Variance In Ratings Research Articles

Reliability of the National Institutes of Health Stroke Scale

Background: The National Institutes of Health Stroke Scale (NIHSS) is widely used to measure stroke deficits and is deemed to be reliable when used by a range of professionals. Aims: This study aimed to establish the inter-rater reliability of the NIHSS when completed via telemedicine. Secondary aims were to explore if professional group, length of time since training and/or re-certification, frequency of use and reason for using the NIHSS influenced the inter-rater reliability. Methods: A total of 30 video clips, the equivalent of two whole patient assessments for each of the 15 NIHSS items, were analysed by a range of NIHSS-certified clinical participants. Of these, 10 were nurses and five were consultants. Kappa statistics were used to calculate the inter-rater reliability for each item, with additional data on the range of agreement of items. Data across group characteristics were compared to test hypotheses about factors that could impact reliability. Findings: Overall, the inter-rater reliability was found to be lower than anticipated, and there was a wide variation in ratings. Consultants tended to score better than nurses, and, counter-intuitively, stroke specialist staff and those who used the NIHSS more frequently tended to have poorer reliability than their counterparts. Total agreement on score was only achieved in five out of the 30 video clips (16.6%), with agreement better at either end of the scoring range (i.e. no deficit or worst deficit). These findings indicate that reliability of the NIHSS may be lower than anticipated. Conclusion: Further research is needed to better understand the poor reliability of the NIHSS, as this has implications for care decisions and patient outcomes.

Automated volumetric and statistical shape assessment of cam-type morphology of the femoral head-neck region from clinical 3D magnetic resonance images.

BackgroundFemoroacetabular impingement (FAI) cam morphology is routinely assessed using manual measurements of two-dimensional (2D) alpha angles which are prone to high rater variability and do not provide direct three-dimensional (3D) data on these osseous formations. We present CamMorph, a fully automated 3D pipeline for segmentation, statistical shape assessment and measurement of cam volume, surface area and height from clinical magnetic resonance (MR) images of the hip in FAI patients.MethodsThe novel CamMorph pipeline involves two components: (I) accurate proximal femur segmentation generated by combining the 3D U-net to identify both global (region) and local (edge) features in clinical MR images and focused shape modelling to generate a 3D anatomical model for creating patient-specific proximal femur models; (II) patient-specific anatomical information from 3D focused shape modelling to simulate ‘healthy’ femoral bone models with cam-affected region constraints applied to the anterosuperior femoral head-neck region to quantify cam morphology in FAI patients. The CamMorph pipeline, which generates patient-specific data within 5 min, was used to analyse multi-site clinical MR images of the hip to measure and assess cam morphology in male (n=56) and female (n=41) FAI patients.ResultsThere was excellent agreement between manual and CamMorph segmentations of the proximal femur as demonstrated by the mean Dice similarity index (DSI; 0.964±0.006), 95% Hausdorff distance (HD; 2.123±0.876 mm) and average surface distance (ASD; 0.539±0.189 mm) values. Compared to female FAI patients, male patients had a significantly larger median cam volume (969.22 vs. 272.97 mm3, U=240.0, P<0.001), mean surface area [657.36 vs. 306.93 mm2, t(95)=8.79, P<0.001], median maximum-height (3.66 vs. 2.15 mm, U=407.0, P<0.001) and median average-height (1.70 vs. 0.86 mm, U=380.0, P<0.001).ConclusionsThe fully automated 3D CamMorph pipeline developed in the present study successfully segmented and measured cam morphology from clinical MR images of the hip in male and female patients with differing FAI severity and pathoanatomical characteristics.

