High Rate Of Agreement Research Articles

Initial validation of a new device for facial skin analysis

The field of dermatology is met with many subjective analysis methods. Due to the relative nature of subjective analysis methods, objective analysis methods with greater accuracy and reliability were developed. Many of these devices are either inaccessible to patients without being a part of a clinical trial, bulky, or costly. However, with the advances in artificial intelligence and handheld devices, measurement methods have become simplified. The purpose of our study was to validate an objective skin analysis software available on a handheld device by comparing it to a board-certified dermatologist’s assessment. Participants of various ages and skin types were analyzed with the facial analysis system on an iPad Pro. The same photographs were ranked by a physician based on 14 common skin characteristics. The facial analysis system and the physician’s rankings had a good agreement rate of 69%. The greatest agreement rates were with the assessment of erythema (83.7%) and wrinkles (81.6%) and the lowest with oiliness (53.1%). The analysis system’s high re-test reliability and good agreement rates with physician assessment support its potential use in the clinical setting.

Karotis aterosklerozunun üç boyutlu analizinde iki farklı yazılım programının karşılaştırılması: Retrospektif bir KIBT çalışması

Aim: The present study aimed to compare two different CBCT software packages, Mimics Medical and 3D-DOCTOR, in performing the volume and areal measurements of extra-cranial carotid artery calcifications (ECACs).
 Material and Methods: A total of 44 scans were evaluated. The calcifications were categorized as unilateral or bilateral. Volumetric and areal measurements of ECACs were done with the two software programs. Intraclass correlation coefficient (ICC) was used to evaluate the intra-observer reliability. The difference in measurements between two software groups was evaluated with the t-test. 
 Results: The ECACs were unilateral in 24 cases and bilateral in 20 cases. There were 25 females and 19 males and the mean age of the sample was 63.31 ± 10.21 years. The overall mean volume obtained with Mimics software was 52.97 ± 48.97 mm3 while that obtained with 3D-DOCTOR software was 39.70 ± 34.40 mm3 (P=0.001). Similarly, significant differences between Mimics (109.55 ± 85.40 mm2) and 3D-DOCTOR (98.99 ± 75.34 mm2) software programs were observed for areal measurements (P=0.001). 
 Conclusion: Although high agreement rates were observed in repeated measurements among two software programs, volumetric and areal measures of the ECACs obtained with Mimics Medical were higher than those obtained with 3D-DOCTOR.

Automatic Scoring Model of Japanese Interpretation Based on Semantic Scoring

In order to improve the current level of Japanese teaching and the difficulty of non-standard Japanese spoken language, the author proposes a method for the study of the automatic scoring model of Japanese ants for scoring. The author introduces a semantic scoring model that integrates the long short-term memory neural network and self-attention mechanism, which can be applied to keyword scoring and sentence semantic scoring. The scoring principle of the model is as follows: firstly, extract the word and sentence features and represent them in a vectorized form, then use a bidirectional long short-term memory neural network to optimize the feature vector, and then use the self-attention mechanism to obtain the semantic features of the word or sentence. Finally, the semantic score is calculated by a simple neural network. Experiments show that compared with the semantic scoring model based on a stretchable recursive autoencoder that performs better in semantic scoring, the average correlation between this model and the original score is 0.444; the lowest rate of agreement with the original score is 95%; and the highest rate of agreement with adjacent ones is 74%. The automatic scoring model for Japanese interpreting with semantic scoring is proved to be practical and has excellent results.

Students’ perceptions, engagement and satisfaction with the use of an e-rubric for the assessment of manual skills in physiotherapy

IntroductionIn recent years, formative assessment has gained importance in health care education to facilitate and enhance learning throughout the training period. Within the frame of active methodologies, rubrics have become an essential instrument for formative assessment. Most rubric-based assessment procedures focus on measuring the effects of rubrics on teachers. However, few studies focus their attention on the perception that students have of the evaluation process through rubrics.MethodsA cross-sectional survey study was carried out with 134 students enrolled in the pre-graduate Physiotherapy education. Assessment of manual skills during a practical examination was performed using an e-rubric tool. Peer-assessment, self-assessment and teacher´s assessment were registered. After completion of the examination process, students’ perceptions, satisfaction and engagement were collected.ResultsQuantitative results related to students’ opinion about e-rubric based assessment, students’ engagement, perceived benefits and drawbacks of the e-rubric as well as the overall assessment of the learning experience were obtained. 86.6% of the students agreed upon the fact that “the rubric allowed one to know what it is expected from examination” and 83.6% of the students agreed upon the fact that “the rubric allowed one to verify the level of competence acquired”. A high rate of agreement (87.3%) was also reached among students concerning feedback.ConclusionsE-rubrics seemed to have the potential to promote learning by making criteria and expectations explicit, facilitating feedback, self-assessment and peer-assessment. The importance of students in their own learning process required their participation in the assessment task, a fact that was globally appreciated by the students. Learning experience was considered interesting, motivating, it promoted participation, cooperative work and peer-assessment. The use of e-rubrics increased engagement levels when attention was focused on their guidance and reflection role.

