Measurement Tools Research Articles

Psychometric evaluation of the Chinese version of the Scale of Effects of Social Media on Eating Behaviour and research of its influencing factors

BackgroundSocial media has become an indispensable part of contemporary young people's lives, and the influence of social media on college students' eating and other health-related behaviors has become increasingly prominent. However, there is no assessment tool to determine the effects of social media on Chinese college students' eating behavior. This study aims to translate the Scale of Effects of Social Media on Eating Behaviour (SESMEB) into Chinese. Its applicability to Chinese college students was examined through reliability and validity indexes, and the influencing factors of SESMEB were explored.MethodsThe questionnaire survey included 2374 Chinese college students. The Brislin translation model was used to translate the original scale into Chinese. Exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) were used to test the construct validity of the scale, and the content validity of the scale was assessed through the content validity index. The internal consistency of the scale was assessed by calculating Cronbach's alpha coefficient, McDonald's Omega coefficient, split-half reliability, and test–retest reliability. Multiple stepwise linear regression analysis was performed to identify potential influences on the effects of social media on eating behavior.ResultsEFA supported the one-factor structure, and the factor loadings of each item on this dimension were higher than 0.40. CFA showed good model fitness indexes. The content validity index of the scale was 0.94. The Cronbach's alpha coefficient and McDonald's Omega coefficient for the scale were 0.964, the split-half reliability coefficient was 0.953, and the test–retest reliability was 0.849. Gender, education, major, frequency of social media use, online sexual objectification experiences, fear of negative evaluations, and physical appearance perfectionism explained 73.8% of the variance in the effects of social media on eating behavior.ConclusionsThe Chinese version of the SESMEB has good psychometric properties and is a valid measurement tool for assessing the effects of social media on college students' eating behavior. Subjects who were female, highly educated, non-medical, had frequent social media use, online sexual objectification experiences, fear of negative evaluations, and physical appearance perfectionism used social media to have a higher impact on eating behavior.

Dynamic test of the continuously variable weak force by a torsion pendulum with pre-applied stress

High-precision, continuously variable weak force testing is required for high-precision drag-free control with micro-thrust of spacecrafts, which is a key technology for space gravitational wave detection programs, such as TianQin, LISA, and Taiji. The continuously variable micro-thrust range is 0.1∼100μN, and the noise is below 0.1 μNHz−1/2 from 10−4Hz to 1 Hz. The torsion pendulum is considered as the most classical weak force measurement tool. However, the large response of non-sensitive modes makes it unsuitable for dynamic weak force measurements. In this study, a dynamic test system is developed for continuously varying weak forces using a torsion pendulum. We pre-applied a stress to the torsion pendulum using a double wire structure, which can effectively reduce the interference of other modes, and used feedback control to improve the stability. The evaluation results obtained using the external continuously variable electrostatic force indicate that the measurement range of the system covers 100 μN, the response time is approximately 1.6 s, and the noise is below 0.1 μNHz−1/2 from 0.9×10−4Hz to 1.4 Hz, which can meet the requirements of the micro-thrust test in space gravitational wave detection missions.

Why do people use Metaverse? A uses and gratification theory perspective

In recent years, continued advancements in 5G and other communications technologies, coupled with the disruptions in physical interactions brought about by the COVID-19 pandemic, have drawn global attention and capital to the metaverse. In this context, the present study was conducted with the aim of developing and validating multidimensional usage motivation factors that capture the unique properties of the metaverse. In addition to extensive literature research, a Delphi study was conducted with a group of 30 professionals to derive the initial items for metaverse usage motivation. Those items were then used to devise a questionnaire that was in turn administered to 1000 metaverse users. Exploratory and confirmatory factor analysis resulted in 13 items based on four factors: communication, experience of new worlds, self-expression, and economic activity. Both convergent and discriminant validity were verified between the factors. Finally, correlation analysis was used to verify the nomological validity of the scale. Metaverse usage motivation, when identified as described in this study, is expected to serve as a useful tool that can be measured more objectively than the existing concept of metaverse usage motivation, as the measurement tool described herein reflects the opinions of actual metaverse users and experts. It is also expected to be used in various contexts as a measurement variable in subsequent studies examining metaverse user usage behavior.

