Random Probability Research Articles

Factors that impact the implementation of blockchain in logistics in the United Arab Emirates

This study investigates the factors influencing the implementation of blockchain in logistics in the United Arab Emirates (UAE), including security, privacy, end-user benefits, quality control, technology infrastructure, and lack of general awareness. A mixed-methods approach was used, with data collected through survey questionnaires and semi-structured interviews. The research targeted logisticians in the UAE's supply chain department, using random probability sampling and a sample size of 151 for surveys and using purposive sampling for recruiting 10 experts. Using SPSS 24.0, the Pearson Correlation analysis revealed a strong association between blockchain in logistics and IT infrastructure and awareness of blockchain in the UAE logistics sector. Exploratory factor analysis showed a significant difference towards the security of data in the implementation of blockchain in the logistics sector in the UAE. This research suggests that implementing blockchain technology in UAE logistics companies can enhance data security and quality control, influencing managers’ decisions positively and recommends prioritizing data security and quality control. The study's geographical context emphasizes its contribution in the research area showing the importance of considering cost, benefits, security, IT infrastructure ownership, and awareness aspects in the adoption of blockchain technology in supply chain management.

Alcohol dependence and motivations for alcohol consumption in nursing students

Introduction: alcohol dependence is a public health problem on which multiple groups of researchers have focused their attention since it mainly affects the young population, as it is the most consumed drug in the world due to its easy access, which makes it imperative to advance in the understanding of this phenomenon.Objective: to determine the dependence and relationship that exists with the motivation to consume alcohol in nursing students. Methods: non-experimental, quantitative, descriptive, and cross-sectional research, in a sample of 363 undergraduate nursing students from two university regions, using simple random probability sampling, applying the Alcohol Use Disorders Identification Questionnaire (AUDIT) and the translation of the Drinking Motives Questionnaire-Revised (DMQ-R). Results: 47,4 % were 21 to 23 years old, 62,3 % were from urban areas; the largest number of students consumed occasionally (62,2 %) and 20,1 % were abstinent (women were the most frequent drinkers). The 97,2 % are motivated to consume alcohol and 0,3 % are highly motivated. Conclusions: there is dependence to alcohol consumption related to motivation in nursing students (rs=,697, p=<0,01). Therefore, it is necessary to implement interventions in prevention and health promotion, to limit access to the substance or reduce their intake patterns

E-Learning and Students Academic Performance in Cameroon’s State Universities

Purpose: The advent of the COVID-19 pandemic significantly disrupted traditional modes of education delivery, leading to concerns about students' poor academic performance in Cameroon state universities. This study examines “E-learning and its effects on students' performances in Cameroonian state universities.” The research questions focus on the extent to which e-notes, e-assignment, e-collaboration, and video conferencing affect students' performance.
 Materials and Methods: The study adopted a descriptive survey design and employed a quantitative approach to collect and analyze data. A sample size of 310 master's students from the Faculty of Education in the University of Yaoundé 1 and University of Buea was selected through simple random probability sampling. The instrument for data collection adopted in this study was a structured questionnaire. Data was presented using tables and frequencies.
 Findings: The findings of the study on the effects of e-learning components, including e-notes, e-collaboration, e-assignments, and video conferencing, suggest positive impacts on students' performances. E-notes and lectures provided easy access to course materials and contributed to students' understanding, although some students still preferred traditional handwritten notes. E-collaboration enhanced learning experiences by promoting knowledge sharing and critical thinking, but challenges such as unequal participation and a preference for physical collaboration need to be addressed. While e-assignments facilitated timely submissions, most students did not believe they improved their performance compared to traditional methods, emphasizing the importance of effective feedback. Video conferencing-maintained classroom community and interaction, positively influencing students' attitudes, although its effect on academic performance was relatively low.
 Implications to Theory, Practice and Policy: The study recommends that educators and policymakers in Cameroon should design e-learning courses that are engaging and interactive, and provide support to students to ensure they are able to succeed in online environments. A balanced approach accommodating diverse learning preferences is also recommended, along with promoting effective e-collaboration practices and providing constructive feedback.