Study on Aircraft Cockpit Function Based on Neural Network

With the rapid development of numerous airlines, various trend designs have been implemented to develop cockpit interiors for pilots. When communicating with most pilots, they express their emotional feelings about the cockpit. The performance-enhanced cockpit provides the pilot with a better emotional experience, further enhancing the comfort and pleasure of driving. Therefore, it is necessary to provide a cockpit with good performance. Therefore, this paper proposes a novel Neural Network-based Balanced Optimization Algorithm (NN-EOA) for cockpit emotion recognition. The proposed NN-EOA technique simulates quantitative computation with high accuracy and minimizes the error rate during evaluation. Here, images of the interior cockpit design were assessed on four emotional terms, namely, user-friendly (interactive), precise (precise), traditional (traditional), and neat (tidy). Finally, experimental results are performed on various parameters, namely, the mean absolute error (MAE), mean absolute percentage error (MAPE), and root mean square error (RMSE) for various techniques. From the experimental evaluations, it can be seen that the proposed NN-EOA provides high agreement rates in the experimental group with the smallest MAE, MAPE, and RMSE.

Curriculum Planning Model in General Education

The purpose of this study was to establish the appropriateness of a comprehensive model for curriculum planning in the Kingdom of Saudi Arabia, including its processes and procedures. The researcher employed a descriptive approach. The researcher created a curriculum planning model containing the objectives, foundations, procedures, and a visual schematic diagram illustrating the 14 specialists' responses. They demonstrated the model elements' suitability for curriculum development by a very high agreement rate of 100%. The average proportion of procedures for each planning process was 100%, and the average percentage of suitable procedures for each process was 99.4%. The average ratio of procedures incorporated into the planning process was 100%. The research concluded that the curriculum planning methodology is appropriate for the Kingdom of Saudi Arabia's public education planning. The study advises that curriculum planners utilize curriculum planning methods.

Simple electrocardiography algorithm for localizing accessory pathway in patients with Wolff–Parkinson–White syndrome

Background Existing algorithms to predict the location of an accessory pathway (AP) in Wolff–Parkinson–White Syndrome (WPW) have good sensitivity and specificity but complex with various accuracy and inter-observer agreement rates. A simple algorithm with high accuracy and inter-observer agreement rates is needed. Methods This was a cross-sectional and retrospective diagnostic study. The data were collected by total population sampling from January 2015 to January 2017. Forty-seven patients were included in the study. Data collected were pre-ablation 12-lead ECGs and ablation reports. These ECGs were evaluated by two independent observers using the simplified algorithm and compared with ablation results. Results The algorithm had a sensitivity of 45% on the left free wall, 80% on septal, 92% on the right free wall, and the specificity of 96% on the left free wall, 69% on the septal, 85% on the right free wall for AP prediction. The positive predictive value was 90% on the left free wall, 55% on the septal, and 67% on the right free wall APs. The negative predictive value was 70% on the left free wall, 88% on the septal, and 97% on right free wall AP. The positive likelihood ratio was 11.23 on the left free wall, 2.23 on septal and 6.57 on right free wall APs, and the negative likelihood ratio was 0.57 on left free wall APs, 0.28 on septal, and 0.09 on the right free wall APs. Algorithm accuracy varied from 73–87%. Inter-observer agreement calculation was kappa 0.93 for left free wall AP, 0.78 for septal AP, and 0.74 for right free wall AP. Conclusion This simple algorithm has a remarkable accuracy and inter-observer agreement; therefore, it may prove to be helpful even to non-electrophysiologists and has the potential to be integrated into clinical practice

