Multimodal Training Research Articles

Facilitation of working memory capacity by transcranial direct current stimulation: a secondary analysis from the augmenting cognitive training in older adults (ACT) study.

Aging is a public health concern with an ever-increasing magnitude worldwide. An array of neuroscience-based approaches like transcranial direct current stimulation (tDCS) and cognitive training have garnered attention in the last decades to ameliorate the effects of cognitive aging in older adults. This study evaluated the effects of 3months of bilateral tDCS over the frontal cortices with multimodal cognitive training on working memory capacity. Two hundred ninety-two older adults without dementia were allocated to active or sham tDCS paired with cognitive training. These participants received repeated sessions of bilateral tDCS over the bilateral frontal cortices, combined with multimodal cognitive training. Working memory capacity was assessed with the digit span forward, backward, and sequencing tests. No baseline differences between active and sham groups were observed. Multiple linear regressions indicated more improvement of the longest digit span backward from baseline to post-intervention (p = 0.021) and a trend towards greater improvement (p = 0.056) of the longest digit span backward from baseline to 1year in the active tDCS group. No significant between-group changes were observed for digit span forward or digit span sequencing. The present results provide evidence for the potential for tDCS paired with cognitive training to remediate age-related declines in working memory capacity. These findings are sourced from secondary outcomes in a large randomized clinical trial and thus deserve future targeted investigation in older adult populations.

Super-resolution reconstruction of single image for latent features

Single-image super-resolution (SISR) typically focuses on restoring various degraded low-resolution (LR) images to a single high-resolution (HR) image. However, during SISR tasks, it is often challenging for models to simultaneously maintain high quality and rapid sampling while preserving diversity in details and texture features. This challenge can lead to issues such as model collapse, lack of rich details and texture features in the reconstructed HR images, and excessive time consumption for model sampling. To address these problems, this paper proposes a Latent Feature-oriented Diffusion Probability Model (LDDPM). First, we designed a conditional encoder capable of effectively encoding LR images, reducing the solution space for model image reconstruction and thereby improving the quality of the reconstructed images. We then employed a normalized flow and multimodal adversarial training, learning from complex multimodal distributions, to model the denoising distribution. Doing so boosts the generative modeling capabilities within a minimal number of sampling steps. Experimental comparisons of our proposed model with existing SISR methods on mainstream datasets demonstrate that our model reconstructs more realistic HR images and achieves better performance on multiple evaluation metrics, providing a fresh perspective for tackling SISR tasks.

Implementing an evidence-based behavioral weight-loss program in community mental health centers: A randomized pilot study.

Obesity is a leading cause of preventable death among individuals with serious mental illness (SMI). A prior randomized controlled trial demonstrated the efficacy of a lifestyle style intervention tailored to this population; however, such interventions need to be adapted and tested for real-world settings. This study evaluated implementation interventions to support community mental health program staff to deliver an evidence-based lifestyle intervention to clients with obesity and SMI. In this cluster-randomized pilot trial, the standard arm combined multimodal training with organizational strategy meetings and the enhanced arm included all standard strategies plus performance coaching. Staff-coaches delivered a 6-month group-based lifestyle intervention to clients with SMI. Primary outcomes were changes in staff knowledge, self-efficacy, and fidelity scores for lifestyle intervention delivery. Linear mixed-effects modeling was used to analyze outcomes, addressing within-site clustering and within-participant longitudinal correlation of outcomes. Three sites were in the standard arm (7 staff-coaches); 5 sites in the enhanced arm (11 staff-coaches). All sites delivered all 26 modules of the lifestyle intervention. Staff-coaches highly rated the training strategy's acceptability, feasibility and appropriateness. Overall, mean knowledge score significantly increased pre-post by 5.5 (95% CI: 3.9, 7.1) and self-efficacy was unchanged; neither significantly differed between arms. Fidelity ratings remained stable over time and did not differ between arms. Clients with SMI achieved a mean 6-month weight loss of 3.8 kg (95% CI: 1.6, 6.1). Mental health staff delivering a lifestyle intervention was feasible using multicomponent implementation interventions, and preliminary results show weight reduction among clients with SMI. The addition of performance coaching did not significantly change outcomes. Future studies are needed to definitively determine the effect on client health outcomes.