Relative food abundance predicts greater binge-eating symptoms in subsequent hours among young adults experiencing food insecurity: Support for the “feast-or-famine” cycle hypothesis from an ecological momentary assessment study

Food insecurity (FI) may increase risk for binge eating through a “feast-or-famine” cycle, where fluctuations in food availability correspond to alternating periods of food restriction and opportunities for binge eating, but research on this topic is limited. To clarify the relationship between food availability and binge eating in the context of FI, this study examined the association between momentary food security level and subsequent binge-eating symptoms among individuals in food-insecure households and investigated how this association differs by factors that may modify the extent to which food availability fluctuates. Ecological momentary assessment data were collected in 2020–2021 from 75 young adults (Mage = 25.3 ± 1.8 years; 72% female; 72% Black, Indigenous, or a Person of Color) in the United States who had experienced past-month household FI. For 14 days, participants reported four times per day on food security and eating episodes, and binge-eating symptoms were assessed for each reported eating episode. About 35% of the variance in momentary food security ratings was accounted for by within-person variability over time. A significant within-person association was observed in multilevel analyses, indicating that instances of greater food security relative to one's average level predicted greater subsequent binge-eating symptoms. Moderation analyses revealed that this association was significant only among individuals reporting use of food assistance programs, high engagement in resource trade-off coping strategies (e.g., skipping bill payments to buy food), or low food security-related self-efficacy. Overall, findings offer support for the “feast-or-famine” cycle hypothesis as an explanation for the link between FI and binge eating, emphasize the importance of identifying approaches to promote more stable access to adequate food, and suggest potential intervention targets to reduce risk for binge eating in populations experiencing FI.

A study to determine students study habits, clinical experiences, and attitudes related to their knowledge and behaviour intentions in the healthcare profession.

Study habits and attitudes are thought to have a significant impact on students' academic performance, and it is assumed that "excellent" study habits will result in "good" academic results. As medical students prepare to become physicians, having the right attitudes can have an influence on the standard of care they provide to their patients. Few longitudinal research studies have examined the degree to which the attitude of pupil’s ratings change as they progress through medical school. This study looked at how a large student cohort's attitude ratings changed as they advanced through medical school. It was also looked into whether student gender affected attitude change. This research included medical trainees from three successive classes (1999-2001). The Medical Skills Questionnaire, an internal tool, and the Attitudes Toward Social Issues in Medicine (ATSIM) survey were both completed by students. Total and subscale attitudinal score reliability estimations fell within a reasonable range. A sustained reduction in various attitude scores was seen as pupils moved through means of the medical education programme, based on multivariate studies of the variation of the mean attitudinal ratings. Compared to men, women scored better on attitudes. As a consequence, as medical school students progress, their attitude ratings decline. Although the causes of the change in terms of attitude are not entirely evident, they may be related to a ceiling of excellent attitude ratings upon admission, a decline in idealism, and the effects of the unanticipated curriculum. More research is needed to determine how medical education affects students' opinions.

Bank systemic risk: An analysis of the sovereign rating ceiling policy and rating downgrades

AbstractWe investigate the impact that the sovereign ceiling policy has on financial stability. In the event of a sovereign rating downgrade, we find that the rating agencies' sovereign ceiling policy leads to a disproportionate downgrade of the most creditworthy financial institutions in the economy and results in increased systemic risk. This asymmetric variation in bank ratings also impairs equity growth that further exacerbates bank insolvency. Our results are robust to several matching techniques, such as propensity score matching and entropy balancing, falsification tests, subsample analyses, alternative empirical proxies and model specifications.

Vertical Versus Horizontal Variance in Online Reviews and Their Impact on Demand

This article examines the differential impact of variances in the quality and taste comments found in online customer reviews on firm sales. Using an analytic model, the authors show that although increased variance in consumer reviews about taste mismatch normally decreases subsequent demand, it can increase demand when mean ratings are low and/or quality variance is high. In contrast, increased variance in quality always decreases subsequent demand, although this effect is moderated by the amount of variance in tastes. Since these theoretical demand effects are predicated on the assumption that consumers can differentiate between the two sources of variation in ratings, the authors conduct a survey to test this assumption, demonstrating that participants are indeed able to reliably distinguish quality from taste evaluations in two subsets of 5,000 reviews taken from larger data sets of reviews for 4,305 restaurants and 3,460 hotels. The authors use these responses to construct sets of reviews that they use in a controlled laboratory experiment on restaurant choice, finding strong support for the theoretical predictions. These responses are also used to train classifiers using a bag-of-words model to predict the degree to which each review in the larger data sets relates to quality and/or taste, allowing the authors to estimate the two types of review variances. Finally, the authors estimate the effects of these variances in overall ratings on establishment sales, again finding support for the theoretical results.

