3. These improvements were most evident in frontal channels. Moreover, results from cognitive tests showed significant enhancement in intellectual and memory functions. Therefore, our findings suggest the usefulness of MI-NFT to improve cognitive functions in the elderly and encourage future studies to use MSE as a metric to characterise EEG changes induced by MI-NFT.

| S-EPMC8700498 | biostudies-literature

Evidence-based treatment strategies in idiopathic pulmonary fibrosis.

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| S-EPMC9487376 | biostudies-literature

Conducting Trial-Based Economic Evaluations Using R: A Tutorial.

Project description:Trial-based economic evaluations are increasingly being conducted to support healthcare decision-making. When analysing trial-based economic evaluation data, different methodological challenges may be encountered, including (i) missing data, (ii) correlated costs and effects, (iii) baseline imbalances and (iv) skewness of costs and/or effects. Despite the broad range of methods available to account for these methodological challenges in effectiveness studies, they may not always be directly applicable in trial-based economic evaluations where costs and effects are analysed jointly, and more than one methodological challenge typically needs to be addressed simultaneously. The use of inappropriate methods can bias results and conclusions regarding the cost-effectiveness of healthcare interventions. Eventually, such low-quality evidence can hamper healthcare decision-making, which may in turn result in a waste of already scarce healthcare resources. Therefore, this tutorial aims to provide step-by-step guidance on how to combine appropriate statistical methods for handling the abovementioned methodological challenges using a ready-to-use R script. The theoretical background of the described methods is provided, and their application is illustrated using a simulated trial-based economic evaluation.

| S-EPMC10570221 | biostudies-literature

Molecular-Based Treatment Strategies for Osteoporosis: A Literature Review.

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Biomaterials-based anti-inflammatory treatment strategies for Alzheimer's disease.

Project description:The current therapeutic drugs for Alzheimer's disease only improve symptoms, they do not delay disease progression. Therefore, there is an urgent need for new effective drugs. The underlying pathogenic factors of Alzheimer's disease are not clear, but neuroinflammation can link various hypotheses of Alzheimer's disease; hence, targeting neuroinflammation may be a new hope for Alzheimer's disease treatment. Inhibiting inflammation can restore neuronal function, promote neuroregeneration, reduce the pathological burden of Alzheimer's disease, and improve or even reverse symptoms of Alzheimer's disease. This review focuses on the relationship between inflammation and various pathological hypotheses of Alzheimer's disease; reports the mechanisms and characteristics of small-molecule drugs (e.g., nonsteroidal anti-inflammatory drugs, neurosteroids, and plant extracts); macromolecule drugs (e.g., peptides, proteins, and gene therapeutics); and nanocarriers (e.g., lipid-based nanoparticles, polymeric nanoparticles, nanoemulsions, and inorganic nanoparticles) in the treatment of Alzheimer's disease. The review also makes recommendations for the prospective development of anti-inflammatory strategies based on nanocarriers for the treatment of Alzheimer's disease.

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