DESiRED — Dynamic, Enhanced, and Smart iRED: A P4-AQM with Deep Reinforcement Learning and In-band Network Telemetry

Active Queue Management (AQM) is a mechanism employed to alleviate transient congestion in network device buffers, such as routers and switches. Traditional AQM algorithms use fixed thresholds, like target delay or queue occupancy, to compute random packet drop probabilities. A very small target delay can increase packet losses and reduce link utilization, while a large target delay may increase queueing delays while lowering drop probability. Due to dynamic network traffic characteristics, where traffic fluctuations can lead to significant queue variations, maintaining a fixed threshold AQM may not suit all applications. Consequently, we explore the question: What is the ideal threshold (target delay) for AQMs? In this work, we introduce DESiRED (Dynamic, Enhanced, and Smart iRED), a P4-based AQM that leverages precise network feedback from In-band Network Telemetry (INT) to feed a Deep Reinforcement Learning (DRL) model. This model dynamically adjusts the target delay based on rewards that maximize application Quality of Service (QoS). We evaluate DESiRED in a realistic P4-based test environment running an MPEG-DASH service. Our findings demonstrate up to a 90x reduction in video stall and a 42x increase in high-resolution video playback quality when the target delay is adjusted dynamically by DESiRED.

Leveraging Scratchpad Memory in a Hierarchical Architecture for Multicore

This paper proposes a novel architecture for multi-core processors, tailored for high-performance parallel computing. The architecture is founded on the innovative notion that complex problems can be decomposed into three relatively independent sub-problems: data processing, data management, and data communication. It features a grid of small, programmable processing units intricately connected to their three neighbouring units, forming a physically scalable and fractal environment. With flexibility, modularity, and scalability as focal points, this architecture aims to address the anticipated real-time signal processing demands in future telecommunication and multimedia systems. One notable aspect of the proposed architecture is its direct support for object-oriented features at the hardware level. Adopting a hybrid approach with Scratchpad Memory (SPM) combined with Cache in the on-chip memory hierarchy enhances performance and adaptability for sophisticated multi-core applications. The study highlights SPM management and introduces a dynamic data management framework. Unlike traditional SPM allocation methods relying on compiler or profiling knowledge, the proposed approach leverages random sampling and probability theory to predict hot-access data during runtime. This dynamic memory access pattern guides SPM allocation, ensuring optimal utilization of SPM's advantages in access speed and energy consumption, complemented by hardware support from DataUnit. This paper presents a paradigm shift in multi-core processor architecture, offering advanced features to meet the evolving requirements of parallel computing, making it well-suited for future telecommunication and multimedia systems. This paper introduces a revolutionary multicore processor architecture designed for high-performance parallel computing. The foundation of the proposed architecture lies in the innovative concept that complex problems can be decomposed into three relatively independent sub-problems: data processing, data management, and data communication. The architecture features a grid of small, programmable processing units, each intricately connected to its three neighboring units, forming a physically scalable and fractal environment. With a focus on flexibility, modularity, and scalability, this architecture addresses the real-time signal processing demands anticipated in future telecommunication and multimedia systems. One distinctive aspect of the proposed architecture is its direct support for object-oriented features at the hardware level. The on-chip memory hierarchy adopts a hybrid approach with Scratchpad Memory (SPM) combined with Cache, enhancing performance and adaptability for sophisticated multi-core applications. The study emphasizes SPM management and introduces a dynamic data management framework. In contrast to traditional SPM allocation methods relying on compiler or profiling knowledge, the proposed approach leverages random sampling and probability theory to predict hot-access data during runtime. This dynamic memory access pattern guides SPM allocation, ensuring optimal utilization of SPM's advantages in access speed and energy consumption, complemented by hardware support from DataUnit. This paper presents a paradigm shift in multicore processor architecture, offering advanced features to meet the evolving requirements of parallel computing, making it well-suited for future telecommunication and multimedia systems