The Relative Importance of Joke and Audience Characteristics in Eliciting Amusement

The current work estimated the relative importance of joke and audience characteristics for the occurrence of amusement. Much psychological research has focused on stimulus characteristics when searching for sources of funniness. Some researchers have instead highlighted the importance of perceiver characteristics, such as dispositional cheerfulness. Across five preregistered studies (Ns = 118–54,905) with varied stimuli and perceiver samples (website visitors, students, Mechanical Turk and Prolific users), variance-decomposition analyses found that perceiver characteristics account for more variance in funniness ratings than stimulus characteristics. Thus, psychological theories focusing on between-persons differences have a relatively high potential for explaining and predicting humor appreciation (here, funniness ratings). Crucially, perceiver-by-stimulus interactions explained the largest amount of variance, highlighting the importance of fit between joke and audience characteristics when predicting amusement. Implications for humor-appreciation theories and applications are discussed.

The quality of reporting in cardiac MRI artificial intelligence segmentation studies - a systematic review

Abstract Funding Acknowledgements Type of funding sources: Public Institution(s). Main funding source(s): This work was supported by an NIHR AI Award, AI_AWARD01706. This research was also funded in part, by the Wellcome Trust [Grant number 205188/Z/16/Z ]. Background There has been a rapid increase in the number of Artificial Intelligence (AI) studies of cardiac MRI (CMR) segmentation. AI has huge potential to improve image analysis assessments. However, advancement and clinical translation in this field depend on researchers presenting their work in a transparent and reproducible manner. Purpose This systematic review aimed to evaluate the quality of reporting in AI studies involving CMR segmentation. Methods MEDLINE and EMBASE databases were searched for AI CMR segmentation studies on 18/11/2021. The flow of study inclusion is shown in Figure 1. Any AI method to segment any cardiac structure on CMR was eligible for inclusion. Each study was assessed for compliance with the Checklist for Artificial Intelligence in Medical Imaging (CLAIM). Results 70 studies were included in the qualitative analysis. Studies were published between 2015 to 2021, with the majority (71%) published in 2020 and 2021. Most studies were performed in Europe (33%), China (27%) and the USA (26%). Short-axis sections were segmented in 70% of studies and most commonly included both ventricles (51%) or the left ventricle alone (30%). 20 different architecture implementations were represented. Figure 2 summarises the most relevant CLAIM domains to AI segmentation. The training sample eligibility criteria, demographics and clinical characteristics were not reported in 47% and 81% of studies, respectively. Ground truth annotations, source of the annotations and annotation tool were absent in 31%, 36% and 51% of studies respectively. Preprocessing steps and software libraries and packages used in training were not included in 27% and 24%. Details on the training approach including the number of models trained and method of selecting the final model were missing in 20% and 17% of the studies. Methods of validation or testing on external data, inter- and intra- rater variability and failure analysis were unreported in 57%, 63% and 74%, respectively. Conclusion This systematic review highlights important gaps in the AI literature of CMR studies. We identified key items missing in the dataset description, model development, validation and testing that limit the transparency, reproducibility and hence validity of published AI studies. This review may support closer adherence to established frameworks for reporting standards.

Automatic rating of therapist facilitative interpersonal skills in text: A natural language processing application.