INVESTIGATION OF THE RELATIONSHIP BETWEEN PRE-SCHOOL TEACHERS' EPISTEMOLOGICAL BELIEFS AND SCIENCE ACTIVITY COMPETENCIES IN TERMS OF SOME VARIABLES

The aim of the study is to examine the epistemological beliefs of preschool teachers and their proficiency in science activities in terms of some variables, and also to investigate the relationship between their epistemological beliefs and their proficiency in science activities. The population of the study consists of 213 preschool teachers working in public schools affiliated to the Ministry of National Education in the province of Gaziantep in the 2021-2022 academic year. The "relational screening model", which is one of the quantitative research models, was used in the study. In the thesis study, in addition to the personal information form containing some demographic information, two scales, "Scale for Determining Preschool Teachers' Competence in Science Activities" and "Epistemological Beliefs Scale", were chosen as data collection tools and SPSS 26 package program was used in the analysis of the data obtained from the measurement tool. With this research, statistical answers were sought to the main problem question and sub-problem questions determined in the study. According to the results obtained from the data analysis of the research, it has been determined that preschool teachers have developed/mature epistemological beliefs and their proficiency in science activities in line with these beliefs is high. These results show that preschool teachers are more efficient and competent in putting science activities into action when they search for knowledge, investigate how knowledge is obtained, add and apply their own interpretations. In addition to these results, as a result of the regression analysis, it was determined that epistemological beliefs predicted and explained their proficiency in science activities.

Assessment of thermographic tools for the validation of physics-based models of an induction sealing process

Measure of temperature dynamics in induction sealing processes is of paramount importance for the validation of physics-based models. In this work, commonly used commercial tools for temperature measurements, such as thermocouples, pyrometers and thermal cameras, are benchmarked for the characterization of the temperature dynamics occurring in multilayer aluminum foil-based packaging material undergoing relatively fast (i.e., ×100 ms) induction heating transients.

Blind Calibration of Environmental Acoustics Measurements Using Smartphones.

Environmental noise control is a major health and social issue. Numerous environmental policies require local authorities to draw up noise maps to establish an inventory of the noise environment and then propose action plans to improve its quality. In general, these maps are produced using numerical simulations, which may not be sufficiently representative, for example, concerning the temporal dynamics of noise levels. Acoustic sensor measurements are also insufficient in terms of spatial coverage. More recently, an alternative approach has been proposed, consisting of using citizens as data producers by using smartphones as tools of geo-localized acoustic measurement. However, a lack of calibration of smartphones can generate a significant bias in the results obtained. Against the classical metrological principle that would aim to calibrate any sensor beforehand for physical measurement, some have proposed mass calibration procedures called "blind calibration". The method is based on the crossing of sensors in the same area at the same time, which are therefore supposed to observe the same phenomenon (i.e., measure the same value). The multiple crossings of a large number of sensors at the scale of a territory and the analysis of the relationships between sensors allow for the calibration of the set of sensors. In this article, we propose to adapt a blind calibration method to data from the NoiseCapture smartphone application. The method's behavior is then tested on NoiseCapture datasets for which information on the calibration values of some smartphones is already available.

Passive Cooling Performance in Vernakular Javanese Architecture

Through the development of passive design solutions, architecture has to deal with issues relating to the subject of the energy crisis and building comfort. Vernacular architecture contains design principles that optimize natural systems for the creation of habitable comfort. This needs to be proven through the study of natural design for thermal environments in vernacular architecture, especially in Joglo buildings. This paper aims to evaluate the performance of passive cooling in Javanese vernacular houses through observation techniques and field measurements. Passive cooling performance is limited to visually appropriate aspects of building elements as well as air temperature measurement results that fall within the comfortable temperature limit along with the magnitude of the decrease in air temperature in the building. Visual methods are used to determine the suitability of passive design parameters, while field measurements are carried out to assess comfort levels and air temperature reductions. The object of this research is Joglo House in Karangjati, Ngawi, East Java. The air temperature and humidity measurement tool used is the RC 4H Data Logger with a measurement duration of seventeen days. The results showed that the main elements of passive cooling based on visual observation techniques were orientation, roof volume and porous walls. Passive cooling performance results include two things, namely: first, the average air temperature (27.5°C) in the building is within the comfortable temperature limit; second, the rate of decrease in air temperature in buildings during the day reaches 3.3°C