The recombinant Erns and truncated E2-based indirect enzyme-linked immunosorbent assays to distinguishably test specific antibodies against classical swine fever virus and bovine viral diarrhea virus

BackgroundClassical swine fever (CSF) virus is the causative agent of an economically important, highly contagious disease of pigs. CSFV is genetically and serologically related to bovine viral diarrhea virus (BVDV). BVDV infection in pigs can mimic CSF clinical signs, which cause difficulty in differentiation. Serological test for detection of virus specific antibodies is a valuable tool for diagnosis and surveillance of CSFV and BVDV infections in animals. The aim of this study was to develop the CSFV Erns and BVDV tE2 -based ELISAs to distinguishably test specific antibodies against CSFV and BVDV.MethodsThe CSFV Erns and truncated E2 (tE2, residues 690–865) of BVDV were expressed in E. coli and purified by Ni–NTA affinity chromatography, respectively. Employing Erns or tE2 protein as diagnostic antigen, indirect ELISAs were developed to distinguishably test specific antibodies against CSFV and BVDV. The specificity and sensitivity of ELISAs were evaluated using a panel of virus specific sera of pigs, immunized rabbits and immunized mice. A total 150 clinical serum samples from farm pigs were measured by the developed ELISAs and compared with virus neutralizing test (VNT).ResultsIndirect ELISA was established based on recombinant CSFV Erns or BVDV tE2 protein, respectively. No serological cross-reaction between antibodies against CSFV and BVDV was observed in sera of immunized rabbits, immunized mice or farm pigs by detections of the Erns and tE2 -based ELISAs. Compared to VNT, the CSFV Erns -based ELISA displayed a high sensitivity (93.3%), specificity (92.0%) and agreement rate (92.7%), and the sensitivity, specificity and agreement rate of BVDV tE2 -based ELISA was 92.3%, 95.2% and 94.7%, respectively.ConclusionThe newly developed ELISAs are highly specific and sensitive and would be valuable tools for serological diagnosis for CSFV and BVDV infections.

Development and Validation of a Deep Learning System for Sound-based Prediction of Urinary Flow

BackgroundUroflowmetry remains an important tool for the assessment of patients with lower urinary tract symptoms (LUTS), but accuracy can be limited by within-subject variation of urinary flow rates. Voiding acoustics appear to correlate well with conventional uroflowmetry and show promise as a convenient home-based alternative for the monitoring of urinary flows. ObjectiveTo evaluate the ability of a sound-based deep learning algorithm (Audioflow) to predict uroflowmetry parameters and identify abnormal urinary flow patterns. Design, setting, and participantsIn this prospective open-label study, 534 male participants recruited at Singapore General Hospital between December 1, 2017 and July 1, 2019 voided into a uroflowmetry machine, and voiding acoustics were recorded using a smartphone in close proximity. The Audioflow algorithm consisted of two models—the first model for the prediction of flow parameters including maximum flow rate (Qmax), average flow rate (Qave), and voided volume (VV) was trained and validated using leave-one-out cross-validation procedures; the second model for discrimination of normal and abnormal urinary flows was trained based on a reference standard created by three senior urologists. Outcome measurements and statistical analysisLin’s correlation coefficient was used to evaluate the agreement between Audioflow predictions and conventional uroflowmetry for Qmax, Qave, and VV. Accuracy of the Audioflow algorithm in the identification of abnormal urinary flows was assessed with sensitivity analyses and the area under the receiver operating curve (AUC); this algorithm was compared with an external panel of graders comprising six urology residents/general practitioners who separately graded flow patterns in the validation dataset. Results and limitationsA total of 331 patients were included for analysis. Agreement between Audioflow and conventional uroflowmetry for Qmax, Qave, and VV was 0.77 (95% confidence interval [CI], 0.72–0.80), 0.85 (95% CI, 0.82–0.88) and 0.84 (95% CI, 0.80–0.87), respectively. For the identification of abnormal flows, Audioflow achieved a high rate of agreement of 83.8% (95% CI, 77.5–90.1%) with the reference standard, and was comparable with an external panel of six residents/general practitioners. AUC was 0.892 (95% CI, 0.834–0.951), with high sensitivity of 87.3% (95% CI, 76.8–93.7%) and specificity of 77.5% (95% CI, 61.1–88.6%). ConclusionsThe results of this study suggest that a deep learning algorithm can predict uroflowmetry parameters and identify abnormal urinary voids based on voiding sounds, and shows promise as a simple home-based alternative to uroflowmetry in the management of patients with LUTS. Patient summaryIn this study, we trained a deep learning–based algorithm to measure urinary flow rates and identify abnormal flow patterns based on voiding sounds. This may provide a convenient, home-based alternative to conventional uroflowmetry for the assessment and monitoring of patients with lower urinary tract symptoms.