Simulation training of intraoperative complication management in laparoscopic cholecystectomy for novices—A randomized controlled study

BackgroundIntraoperative complications occur more often in laparoscopic cholecystectomies (LCs) than in open cholecystectomies. Since LC is a frequent training procedure, surgical residents should be trained to deal with intraoperative complications in a safe and controlled environment. This study aimed to determine whether structured training in coping mechanisms in complication management in LC benefits novices compared to no training in complication management. MethodsThe study included sixty medical students without prior experience in minimally invasive surgery. They were randomly assigned to the intervention or control group and worked in teams of two. Both groups completed multimodal skill training, including one ex-vivo porcine LC. The intervention group (n=30) was then informed about the complications that can occur during an LC and how to manage them using the Coping Mechanisms for Intraoperative Complication Management in Laparoscopic Cholecystectomy (COMIC-LC) tool specially developed for this study. Afterward, they performed two LCs receiving structured training in coping mechanisms for intraoperative complication management. The control group (n=30) performed two LCs, receiving no information about managing complications. Both groups performed two postinterventional LCs. Complication management of the two groups was evaluated using the COMIC-LC assessment score. ResultsThe intervention group demonstrated better management of intraoperative complications in LCs compared to the control group (gallbladder perforation: 8.5 vs. 3.0 points, p<0.001; injury to the liver parenchyma: 7.0 vs. 2.0 points, p<0.001; cystic artery injury: 8.0 vs. 5.0 points, p<0.001; cystic duct injury: 6.0 vs. 1.0, p<0.001). ConclusionStructured training in coping mechanisms for managing intraoperative complications during LC can improve complication handling and potentially reduce adverse events. Translation to clinical practice should be evaluated.

SOLVING THE HIGH-INTENSITY MUTLIMODAL TRAINING PRESCRIPTION PUZZLE: A SYSTEMATIC MAPPING REVIEW

INTRODUCTION &amp; AIMS High-Intensity Multimodal Training (HIMT) refers to all styles of high-intensity combined aerobic, resistance and/or bodyweight exercise. Previous heterogeneity in exercise prescription and reporting in HIMT reduces the understanding of which factors should be commonly considered when prescribing HIMT (e.g., exercise volume, intensity, duration). Previous studies have demonstrated positive effects of HIMT on health and performance outcomes. However, methodological disparities limit comparisons between findings. This systematic mapping review examines the prescriptive considerations and health and performance outcomes of HIMT in the context of training. METHODS A systematic literature search was conducted using Ovid Medline, SPORTDiscus and Cochrane Library databases and additional sources to identify studies up until February 2023. A total of 37090 records were retrieved, of which 221 were included for review. 247 individual HIMT protocols were included for categorical analysis against the Consensus on Exercise Reporting Template (CERT) and Applied Research Model for the Sport Sciences. RESULTS A total of 85 unique terms were used to describe HIMT. Included studies most commonly prescribed HIMT using a consistent exercise selection and circuit format. Exercise intensity was inconsistently reported on and a large proportion of studies incorrectly prescribed ‘high-intensity’ exercise according to ACSM definitions (i.e., &amp;lt;77% HRmax). Participation location, supervision and participation format were the most commonly reported non-training variables. The most frequently reported outcomes were cardiovascular health, perceptual outcomes, body composition and biochemical outcomes. A large proportion of previous HIMT research was experimental in design. CONCLUSIONS Previous HIMT research demonstrates a lack of standardisation in reporting. Future studies should seek to follow guidelines such as the CERT to improve reporting rigour. Additionally, forthcoming research should attempt to actively involve practitioners in implementation studies to improve ecological validity among interventions. REGISTRATION This review adhered to PRISMA-ScR guidelines. Preregistration: osf.io/yknq4.