The Future of Organic Cosmetics: AI-Enabled Sustainability

AI colour cosmetics applications emerged as an innovative solution to promote branded colour cosmetics and improve consumer decision making, primarily as a trial function. The purpose of this study is to investigate the factors that influence the adoption of AI colour cosmetics applications through the lens of social comparison theory. For promotion managers of cosmetic retailers and developers of AI colour cosmetics applications looking to promote and reach a large segment, managerial implications of this research are provided. Many leading retailers and cosmetic companies are adopting AI and machine learning technologies to better cater to their customers in the US by providing personalized products. The latest skin measurement tools allow for direct visualization and quantification of data, and as a result, there is great potential for further integration of machine learning in the cosmetics industry. With the aid of high- International Journal of Scientific Research in Engineering and Management (IJSREM) Volume: 08 Issue: 02 | February - 2024 SJIF Rating: 8.176 ISSN: 2582-3930 © 2024, IJSREM | www.ijsrem.com DOI: 10.55041/IJSREM28686 | Page 2 resolution visualization and IoT devices that can handle massive data flow, there is likely to be a significant impact on the industry in the future. It is expected that AI will become more prevalent in skin and cosmetics, facilitating age prediction, skin type assessment, and the development of analytical tools. As scientific and technological advancements continue, the use of artificial intelligence models is becoming more widespread. In cosmetic dermatology, artificial intelligence is being used in various new applications that are available to both patients and doctors. Patients now have greater control over their cosmetic care, thanks to the development of customizable skincare, augmented reality applications, and at-home skin analysis tools. Doctors are also utilizing artificial intelligence in innovative ways, including the creation of models for predicting treatment outcomes and instruments for comprehensive skin analysis. Further research is needed in areas such as robotically assisted treatments and automated energy-based therapy apparatuses. Artificial intelligence models in cosmetic dermatology are empowering patients to make more informed decisions about their skin care. Although AI has many benefits and applications, there are still areas where it needs to improve. Data protection and security must be a top priority. There is always a risk when relying on information provided by augmented reality platforms. We have seen recent examples of security breaches associated with such programs. Moreover, the outcomes produced by these applications may not always be reliable, and therefore, AI may not be entirely trustworthy. The skincare industry has experienced significant growth over the last decade, with a surge during the pandemic when the world became increasingly digital. Therefore, integrating AI into skincare is a promising concept. Keywords: Organic cosmetics, Sustainability, Artificial intelligence

New Viscometers for Measuring the Viscosity of Liquids

This article’s goal is to present a viscometer that makes use of a novel viscometry measurement technique. The post will also suggest brand-new vibration viscometers. The development of new viscometers has allowed for the continuous and instantaneous measurement of liquid viscosity. The viscosity can be precisely measured automatically using these viscometers, which are made for industrial application. These viscosity measurement tools can currently be applied to a number of different tasks, including the research of recently developed oil products, the choice of the best flow characteristics for different transfer situations, and the advancement and refinement of fuel preparation techniques.

Development of a Cr2AlC MAX phase/g-C3N4 composite-based electrochemical sensor for accurate cabotegravir determination in pharmaceutical and biological samples.

Ahighly sensitive electrochemical sensor is reportedthat employs a modified electrode for the precise measurement of cabotegravir, a potent anti-HIV drug. Cyclic voltammetry (CV), differential pulse voltammetry (DPV), and electrochemical impedance spectroscopy (EIS) were utilized for this purpose. Electrode modification involved the immobilization of Cr2AlC MAX phase/g-C3N4 onto a glassy carbon electrode (GCE) to enhance its electrocatalytic activity and selectivity for cabotegravir detection. Under the optimal experimental conditions, the working potential (vs. Ag/AgCl) was to 0.93V. The developed sensor exhibited a good linear relationship in the range 0.05µM to 9.34µM with a low limit of detection of 4.33nM, signifying its exceptional sensitivity. Additionally, it demonstrated successful cabotegravir detection in pharmaceutical formulations and biological samples, achieving an RSD below 3.0%. The recoveries fell within the range 97.7 to 102%, confirming the sensor's potential for real-sample applications. This innovative electrochemical sensor represents a significant advancement, providing a simple, reliable, and sensitive tool for the accurate measurement of cabotegravir. Its potential applications include optimizing drug dosages, monitoring treatment responses, and supporting the development of cabotegravir-based pharmaceutical products, thereby contributing to advancements in HIV therapy and prevention strategies.