BackgroundWhile message-based therapy has been shown to be effective in treating a range of mood disorders, it is critical to ensure that providers are meeting a consistently high standard of care over this medium. One recently developed measure of messaging quality–The Facilitative Interpersonal Skills Task for Text (FIS-T)–provides estimates of therapists’ demonstrated ability to convey psychotherapy's common factors (e.g., hopefulness, warmth, persuasiveness) over text. However, the FIS-T's scoring procedure relies on trained human coders to manually code responses, thereby rendering the FIS-T an unscalable quality control tool for large messaging therapy platforms.ObjectiveIn the present study, researchers developed two algorithms to automatically score therapist performance on the FIS-T task.MethodsThe FIS-T was administered to 978 messaging therapists, whose responses were then manually scored by a trained team of raters. Two machine learning algorithms were then trained on task-taker messages and coder scores: a support vector regressor (SVR) and a transformer-based neural network (DistilBERT).ResultsThe DistilBERT model had superior performance on the prediction task while providing a distribution of ratings that was more closely aligned with those of human raters, versus SVR. Specifically, the DistilBERT model was able to explain 58.8% of the variance (R2 = 0.588) in human-derived ratings and realized a prediction mean absolute error of 0.134 on a 1–5 scale.ConclusionsAlgorithms can be effectively used to ensure that digital providers meet a consistently high standard of interactions in the course of messaging therapy. Natural language processing can be applied to develop new quality assurance systems in message-based digital psychotherapy.

Uncertainty about Rater Variance and Small Dimension Effects Impact Reliability in Supervisor Ratings

ABSTRACT We modeled the effects commonly described as defining the measurement structure of supervisor performance ratings. In doing so, we contribute to different theoretical perspectives, including components of the multifactor and mediated models of performance ratings. Across two reanalyzed samples (Sample 1, N ratees = 392, N raters = 244; Sample 2, N ratees = 342, N raters = 397), we found a structure primarily reflective of general (>27% of variance explained) and rater-related (>49%) effects, with relatively small performance dimension effects (between 1% and 11%). We drew on findings from the assessment center literature to approximate the proportion of rater variance that might theoretically contribute to reliability in performance ratings. We found that even moderate contributions of rater-related variance to reliability resulted in a sizable impact on reliability estimates, drawing them closer to accepted criteria.

Age-Related Variance in Performance versus Ratings of Attention and Impulse Regulation in Children: Implications for the Assessment of ADHD.

Executive function task (EF) deficits are hypothesized to underlie difficulties with self-regulation. However, tasks assessing EF impairments have only been weakly correlated with rating scales that index self-regulation difficulties. A community sample of children and youth aged between 8 and 20 years old were assessed longitudinally. Growth curve analyses and correlations were conducted to better understand how these two types of measures relate to one another across development, as well as the impact of age-related variance. EF was assessed using the Stroop Task and Trail Making test and behavioral ratings of self-regulation were captured using the SWAN scale. EF task performance improved steeply until age 14–15, whereas the SWAN Scale showed small age-related decreases. EF task performance was moderately correlated with age among 8–13-year-olds and to a lesser extent among 14–20-year-olds. SWAN scores were not significantly related to age in either group. Correlations were similar in an ADHD “at-risk” subgroup. EF task performance and parent ratings of attention regulation have different developmental trajectories, which may partly explain why correlations are low to modest in these samples. In particular, age-related variance is an important methodological consideration with significant implications for the assessment of self-regulation in children and youth with ADHD.

Core job characteristics and change oriented organization citizenship behavior: what can managers do on a day-to-day basis?

The purpose of this study is to examine the dynamic relationship between daily job characteristics proposed by job characteristics theory (job autonomy, task variety, significance, identity, and feedback) and change oriented organizational citizenship behavior (OCB-CH). A daily diary survey study design was used, in which 61 employees working in different organizations in Greece, completed a structured questionnaire for five consecutive working days (N = 305 occasions). Results from multilevel regression analysis supported the role of daily job autonomy, daily task significance and daily job feedback as within-person positive correlates of OCB-CH. Our model explained 17.72% of the variance in OCB-CH ratings. The study highlights the importance of core job characteristics, for the execution of daily OCB-CH in organizations. However not all job characteristics are suitable for promoting the execution of daily OCB-CH. Managers can enhance their employees’ daily OCB-CH by interventions aiming at increasing daily task variety, and task significance along with the degree of daily job autonomy granted to employees.