Prospective Study of the Detection of Bacterial Pathogens in Pediatric Clinical Specimens Using the Melting Temperature Mapping Method.

ABSTRACTThe melting temperature (Tm) mapping method is a novel technique that uses seven primer sets without sequencing to detect dominant bacteria. This method can identify pathogenic bacteria in adults within 3 h of blood collection without using conventional culture methods. However, no studies have examined whether pathogenic bacteria can be detected in clinical specimens from pediatric patients with bacterial infections. Here, we designed a new primer set for commercial use, constructed a database with more bacterial species, and examined the agreement rate of bacterial species in vitro. Moreover, we investigated whether our system could detect pathogenic bacteria from pediatric patients using the Tm mapping method and compared the detection rates of the Tm mapping and culture methods. A total of 256 pediatric clinical specimens from 156 patients (94 males and 62 females; median age, 2 years [<18 years of age]) were used. The observed concordance rates between the Tm mapping method and the culture method for both positive and negative samples were 76.4% (126/165) in blood samples and 79.1% (72/91) in other clinical specimens. The Tm mapping detection rate was higher than that of culture using both blood and other clinical specimens. In addition, using the Tm mapping method, we identified causative bacteria in pediatric clinical specimens quicker than when using blood cultures. Hence, the Tm mapping method could be a useful adjunct for diagnosing bacterial infections in pediatric patients and may be valuable in antimicrobial stewardship for patients with bacterial infections, especially in culture-negative cases.IMPORTANCE This study provides novel insights regarding the use of the melting temperature (Tm) mapping method to identify the dominant bacteria in samples collected from pediatric patients. We designed a new set of primers for commercial use and developed a database of different bacteria that can be identified using these primers. We show that the Tm mapping method could identify bacteria from blood samples and other clinical specimens. Moreover, we provide evidence that the Tm mapping method has a higher detection rate than that of the culture-based methods and can achieve a relatively high agreement rate. We believe that our study makes a significant contribution to this field because rapid identification of the source of bacterial infections can drastically improve patient outcomes and impede the development of antibiotic-resistant bacteria.

89-OR: Effective Real-World Usage of Artificial Intelligence–Based Decision Support System for Diabetes Management

Background: Artificial intelligence-based decision support system (AI-DSS) for frequent insulin dose adjustment was demonstrated to be effective in improving glycemic control in our previous clinical trials. We aimed to assess the effectiveness of AI-DSS in real world diabetes clinics. Methods: Data was collected and evaluated from routine AI-DSS usage for individuals with type 1 diabetes treated at 21 diabetes clinics (in the USA and 2 in Israel) . Two analyses were made: (1) Insulin dose recommendations were compared for rate of agreement/disagreement between those suggested by the AI-DSS and the approved recommendations by health care providers (HCP) . (2) Glycemic outcomes were compared between baseline and after 3 months of AI-DSS use. Included in this analysis were individuals who had mean baseline glucose level ≥ 182 mg/dL and at least one AI-DSS recommendation within the 3-months. Results: A total of 8 recommendations, provided to 370 individuals, were evaluated. Full agreement on the direction of insulin dose adjustments was observed in 87%, 87%, and 83% of the basal rate, carbs ratio (CR) , and correction factor (CF) pump settings parameters, respectively. Full disagreement on the direction of dose change was observed in only 0.9%, 0.5%, and 1.2% for the basal rate, CR and CF, respectively. Glycemic outcome analysis included 1 eligible individuals (mean of 1.6 recommendations within a 3-month interval) . Average sensor percentage of time in range [70-180 mg/dL] increased by 4% (p=0.003) : 43% increased time in range by more than 5% and 33% increased by 10% or more. Time in hyperglycemia [&amp;gt; 180 mg/dL] was reduced by 5% (p&amp;lt;0.01) while time in severe hypoglycemia [&amp;lt; 54 mg/dL] remained below 0.5%. Conclusion: A high rate of agreement with automated insulin adjustments was observed among HCPs at academic centers who used the AI-DSS in their workflow. Glycemic control was significantly improved for sub-optimally controlled individuals already after 3-months of follow up. Disclosure R.Nimri: Employee; DreaMed Diabetes, Ltd., Research Support; Abbott Diabetes, Dexcom, Inc., Insulet Corporation, Medtronic, Speaker's Bureau; Eli Lilly and Company, Novo Nordisk, Stock/Shareholder; DreaMed Diabetes, Ltd. A.Tirosh: Advisory Panel; Abbott Diagnostics, AstraZeneca, Boehringer Ingelheim International GmbH, Merck &amp; Co., Inc., Novo Nordisk, Sanofi, Consultant; Bayer AG, DreaMed Diabetes, Ltd., Research Support; Medtronic, Speaker's Bureau; Eli Lilly and Company. I.Muller: Board Member; DreaMed Diabetes, Ltd. Y.Shtrit: Employee; DreaMed Diabetes, Ltd. M.Phillip: Advisory Panel; Dompé, Insulet Corporation, Medtronic, Pfizer Inc., Board Member; DreaMed Diabetes, Ltd., Consultant; QuLab Medical Ltd., Other Relationship; Dexcom, Inc., Dompé, DreaMed Diabetes, Ltd., Eli Lilly and Company, Medtronic, NG Solutions Ltd, Novo Nordisk, OPKO, Pfizer Inc., Sanofi, Stock/Shareholder; DreaMed Diabetes, Ltd., NG Solutions Ltd.

