Set Of Items Research Articles

Suite test. A virtual reality based neuropsychological assessment tool for memory. A normative study on immediate, short-term and delayed memory tasks

Objective To collect normative data for the Suite test, a virtual reality (VR) tool designed to assess memory processes. Method The normative sample included 676 subjects (49.7% female), aged from 12 to 85 years. The Suite test comprises a 360-degree VR environment designed as a furniture shop, in which participants must group specific sets of furniture items (ordered by different families of customers) by clicking on the furniture to be packed following instructions from a voice-over. Results Core variables provided were grouped into immediate, short-term and long-term delayed recall. Cluster analyses established five age groups (12 years old, 13 to 26, 27 to 44, 45 to 58, and 59 to 85) with gender differentiated norms only deemed necessary for those transitioning from adolescence to adulthood (13 to 26) and from middle age to older adulthood (45 to 58). No statistically significant differences were found for additional gender × age normative groups, or for any group differentiated by educational level. A confirmatory factor analysis raised the existence of two differentiated factors, one associated to encoding processes (immediate memory trials) and the other to retrieval processes (both short term and long-term delayed recall trials grouping into the same factor). Additional results on the test reliability and internal consistency are presented. Conclusions Suite Test can help explore memory deficits across the life span and differentiate between visual and verbal memory strategies. Further research is required to study the test sensitivity and specificity, as well as convergent validity studies with well-established memory assessment tools.

Learning to Synthesize Compatible Fashion Items Using Semantic Alignment and Collocation Classification: An Outfit Generation Framework.

The field of fashion compatibility learning has attracted great attention from both the academic and industrial communities in recent years. Many studies have been carried out for fashion compatibility prediction, collocated outfit recommendation, artificial intelligence (AI)-enabled compatible fashion design, and related topics. In particular, AI-enabled compatible fashion design can be used to synthesize compatible fashion items or outfits to improve the design experience for designers or the efficacy of recommendations for customers. However, previous generative models for collocated fashion synthesis have generally focused on the image-to-image translation between fashion items of upper and lower clothing. In this article, we propose a novel outfit generation framework, i.e., OutfitGAN, with the aim of synthesizing a set of complementary items to compose an entire outfit, given one extant fashion item and reference masks of target synthesized items. OutfitGAN includes a semantic alignment module (SAM), which is responsible for characterizing the mapping correspondence between the existing fashion items and the synthesized ones, to improve the quality of the synthesized images, and a collocation classification module (CCM), which is used to improve the compatibility of a synthesized outfit. To evaluate the performance of our proposed models, we built a large-scale dataset consisting of 20 000 fashion outfits. Extensive experimental results on this dataset show that our OutfitGAN can synthesize photo-realistic outfits and outperform the state-of-the-art methods in terms of similarity, authenticity, and compatibility measurements.

Semantic richness effects in isolated spoken word recognition: Evidence from massive auditory lexical decision.

While known to influence visual lexical processing, the semantic information we associate with words has recently been found to influence auditory lexical processing as well. The present work explored the influence of semantic richness in auditory lexical decision. Study 1 recreated an experiment investigating semantic richness effects in concrete nouns (Goh et al., 2016). In Study 2, we expanded the stimulus set from 442 to 8,626 items, exploring the robustness of effects observed in Study 1 against a larger data set with increased diversity in both word class and other characteristics of interest. We also utilized generalized additive mixed models to investigate potential nonlinear effects. Results indicate that semantic richness effects become more nuanced and detectable when a wider set of items belonging to different parts of speech is examined. Findings are discussed in the context of models of spoken word recognition. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Mitigating the Impact of Inaccurate Feedback in Dynamic Learning-to-Rank: A Study of Overlooked Interesting Items