Structured feedback and operative video debriefing with critical view of safety annotation in training of laparoscopic cholecystectomy: a randomized controlled study

BackgroundThe learning curve in minimally invasive surgery (MIS) is lengthened compared to open surgery. It has been reported that structured feedback and training in teams of two trainees improves MIS training and MIS performance. Annotation of surgical images and videos may prove beneficial for surgical training. This study investigated whether structured feedback and video debriefing, including annotation of critical view of safety (CVS), have beneficial learning effects in a predefined, multi-modal MIS training curriculum in teams of two trainees.MethodsThis randomized-controlled single-center study included medical students without MIS experience (n = 80). The participants first completed a standardized and structured multi-modal MIS training curriculum. They were then randomly divided into two groups (n = 40 each), and four laparoscopic cholecystectomies (LCs) were performed on ex-vivo porcine livers each. Students in the intervention group received structured feedback after each LC, consisting of LC performance evaluations through tutor-trainee joint video debriefing and CVS video annotation. Performance was evaluated using global and LC-specific Objective Structured Assessments of Technical Skills (OSATS) and Global Operative Assessment of Laparoscopic Skills (GOALS) scores.ResultsThe participants in the intervention group had higher global and LC-specific OSATS as well as global and LC-specific GOALS scores than the participants in the control group (25.5 ± 7.3 vs. 23.4 ± 5.1, p = 0.003; 47.6 ± 12.9 vs. 36 ± 12.8, p < 0.001; 17.5 ± 4.4 vs. 16 ± 3.8, p < 0.001; 6.6 ± 2.3 vs. 5.9 ± 2.1, p = 0.005). The intervention group achieved CVS more often than the control group (1. LC: 20 vs. 10 participants, p = 0.037, 2. LC: 24 vs. 8, p = 0.001, 3. LC: 31 vs. 8, p < 0.001, 4. LC: 31 vs. 10, p < 0.001).ConclusionsStructured feedback and video debriefing with CVS annotation improves CVS achievement and ex-vivo porcine LC training performance based on OSATS and GOALS scores.

Multimodal exercise training to reduce frailty in people with multiple sclerosis: study protocol for a pilot randomized controlled trial

BackgroundFrailty, a syndrome characterized by decreased reserve and resistance to stressors across multiple physiologic systems, is highly prevalent in people living with multiple sclerosis (pwMS), independent of age or disability level. Frailty in MS is strongly associated with adverse clinical outcomes, such as falls, and may aggravate MS-related symptoms. Consequently, there is a pressing necessity to explore and evaluate strategies to reduce frailty levels in pwMS. The purpose of this pilot randomized controlled trial (RCT) will be to examine the feasibility and preliminary efficacy of a multimodal exercise training program to reduce frailty in pwMS.MethodsA total of 24 participants will be randomly assigned to 6 weeks of multimodal exercise or to a waitlist control group with a 1:1 allocation. PwMS aged 40–65 years and living with frailty will be eligible. The multimodal exercise program will consist of cognitive-motor rehabilitation (i.e., virtual reality treadmill training) combined with progressive, evidence-based resistance training. At baseline and post-intervention, participants will complete the Evaluative Frailty Index for Physical Activity (EFIP), measures of fall risk, and quality of life. Frailty-related biomarkers will also be assessed. In addition, the feasibility of the multimodal exercise program will be systematically and multidimensionally evaluated.DiscussionTo date, no RCT has yet been conducted to evaluate whether targeted exercise interventions can minimize frailty in MS. The current study will provide novel data on the feasibility and preliminary efficacy of multimodal exercise training as a strategy for counteracting frailty in pwMS.Trial registrationClinicalTrials.gov, NCT06042244 (registered in September 2023).