INFLUENCE OF SEX, BODY MASS INDEX, AND SKIN COLOR ON THE ACCURACY OF NON-INVASIVE CUFFLESS PHOTOPLETHYSMOGRAPHY-BASED BLOOD PRESSURE MEASUREMENTS

Objective: It is suggested that vital signs obtained by photoplethysmography-based devices might be influenced by subcutaneous fat and skin color. This study aimed to test the accuracy of blood pressure (BP) measurements taken using a photoplethysmography-based device by stratifying participants based on sex, body mass index (BMI), and skin color. Design and method: Ambulatory individuals coming for a routine BP checkup were recruited for an observational, comparative study. Systolic BP (SBP) and diastolic BP (DBP) measurements compared between the photoplethysmography-based and the cuff-based devices were stratified based on sex, BMI, and skin color (types 1–3 and 4–6 by the Fitzpatrick scale). Results: A total of 1548 measurements were nalysed. Correlations of SBP and DBP between the devices among males and females were between 0.914 to 0.987 (p &lt; 0.001), Bland-Altman analysis of SBP and DBP showed a bias of less than 0.5 mmHg for both sexes. Correlations of SBP and DBP between the devices among BMI groups were between 0.931 to 0.991 (p &lt; 0.001), Bland-Altman analysis of SBP and DBP showed a bias of less than 1 mmHg for all. Correlations of SBP and DBP between the devices among the skin color groups were between 0.936 to 0.983 (p &lt; 0.001), Bland-Altman analysis of SBP and DBP showed a bias of less than 1 mmHg for all. Conclusions: This study shows similar and high agreement rates between BP measurements obtained using a PPG-based non-invasive cuffless BP device and a cuff-based BP device across sex, BMI groups, and skin color.

A Recommendation Model for Selling Rules in the Telecom Retail Industry

The recommendation of the optimal selling rules for any product or service is challenging, owing to the complexity of the customer’s behavior and the competitiveness existing in the telecom retail industry. This study proposes a recommendation model for selling rules that utilizes a hybrid decision-making approach based on K-means and the C5.0 decision tree to analyze the historical sales information of telecom retailers. To evaluate the efficacy of the proposed recommendation model, it was used to analyze original data from a case company. The results indicated that the proposed hybrid decision-making approach resulted in sales content with a high gross profit and high agreement rates. The experimental results show each cluster that can be used to identify rules for the combination of good tariff items in different tariff ranges. Rules for the recommendation of special tariffs are also established to assist salespeople.