Dynamic Learning-to-Rank (DLTR) is a method of updating a ranking policy in real-time based on user feedback, which may not always be accurate. Although previous DLTR work has achieved fair and unbiased DLTR under inaccurate feedback, they face the trade-off between fairness and user utility and also have limitations in the setting of feeding items. Existing DLTR works improve ranking utility by eliminating bias from inaccurate feedback on observed items, but the impact of another pervasive form of inaccurate feedback, overlooked or ignored interesting items, remains unclear. For example, users may browse the rankings too quickly to catch interesting items or miss interesting items because the snippets are not optimized enough. This phenomenon raises two questions: i) Will overlooked interesting items affect the ranking results? ii) Is it possible to improve utility without sacrificing fairness if these effects are eliminated? These questions are particularly relevant for small and medium-sized retailers who are just starting out and may have limited data, leading to the use of inaccurate feedback to update their models. In this paper, we find that inaccurate feedback in the form of overlooked interesting items has a negative impact on DLTR performance in terms of utility. To address this, we treat the overlooked interesting items as noise and propose a novel DLTR method, the Co-teaching Rank (CoTeR), that has good utility and fairness performance when inaccurate feedback is present in the form of overlooked interesting items. Our solution incorporates a co-teaching-based component with a customized loss function and data sampling strategy, as well as a mean pooling strategy to further accommodate newly added products without historical data. Through experiments, we demonstrate that CoTeRx not only enhances utilities but also preserves ranking fairness, and can smoothly handle newly introduced items.

Repeated Fair Allocation of Indivisible Items

The problem of fairly allocating a set of indivisible items is a well-known challenge in the field of (computational) social choice. In this scenario, there is a fundamental incompatibility between notions of fairness (such as envy-freeness and proportionality) and economic efficiency (such as Pareto-optimality). However, in the real world, items are not always allocated once and for all, but often repeatedly. For example, the items may be recurring chores to distribute in a household. Motivated by this, we initiate the study of the repeated fair division of indivisible goods and chores, and propose a formal model for this scenario. In this paper, we show that, if the number of repetitions is a multiple of the number of agents, there always exists a sequence of allocations that is proportional and Pareto-optimal. On the other hand, irrespective of the number of repetitions, an envy-free and Pareto-optimal sequence of allocations may not exist. For the case of two agents, we show that if the number of repetitions is even, it is always possible to find a sequence of allocations that is overall envy-free and Pareto-optimal. We then prove even stronger fairness guarantees, showing that every allocation in such a sequence satisfies some relaxation of envy-freeness. Finally, in case that the number of repetitions can be chosen freely, we show that envy-free and Pareto-optimal allocations are achievable for any number of agents.

Pre-Turkic Burial in the Northern Altai: Cultural and Chronological Interpretation

Purpose. One of the problems in the archeology of Altai of the Great Migration period remains the chronology of funerary sites. The article concerns the materials of one of representative burials of the Choburak-I necropolis in the Northern Altai, demonstrating the wide possibilities of research in this direction.Methods and Results. A man of 25–30 years old was buried in the grave of barrow № 38. The key features of the object are a small mound with a crepe, the western orientation of the deceased person, as well as the burial of a horse «at the feet» of the man. The accompanying inventory included numerous weapons, tools, equipment for a man and a horse. The analysis of the finds testifies to the period of the construction of mound № 38 not earlier than the middle of the 4th century AD. The results of radiocarbon dating were obtained, which supplement this information and indicate the upper chronological boundary no later than the beginning of the 5th century AD.Conclusion. The correlation of the available data makes it possible to determine the chronology of mound no. 38 with-in the middle – second half of the 4th century AD. The recorded characteristics of the funeral rite indicate that this object belongs to the Dialyan tradition of ritual practice of the Bulan-Koby culture. The set of items found with the de-ceased man testifies to his high status in the nomadic society during his lifetime.

The SKIN-Q: An Innovative Patient-Reported Outcome Measure for Evaluating Minimally Invasive Skin Treatments for the Face and Body.

Background: As the aesthetics field continues to innovate, it is important that outcomes are carefully evaluated. Objectives: To develop item libraries to measure how skin looks and feels from the patient perspective, that is, SKIN-Q. Methods: Concept elicitation interviews were conducted and data were used to draft the SKIN-Q, which was refined with patient and expert feedback. An online sample (i.e., Prolific) provided field-test data. Results: We conducted 26 qualitative interviews (88% women; 65% ≥ 40 years of age). A draft of the SKIN-Q item libraries were formed and revised with input from 12 experts, 11 patients, and 174 online participants who provided 180 survey responses. The psychometric sample of 657 participants (82% women; 36% aged ≥40 years) provided 713 completed surveys (facial, n = 595; body, n = 118). After removing 14 items, the psychometric analysis provided evidence of reliability (≥0.85) and validity for a 20-item set that measures how skin feels and a 46-item set that measures how skin looks. Short-form scales were tested to provide examples for how to utilize the item sets. Conclusion: The SKIN-Q represents an innovative way to measure satisfaction with skin (face and body) in the context of minimally invasive treatments.