Investigation of environmental and health impacts solid waste management problems and associated factors in Asella town, Ethiopia

Solid wastes are substances thrown away by the institutions of individual households in the urban community. The solid waste management practice in Asella town was inappropriate caused environmental pollution and exposed different urban health difficulties. The main objective was to determine the environmental and health impacts of solid waste management problems and associated factors in Asella town. Data collection was carried out through a house-to-house community survey process with a method of cross-sectional study design. A total sample size of 418 households was selected and implemented a simple random and systematic probability sampling technique. The statistical analysis of the binary logistic regression model was used to perform the correlational test about health issues in Asella town.The environmental impact assessment indicators were 13.4% soil pollution, 31.6% air pollution, 20.8% environmental deterioration, and 34.2% water pollution. The health impact indicators were 49.5% respiratory diseases, 18.2% asthmatic (bronchitis) cases, 15.8% diarrheal diseases, 14.8% protozoan illnesses, and 1.7% cancer cases.The odds ratio of females AOR = 1.18; 95%, CI:0.48–2.89, educational districts of can't read and write AOR = 2.31: 95% CI = 0.48–11.1, primary cycle AOR = 2.32, 95% CI:0.58–9.21, Secondary cycle AOR = 2.19, 95% CI = 0.60–7.98, and tertiary cycle AOR = 4.98, 95% C1.06–23.46. the odds ratio of house ownership of government AOR = 2.95, 95% CI:0.54–16.14, private households AOR = 4.18, 95% CI:0.79–22.16 and rented house property AOR = 1.71, 95% CI:0.32–9.18. The odds ratio of income group of lower status AOR = 2.0, 95% CI:0.91–4.98, middle income AOR = 5.7, 95% CI: 0.73–44.53 and higher income AOR = 2.8, 95% CI:0.35–23.14. The odds ratio for sorting of solid waste AOR = 1.38, 95% CI:0.56–3.40, and reusing of solid waste AOR = 7.90, 95% CI:2.12–29.42. Thus, the odds ratio of reusing solid waste was statistically significant correlated factors that limit health issues in Asella town.Therefore, the inadequate solid waste management practice was a query for environmental and health impacts in Asella town. The principles of reusing, reducing, and recovering solid waste management practice must be supported by professional interventions and government policy.

Leisure Attitude, Self-Rated Health, and Psychological Well-Being in Older Adults: A Moderated Mediation Model.

A positive leisure attitude among older adults may have a beneficial effect on psychological well-being, both directly and indirectly by fostering a more positive perception of one's health. This paper presents a correlational design that explores associations among leisure attitude, self-rated health, and psychological well-being, and analyzes the potential moderating role of gender in these relationships. The sample was selected using simple random probability sampling (N= 409; 61.9% female; Mean age = 72.9; SD = 8.43¸ Range of age 53 to 93 years). Diverse sociodemographic information was collected, and leisure attitudes, self-perceived health, and psychological well-being (positive affect and emotional ties) were assessed. The results revealed a positive effect of leisure attitude on self-rated health and psychological well-being, with self-rated health fully mediating the association between the behavioral component of leisure attitude and psychological well-being. Furthermore, the moderating effect of gender on the relationship between self-rated health and psychological well-being was stronger among men. Positive cognitive and emotional perceptions of leisure among older adults seem to benefit psychological well-being and improve self-rated health, thereby contributing to healthy ageing.

운용 환경을 고려한 우발고장확률의 통계적 추정

운용 환경을 고려한 우발고장확률의 통계적 추정

Using the Moodle Platform in the English Reading Comprehension of Students at a Higher Education Military School

The use of virtual educational platforms has experienced a remarkable increase in the academic field, offering innovative tools that enhance the quality of teaching and the learning process. The objective of the research was to determine the influence of the use of the Moodle platform on the English reading comprehension of students in a higher education military school. The study was a basic, causal correlational, non-experimental, cross-sectional design. The population included 1.341 students from a military school in Lima, Peru, and the sample consisted of 300 students selected by random probability sampling. The results showed that the use of the Moodle platform has a regular performance (45.7%), while English reading comprehension is in process (39.7%). It was concluded that the use of the Moodle platform has a significant influence on English reading comprehension, being this influence high (Nagelkerke’s R2 = 0.808).

