Jurnal STAI Al-Hamidiyah
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Which Immigrants do Citizens Prefer? A Meta-Reanalysis of 100 Conjoint Experiments
No full textIn the last decade, an important literature in the social sciences has examined public attitudes toward immigrants in host societies. In it, a prominent experimental method---the conjoint design, where participants are tasked with rating or choosing between randomized profiles---has been used reliably to understand how immigrant characteristics shape admission preferences. We collate replication datasets from 100 individual studies spanning 1,475,403 immigrant profiles with 26 randomized attributes evaluated by 142,817 survey respondents from 36 countries. Meta-analyses reinforce well-established findings: economic, cultural, humanitarian, and procedural factors all influence evaluations. Meta-reanalyses show that preferences are broadly similar across countries and demographic groups. However, they also reveal two additional patterns: economic considerations have become more influential over time, and evaluations of individual immigrants differ sharply depending on where people stand on the broader immigration debate. These findings shed light on ongoing debates and point to fruitful areas for future research
The Impact of Contextual Factor and Need for Uniqueness on Sustainable Luxury Purchase Intention — An Integrated Model in an Emerging Market
No full textI would like to store the data of this study
Prediction-based Attention Computing: a proof of concept study
No full textRecent advancements in extended reality (XR) and data modelling present new opportunities for adaptive simulation solutions, which can measure and respond to individual neuropsychological states. However, questions remain about the optimal metrics for real-time data capture and the applicability of these solutions for enhancing user experiences. The present research examined a novel form of adaptive XR, called “prediction-based attention computing” (PbAC), which tailors simulations based on computational models of the brain and, thus, the dynamic sensorimotor processes theorised to underpin human perception and learning. Specifically, this study aimed to demonstrate whether PbAC can adaptively capture users’ internal state predictions and modulate associated neuropsychological responses. To test this, we used an XR-based racquetball paradigm, in which participants were tasked with intercepting virtual balls that emerged from different starting locations. For PbAC conditions, in-situ eye tracking data assessments were utilised to index participant’s prior beliefs and manipulate levels of expectedness (i.e., prediction error) on each trial. Various measures of predictive sensorimotor behaviour were then extracted and compared with data from probability-controlled and matched-order control conditions. Results showed that sensorimotor responses were affected by the expectedness of XR stimuli, and that clear, prediction-related biases emerged within PbAC conditions. The novel computing software also provoked marked surprisal responses on trials designed to elicit high levels of prediction error, and these surprisal effects were similar, or even greater than, those in our comparison conditions. Together, the findings provide proof of concept for PbAC and support its development within future research and technology innovations
A Comparison of Real and Hypothetical Computerized Delay Discounting Tasks with Matching Delay Durations and Reward Values in Typically Developing Adolescents
No full textDelay discounting (DD) tasks involve choosing between smaller immediate rewards and larger delayed rewards aiming to assess choice impulsivity, a typical behavior in adolescence. The predominant task types are 'hypothetical' (imagined delays and rewards) and 'real' (experienced delays and real rewards). Although often considered equivalent, these tasks frequently involve different delays and rewards. Hence, it is unclear whether they assess the same cognitive abilities. Our study aimed to cross-sectionally compare performance in 'hypothetical' and 'real' computerized DD tasks with matching delays and rewards across adolescence in 69 typically developing 9 to 18-year-olds. The dependent variable was DD scores, measured by the area under the curve (AUC) (higher AUC indicates lower impulsivity) with age as a continuous predictor. We found that the DD performance improved with age in the ‘real’ task, better described as a curvilinear than linear pattern that peaked between 14-17 years, possibly due to increased reward sensitivity. Performance on the 'hypothetical' task did not change with age and, overall, was higher, suggesting that adolescents, especially younger ones, overestimate their ability to wait for hypothetical rewards. Hence, in adolescents, 'hypothetical' and 'real' tasks lead to different results even when the delay duration and reward magnitudes are matched
Concept and use of the term clean label in the labeling of processed foods: a scoping review
No full textObjective: To identify and analyze the concepts and use of the term clean label in the scientific literature regarding the labeling of processed foods.