Development of a novel clinimetric tool: PAtient Reported Disease Activity Index in Rheumatoid Arthritis (PARDAI-RA) by PANLAR, for the assessment of patients living with rheumatoid arthritis.

Clinical experience has shown that a single measure is not sufficient to assess disease activity in rheumatoid arthritis (RA). Various clinimetric tools are necessary to address the many clinical situations that can arise. In order to develop a comprehensive measurement tool, the Pan American League of Associations for Rheumatology searched for the most frequent measures of disease activity applied in RA by means of a semi-systematic review of the available literature. We found that the most frequently reported measures of disease activity were the 28-joint Disease Activity Score, C-reactive protein, and the erythrocyte sedimentation rate, followed by patient-reported measures of pain and stiffness and many other composite indices and patient-reported outcome measures. The most frequent physician-reported sign of disease was the swollen joint count, and the most frequently self-reported feature was the increase in disease activity or flares. In this article, we present a new clinimetric tool developed based on expert consensus and on data retrieved from our search. Disease activity can be better assessed by combining various data sources, such as clinical, laboratory, and self-reported outcomes. These variables were included in our novel clinimetric tool. Key Points • The goal of treatment of RA is to achieve the best possible control of inflammation, or even remission; therefore, disease management should include systematic and regular evaluation of inflammation and health status. • Clinimetric tools evaluate a series of variables (e.g., symptoms, functional capacity, disease severity, quality of life, disease progression) and can reveal substantial prognostic and therapeutic differences between patients. • Our clinimetric tool, which is based on a combination of data (e.g., clinical variables, laboratory results, PROMs), can play a relevant role in patient assessment and care.

False confessions among suspects in police custody: Implications of anxiety and perceived stress

Purpose: The purpose of the study was to examine the effect of anxiety and stress on false confessions among police suspects in custody.
 Design/Methodology/Approach: The study adopted an ex post facto design. Participants were one hundred and nine (N 109) suspects in custody at the State Criminal Investigation Department of Kaduna State Police Command, Kaduna State, Nigeria. The present study included three measurement tools to assess different constructs: The Gudjonsson Confession Questionnaire-Revised (GCQ-R) was utilized to evaluate false confession, the State-Trait Anxiety Inventory (STAI) was employed to assess anxiety levels, and the Perceived Stress Scale (PSS) was utilized to measure perceived stress.
 Findings: Results revealed that state anxiety positively predicted false confession (β =0.191, p < 0.05), whereas trait anxiety has no significant effect on false confession (β=- 0.050, p > 0.05), while perceived stress positively predicted false confession (β =0.273, p < 0.05).
 Conclusion: The study concluded that state anxiety and perceived stress contribute to a suspect’s predisposition to make a false confession. It was recommended that police officers be more cognizant of when and under what conditions they use interrogation methods in view of the level of anxiety and stress the suspect might be in.

Measurement Tool for The Influence of Sales Promotion, Utilitarian Motive, Self Esteem Motive, and Hedonic Motive on Purchase Decision with Impulse Buying and Behavior Intention as Variable Intervening in E-commerce XYZ

One proof of the ease of technology is the emergence of e-commerce. E-commerce is a medium that allows sellers and buyers to meet face-to-face. This research aims to provide a measurement tool to analyze the influence of sales promotion, utilitarian motive, self-esteem, and hedonic motive on purchasing decisions with impulse buying and behavioral intention as intervening variables. This research surveyed with the participation of 30 respondents who had purchased products through XYZ e-commerce Therefore, this measuring instrument meets the requirements and is acceptable for further research.

Western blotting: evolution of an old analytical method to a new quantitative tool for biomarker measurements.