Population genetic analyses of Eastern Chinese Han nationality using ForenSeq™ DNA Signature Prep Kit.

Currently, the most commonly used method for human identification and kinship analysis in forensic genetics is the detection of length polymorphism in short tandem repeats (STRs) using polymerase chain reaction (PCR) and capillary electrophoresis (CE). However, numerous studies have shown that considerable sequence variations exist in the repeat and flanking regions of the STR loci, which cannot be identified by CE detection. Comparatively, massively parallel sequencing (MPS) technology can capture these sequence differences, thereby enhancing the identification capability of certain STRs. In this study, we used the ForenSeq™ DNA Signature Prep Kit to sequence 58 STRs and 94 individual identification SNPs (iiSNPs) in a sample of 220 unrelated individuals from the Eastern Chinese Han population. Our aim is to obtain MPS-based STR and SNP data, providing further evidence for the study of population genetics and forensic applications. The results showed that the MPS method, utilizing sequence information, identified a total of 486 alleles on autosomal STRs (A-STRs), 97 alleles on X-chromosome STRs (X-STRs), and 218 alleles on Y-chromosome STRs (Y-STRs). Compared with length polymorphism, we observed an increase of 260 alleles (157, 31, and 72 alleles on A-STRs, X-STRs, and Y-STRs, respectively) across 36 STRs. The most substantial increments were observed in DYF387S1 and DYS389II, with increases of 287.5% and 250%, respectively. The most increment in the number of alleles was found at DYF387S1 and DYS389II (287.5% and 250%, respectively). The length-based (LB) and sequence-based (SB) combined random match probability (RMP) of 27 A-STRs were 6.05E-31 and 1.53E-34, respectively. Furthermore, other forensic parameters such as total discrimination power (TDP), cumulative probability of exclusion of trios (CPEtrio), and duos (CPEduo) were significantly improved when using the SB data, and informative data were obtained for the 94 iiSNPs. Collectively, these findings highlight the advantages of MPS technology in forensic genetics, and the Eastern Chinese Han genetic data generated in this study could be used as a valuable reference for future research in this field.

PENGARUH TIME DEMAND OF WORK,WORK LIFE BALANCE DAN TURNOVER INTENTION TERHADAP PRODUKTIVITAS KERJA KARYAWAN DI PT PINNACEL APPAREL UNIT 3

Productivity and human resources have an important role for the progress of the company. Because all production activities of the enterprise are strongly influenced by labor in product production (output). The many demands and pressures given by the company to employees where there is continuous work coercion which results in employees feeling their lives are only for work and their personal lives are sidelined so as to make employees stressed or depressed which can hinder work which can hinder the achievement of productivity. So this study aims to determine the effect of Time demand of work, work life balance, Turnover intention on employee work productivity special study of the sewing section at PT. Pinnacel Apparel Unit 3. This study uses a sampling technique in this study conducted by simple random sampling technique probability sampling. Methods of data collection using a questionnaire. The sample in this research is 112 respondents. The analysis technique used is validity test, reliability test, simple and multiple correlation test, simple and multiple regression test, coefficient of determination test and hypothesis test (t test and F test) through SPSS software. The results of the analysis show that the time demand of work variable has an effect on work productivity, with the results obtained that the t count (4.422) > t table (1.982) and a significant level of 0.000 t table (1.982) and a significant value of 0.000 < (1.982) and a significant value of 0.485 > 0.05. This shows that there is no significant effect of turnover intention on work productivity. The results of the study simultaneously obtained a calculated F value (66.952) > F table (3.08) and a significant value of 0.000 <0.05 meaning that the time demand of work, work life balance, and turnover intention variables simultaneously have a positive and significant effect on productivity Work.