Simultaneous monitoring of the middle cerebral and basilar arteries to detect right-to-left shunts using transcranial Doppler by agitated saline administration

Transcranial Doppler (TCD) is an easy, non-invasive, and real-time monitoring device for detecting right-to-left shunts (RLS). Nonetheless, it has limited benefits in patients with poor temporal windows. Therefore, we aimed to investigate whether the basilar artery (BA) window was as effective as the middle cerebral artery (MCA) in detecting RLS during TCD monitoring. Overall, we enrolled 344 patients with stroke, transient ischemic attack, headache, or dizziness. MCA and BA were monitored using a modified headset. To investigate the feasibility of the suboccipital window in detecting RLS, we instituted an evaluation tool with three tiers to evaluate microembolic signals (MESs) during TCD monitoring. Tier 1: TCD monitoring of the MCA (bilaterally) in the resting state, tier 2: TCD monitoring of the MCA (bilaterally) while performing the Valsalva maneuver, and tier 3: TCD monitoring of the index MCA and BA while performing the Valsalva maneuver. In tiers 2 and 3, a high agreement rate of 0.808 and 0.809 (p < 0.001), respectively, on the weighted kappa index, and a high intra-class correlation coefficient of 0.982 and 0.986 (p < 0.001), respectively, were observed on detecting MESs. Our data suggests that the BA window is as effective as the MCA window for detecting RLS on TCD.

Event-related responses reflect chunk boundaries in natural speech

Chunking language has been proposed to be vital for comprehension enabling the extraction of meaning from a continuous stream of speech. However, neurocognitive mechanisms of chunking are poorly understood. The present study investigated neural correlates of chunk boundaries intuitively identified by listeners in natural speech drawn from linguistic corpora using magneto- and electroencephalography (MEEG). In a behavioral experiment, subjects marked chunk boundaries in the excerpts intuitively, which revealed highly consistent chunk boundary markings across the subjects. We next recorded brain activity to investigate whether chunk boundaries with high and medium agreement rates elicit distinct evoked responses compared to non-boundaries. Pauses placed at chunk boundaries elicited a closure positive shift with the sources over bilateral auditory cortices. In contrast, pauses placed within a chunk were perceived as interruptions and elicited a biphasic emitted potential with sources located in the bilateral primary and non-primary auditory areas with right-hemispheric dominance, and in the right inferior frontal cortex. Furthermore, pauses placed at stronger boundaries elicited earlier and more prominent activation over the left hemisphere suggesting that brain responses to chunk boundaries of natural speech can be modulated by the relative strength of different linguistic cues, such as syntactic structure and prosody.

Deep Learning-Based Channel Reciprocity Learning for Physical Layer Secret Key Generation

Using the physical layer channel information of wireless devices to establish the highly consistent secret keys is a promising technology for improving the security of wireless networks. Nevertheless, in the time division duplex system, the reciprocity of the wireless channel that is the basic principle of key generation is impaired by nonsimultaneous sampling and noise factors. Existing physical layer key generation approaches rely on hand-crafted feature extraction algorithms, which have high overhead or security issues and are impractical in real-world situations. This paper presents a novel physical layer key generation method to extract highly consistent keys from imperfect channel responses, which exploits channel reciprocity through deep learning. Specifically, we first design the Channel Reciprocity Learning Net (CRLNet), a neural network for efficiently learning channel reciprocity features from the wireless channel in TDD OFDM systems. Later, a new key generation scheme based on CRLNet is developed that can achieve a high key agreement rate. Experiments indicate that the CRLNet-based key generation scheme performs excellently in terms of key generation rate, key error rate, and randomness, confirming that our method has better performance and lower overhead than existing methods.

The impact of student learning aids on deep learning and mobile platform on learning behavior

PurposeDeep learning (DL) technology is used to design a voice evaluation system to understand the impact of learning aids on DL and mobile platforms on students’ learning behavior.Design/methodology/approachDL technology is used to design a speech evaluation system.FindingsThe experimental results show that the speech evaluation system designed has a high accuracy rate, the highest agreement rate with manual evaluation of pronunciation is 89.5%, and the correct speech recognition rate is 96.64%. The designed voice evaluation system and the manual voice rating system have a maximum error rate of 2%. The experimental results suggest that it is necessary to further optimize the learning aids for mobile platform. The learning aids of the mobile platform need to be further optimized to promote the improvement of student learning efficiency.Originality/valueThe results show that the speech evaluation system designed has good practical application value, and it provides a certain reference value for the future study of learning tools on DL.