Healthcare consumers' and professionals' perceived acceptability of evidence-based interventions for rural transitional care.

There is a pressing need for high quality hospital-to-home transitional care in rural communities. Four evidence-based interventions (discharge planning, treatments, warning signs, and physical activity) have the potential to improve rural transitional care. However, there is limited understanding of how the perceptions of healthcare consumers and professionals compare on the acceptability of the interventions. Convergent views on intervention acceptability support implementation, whereas divergent views highlight areas requiring reconciliation prior to implementation. This study compared the acceptability of four evidence-based interventions proposed for rural transitional care, as perceived by healthcare consumers and professionals. A cross-sectional, comparative design was used. The convenience sample included 36 healthcare consumers (20 patients and 16 family caregivers) who had experienced a hospital-to-home transition in the past month and 30 healthcare professionals (29 registered nurses and one nurse practitioner) who provided transitional care in rural Ontario, Canada. Participants were presented with descriptions of the four interventions and completed an established intervention acceptability measure. Presentation of the four intervention descriptions and respective acceptability measures was randomized to control for possible order effects. The perceived overall acceptability of the interventions and their attributes (i.e., effectiveness, appropriateness, risk, and convenience) were compared using independent samples t-tests. Consumer ratings were consistently higher across all four interventions in terms of overall acceptability as well as effectiveness, appropriateness, and convenience (all p's < .01; effect sizes 0.70-1.13). No significant between-group differences in perceived risk were found. Contextual and methodological differences may account for variability in ratings, but further research is needed to explore these propositions. The results support future qualitative inquiry targeting professionals to better understand their perspectives on the effectiveness, appropriateness, and convenience of the four interventions.

The influence of ceremonial settings on mystical and challenging experiences occasioned by ayahuasca: A survey among ritualistic and religious ayahuasca users.

Recent studies have recognized the importance of non-pharmacological factors such as setting to induce or promote mystical experiences or challenging experiences among ayahuasca users. This study aimed to evaluate the association between the setting in which ayahuasca is consumed and the intensity of mystical and challenging experiences considering three ayahuasca using traditions (União do Vegetal, Santo Daime and neo-shamanic groups). A cross-sectional analysis was performed on survey data collected online from 2,751 participants. The Setting Questionnaire for the Ayahuasca Experience (SQAE) was used to evaluate six dimensions of the setting characteristics. The Mystical Experience Questionnaire (MEQ) and the Challenging Experience Questionnaire (CEQ) were used to quantify the psychedelic experience. Ratings on every SQAE setting dimension were negatively correlated with ratings of the CEQ (r values between 0.21 and 0.36) for all ayahuasca using traditions. Regression analysis revealed that ratings on four SQAE dimensions (Social, Comfort, Infrastructure and Decoration) explained 41% of the variance in CEQ ratings. Associations between SQAE and MEQ ratings were relatively weak and confined to the dimensions Leadership and Comfort, explaining 14% of the variance in MEQ ratings. Ratings of Social context were higher among members of União do Vegetal compared to Santo Daime and neo-shamanic members. Ratings of Infrastructure, Comfort and Decoration were more consistently correlated with MEQ in the neoshamanic tradition compared to the other traditions. This study shows that the setting is an important moderator of a challenging experience under ayahuasca. Maximizing the quality of the setting in which ayahuasca is taken will reduce the chance of a challenging experience while contributing positively to a mystical experience. The present findings can be considered when designing rituals and the (social) environment of ayahuasca ceremonies, and indicate that the SQAE questionnaire can be employed to monitor the influence of ceremonial settings on the ayahuasca experience.