Multi-Objective Dynamic Reconstruction of Distributed Energy Distribution Networks Based on Stochastic Probability Models and Optimized Beetle Antennae Search

In the dynamic optimization problem of the distribution network, a dynamic reconstruction method based on a stochastic probability model and optimized beetle antennae search is proposed. By implementing dynamic reconstruction of distributed energy distribution networks, the dynamic regulation and optimization capabilities of the distribution network can be improved. In this study, a random probability model is used to describe the uncertainty in the power grid. The beetle antennae search is used for dynamic multi-objective optimization. The performance of the beetle antennae search is improved by combining it with the simulated annealing algorithm. According to the results, the optimization success rate of the model was 98.7%. Compared with the discrete binary particle swarm optimization algorithm and bacterial foraging optimization algorithm, it was 9.3% and 26.1% faster, respectively. For practical applications, this model could effectively reduce power grid transmission losses, with a reduction range of 16.7–18.6%. Meanwhile, the charging and discharging loads were effectively reduced, with a reduction range of 16.2–19.7%. Therefore, this method has significant optimization effects on actual power grid operation. This research achievement contributes to the further development of dynamic reconstruction technology for distribution networks, improving the operational efficiency and stability of the power grid. This has important practical significance for achieving green and intelligent operation of the power system.

The one-sayers model for the Extended Crosswise design

Abstract The Extended Crosswise design is a randomized response design characterized by a sensitive and an innocuous question and two sub-samples with complementary randomization probabilities of the innocuous question. The response categories are ‘One’ with two different answers and ‘Two’ with two answers that are the same. Due to the complementary randomization probabilities, ‘One’ is the incriminating response in one sub-sample, and ‘Two’ in the other. The use of two sub-samples generates a degree of freedom to test for response biases with a goodness-of-fit test, but this test is unable to detect bias resulting from self-protective respondents giving the non-incriminating response when the incriminating response was required. This raises the question what a significant goodness-of-fit test measures? In this paper, we hypothesize that respondents are largely unaware which response is associated with the sensitive characteristic, and intuitively perceive ‘One’ as the safer response. We present empirical evidence for one-saying in six surveys among a total of 4,242 elite athletes, and present estimates of doping use corrected for it. Furthermore, logistic regression analyses are conducted to test the hypothesis that respondents who complete the survey in a short time are more likely to answer randomly, and therefore are less likely to be one-sayers.

Note on the density of ISE and a related diffusion

The integrated super-Brownian excursion (ISE) is the occupation measure of the spatial component of the head of the Brownian snake with lifetime process the normalized Brownian excursion. It is a random probability measure on \mathbb{R} , and it is known to describe the continuum limit of the distribution of labels in various models of random discrete labelled trees. We show that f_{\mathrm{ISE}} , its (random) density, has almost surely a derivative f'_{\mathrm{ISE}} which is continuous and (\frac{1}{2}-\varepsilon) -Hölder for any \varepsilon >0 but for no \varepsilon<0 (proving a conjecture of Bousquet-Mélou and Janson). We conjecture that f_{\mathrm{ISE}} can be represented as a second-order diffusion of the form df'_{\mathrm{ISE}}(t) ={2}\sqrt{f_{\mathrm{ISE}}(t)}\, dB_{t} + g\bigg(f'_{\mathrm{ISE}}(t), f_{\mathrm{ISE}}(t),\int_{-\infty}^{t} f_{\mathrm{ISE}}(s)\,ds\bigg)dt, for some continuous function g , for t>0 , and we give a number of remarks and questions in that direction. The proof of regularity is based on a moment estimate coming from a discrete model of trees, while the heuristic of the diffusion comes from an analogous statement in the discrete setting, which is a reformulation of explicit product formulas of Bousquet-Mélou and the first author (2012).

Uncertainty directed factorial clinical trials.