On Item-Sampling Evaluation for Recommender System

Personalized recommender systems play a crucial role in modern society, especially in e-commerce, news, and ads areas. Correctly evaluating and comparing candidate recommendation models is as essential as constructing ones. The common offline evaluation strategy is holding out some user-interacted items from training data and evaluating the performance of recommendation models based on how many items they can retrieve. Specifically, for any hold-out item or so-called target item for a user, the recommendation models try to predict the probability that the user would interact with the item and rank it among overall items, which is called global evaluation . Intuitively, a good recommendation model would assign high probabilities to such hold-out/target items. Based on the specific ranks, some metrics like Recall@K and NDCG@K can be calculated to further quantify the quality of the recommender model. Instead of ranking the target items among all items, Koren first proposed to rank them among a small sampled set of items , then quantified the performance of the models, which is called sampling evaluation . Ever since then, there has been a large amount of work adopting sampling evaluation due to its efficiency and frugality. In recent work, Rendle and Krichene argued that the sampling evaluation is “inconsistent” with respect to a global evaluation in terms of offline top- K metrics. In this work, we first investigate the “inconsistent” phenomenon by taking a glance at the connections between sampling evaluation and global evaluation. We reveal the approximately linear relationship between sampling with respect to its global counterpart in terms of the top- K Recall metric. Second, we propose a new statistical perspective of the sampling evaluation—to estimate the global rank distribution of the entire population. After the estimated rank distribution is obtained, the approximation of the global metric can be further derived. Third, we extend the work of Krichene and Rendle, directly optimizing the error with ground truth, providing not only a comprehensive empirical study but also a rigorous theoretical understanding of the proposed metric estimators. To address the “blind spot” issue, where accurately estimating metrics for small top- K values in sampling evaluation is challenging, we propose a novel adaptive sampling method that generalizes the expectation-maximization algorithm to this setting. Last but not least, we also study the user sampling evaluation effect. This series of works outlines a clear roadmap for sampling evaluation and establishes a foundational theoretical framework. Extensive empirical studies validate the reliability of the sampling methods presented.

Investigating the Relationship Between the Scores of the Persian Reading Comprehension Assessment Task and the Reading and Dyslexia Test

Background and Objectives: Today, comparing the scores of tests and evaluation scales with each other and the correlation between them is done to check and compare the test’s accuracy in diagnosing reading problems. The present study investigated the correlation between the scores of the Persian reading comprehension assessment task (PRCAT) and the text comprehension subtest of the reading and dyslexia test (NEMA) in fourth and fifth-grade elementary school students. Methods: In this study, 24 students from the fourth and fifth grades of elementary schools in Tehran City, Iran with normal reading skills participated. The set of items for the Persian reading comprehension assessment task and the text comprehension subtest of the NEMA test were taken from the students. Results: The results showed a positive correlation between the scores of the PRCAT and the text comprehension subtest of NEMA, and the correlation coefficient between them is 0.622 (r=0.622, P<0.01). Conclusion: The results showed that the PRCAT has an acceptable validity compared to the text comprehension subtest of the NEMA test.

Measuring susceptibility to use tobacco in an increasingly complex consumer marketplace: How many questions do we really need?

Predicting which young people are likely to use tobacco in the future is critical for prevention and intervention. Although measures for assessing susceptibility to using tobacco have fulfilled this goal for decades, there is almost no standard for the number of items that should be administered, or which items should be administered for which products. This study explored whether brief but psychometrically sound versions of commonly used susceptibility measures can adequately capture the construct relative to longer measures. A sample of young people (N = 451; Mage = 16.5 years; 64% females; 65% White) completed 33 susceptibility items, which are designed to assess susceptibility to use different types of tobacco products (cigarette, smokeless tobacco, vaping products, and little cigars/cigarillos) of various flavors (tobacco, menthol, and sweet). Analysis of these 33 items indicated that asking about the likelihood of using each tobacco product class when a best friend offers it (four items in all) captures 98.5% of information that is captured using the longer set of items; asking the best friend question for each product by each flavor category (11 items in all) captures 99.7% of the information. Depending on research needs, tobacco use susceptibility can be measured with little loss of information by administering a limited set of items assessing the likelihood that a young person will use a tobacco product if a friend offers it for any product-flavor combination. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

ChatGPT (GPT-4) passed the Japanese National License Examination for Pharmacists in 2022, answering all items including those with diagrams: a descriptive study.

