Test Performance In Practice Research Articles

Health practitioner beliefs regarding the impact of age-based stereotype threat on performance in the cognitive assessment of older adults

Objectives Health practitioners’ understanding of the impact of age-based stereotype threat (ABST) on the cognitive test performance of older adults is not well understood. This study aimed to investigate health practitioners’ ability to recognize the influence of ABST in the cognitive assessment of older adults and their perceptions of its impact in practice. Methods One-hundred and twenty-nine health practitioners (86% female; M age = 39.75, SD = 11.50) with experience in conducting cognitive assessments with older adults (mainly psychologists and occupational therapists) completed an online survey assessing demographic and practice characteristics, aging beliefs, a hypothetical cognitive assessment scenario, and perceived impact of ABST on practice. Results Overall, health practitioners rated ABST factors in the assessment scenario as less detrimental to cognitive performance than internal and external factors. In a hierarchical regression model, lower recognition of ABST and negative aging beliefs significantly accounted for lower perceived impact of ABST on older adults’ cognitive test performance in practice (R 2 = .37, p < .001). Conclusion Health practitioners may not recognize the influence of ABST on assessment findings, especially if they hold negative aging beliefs. The findings highlight the need to improve health practitioners’ knowledge of ABST to increase the validity of cognitive testing in older adults.

Diagnostic use of ultrasound in giant cell arteritis in Counties Manukau District Health Board, New Zealand.

ObjectivesA retrospective observational study was undertaken to assess the diagnostic performance (sensitivity and specificity) of colour duplex ultrasound (CDUS) compared with temporal artery biopsy (TAB) for the diagnosis of GCA in the Counties Manukau District Health Board (CMDHB), New Zealand using clinical diagnosis as the reference standard.MethodsThe study population included patients with clinically suspected GCA who were referred to Middlemore Hospital and underwent CDUS, TAB or both between January 2019 and December 2020.ResultsSixty-nine patients were included in the study. Sixty-one percent were >75 years of age, with no cases <50 years of age and a female predominance of 71%. The sensitivity of CDUS was 26% (95% CI 10, 48) and specificity was 97% (95% CI 84, 100). The sensitivity of TAB was 57% (95% CI 34, 77) and specificity was 100%. CDUS had a positive predictive value of 86% (95% CI 42, 99) and a negative predictive value of 65% (95% CI 49, 78).ConclusionA positive CDUS in patients with a high risk for GCA may preclude the need for TAB due to the high specificity of CDUS in GCA. In contrast, patients with a high risk for GCA with a negative CDUS may still need TAB to confirm or exclude GCA. The duration from commencement of steroids to the time of CDUS is crucial in confirming GCA and, for this, shortening the waiting time in the CMDHB would be necessary to ensure adequate test performance in practice.

Stochastic configuration network ensembles with selective base models

Studies have demonstrated that stochastic configuration networks (SCNs) have good potential for rapid data modeling because of their sufficient adequate learning power, which is theoretically guaranteed. Empirical studies have verified that the learner models produced by SCNs can usually achieve favorable test performance in practice but more in-depth theoretical analysis of their generalization power would be useful for constructing SCN-based ensemble models with enhanced generalization capacities. In particular, given a collection of independently developed SCN-based learner models, it is useful to select certain base learners that can potentially obtain preferable test results rather than considering all of the base models together, before simply taking their average in order to build an effective ensemble model. In this study, we propose a novel framework for building SCN ensembles by exploring key factors that might potentially affect the generalization performance of the base model. Under a mild assumption, we provide a comprehensive theoretical framework for examining a learner model’s generalization error, as well as formulating a novel indicator that contains measurement information for the training errors, output weights, and a hidden layer output matrix, which can be used by our proposed algorithm to find a subset of appropriate base models from a pool of randomized learner models. A toy example of one-dimensional function approximation, a case study for developing a predictive model for forecasting student learning performance, and two large-scale data sets were used in our experiments. The experimental results indicate that our proposed method has some remarkable advantages for building ensemble models.

Retrieval practice can improve classroom review despite low practice test performance

SummaryReview is often more effective when it involves deliberate memory retrieval. However, this advantage may depend on a high rate of retrieval success; students who are less capable with the material may be better served by another activity. In our study, year 9 geography students listened to factual information, then reviewed some of it with a retrieval practice and feedback activity, some with a reading activity and left some unreviewed. We also manipulated the presence of hints during review—hints can affect the rate of retrieval success during practice and are relatively easy for teachers to provide. When tested 1 week later, most students showed a benefit of retrieval practice, even those who had performed poorly during review. There was also some evidence that hints improved learning when they made retrieval practice easier. Our findings suggest that retrieval practice, properly implemented, is advantageous for students of all ability levels.

Fundamentals of Counting Statistics in Digital PCR: I Just Measured Two Target Copies-What Does It Mean?