The development and evaluation of novel treatment combinations is a key component of modern clinical research. The primary goals of factorial clinical trials of treatment combinations range from the estimation of intervention-specific effects, or the discovery of potential synergies, to the identification of combinations with the highest response probabilities. Most factorial studies use balanced or block randomization, with an equal number of patients assigned to each treatment combination, irrespective of the specific goals of the trial. Here, we introduce a class of Bayesian response-adaptive designs for factorial clinical trials with binary outcomes. The study design was developed using Bayesian decision-theoretic arguments and adapts the randomization probabilities to treatment combinations during the enrollment period based on the available data. Our approach enables the investigator to specify a utility function representative of the aims of the trial, and the Bayesian response-adaptive randomization algorithm aims to maximize this utility function. We considered several utility functions and factorial designs tailored to them. Then, we conducted a comparative simulation study to illustrate relevant differences of key operating characteristics across the resulting designs. We also investigated the asymptotic behavior of the proposed adaptive designs. We also used data summaries from three recent factorial trials in perioperative care, smoking cessation, and infectious disease prevention to define realistic simulation scenarios and illustrate advantages of the introduced trial designs compared to other study designs.

COVID-19 and Mental Health in Ohio: Trends from 2017 to 2021

Background: Mental health impairment (MHI) refers to a high threshold of mental health diagnosis, whereby individuals are unable to participate in work or other usual activities due to a mental health condition or emotional problem. This study aimed to estimate COVID-19-related trends and disparities in high MHI for Ohio adults throughout the COVID-19 pandemic. An additional goal was to identify modifiable factors associated with high MHI.Methods: Analyses were conducted using data from the 2017, 2019, and 2021 Ohio Medicaid Assessment Survey (OMAS). This a repeated, cross-sectional random probability survey of noninstitutionalized adults assessing the health of residential Ohioans, with a concentration on Ohio’s Medicaid, potentially Medicaid eligible, and non-Medicaid populations.Results: The prevalence of high MHI among Ohio adults rose between 2017 (6.4%) and 2021 (8.2%). This increase was particularly pronounced among Black and Hispanic individuals; 2021 also saw high MHI among young women. In adjusted analysis, indicators of low fiscal stability and having unmet health care needs were associated with greater prevalence of high MHI.Conclusion: Pandemic-related mental health trends and disparities extended to those at the highest levels of mental illness severity and treatment need. Several modifiable factors could be targeted to potentially improve mental health symptoms and to be better prepared for the next public health crisis.

The effect of 1% tropicamide on central corneal thickness and intraocular pressure

Background: Dilating the eye with tropicamide may alter the intraocular pressure (IOP) because of an obstruction of the iridocorneal angle, resulting in decreased aqueous outflow drainage. Also, the repeated application of eyedrops and instrumentation could lead to increased central corneal thickness (CCT), consequently affecting IOP.Aim: This study aimed to determine the effect of 1% tropicamide on CCT and IOP post-mydriasis among the University of Limpopo optometry students.Setting: The data were collected at the optometry clinic of the University of Limpopo.Methods: A within-subject experimental study was conducted on 59 healthy subjects aged 18 years – 28 years. A computer assisted simple random probability sampling was used to identify a sample of participants from the study population (N = 200). Baseline and post-mydriasis IOP (20 min, 30 min, and 45 min intervals) were measured with a Goldmann applanation tonometer. Central corneal thickness and IOP were analysed using means, correlations and paired t-tests.Results: The mean CCT pre-mydriasis was 504.68 μm, and post-dilation was 507.90 μm, 510.08 μm and 509.25 μm at 20 min, 30 min, and 45 min, P = 026, p = 0.033, P = 0.004, respectively. Moreover, the mean IOP pre-mydriasis was 15.97 mmHg, and post-dilation was 16.85 mmHg, 16.46 mmHg and 16.85 mmHg over 20 min, 30 min, and 45 min of followed-up time, p = 0.140, p = 0.432, and p = 0.183, respectively.Conclusion: Measuring IOP post-dilation is still valid; however, CCT should be measured before the instillation of tropicamide.Contribution: This study analysed the effect of 1% tropicamide on CCT and IOP post-mydriasis in a clinical South African context.