Discretization and decoupled knowledge distillation for arbitrary oriented object detection

In recent years, lightweight object detection networks have been increasingly applied to remote sensing platforms due to their fast inference speed and flexible deployment advantages. Knowledge distillation methods have been widely used to reduce the performance gap between large and small models, and many studies have combined knowledge distillation with object detection. However, existing knowledge distillation methods often overlook the transfer of localization knowledge. Therefore, this paper proposes a method called Discretized Position Knowledge Distillation (DPKD) to improve the use of knowledge distillation in object detection. Specifically, the DPKD method incorporates a Discretization Algorithm Module (DAM), which leverages both general probability distribution and cross-Gaussian distribution to transfer high-quality bounding box position and pose information. Additionally, the Position Knowledge Distillation (PKD) method splits the target and non-target bounding boxes to form the distillation loss function, addressing the issue of missing background knowledge transfer during the distillation process. To further enhance the learning of high-quality bounding boxes, a Region Weighting Module (RWM) based on EIoU is introduced in DPKD, assigning weights to the various bounding boxes in the teacher's output. The effectiveness of DPKD in the field of remote sensing image object detection in multi-modal scenarios was verified through multi-modal training on the publicly available DOTA and HRSID datasets.

Study on the differential diagnosis of benign and malignant breast lesions using a deep learning model based on multimodal images.

To establish a multimodal model for distinguishing benign and malignant breast lesions. Clinical data, mammography, and MRI images (including T2WI, diffusion-weighted images (DWI), apparent diffusion coefficient (ADC), and DCE-MRI images) of 132 benign and breast cancer patients were analyzed retrospectively. The region of interest (ROI) in each image was marked and segmented using MATLAB software. The mammography, T2WI, DWI, ADC, and DCE-MRI models based on the ResNet34 network were trained. Using an integrated learning method, the five models were used as a basic model, and voting methods were used to construct a multimodal model. The dataset was divided into a training set and a prediction set. The accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of the model were calculated. The diagnostic efficacy of each model was analyzed using a receiver operating characteristic curve (ROC) and an area under the curve (AUC). The diagnostic value was determined by the DeLong test with statistically significant differences set at P < 0.05. We evaluated the ability of the model to classify benign and malignant tumors using the test set. The AUC values of the multimodal model, mammography model, T2WI model, DWI model, ADC model and DCE-MRI model were 0.943, 0.645, 0.595, 0.905, 0.900, and 0.865, respectively. The diagnostic ability of the multimodal model was significantly higher compared with that of the mammography and T2WI models. However, compared with the DWI, ADC, and DCE-MRI models, there was no significant difference in the diagnostic ability of these models. Our deep learning model based on multimodal image training has practical value for the diagnosis of benign and malignant breast lesions.

The Impact of Multimorbidity Patterns on Changes in Physical Activity and Physical Capacity Among Older Adults Participating in a Year-Long Exercise Intervention.

This study investigated the impact of multimorbidity patterns on physical activity and capacity outcomes over the course of a year-long exercise intervention, and on physical activity 1year later. Participants were 314 physically inactive community-dwelling men and women aged 70-85years, with no contraindications for exercise at baseline. Physical activity was self-reported. Physical capacity measurements included five-time chair-stand time, 6-minute walking distance, and maximal isometric knee-extension strength. The intervention included supervised and home-based strength, balance, and walking exercises. Multimorbidity patterns comprised physician-diagnosed chronic disease conditions as a predictor cluster and body mass index as a measure of obesity. Multimorbidity patterns explained 0%-12% of baseline variance and 0%-3% of the change in outcomes. The magnitude and direction of the impact of unique conditions varied by outcome, time point, and sex. Multimorbid older adults with no contraindications for exercise may benefit from multimodal physical training.

Heterogeneous Test-Time Training for Multi-Modal Person Re-identification

Multi-modal person re-identification (ReID) seeks to mitigate challenging lighting conditions by incorporating diverse modalities. Most existing multi-modal ReID methods concentrate on leveraging complementary multi-modal information via fusion or interaction. However, the relationships among heterogeneous modalities and the domain traits of unlabeled test data are rarely explored. In this paper, we propose a Heterogeneous Test-time Training (HTT) framework for multi-modal person ReID. We first propose a Cross-identity Inter-modal Margin (CIM) loss to amplify the differentiation among distinct identity samples. Moreover, we design a Multi-modal Test-time Training (MTT) strategy to enhance the generalization of the model by leveraging the relationships in the heterogeneous modalities and the information existing in the test data. Specifically, in the training stage, we utilize the CIM loss to further enlarge the distance between anchor and negative by forcing the inter-modal distance to maintain the margin, resulting in an enhancement of the discriminative capacity of the ultimate descriptor. Subsequently, since the test data contains characteristics of the target domain, we adapt the MTT strategy to optimize the network before the inference by using self-supervised tasks designed based on relationships among modalities. Experimental results on benchmark multi-modal ReID datasets RGBNT201, Market1501-MM, RGBN300, and RGBNT100 validate the effectiveness of the proposed method. The codes can be found at https://github.com/ziwang1121/HTT.