Western blotting (WB) is a widely used laboratory technique for detecting specific proteins in biological matrices. Recent advances in antibody production, automation, gel and membrane manufacturingand highly sensitive detection platforms have transformed WB from a labor-intensive and qualitative method into a highly reproducible and quantitative assay suitable for biomarker detection. Despite these significant improvements in the capabilities and efficiency of WB, there remain challenges that hinder its widespread application as aresearch, diagnostic (in two-tiered assays like Lyme disease testing)and drug development tool. This article describesrecent innovations introduced to WB methodology and the remaining challenges that prevent its wider adoption for biomarker measurements throughout the drug development process.

Automated zooplankton size measurement using deep learning: Overcoming the limitations of traditional methods

Zooplankton size is a crucial indicator in marine ecosystems, reflecting demographic structure, species diversity and trophic status. Traditional methods for measuring zooplankton size, which involve direct sampling and microscopic analysis, are laborious and time-consuming. In situ imaging systems are useful sampling tools; however, the variation in angles, orientations, and image qualities presented considerable challenges to early machine learning models tasked with measuring sizes.. Our study introduces a novel, efficient, and precise deep learning-based method for zooplankton size measurement. This method employs a deep residual network with an adaptation: replacing the fully connected layer with a convolutional layer. This modification allows for the generation of an accurate predictive heat map for size determination. We validated this automated approach against manual sizing using ImageJ, employing in-situ images from the PlanktonScope. The focus was on three zooplankton groups: copepods, appendicularians, and shrimps. An analysis was conducted on 200 individuals from each of the three groups. Our automated method's performance was closely aligned with the manual process, demonstrating a minimal average discrepancy of just 1.84%. This significant advancement presents a rapid and reliable tool for zooplankton size measurement. By enhancing the capacity for immediate and informed ecosystem-based management decisions, our deep learning-based method addresses previous challenges and opens new avenues for research and monitoring in zooplankton.

The influence of perceived teacher support on online English learning engagement among Chinese university students: a cross-sectional study on the mediating effects of self-regulation.

This study examines the association between perceived teacher support and self-regulation in learning, and their combined relationship with online English learning engagement among university students in China. The objective is to uncover the underlying mechanisms of this relationship, with a particular focus on the role of self-regulation in learning as a mediator. The study involved 1,361 university students from Southwest China, predominantly female (73.84%) with an average age of 18.94 years (SD = 1.07). Refined measurement tools were employed to assess perceived teacher support, online English learning engagement, and self-regulation in learning. The findings indicate that components of self-regulation, such as goal setting, environmental structuring, and time management, act as full mediators in the relationship between perceived teacher support and online English learning engagement. This research underscores the importance of self-regulation in learning in linking perceived teacher support with online English learning engagement. The insights gained are crucial for enhancing teaching strategies in online English language education.

In Pursuit of Impact: How Psychological Contract Research Can Make the Work-World a Better Place

This paper is the result of the collective work undertaken by a group of Psychological Contract (PC) and Sustainability scholars from around the world, following the 2023 Bi-Annual PC Small Group Conference (Kedge Business School, Bordeaux, France). As part of the conference, scholars engaged in a workshop designed to generate expert guidance on how to aid the PC field to be better aligned with the needs of practice, and thus, impact the creation and maintenance of high-quality and sustainable exchange processes at work. In accordance with accreditation bodies for higher education, research impact is not limited to academic papers alone but also includes practitioners, policymakers, and students in its scope. This paper therefore incorporates elements from an impact measurement tool for higher education in management so as to explore how PC scholars can bolster the beneficial influence of PC knowledge on employment relationships through different stakeholders and means. Accordingly, our proposals for the pursuit of PC impact are organized in three parts: (1) research, (2) practice and society, and (3) students. Further, this paper contributes to the emerging debate on sustainable PCs by developing a construct definition and integrating PCs with an ‘ethics of care’ perspective.

Efficacy and safety of tongxinluo capsule for angina pectoris of coronary heart disease: an overview of systematic reviews and meta-analysis.