THE INFLUENCE OF HEALTH EDUCATION ON ATTITUDES IN PREVENTING HIV/AIDS TRANSMISSION IN ADOLESCENTS

These days, pre-sexual conduct stemming from promiscuity has become the norm for youths. Teens are more likely to be infected with HIV/AIDS and other STDs due to their lack of awareness of potential risks associated with sexual activity. The purpose of this study is to determine how health education affects teenagers' perspectives on stopping the spread of HIV/AIDS. This study was carried out at SMAS Riyadlul Jannah using a quasi-experimental one-group pre-post test design with quantitative research. In total, 74 persons were selected utilizing proportionate stratified random sampling and probability sampling procedures, with the study's population consisting of 286 students at SMAS Riyadlul Jannah. The Paired T Test is used to examine the primary data for the study, which was gathered through a questionnaire. The results of the research indicated that teens' excitement for stopping the spread of HIV/AIDS was influenced by health education (Pvalue=0.000). Teenagers' attitudes ranged from 59.51 to 78.24 on average before receiving health education to after receiving it. The goal of health education is to help people maintain and improve their own health by giving them the knowledge, attitudes, and practices they need

Incorporating participants' welfare into sequential multiple assignment randomized trials.

Dynamic treatment regimes (DTRs) are sequences of decision rules that recommend treatments based on patients' time-varying clinical conditions. The sequential, multiple assignment, randomized trial (SMART) is an experimental design that can provide high-quality evidence for constructing optimal DTRs. In a conventional SMART, participants are randomized to available treatments at multiple stages with balanced randomization probabilities. Despite its relative simplicity of implementation and desirable performance in comparing embedded DTRs, the conventional SMART faces inevitable ethical issues, including assigning many participants to the empirically inferior treatment or the treatment they dislike, which might slow down the recruitment procedure and lead to higher attrition rates, ultimately leading to poor internal and external validities of the trial results. In this context, we propose a SMART under the Experiment-as-Market framework (SMART-EXAM), a novel SMART design that holds the potential to improve participants' welfare by incorporating their preferences and predicted treatment effects into the randomization procedure. We describe the steps of conducting a SMART-EXAM and evaluate its performance compared to the conventional SMART. The results indicate that the SMART-EXAM can improve the welfare of the participants enrolled in the trial, while also achieving a desirable ability to construct an optimal DTR when the experimental parameters are suitably specified. We finally illustrate the practical potential of the SMART-EXAM design using data from a SMART for children with attention-deficit/hyperactivity disorder.

Validation and normative data on the Revised Child Anxiety and Depression Scale RCADS‐25 in a Swedish national probability sample of children and adolescents aged 4–17 years

AbstractBackgroundMental health problems among children and adolescents are a growing public health concern. Self‐report questionnaires are pivotal for screening and early detection of mental health issues. We evaluate the psychometric properties and provide norm data of the 25‐item child and 25‐item parent‐report versions of the Revised Child Anxiety and Depression Scale (RCADS).MethodsA random probability sample of 29,000 children and adolescents (ages 4–17) from the Swedish population registry was invited. Data collection occurred from September 2021 to January 2022, accompanied by one postal and four SMS reminders.ResultsParticipants (N = 7045, 48.98% girls) demonstrate that the RCADS‐25 possesses relatively sound psychometric properties, albeit that the child‐report version assessed with children and adolescents aged 8 to 17 years rendered relatively better psychometric properties (e.g., ω = 0.87–0.92, CFI = 0.89) compared with the parent‐report version and the children 4 to 7 years old (e.g., ω = 0.72–0.82, CFI = 0.84).ConclusionThe RCADS‐25 instruments may be used as an effective instrument for the initial assessment of anxiety and depression in children and adolescents in Sweden.