Current commercially available digital PCR (dPCR) systems and assays are capable of detecting individual target molecules with considerable reliability. As tests are developed and validated for use on clinical samples, the need to understand and develop robust statistical analysis routines increases. This chapter covers the fundamental processes and limitations of detecting and reporting on single molecule detection. We cover the basics of quantification of targets and sources of imprecision. We describe the basic test concepts: sensitivity, specificity, limit of blank, limit of detection, and limit of quantification in the context of dPCR. We provide basic guidelines how to determine those, how to choose and interpret the operating point, and what factors may influence overall test performance in practice.

Fault domain-based testing in imperfect situations: a heuristic approach and case studies

Model-based testing (MBT) involves creating an abstraction, called a model, to represent the system and automatically deriving test cases from this model. MBT can be performed using various approaches that generally employ certain assumptions or requirements affecting the test performance in practice. Here, we consider the harmonized state identifiers (HSI) method, which is based on finite state machine (FSM) models and generates test sets that cover all faults in a given domain under certain conditions. We are interested in the application of the HSI method in practical scenarios where some conditions do not hold or are not straightforward to satisfy. Thus, we propose a heuristic extension to the HSI method, called heuristic HSI (HHSI), to consider imperfect situations as they often occur in practice. To analyze the characteristics of HHSI, we empirically compare it to random testing and coverage-based testing using non-trivial case studies. The experiments include model-based mutation analyses over several FSM models.

Long-term Effects of Subliminal Priming on Academic Performance

This research examines the temporal range of subliminal priming effects on complex behavior. In Experiments 1 and 2, participants were subliminally primed with words either related or unrelated to intelligence before completing a practice exam, administered 1 to 4 days before an actual course midterm. Results revealed that the intelligence primes increased performance on the midterm compared to neutral primes. Experiment 1 demonstrated that being told that the priming task was designed to help exam performance moderated the effect of the intelligence primes. In Experiment 2, practice test performance mediated the effect of the primes on midterm performance. These experiments demonstrated that subliminal priming may have long-term effects on real-world behavior, and demonstrates one means by which long-term priming effects may occur.

Long-Term Effects of Subliminal Priming on Academic Performance

This research examines the temporal range of subliminal priming effects on complex behavior. In Experiments 1 and 2, participants were subliminally primed with words either related or unrelated to intelligence before completing a practice exam, administered 1 to 4 days before an actual course midterm. Results revealed that the intelligence primes increased performance on the midterm compared to neutral primes. Experiment 1 demonstrated that being told that the priming task was designed to help exam performance moderated the effect of the intelligence primes. In Experiment 2, practice test performance mediated the effect of the primes on midterm performance. These experiments demonstrated that subliminal priming may have long-term effects on real-world behavior, and demonstrates one means by which long-term priming effects may occur.

A comparative meta-analysis on the variability in test performance among FDA-licensed enzyme immunosorbent assays for HIV antibody testing

Background. Although independently published studies have compared diagnostic test performance among various manufactured enzyme immunosorbent assays (EIAs) used in HIV antibody testing, none have attempted to formally synthesize such results through a comparative meta-analysis. In particular, no estimates of post-FDA approval test performance, in terms of sensitivity and specificity, and their associated variability within each manufacturer, has been reported in the literature, along with an analysis of the relative differences in manufacturer test performance in practice (after FDA approval). Methods. Retrieval of studies was done using several searching strategies, while retrieval of manufacturer information was done through package inserts and direct contacts. Comparisons of HIV antibody test performance across manufacturers and within a single manufacturer were made based on 16 estimates (from 11 articles) and 33 estimates (from 19 articles), respectively. A generalized linear model, based upon Bayes estimates of sensitivity and specificity, was used to assess the impact of several study-level covariates on the performance of these EIAs, with overall estimates of manufacturer test performance and associated variability obtained based on generalized estimating equations. Results. Estimates of test performance were obtained across studies, with a significant (P < 0.01) difference between manufacturers. The test performance of each manufacturer significantly interacted (P < 0.05) with the following study-level covariates: type of population screened, year of diagnostic testing and study quality. Among a single manufacturer, Abbott, significant improvement in estimates of test sensitivity (P < 0.01) and specificity (P < 0.01) was observed with each newly produced antibody kit. Conclusion. Estimates on the relative differences in test performance within each manufacturer may be used for guiding decisions on the choice of EIA test kit for HIV antibodies, given the type of population screened, as well as cost and time considerations. In addition, the results of this meta-analysis may be used in modeling HIV prevalence when used as prior information within a Bayesian framework or for standardizing test results among various manufacturers.

Effects of Cooperative Learning and Learner-Control Modes in Computer-Based Instruction

AbstractThe purpose of this study was to investigate the effects of 2 instructional methods (cooperative and individual) and 2 approaches to learner control (full-minus and lean-plus) on practice-test performance, posttest performance, attitudes, option use, and student interactions. The participants worked alone or with a partner on a computer lesson that either provided a full program with the option to bypass instruction or a lean program with the option to request additional instruction. Those participants who worked alone used significantly more optional practice items and had better attitudes toward the instruction than those who worked cooperatively. Participants using the full-minus program used significantly more optional practice, summary, and review than those using the lean-plus program. Full-minus learners also had significantly higher practice-test scores than lean-plus students. However, posttest performance was not influenced by either learner-control mode or instructional method. Implicat...