Introduction: Consumption of processed foods have increased in Brazil in recent decades (Louzada et al., 2023). Processed foods with higher amounts of industrial additives and ingredients are classified as ultra-processed (Monteiro et al., 2016) and their consumption is associated with the development of non-communicable chronic diseases (Lane et al., 2021; Louzada et al., 2021), obesity (Lane et al., 2021; Pagliai et al., 2021; Louzada et al., 2021; Askari et al., 2020), and all-cause mortality (Lane et al., 2021; Pagliai et al., 2021; Louzada et al., 2021). Consequently, consumers of these foods have demanded from manufacturers products considered more natural, organic (Guney; Sangun, 2021; Saraiva et al., 2020), less processed, without allergenic ingredients, and without industrial additives (Martinez-Pineda; Yague-Ruiz, 2022; Soon; Wahab, 2021). Food labels are the primary source of information for consumers (WHO, 2007) and should not contain information that may mislead or confuse consumers regarding the nature, composition, and quality of the food (Brazil, 2022). In Brazil, terms such as homemade, traditional, original, and other similar expressions have been used on labels of processed foods without regulation (Machado et al., 2018). Similarly, for the term clean label, there is currently no regulation or official definition in Brazil or worldwide. However, these terms seem to be used on labels of processed foods free from artificial additives, with organic ingredients (Cegielka, 2020; Asioli et al., 2017; Dolle; Carreno, 2020), with lists of simple ingredients and/or based on traditional recipes known to consumers (Cegielka, 2020; Asioli et al., 2017; Dolle; Carreno, 2020; Negowetti et al., 2021; Singh et al., 2021). It is noteworthy that there are still no studies proposing a standardized concept for the use of the term on labels of processed foods. Furthermore, no review studies were found that examined the use of the term in the formulation or labeling of packaged foods, as well as proposing a clean label concept.
Inclusion criteria: Quantitative and/or qualitative articles with primary and/or secondary data that: discuss some definition of clean label or criteria for the use of the term on labels of processed foods; or have evaluated the application of the concept or term clean label in the development or labeling of processed foods.
Methods: The search will be conducted using keywords related to the term "clean label" and "labeling of processed foods" and Boolean operators "AND" and "OR" in the databases PubMed/MEDLINE, Embase, FSTA - Food Science and Technology Abstracts, Scopus, Web of Science, The Cochrane Library, and Google Scholar. Article selection will follow the flowchart suggested by the PRISMA-ScR protocol, and data extraction will follow a table prepared by the authors
Abstract structural rules in novel meaning composition: Divergent learning strategies revealed by implicit and explicit measures
No full textThe ability to generalize previously learned knowledge to novel situations is fundamental for adaptive behavior, including interpreting unfamiliar compositional words. To investigate how people construct novel meanings based on structural rules, we developed a semi-artificial language paradigm that combines explicit meaning judgments with implicit semantic priming measures, allowing us to assess rule-based composition across multiple behavioral levels. Participants learned pseudo-words composed of known stems and unknown affixes, and were subsequently tested on novel combinations that required generalizing abstract structural rules. Across three behavioral experiments, we found reliable evidence for generalization on both implicit and explicit measures, yet these measures diverged in sensitivity. Critically, individuals differed in the degree to which they relied on the sequential order of word parts: Some employed a “building” strategy that integrated parts positionally, while others adopted a “mixing” strategy that ignored order. We further explored whether this variability could be explained by individual differences in stable trait factors. Together, this work offers a methodologically integrated approach for studying compositional meaning construction and provides an experimentally controlled paradigm suitable for future neuroimaging research on rule-based inference
A situational analysis of the adoption of oncology, inflammation, and supportive care biosimilars in the United States
No full textThis is a non-systematic review of the holistic impact of biosimilars in the U
Demographic Variation in Sense of Mastery Across 22 Countries: A Cross-National Analysis
No full textPrior research documents strong associations between an increased sense of mastery with improved health and well-being outcomes. However, less is known about how levels of mastery differ across cultures and across demographic groups within those different cultures. This study presents an in-depth, cross-national exploration of sense of mastery across cultures, and its variations across key demographic groups. Using a diverse and international dataset of approximately 200,000 individuals from 22 countries, we will examine relationships between sense of mastery and key demographics, including: age, gender, marital status, employment status, religious service attendance, education, and immigration status. Our descriptive results will also present the ordered means of sense of mastery across countries. We will be mindful of potential interpretation challenges due to varying cultural contexts and response scales used. Our work will illuminate the distributions and descriptive statistics of mastery across these demographic features, offer insight into country-specific variations in sense of mastery, and lay a valuable foundation for future investigations into sociocultural influences that might shape mastery
Reframing Medical Treatment: A Proposal for Harnessing Complexity and Drug Interactions for Improved Outcomes
No full textThis project proposes a new, holistic philosophy for medical treatment that leverages drug interactions and multi-target strategies to address the complexity of diseases. By reframing side effects as potential synergies and embracing an integrated approach to treatment, this model aims to improve patient outcomes in complex diseases like Alzheimer's.
The project provides a comprehensive overview of the traditional view of medical treatment, highlighting its limitations in addressing complex diseases. It then introduces the new philosophy, detailing its key innovations and providing a case study on Alzheimer's disease to illustrate its potential applications.
By challenging the status quo and encouraging a shift towards a more holistic and integrated approach, this project aims to stimulate further research and discussion on how to optimize medical treatment for the benefit of patients