Tongxinluo capsule (TXLC) is a common drug for treating angina pectoris of coronary heart disease (CHD). In recent years, many systematic reviews (SRs) and meta-analyses (MAs) have reported the efficacy and safety of TXLC for improving angina symptoms in patients with CHD. We aimed to comprehensively evaluate the existing SRs and MAs of TXLC in treating angina pectoris of CHD, summarize the evidence quality, and provide scientific evidence and recommendations. We searched seven databases for relevant SRs/MAs published up to 1 June 2023. Two reviewers independently completed the literature retrieval, screening, and data extraction. We used A Measurement Tool to Assess Systematic Reviews 2 (AMSTAR 2) to evaluate the methodological quality, the Risk of Bias in Systematic Reviews (ROBIS) to assess the risk of bias, and the Grading of Recommendations Assessment, Development and Evaluation (GRADE) to determine the strength of the evidence. RevMan 5.3 was used to synthesize data. We identified 15 SRs/MAs, including 329 RCTs and 33,417 patients. According to the evaluation results of AMSTAR-2, only one SR was of high methodological quality, the others were very low. ROBIS assessment showed that one SR (6.67%) had a low risk, 3 SRs (20%) had an unclear risk, and 11 SRs (73.33%) had a high risk. We assessed 42 outcomes by the GRADE, 10 (23.81%) for moderate-quality evidence, 17 (40.48%) for low-quality evidence, and 15 (35.71%) for very-low-quality evidence. Mate-analysis showed that TXLC combined with conventional western medications improved electrocardiogram efficacy (RR = 1.38, 95% CI: 1.23-1.43, P < 0.001) and angina efficacy (OR = 3.58, 95% CI: 3.02-4.24, P < 0.001), reduced angina attack frequency (SMD = -0.54, 95% CI: -0.64 to -0.44, P < 0.001) and angina duration (SMD = -0.42, 95% CI: -0.57 to -0.28, P < 0.001), with general heterogeneity. The pooled results showed that TXLC appears to have some efficacy in improving cardiac function and relieving angina symptoms, but there is limited evidence that it improves cardiovascular event rates, hemorheology, lipids, or hs-CRP. In the assessment of drug safety, TXLC was associated with different degrees of adverse drug reactions. Based on the evidence, TXLC may be effective as an adjuvant treatment for angina pectoris of CHD. However, the quality of the evidence is low, and the drug's safety must be carefully interpreted. In future studies, high-quality randomized controlled trials are needed to confirm the effectiveness and safety of TXLC. http://www.crd.york.ac.uk/PROSPERO/, identifier (CRD42022365372).

A Critical Overview of the Construct of Supportive Care Need in the Cancer Literature: Definitions, Measures, Interventions and Future Directions for Research.

The growing amount of evidence about the role of supportive care in enhancing cancer patients' outcomes has made healthcare providers more sensitive to the need for support that they experience during cancer's trajectory. However, the lack of a consensus in the definition of supportive care and lack of uniformity in the theoretical paradigm and measurement tools for unmet needs does not allow for defined guidelines for evidence-based best practices that are universally accepted. Contemporary cancer literature confirms that patients continue to report high levels of unmet supportive care needs and documents the low effectiveness of most of the interventions proposed to date. The aim of this critical review is to consolidate the conceptual understanding of the need for supportive care, providing definitions, areas of expertise and a careful overview of the measurement tools and intervention proposals developed to date. The possible reasons why the currently developed interventions do not seem to be able to meet the needs, and the issues for future research were discussed.

Reliability Generalization Meta-Analysis of Seven Wisdom Self-Rating Scales From 2004 to 2023

Accurate measurement of wisdom is the cornerstone of wisdom research. To provide a representative reference for the reliability level and moderating factors of various wisdom self-rating scales, we carried out a reliability generalization meta-analysis of Chinese and English references retrieved from 2004 to 2023. A total of 149 articles were included, as well as seven wisdom self-rating scales. The results showed that all seven wisdom self-rating scales had good internal consistency reliability. The reliability of the original scale was higher than that of the simplified version, and the reliability of the total of the original scale was higher than those of each dimension. Future research should avoid “reliability introduction,” and rather focus on cross-cultural translation of the wisdom scale, selecting the most appropriate measurement tool for the particular field of wisdom, and strengthen theoretical interpretations by connotation and structure of wisdom itself.