Creating transformational learning experiences for 21st century healthcare students through preclinical skills training at a South African university.

Creating an inclusive interprofessional teaching and learning community can enhance student engagement and ultimately develop essential graduate attributes (GA) (also known as generic, transferable, core, soft, work-ready or nontechnical skills). The early practical development of GA within a diverse space is essential in health profession education, as students experience the transition to clinical training as challenging. This paper describes the conceptualization and implementation of an inclusive interprofessional curriculum focused on GA development in the preclinical years. A phased multimethod research design was applied. Phase 1 focused on the conceptualization of a preclinical GA development curriculum through a consensus-seeking process among all staff in the School of Health and Rehabilitation Sciences (N = 36). Subsequently, in Phase 2, quantitative and qualitative data were gathered from participating first-year students (N = 135) as an early curricular implementation review. Descriptive statistical analyses for quantitative and thematic analyses for qualitative data were performed. During Phase 1, five themes were identified (Ethics, Professionalism, General principles for interventions, Organizations and institutions, Management) informing preclinical curriculum development. Forty-one first-year students (30%) participated in Phase 2. The majority of participants (87%) indicated that they had a positive learning experience during Phase 2. Students expressed that engagement was encouraged (83%) within a space of mutual respect (83%), with interprofessional groups assisting in building "a trusting environment and a supportive one". Students indicated they "liked that it [module] wasn't just about one topic", as it concretized that "there is more to being a healthcare professional that just treating people". GA development provides an invaluable opportunity for interprofessional engagement. Creating a diverse and inclusive curricular space through multimodal and interprofessional training, GA training was transformed to be more practical and future-focused, creating a positive learning experience. Future research should focus on the longer-term impact of this practical, preclinical GA development during the transition of these students into the clinical training space.

Multimodal and conventional resistance training interventions improve muscle function in older adults: Findings from the Training IMCT study

Age-associated remodeling processes affect the intramuscular connective tissue (IMCT) network, which may significantly impair muscle function. Thus, we aimed to test whether including exercises shown to efficiently target the IMCT to a conventional resistance exercise intervention (CONV) would result in greater functional gains as compared to CONV alone. Fifty-three men and women (66.2 ± 3.3 years) were assigned to either CONV (n = 15), multimodal training (MULTI; n = 17) or a control (CTRL; n = 21) group. All subjects were tested at baseline, and those assigned to CONV or MULTI underwent a 16-week training intervention. The CONV group followed a progressive resistance training program, in which the number of weekly training sessions gradually increased from 1 to 3. In the MULTI group, one of these sessions was replaced with plyometric training, followed by self-myofascial release. Testing included maximal strength and power, imaging-based muscle volume, architecture, and functional performance. The intervention effects were analyzed using two- or three-way repeated measures ANOVA models (α = 0.05). Briefly, the maximal knee extension isometric contraction, one-repetition maximum, and isokinetic peak torque increased in all groups (p < 0.05), albeit to a lesser extent in CTRL. On the other hand, quadriceps femoris muscle volume (p = 0.019) and vastus lateralis pennation angle (p < 0.001) increased only in the MULTI group. Handgrip strength did not change in response to the intervention (p = 0.312), whereas Sit-to-Stand performance improved in all groups after the first 8-wks, but only in MULTI and CONV after 16-wks (all p < 0.001). In conclusion, we found that a resistance training intervention in which one weekly training session is replaced by plyometric training is feasible and as effective as a program consisting solely of conventional strength training sessions for inducing gains in muscle strength and function in older adults. Muscle size and architecture improved only in the MULTI group. German Clinical Trials: DRKS00015750.

