Size Estimation Research Articles

Estimating the Effective Size of European Wolf Populations.

Molecular methods are routinely used to estimate the effective size of populations (N e). However, underlying model assumptions are frequently violated to an unknown extent. Although simulations can detect sources of bias and help to adjust sampling strategies and analyses methods, additional information from empirical data can also be used to calibrate methods and improve molecular N e estimation methods. Here, we take advantage of long-term genetic and ecological monitoring data of the grey wolf (Canis lupus) in Germany, and detailed population genetic studies in Poland, Spain and Portugal to improve N e estimation strategies in this species, and species with similar life history traits. We first calculated N e from average lifetime reproductive success and detailed census data from the German population, which served as a baseline to compare to molecular estimates based on linkage disequilibrium and sibship frequency. This yielded a robust N e/N c estimation that we used to calibrate molecular estimates of German, Polish and Iberian wolf populations. The linkage disequilibrium method was strongly influenced by spatial genetic structure, much more than the sibship frequency method. When N e was estimated in local neighbourhoods, both methods yielded comparable results. Estimates of the metapopulation effective size seemed to correspond generally well with the sum of the estimates of local neighbourhoods. Overall, we found that the number of packs is a good proxy of the effective population size. Using this as a rule of thumb, we evaluated for all European wolf populations the N e 500 indicator and concluded that half of the European wolf populations do not yet fulfil this criterion.

Airborne ultrafine particle concentrations and brain cancer incidence in Canada’s two largest cities

BackgroundMalignant brain tumours are rare, but are important to study because survival rates are low and few modifiable risk factors have been identified. Existing evidence suggests that outdoor ultrafine particles (UFPs) (particulate matter < 100 nm, sometimes referred to as nanoparticles) can deposit in the brain and could encourage initiation and progression of cancerous tumours, but epidemiological data are limited. MethodsHigh-resolution estimates of outdoor UFP concentrations and size were linked to residential locations of approximately 1.5 million people in Montreal and Toronto, Canada from 2001 to 2015. Cox proportional hazards models were used to estimate associations between annual average outdoor UFPs and malignant brain tumour incidence while adjusting for potential confounding factors including other outdoor air pollutants. FindingsIn total, 1400 incident brain tumour cases occurred during follow-up. Consistent positive associations were observed between long-term exposures to outdoor UFPs and brain tumour incidence with increased risk ranging from 10.5% (95% CI: −1.4, 24.0%) to 15.3% (95% CI: 0.4, 32.5%) per 10,000 particle/cm3 increase. Long-term exposures to oxidant gases, black carbon, or fine particulate matter (PM2.5) were not associated with increased brain tumour incidence. InterpretationOur results suggest that long-term exposures to outdoor UFPs are associated with an increased risk of developing malignant brain tumours. On an absolute scale, the magnitude of this risk translates into approximately 24 additional cases per year per 10,000 particle/cm3 increase in annual average outdoor UFPs in a hypothetical city of 3-million people. FundingCanadian Institutes of Health Research (CIHR) Foundation Grant and The United States Health Effects Institute (HEI).

Effects of Aerobic Exercise on Vascular Wall Thickness: A Meta-Analysis of Pre-Clinical Trials on Rat Model.

Exercise instigates adaptations in structural as well as functional organisation of the body at tissue and organ levels. However, the effect of exercise on vascular wall morphology is still under investigation. The objective of the review is to provide a meta-analysis of data from the previously published research to provide compiled analysis to determine the effect of exercise on the thickness of large-sized vessel walls. This meta-analysis was executed at the Ziauddin College of Rehabilitation Sciences with an extensive literature search using databases and search engines such as Pubmed, CINAHL, Web of Science, Scopus, and Google Scholar between September 2022 and January 2023. Studies were appraised according to an estimate of mean difference and pooled effect size was calculated using a random effect model. The risk of bias was also calculated using SYRCLE's risk of bias tool and CAMARADES. Overall, five eligible pre-clinical trials using rat models with pertinent data to determine the effect of exercise on vessel wall thickness were included in the meta-analysis. The results showed that aerobic exercise significantly reduced the vessel wall thickness (SMD -0.854 5%; CI: -1.365 to -0.344; p <0.001). Moreover, no significant publication bias was found through funnel plot and statistical test (Egger's p = 0.276; Begg's p = 0.624). However, an extensive review of the literature currently available on the topic has shown mixed findings that are consistent with the study and vice versa. Therefore, it indicated the need for sub-group analysis with different types of exercises for more peculiar clinical approaches. Key Words: Morphometry, Animal studies meta-analysis, Media thickness, Physical activity, Vascular morphology.