Resident Autonomy and Performance Independence in Surgical Training Are Time- and Skill-Dependent

IntroductionAppropriate faculty supervision and conditional independence of residents during training are required for autonomous and independent postgraduate practice. However, there is a growing concern that competence for transition to independent practice is not universally met. We hypothesize that surgery residents play a significant and active role in achieving their own independent status. MethodsOver seven academic years (July 2014 through June 2021), 46 surgeons supervised and intraoperatively assessed the performance of 51 residents using validated Objective Structured Assessment of Technical Skill (OSATS) and Zwisch Operative Autonomy (ROA) assessments. Resident readiness to perform procedures independently (RRI) was graded as yes, no, or not applicable. Data were analyzed using descriptive statistics with categorical variables reported as frequencies and percentages. ResultsA total of 1657 elective procedures were performed by residents supervised by faculty. Association between RRI and postgraduate year (PGY), OSATS scores, ROA, resident and faculty gender, and case complexity was analyzed. Results indicated positive correlation between RRI and summative OSATS score (r = 0.510, P < 0.001), PGY (r = 0.535, P < 0.001) and ROA (r = 0.473, P < 0.001). Percentage of overall RRI increased from 7% at PGY1 to 87.4% at PGY5. Meaningful autonomy ratings increased from 23.6% at PGY1 to 92.5% at PGY5. Variations in ratings was observed when considering case category and complexity. ConclusionsRRI increases with years of training with variation when considering the specialty/The Accreditation Council for Graduate Medical Education procedure category and the complexity of cases. Specialty fellowships are a viable option to address the gap in The Accreditation Council for Graduate Medical Education categories when residency alone cannot reach appropriate independence. Residents’ technical skills play a crucial role in evaluating RRI and granting operative autonomy.

The latent distribution of a rating observed

ABSTRACT While extensive literature shows that the rating assigned by a critic or judge to a wine is one draw from a latent distribution, little has been published about the shape of that distribution. This article presents a derivation and test of a discrete and bounded probability mass function (PMF) that describes the distribution of the rating that a judge assigns to a wine. That PMF and the ratings that 72 wine judges assigned to blind triplicates in a commercial wine competition show that judges’ ratings are not identically distributed and that variance in ratings is a function of both the wine and the judge. Some wines are more difficult to rate consistently than others. Seventy percentage of judges reduce the variance due the wine alone, the standard deviation of the rating that a judge assigns averages 1.3 out of 10 ratings, and that deviation is significantly less than the standard deviation of random draws. The PMF and those results can be employed to improve wine-related and perhaps other taste-related research by considering the latent distribution that surrounds a rating observed.

The Chinese version of the Maltreatment and Abuse Chronology of Exposure (MACE) scale: Psychometric properties in a sample of young adults.

There are several effective self-report instruments used by Chinese researchers to retrospectively assess exposure to childhood maltreatment. However, these measures do not assess the timing of exposure, restricting efforts to identify periods of development when childhood maltreatment maximally increases vulnerability to psychopathology and health outcomes. In the current study we created a Chinese version of the Maltreatment and Abuse Chronology of Exposure (MACE) scale, which assesses multiplicity (number of types of maltreatment experienced) and severity of maltreatment as well as when it occurred during childhood and adolescence. Rasch modeling was used for scale development in a sample of 812 undergraduate students. Item reduction analysis of the original 75 items produced a 58-item Chinese version with ten subdimensions. The new scale showed good three-week test-retest reliability, and good convergent validity with the Childhood Trauma Questionnaire (CTQ) and the revised Adverse Childhood Experiences Questionnaire (ACEQ-R). Variance decomposition analyses found that compared to the CTQ and ACE, the MACE Severity and Multiplicity scores explained higher variance in self-reported depression and anxiety symptom ratings on the Depression Anxiety Stress Scales (DASS). The results of the present study confirmed that the Chinese version of the MACE has sound psychometric properties in the Chinese cultural context. This new instrument will be a valuable tool for Chinese researchers, psychiatrists and psychologists to ascertain the type and timing of exposure to maltreatment.

How Stable, Really? Traditional and Nonlinear Dynamics Approaches to Studying Temporal Fluctuations in Personality and Affect.