High-frequency multimodal training with a focus on Tai Chi in people with Parkinson's disease: a pilot study.

Cognitive decline is an important and common complication in patients with Parkinson's disease (PD) since it significantly reduces the quality of life. A breakthrough in treating and preventing cognitive decline in PD remains to be achieved. This study aimed to evaluate the effectiveness of high-frequency and intensive multimodal training in improving motor and cognitive function. Twenty-eight patients diagnosed with idiopathic PD completed a comprehensive neuropsychological test battery and were neurologically examined. The patients of the intervention group (n = 15) underwent 2 weekly sessions of Tai Chi therapy over 4 weeks and participated in an individually tailored training program consisting of two modules (smartphone-based speech training and cognitive training). A matched control group consisted of n = 13 patients with PD who received computer-assisted cognitive training. The data were analyzed with repeated-measures ANOVA. Four weeks of high-frequency training showed significant effects on verbal and figural episodic memory and visuospatial function in the intervention groupCompared to the control group, the cognitive performance of the intervention group improved significantly in visuospatial function and figural episodic memory. A significant improvement was also shown in the intervention group in the Tinetti Mobility Test and the Epworth Sleepiness Scale. The significant effects in the Tinetti mobility test remained after the 6 months follow-up. After the intervention, the patients reported high motivation and satisfaction with the multimodal training. In patients with PD, a multimodal training program not only improves gait and stability but may also contribute to improving cognition. ClinicalTrials.gov Identifier: NCT04103255; https://register.clinicaltrials.gov/prs/app/action/LoginUser?ts=1&cx=-jg9qo4.

Effect of a multimodal training on the ability of medical students to administer the MMSE: a comparative study

BackgroundsThe Mini-Mental State Examination (MMSE) is the main screening and follow-up test for neurocognitive disorders. In France, it is often administered by medical students. Conditions allowing to administer the MMSE are strict but not well known by students, leading to mistakes in scoring. Our objectives were to assess the effect of a multimodal training on medical students’ ability to administer the MMSE and to describe their previous training.Methods75 medical students between the 4th and 6th year of study were included. Previous MMSE training was assessed by a standardized questionnaire. The teaching material used for our training was the article validating MMSE in French, a video explaining the steps on how to administer the MMSE test, and MMSE’s scoring exercises. The ability to administer the MMSE was assessed by a Standardized practical exam (SPE). Students were self-selected and then assigned in two groups, one benefiting from all the training before SPE, and the other receiving only the article before SPE.Results41 students were included in the training group and 34 in the control group. There was no difference between groups regarding previous training. 71% of the students had already administered a MMSE test and only 17% had received specific training. Students considered their previous training as insufficient in most cases. The overall score and scores of each subpart of the SPE were significantly higher in the training group than in the control group (overall score: median [IQR]: 71 [62–78] vs. 52 [41–57], p < 0.001). The rate of students able to complete the MMSE was higher in the training group compared to the control (85% vs. 44%, p < 0.001). Quality of the training and its usefulness were judged to be good or very good by all participants.ConclusionsA multimodal training improves the ability of medical students to administer the MMSE.

Model-Agnostic Binary Patch Grouping for Bone Marrow Whole Slide Image Representation

Histopathology is the reference standard for pathology diagnosis, and has evolved with the digitization of glass slides, i.e. whole slide images (WSIs). Trained histopathologists can help to diagnose disease by examining WSIs visually, but this process is time-consuming and prone to variability. To address these issues, AI models are being developed to create slide-level representations of WSIs, summarizing the entire slide as a single vector. This enables various computational pathology applications, including inter-slide search, multi-modal training, and slide-level classification. Achieving expressive and robust slide-level representations hinges on patch feature extraction and aggregation steps. We propose integrating an additional Binary Patch Grouping (BPG) step, a plugin that can be integrated into various slide-level representation pipelines to enhance the quality of slide-level representation in bone marrow histopathology. BPG excludes patches with less clinical relevance through minimal interaction with the pathologist: a one-time human intervention for the entire process. We further investigated domain-general versus domain-specific feature extraction models based on convolution and attention and examined two different feature aggregation methods, with and without BPG, showing BPG’s generalizability. We show that BPG boosts the performance of WSI retrieval (mAP@10) by 4% and improves WSI classification (weighted-F1) by 5% relative to not using BPG. Additionally, we found that the pipeline with BPG, domain-general large models and parameterized pooling produced the best-quality slide-level representations.