The objective of this study was to assess the performance of ChatGPT (GPT-4) on all items, including those with diagrams, in the Japanese National License Examination for Pharmacists (JNLEP) and compare it with the previous GPT-3.5 model’s performance. The 107th JNLEP, conducted in 2022, with 344 items input into the GPT-4 model, was targeted for this study. Separately, 284 items, excluding those with diagrams, were entered into the GPT-3.5 model. The answers were categorized and analyzed to determine accuracy rates based on categories, subjects, and presence or absence of diagrams. The accuracy rates were compared to the main passing criteria (overall accuracy rate ≥62.9%). The overall accuracy rate for all items in the 107th JNLEP in GPT-4 was 72.5%, successfully meeting all the passing criteria. For the set of items without diagrams, the accuracy rate was 80.0%, which was significantly higher than that of the GPT-3.5 model (43.5%). The GPT-4 model demonstrated an accuracy rate of 36.1% for items that included diagrams. Advancements that allow GPT-4 to process images have made it possible for LLMs to answer all items in medical-related license examinations. This study’s findings confirm that ChatGPT (GPT-4) possesses sufficient knowledge to meet the passing criteria.

A Flexible Inventory of Survey Items for Environmental Concepts Generated via Special Attention to Content Validity and Item Response Theory

We demonstrate how many important measures of belief about the environmental suffer from poor content validity and inadequate conceptual breadth (dimensionality). We used scholarship in environmental science and philosophy to propose a list of 13 environmental concepts that can be held as beliefs. After precisely articulating the concepts, we developed 85 trial survey items that emphasized content validity for each concept. The concepts’ breadth and the items’ content validity were aided by scrutiny from 17 knowledgeable critics. We administered the trial items to 449 residents of the United States and used item response theory to reduce the 85 trial items to smaller sets of items for use when survey brevity is required. The reduced sets offered good predictive ability for two environmental attitudes (R2 = 0.42 and 0.46) and indices of pro-environmental behavior (PEB, R2 = 0.23) and behavioral intention (R2 = 0.25). The predictive results were highly interpretable, owing to their robust content validity. For example, PEB was predicted by the degree to which one believes nature to be sacred, but not by the degree of one’s non-anthropocentrism. Concepts with the greatest overall predictive ability were Sacredness and Hope. Belief in non-anthropocentrism had little predictive ability for all four response variables—a claim that previously could not have been made given the widespread poverty of content validity for items representing non-anthropocentrism in existing instruments. The approach described here is especially amenable to incremental improvement, as other researchers propose more informative survey items and potentially important concepts of environmental beliefs we overlooked.

A comparison of objective priors for Cronbach’s coefficient alpha using a balanced random effects model

. In this article, the reference and probability matching priors for Cronbach’s alpha will be derived. The performance of these two priors will be compared to that of the well-known Jeffreys prior and a divergence prior. Cronbach’s alpha is a measure used to assess the reliability of a set of test items. A simulation study will be considered to compare the performance of the priors, where the coverage rates, average interval lengths, and standard deviations of the interval lengths will be computed. A second simulation study will be considered where the mean relative error will be compared for the various priors using three different loss functions. The following loss functions will be considered, Squared error loss, Absolute error loss, and Linex loss. An illustrative example will also be considered. Throughout the article, the random effects approach will be used.