Semi-empirical supported, Ab initio derived thermodynamic properties for ClO2 and its sub and extended species, applied in water treatment cycles

This paper describes a group of sixty (60) sub and extended chlorine oxide species with the general formulae of ClxOy (with x ≤ 2, y ≤ 8). Their role in water treatment cycles, behaving as key reactive species, is represented by a complex sequence of chemical inter-dependencies, exposed as a cohesive set of chemical reactions to demonstrate their cyclic role in aqueous media. An empirical/semi-empirical computational approach, supported by Ab Initio simulations, in accordance with open-shell character, has been followed to determine their optimum molecular geometries, to obtain their thermochemical properties. Besides a single molecular analysis, Grand Canonical Ensemble simulations, supported by a revised library of force field parameters, constituted a core component of the computational approach and proved to be invaluable in confirming thermochemical properties. This approach also offered finite estimates of optimum model sizes, a benefit with wider modelling application. Extended molecular species of ClO2 display a complex sequence of bonding character, with a variable charge dissipation (reported as partial charges), which complicates selection of basis sets in optimizing molecular geometries, during Ab Initio analyses.Optimum molecular geometries were obtained using Gaussian and MOPAC, which in turn resulted in reliable Heats of Formation. These correlated well with energies extracted from the open literature. Thermodynamic Analysis of the reaction of selected chlorine oxides with water using FactSage, predicted the production of known and two previously undetected chlorine species, [ClO4]- and [ClOH2]+.

On the low-latitude ionospheric irregularities under geomagnetically active and quiet conditions using NavIC observables: A spectral analysis approach

Ionospheric irregularities and associated scintillations under geomagnetically active/quiet conditions have detrimental effects on the reliability and performance of space- and ground-based navigation satellite systems, especially over the low-latitude region. The current work investigates the low-latitude ionospheric irregularities using the phase screen theory and the corresponding temporal Power Spectral Density (PSD) analysis to present an estimate of the outer irregularity scale sizes over these locations. The study uses simultaneous L5 signal C/No observations of NavIC (a set of GEO and GSO navigation satellite systems) near the northern crest of EIA (Indore: 22.52∘N, 75.92∘E, dip: 32.23∘N) and in between the crest and the dip equator (Hyderabad: 17.42∘N, 78.55∘E, dip: 21.69∘N). The study period (2017–2018) covers disturbed and quiet-time conditions in the declining phase of the solar cycle 24. The PSD analysis brings forward the presence of irregularities, of the order of a few hundred meters during weak-to-moderate and quiet-time conditions and up to a few km during the strong event, over both locations. The ROTI values validate the presence of such structures in the Indian region. Furthermore, only for the strong event, a time delay of scintillation occurrence over Indore, with values of 36 min and 50 min for NavIC satellites (PRNs) 5 and 6, respectively, from scintillation occurrence at Hyderabad is observed, suggesting a poleward evolution of irregularity structures. Further observations show a westward propagation of these structures on this day. This study brings forward the advantage of utilizing continuous data from the GEO and GSO satellite systems in understanding the evolution and propagation of the ionospheric irregularities over the low-latitude region.

Understanding p-values and significance.

P-values combined with estimates of effect size are used to assess the importance of experimental results. However, their interpretation can be invalidated by selection bias when testing multiple hypotheses, fitting multiple models or even informally selecting results that seem interesting after observing the data. We offer an introduction to principled uses of p-values (targeted at the non-specialist) and identify questionable practices to be avoided.

Comparison of Neighborhood Disadvantage Indices on Emergency Medical Services Interventions and Outcomes for Pediatric Out-of-Hospital Emergencies

ObjectiveMeasures of neighborhood disadvantage demonstrate correlations to health outcomes in children. We compared differing indices of neighborhood disadvantage with emergency medical services (EMS) interventions in children. MethodsWe performed a retrospective study of EMS encounters for children (<18 years) from approximately 2000 US EMS agencies between 2021 and 2022. Our exposures were the Child Opportunity Index (COI; v2.0), 2021 Area Deprivation Index (ADI), and 2018 Social Vulnerability Index (SVI). We evaluated the agreement in how children were classified with each index using the intraclass correlation coefficient. We used logistic regression to evaluate the association of each index with transport status, presence of cardiac arrest, and condition-specific interventions and assessments. ResultsWe included 738,892 encounters. The correlation between the indices indicated good agreement (intraclass correlation coefficient=0.75). There was overlap in relationships between the COI, ADI, and SVI for each of the study outcomes, both when visualized as a splined predictor and when using representative odds ratios (OR) comparing the third quartile of each index to the lower quartile (most disadvantaged). For example, the OR of non-transport was 1.12 (95% confidence interval [CI]: 1.10–1.14) for COI, 1.18 (95% CI: 1.16–1.20) for ADI, and 1.22 (95% CI: 1.20–1.23) for SVI. ConclusionThe COI, ADI, and SVI had good correlation and demonstrated similar effect size estimates for a variety of clinical outcomes. While investigators should consider potential causal pathways for outcomes when selecting an index for neighborhood disadvantage, the relative strength of association between each index and all outcomes was similar.