Co-designing consumer and carer peer support principles to assess quality

ABSTRACT Objectives: Peer support has recently been integrated into post-discharge adult mental health services in Australia. This study establishes a consensus on the underpinning, context-specific peer support principles for both consumer and carer peer support and develops and pilot tests a scale to assess the quality of peer support. Methods: A co-design mixed methods approach was taken to iteratively develop peer support principles and to design co-responding survey items. Initial testing of the scale was undertaken with a convenience sample of 33 consumers and 35 carers who received peer support in the preceding nine months. Data were triangulated across multiple data sets for integration across consumers and carers. Scale internal reliability was assessed and comparisons between consumers and carers were investigated. Results: High rates of agreement on scale items measuring five co-designed peer support principles indicated strong service quality. Mann–Whitney U tests demonstrated no difference between consumer and carer responses and scale reliability was α = .93. Open-ended questions were filtered through the five peer support principles and on the whole showed convergence on the peer support principles by the various stakeholders. Discussion: To date, this is the first known development and application of an integrated scale for both consumers and carers in a post-discharge clinical mental health setting. Opportunity exists for further testing fidelity to peer support principles across various post-discharge peer support settings.

Production and comprehension of grammatical gender by Spanish heritage speakers: Evidence from accusative clitic pronouns

Objectives: This study investigates (a) the accuracy of Heritage Speakers (HSs) in production and comprehension of Spanish clitic pronouns when compared to monolingual children, (b) the differences in error patterns between groups, and (c) the possible asymmetry in production and comprehension in gender clitics. Methodology: The participants included six groups, a group of Spanish-HS divided into three age groups, PreKinder, 3rd-Grade, and Adults, and a group of Spanish-monolinguals of the same ages. Agreement data were obtained using a cloze-format task for production and a picture selection task for comprehension. Data and Analysis: The results compared accuracy and response time scores between HSs and monolingual speakers, between age groups, and target gender using a 2 × 3 multivariable analysis of variance. Findings: Children in the HS-group scored lower in accuracy than the monolingual children, but Adult-HS performed at the same level as Adult-Monolinguals. HSs, but not monolinguals, overused the masculine form. Production and comprehension scores showed an asymmetrical development in which speakers are better at clitic production than comprehension. Gender clitic agreement is a difficult aspect at age 4, even in monolingual contexts. Originality: The potential contribution of this study is twofold. First, it contributes to the continuing debate on the development of HSs’ grammar by comparing comprehension and production data of monolinguals and HSs, matched for age. Second, it provides evidence of high rates of gender agreement in Adult-HSs. Significance: Grammatical gender is a vulnerable aspect of Spanish-HS grammar, but it is not an incompletely acquired representation. Results support a dissociation between production and comprehension of gender clitic.

Improvement prostate cancer detection rate of suspicious lesions through MRI/TRUS fusion guided biopsy by a multiteam of radiologists

BackgroundThe objective of our study was to analyze the data of our biopsies, determine a detection rate (DR), compare it with the data in the literature and draw possible deductions, so as to offer the patient the possibility of not having other biopsies in the future.MethodsWe have enrolled 189 biopsy-naive patients in the period between September 2018 and December 2020. Each patient underwent multiparametric (mp)-MRI which was reviewed by our team of radiologists. In our center, each examination is examined by 4 radiologists separately with an overall final result. Through the t student test, any statistically significant differences between the DRs and the concordance rate between the positive cores and the suspected area on MRI were analyzed for each urologist who performed the procedure.ResultsThe absolute (DR) was 69.3% (131/189 patients). The relative DR for each PIRADS score was 41% for PIRADS 3, 70.2% for PIRADS 4, 89.3% for PIRADS 5. We found a high percentage of agreement between the positive biopsy samples and the suspicious area identified on MRI: 90.8% (119/131 patients). There were no statistically significant differences between the DRs of the urologists who performed the procedure (p = 0.89), nor for the percentage of agreement between the positivity of the core and the suspected area on MRI (p = 0.92).ConclusionsMRI in the future could become the gold standard for performing MRI fusion-guided biopsies to have a better diagnostic result and avoid rebiopsies. A team MRI reading allows greater accuracy in identifying the suspected lesion, which is demonstrated by a high rate of agreement with the positivity of the cores (90.8%). There is a cost problem due to the need to carry out the mpMRI but it could have less impact in the future. In addition, the MRI provides useful information on the extent of the disease (e.g., cT3a/b) which allows you to better plan the surgical strategy or other therapies.