DETERMINING CONCESSIONARY ITEMS FOR “AVAILABILITY PAYMENT ONLY” PPP PROJECTS: A HOLISTIC FRAMEWORK INTEGRATING VALUE-FOR-MONEY AND SOCIAL VALUES

Public-private partnerships (PPPs) have been widely applied in infrastructure development around the world. However, reasonable concessionary items are critical to compromise interest conflicts between government agencies and sponsors to ensure project success. A broad literature review centering on PPP transaction structuring revealed two significant research gaps: (1) a lack of attention to the ‘availability payment only’ (APO) funding method and (2) negligence of the public side’s perspective in determining concessionary items. The research objective was to develop a methodological framework for determining concessionary items in APO PPP projects while considering the interests of the public side. This study proposed a value-for-money (VFM) and social values integrated framework which accommodates discounted cash flow (DCF) analysis, bargaining game modeling, and multi-objectives decision-making (MODM). This framework enables a decision-making process based on both an indifferent feasible interval of concessionary items under a discount rate agreed upon by both parties and an optimal set of concessionary items. Additionally, results of a sensitivity analysis indicated that project construction profit can significantly affect feasible and optimal concession items, and the optimal concession period is less sensitive to changes in risk allocation. The application of proposed model indicated that this paper successfully provides a methodology for determining a feasible interval and an optimal concession items group tailored to APO PPP projects. This study paves the way towards a platform for the public and private partners to jointly and quickly come up with sound PPP concessional items in light of the win-win principle, particularly under the APO funding mechanism.

Evidence to support test interpretation: Evaluating the content validity of a new item set for the Transition Pragmatics Interview

Purpose There is little consensus on evidence-based practice guidelines for the selection of criterion-referenced assessments. Having confidence in scores from criterion-referenced assessments requires evidence that items align with their intended constructs. The purposes of these studies were to demonstrate evidence of content validity for the revised item set of a developing social communication assessment and to provide clinicians with a model of content validity evaluations that can be generalised to the review of other assessments. Method In Study 1, 10 experts rated 25 newly-developed items for how well they represented the intended construct. In Study 2, seven participants ages 14–20 were administered the Three Step Test Interview to assess their cognitive processes for responding to new items. Examinee responses were coded for construct-relevant and construct-irrelevant factors. Result Twenty-three of the 25 newly-developed items were deemed representative of the intended construct by experts and elicited construct-relevant response processes from examinees. Conclusion The integration of expert review and examinee cognitive interviewing provides a more complete evaluation of the alignment of the items to their intended construct. Transparent reports of the methods and findings of content validity studies strengthen the ability of clinicians to select criterion-referenced assessments that support valid decisions.

Development of an ultra-short measure of eight domains of health-related quality of life for research and clinical care: the patient-reported outcomes measurement information system® PROMIS®-16 profile.

We describe development of a short health-related quality of life measure, the patient-reported outcomes measurement information system® (PROMIS®)-16 Profile, which generates domain-specific scores for physical function, ability to participate in social roles and activities, anxiety, depression, sleep disturbance, pain interference, cognitive function, and fatigue. An empirical evaluation of 50 candidate PROMIS items and item pairs was conducted using data from a sample of 5775 respondents from Amazon's Mechanical Turk (MTurk). Results and item response theory information curves for a subset of item pairs were presented and discussed in a stakeholder meeting to narrow the candidate item sets. A survey of the stakeholders and 124 MTurk adults was conducted to solicit preferences among remaining candidate items and finalize the measure. Empirical evaluation showed minimal differences in basic descriptive statistics (e.g., means, correlations) and associations with the PROMIS-29 + 2 Profile, thus item pairs were further considered primarily based on item properties and content. Stakeholders discussed and identified subsets of candidate item pairs for six domains, and final item pairs were agreed upon for two domains. Final items were selected based on stakeholder and MTurk-respondent preferences. The PROMIS-16 profile generates eight domain scores with strong psychometric properties. The PROMIS-16 Profile provides an attractive brief measure of eight distinct domains of health-related quality of life, representing an ideal screening tool for clinical care, which can help clinicians quickly identify distinct areas of concern that may require further assessment and follow-up. Further research is needed to confirm and extend these findings.

Pembuatan Item Pertanyaan Mata Pelajaran Ekonomi SMA Kelas XI Mengacu pada Kurikulum Merdeka

This study aimed to analyze the question items of Economics subjects classically in order to develop question items for summative assessment, which refers to Kurikulum Merdeka. This research used development research which refers to the development research design from Sugiyono. The results showed that the question items produced had a range of varying levels of difficulty, difficult 49%, medium 30% and easy 21%. The discrimination index possessed by a set of items made was good as general, this was indicated by the proportion of discrimination index of most items or 66% usable, although the other 18 items of the question of 34% must be revised. The distractors in the items that have been created most or 74.3% are accepted, the rest others require revision and replacement.