Patient Perceived Impact of Outpatient Group Substance Use Disorder Treatment in a Hybrid Model or Virtual-Only Model Relative to In-Person Delivery.

Telehealth use has grown tremendously since the onset of the COVID-19 pandemic. While the benefits of virtual care delivery are numerous, little is known about patient experiences in group treatment settings when members join both virtually and in person with the counselor (a hybrid model). We sought to fill this gap by comparing patient survey data across care delivery models. Adult patients with a substance use disorder enrolled at one of seven intensive outpatient (IOP) programs in rural Minnesota voluntarily completed a questionnaire assessing patient satisfaction, perceived therapeutic alliance, group cohesion, and insight gained from treatment. Starting 7/1/2021, groups were either all virtual, all in-person, or a hybrid model. The survey began on 1/1/2022. Analysis of covariance (ANCOVA) tested for differences among treatment groups. Separate models were used for each survey question, where the dependent variable was the survey response, the test of interest being treatment group-type, with covariates of length of stay and age. Model estimates and model-based standard deviations were used to calculate the Cohen's d effect size. Survey results from a total of 1037 individuals were included, one survey per respondent. Data was deidentified upon receipt of the survey, preventing specific demographic comparisons. For the hybrid groups, no significant differences were noted with survey responses relative to in-person, with negligible to small effect sizes seen. When comparing virtual to in-person, virtual was rated as significantly worse than in-person on 6 of the 8 questions; effect size estimates exceeded the small effect size cut-off, and the 95% CI exceeded the moderate cut-off. Creating a group model where patients can attend both virtually and in-person together appears to improve perceived therapeutic alliance, group cohesion, and treatment insight, compared to virtual-only groups, which may have a negative effect relative to in-person.

Heterogeneity of animal experiments and how to deal with it.

Heterogeneity of study samples is ubiquitous in animal experiments. Here, we discuss the different options of how to deal with heterogeneity in the statistical analysis of a single experiment. Specifically, data from different sub-groups (e.g. sex, strain, age cohorts) may be analysed separately, heterogenization factors may be ignored and data pooled for analysis, or heterogenization factors may be included as additional variables in the statistical model. The cost of ignoring a heterogenization factor is an inflated estimate of the variance and a consequent loss of statistical power. Therefore, it is usually preferable to include the heterogenization factor in the statistical model, especially if the heterogenization factor has been introduced intentionally (e.g. using both sexes). If heterogenization factors are included, they can be treated either as fixed factors in an analysis of variance design or sometimes as random effects in mixed effects regression models. Finally, for an appropriate sample size estimation, it is necessary to decide whether to treat heterogenization factors as nuisance variables, or whether the experiment should be powered to be able to detect not only the main effect of the treatment but also interactions between heterogenization factors and the treatment variable.

Reactive Immunomodulator Addition to Infliximab Monotherapy Restores Clinical Response in Inflammatory Bowel Disease: A Meta-Analysis.

Patients with inflammatory bowel disease (IBD) receiving infliximab (IFX) commonly experience immunogenic loss of response (LOR) by formation of anti-drug antibodies (ADAs). An immunomodulator (IMM) used in combination with initial IFX induction is known to reduce ADA development and improve clinical outcomes. We aimed to assess the impact of reactively adding an IMM to patients on IFX monotherapy. We conducted a retrospective cohort study and systematic review with meta-analysis of patients with IBD demonstrating immunologic LOR, with or without clinical LOR, that had an IMM (azathioprine, 6-mercaptopurine, or methotrexate) reactively added (reactive combination therapy; rCT) to combat elevated ADAs and raise IFX level. Data were extracted for pooled effect size estimation using random-effects models, and ADA and IFX trough levels were compared pre- and post-IMM initiation. We identified 6 patients who received rCT due to rising ADA titers and low IFX levels. Median ADA titer decreased from 506ng/mL (interquartile range (IQR) [416-750]) to 76.5ng/mL (IQR [25.8-232]), an 85% decrease (p = 0.031). Median IFX trough increased from 0.4µg/mL (IQR [0.4-0.48]) to 8.25µg/mL (IQR [3.7-9.6]), a 20.6-fold increase (p = 0.038). Meta-analysis pooled effect size of 7 studies with 89 patients showed an 87% ADA titer reduction [95% confidence interval (CI) = 72-94%], 6.7-fold increased IFX trough (95% CI = 2.4-18.7), and 76% clinical remission rescue rate (95% CI = 59-93%). These results suggest rCT is a valid rescue strategy in patients with immunogenic LOR to IFX to reduce ADA titers, restore therapeutic IFX levels, and recapture clinical remission of IBD.