A pair of quantitative case studies is presented to demonstrate how different approaches to quantifying temporal variability in ratings of traits and affect can provide rich information for personality researchers. Data are presented and analyzed from two college students who completed an Ecological Momentary Assessment protocol sampling ratings of affect and traits up to 24 times daily for one week. Both classical and nonlinear data analytic techniques were applied to the data to summarize and examine the temporal dynamics of both traits and affect. For the purposes of exposition, one Big Five trait rating, extraversion, and the PANAS positive and negative affects, are discussed. The results support previous research demonstrating a high degree of variability in ratings of both traits and affect over time. Analyses using nonlinear and complexity expand on these findings and suggest temporal patterning as well as disorder; implications of phase portraits for understanding variability are discussed. The findings are discussed in light of a processing dynamics approach to resolving the role of variability in understanding personality.

Automatic femoral articular cartilage segmentation using deep learning in three-dimensional ultrasound images of the knee

ObjectiveThis study aimed to develop a deep learning-based approach to automatically segment the femoral articular cartilage (FAC) in 3D ultrasound (US) images of the knee to increase time efficiency and decrease rater variability. DesignOur method involved deep learning predictions on 2DUS slices sampled in the transverse plane to view the cartilage of the femoral trochlea, followed by reconstruction into a 3D surface. A 2D U-Net was modified and trained using a dataset of 200 2DUS images resliced from 20 3DUS images. Segmentation accuracy was evaluated using a holdout dataset of 50 2DUS images resliced from 5 3DUS images. Absolute and signed error metrics were computed and FAC segmentation performance was compared between rater 1 and 2 manual segmentations. ResultsOur U-Net-based algorithm performed with mean 3D DSC, recall, precision, VPD, MSD, and HD of 73.1 ​± ​3.9%, 74.8 ​± ​6.1%, 72.0 ​± ​6.3%, 10.4 ​± ​6.0%, 0.3 ​± ​0.1 ​mm, and 1.6 ​± ​0.7 ​mm, respectively. Compared to the individual 2D predictions, our algorithm demonstrated a decrease in performance after 3D reconstruction, but these differences were not found to be statistically significant. The percent difference between the manually segmented volumes of the 2 raters was 3.4%, and rater 2 demonstrated the largest VPD with 14.2 ​± ​11.4 ​mm3 compared to 10.4 ​± ​6.0 ​mm3 for rater 1. ConclusionThis study investigated the use of a modified U-Net algorithm to automatically segment the FAC in 3DUS knee images of healthy volunteers, demonstrating that this segmentation method would increase the efficiency of anterior femoral cartilage volume estimation and expedite the post-acquisition processing for 3D US images of the knee.

Assessing the effects of student perceptions of instructional quality: A cross-subject within-student design

This study examines associations between student-perceived instructional quality and a student’s motivation and achievement using unique data from Germany in which 9th-grade students reported on instructional quality in their English and German classes in the same academic year. Student outcomes, including self-efficacy, course grades, and standardized achievement were measured in both subjects. We utilized a cross-classified random effects model to decompose the variance in student reports of teacher support and monitoring, finding that 17% and 16%, respectively, of the variation in ratings was due to the student reporter with 26% and 27%, respectively, due to the teacher being rated. Students and teachers were further nested within classes of students who stayed together across the two subjects; however, almost no variance was attributable to class groupings. Student-reported teacher support was positively associated with achievement gains and self-efficacy at the within-student, between-student, and between-teacher levels whereas monitoring was inconsistently associated with outcomes. Standardized betas of perceived teacher support on test score gains were small (<0.10), small-to-medium on course grade gains (0.16–0.24), and medium to large on self-efficacy (0.33–0.52). Measuring the same students with different teachers allows us to disentangle dyadic student-teacher variance from student rater variance in student perceptions and outcomes and facilitates the use of powerful within-student analytical techniques to quantify the effects of educational environments on student learning and self-efficacy.