Enhancing N-List Structure and Performance for Efficient Large Dataset Analysis

One of the main challenges in data-intensive sectors like scientific research, data mining, and machine learning is efficiently analyzing enormous datasets. A popular data structure in similarity search algorithms to speed up the retrieval of closest neighbors is the N-List. In this paper, a high-performance method for mining frequent item sets called EN-list is presented. It represents item sets using an N-list and finds frequently recurring item sets directly using an aset-enumeration search tree. Specifically, it drastically reduces the search field by applying the powerful pruning approach known as Children-Parent Equivalency pruning. We conducted extensive experiments to compare En-list against three state-of-the-art algorithms: Fin, PrePost, and DiffNodesets on four distinct real datasets. The experimental results show that EN-list is always the fastest approach across all datasets. Furthermore, EN-list shows good memory consumption performance, requiring less memory than DiffNodesets and PrePost methods and just slightly more than the Fin approach.

The Even Shorter Almost Perfect Scale: Psychometric Evaluation and Cross-National Implications for Psychological Outcomes

Short empirically-supported scales or individual items are preferred in comprehensive surveys, brief screeners, and experience sampling studies. To that end, we examined the Short Almost Perfect Scale (SAPS) to evaluate empirical support for the interchangeability of items to measure perfectionistic strivings (Standards) and perfectionistic concerns (Discrepancy). Based on a large and diverse sample (N = 1,103) and tests of tau-equivalence (equal factor loadings) for each respective set of items, Study 1 advanced a subset of SAPS items to measure Standards (2 items) and Discrepancy (3 items). Cross-sectional gender and race/ethnicity invariance were supported, and in structural equations analyses, the SAPS5 factors were significantly associated with depression, state anxiety, life satisfaction, and gratitude. Study 2 cross-validated Study 1 measurement and structural findings with a new U.S. sample (N = 803). The three items representing the Discrepancy (perfectionistic concerns) factor also were supported in a cross-national comparison between the U.S. sample and a scale development sample in New Zealand (N = 3,921). For the most part, across both studies and all analyses, the three Discrepancy items were empirically interchangeable indicators of perfectionistic concerns and comparably strong predictors of psychological outcomes, supporting their use in studies or other contexts with space or time restrictions for measurement.

Examining the Relationship Between Multiple Tests of Receptive Vocabulary.

Numerous tasks have been developed to measure receptive vocabulary, many of which were designed to be administered in person with a trained researcher or clinician. The purpose of the current study is to compare a common, in-person test of vocabulary with other vocabulary assessments that can be self-administered. Fifty-three participants completed the Peabody Picture Vocabulary Test (PPVT) via online video call to mimic in-person administration, as well as four additional fully automated, self-administered measures of receptive vocabulary. Participants also completed three control tasks that do not measure receptive vocabulary. Pearson correlations indicated moderate correlations among most of the receptive vocabulary measures (approximately r = .50-.70). As expected, the control tasks revealed only weak correlations to the vocabulary measures. However, subsets of items of the four self-administered measures of receptive vocabulary achieved high correlations with the PPVT (r > .80). These subsets were found through a repeated resampling approach. Measures of receptive vocabulary differ in which items are included and in the assessment task (e.g., lexical decision, picture matching, synonym matching). The results of the current study suggest that several self-administered tasks are able to achieve high correlations with the PPVT when a subset of items are scored, rather than the full set of items. These data provide evidence that subsets of items on one behavioral assessment can more highly correlate to another measure. In practical terms, these data demonstrate that self-administered, automated measures of receptive vocabulary can be used as reasonable substitutes of at least one test (PPVT) that requires human interaction. That several of the fully automated measures resulted in high correlations with the PPVT suggests that different tasks could be selected depending on the needs of the researcher. It is important to note the aim was not to establish clinical relevance of these measures, but establish whether researchers could use an experimental task of receptive vocabulary that probes a similar construct to what is captured by the PPVT, and use these measures of individual differences.