Experiences of fatigued persons with multiple sclerosis with multimodal agility-based exercise training and the ReFEx study protocol: a qualitative extension of a feasibility study

Objectives(1) To explore experiences of fatigued persons with multiple sclerosis (pwMS) with a new multimodal agility-based exercise training (MAT) framework and (2) to investigate the demands of the Rehabilitation, Fatigue,...

Multimodal training methods at the Pacific Northwest Center for cryo-EM

Multimodal training methods at the Pacific Northwest Center for cryo-EM

Implementation of a high fidelity simulation based training program for physicians of children requiring long term invasive home ventilation: a study by ISPAT team.

The number of children requiring long-term invasive home ventilation (LTIHV) has increased worldwide in recent decades. The training of physicians caring for these children is crucial since they are at high risk for complications and adverse events. This study aimed to assess the efficacy of a comprehensive high-fidelity simulation-based training program for physicians caring for children on LTIHV. A multimodal training program for tracheostomy and ventilator management was prepared by ISPAT (IStanbul PAediatric Tracheostomy) team. Participants were subjected to theoretical and practical pre-tests which evaluated their knowledge levels and skills for care, follow-up, and treatment of children on LTIHV. Following the theoretical education and hands-on training session with a simulation model, theoretical and practical post-tests were performed. Forty-three physicians from 7 tertiary pediatric clinics in Istanbul were enrolled in the training program. Seventy percent of them had never received standardized training programs about patients on home ventilation previously. The total number of correct answers from the participants significantly improved after the theoretical training (p < 0.001). The number of participants who performed the steps correctly also significantly increased following the hands-on training session (p < 0.001). All of the 43 participants who responded rated the course overall as good or excellent. The knowledge and skills of clinicians caring for children on LTIHV can be enhanced through a comprehensive training program consisting of theoretical training combined with hands-on training in a simulation laboratory.

Adherence and potential factors of adherence to a resistance, coordination and endurance training in older retirement home residents over 6 months.

High exercise adherence is a key factor for effective exercise programmes. However, little is known about predictors of exercise adherence to a multimodal machine-based training in older retirement home residents. To assess exercise adherence and potential predictors of adherence. Furthermore, to evaluate user acceptance of the multimodal training and the change in exercise self-efficacy. In this sub-analysis of the bestform-F study, a total of 77 retirement home residents ≥65 years (mean age: 85.6 ± 6.6 years, 77.9% female) participated in a 6-month machine-based resistance, coordination and endurance training. Attendance to the training was documented for each training session. To identify potential predictors a multiple linear regression model was fitted to the data. Analyzed predictors included age, sex, body mass index (BMI), physical function, exercise self-efficacy, and physical activity history. Different domains of user acceptance (e.g. safety aspects, infrastructure) and exercise self-efficacy were assessed by a questionnaire and the exercise self-efficacy scale (ESES), respectively. Mean exercise adherence was 67.2% (median: 74.4%). The regression model (R2 = 0.225, p = 0.033) revealed that the 6-minute walk test (6-MWT) at baseline significantly predicted exercise adherence (β: 0.074, 95% confidence interval (CI): 0.006-0.142, p = 0.033). Different user domains were rated at least as good by 83.9%-96.9% of participants, reflecting high acceptance. No statistically significant change was found for exercise self-efficacy over 6 months (mean change: 0.47 ± 3.08 points, p = 0.156). Retirement home residents attended more than two thirds of offered training sessions and physical function at baseline was the key factor for predicting adherence. User acceptance of the training devices was highly rated. These findings indicate good potential for implementation of the exercise programme.