Emerging EAT-Lancet planetary health diet is associated with major cardiovascular diseases and all-cause mortality: A global systematic review and meta-analysis

Background&AimsIn 2019, the EAT-Lancet Commission promoted a plant-based diet, emphasizing its potential to enhance human health and environmental sustainability. Nevertheless, a thorough evaluation of health benefits associated with EAT-Lancet diet requires robust statistical backing. This synthesis seeks to compile evidence related to the effects of the EAT-Lancet diet on major cardiovascular disease (CVD) and mortality. MethodsA systematic review and meta-analysis were conducted utilizing data from MEDLINE, EMBASE, PubMed, Web of Science, and medRxiv, covering the period from January 2019 to October 8, 2024. We included all cohort and case-control studies that investigated the association between the emerging EAT-Lancet diet and outcomes such as diabetes, CVD, all-cause mortality, and cancer. Summary effect size estimates are presented as hazard ratios (HRs) and were analyzed using random-effects models. Study heterogeneity was assessed with the Q statistic and I2 statistic. Subgroup analyses were performed to identify potential sources of variability, while publication bias was evaluated using Begg’s and Egger’s tests. Additionally, sensitivity analyses were conducted to assess the robustness of the results. ResultsWe identified 28 publications that included a total of over 2.21 million participants. Adhering to the EAT-Lancet dietary patterns was negatively associated with diabetes, CVD (mortality), all-cause mortality, and cancer (mortality), with HRs of 0.78 (95% CI: 0.65-0.92), 0.84 (95% CI: 0.81-0.87), 0.83 (95% CI: 0.78-0.89), and 0.86 (95% CI: 0.80-0.92), respectively. Significant heterogeneity was observed for diabetes (I2=94.0%), all-cause mortality (I2=85.5%), and cancer incidence (I2=79.3%). Importantly, no evidence of publication bias was found for any of the clinical outcomes analyzed. Sensitivity analyses confirmed the robustness of the results across various dietary scoring systems for CVD mortality, all-cause mortality, and cancer. ConclusionFollowing the EAT-Lancet diet was significantly associated with reduced odds of diabetes, CVD, cancer and mortality. These findings are clinically important, highlighting the beneficial effects of the recent EAT-Lancet diet on various health outcomes.

It’s Relative! The Cross-Modal Effects of Music Density on Perception of Product Size

Individuals inevitably make inferences concerning size when they consider an object presented without cues to its actual size. Recent studies show that structural differences in background music can influence consumers’ perceptions of product attributes through cross-modal correspondence. We introduce a new structural element of music, the “music event rate.” To this end, we make a distinction between the absolute density (notes per time unit) and the relative density (notes per measure or music event rate) and propose an influence of the latter on consumers’ perceptions of product size. Our study employs a 2 (notes per measure: four vs. eight) × 2 (music tempo: slow vs. fast) × 2 (music mode: major vs. minor) between-subject experimental design. Dependent variables are participants’ size estimates of three different food items (pictures of burger, pizza, wine bottle) presented online. The results show that the number of notes per measure has an influence on consumers’ size perception of food items insofar as a higher event rate or number of notes per measure in a music stimulus leads consumers to infer a smaller product size, whereas a lower number of notes per measure leads consumers to perceive products as larger. This cross-modal effects of the music event rate on product size perception represent a previously unexplored influence on consumer behavior.

Unraveling the Complexity of the N e/N c Ratio for Conservation of Large and Widespread Pelagic Fish Species: Current Status and Challenges.

Estimating and understanding the ratio between effective population size (N e) and census population size (N c) are pivotal in the conservation of large marine pelagic fish species, including bony fish such as tunas and cartilaginous fish such as sharks, given the challenges associated with obtaining accurate estimates of their abundance. The difficulties inherent in capturing and monitoring these species in vast and dynamic marine environments often make direct estimation of their population size challenging. By focusing on N e, it is conceivable in certain cases to approximate census size once the N e/N c ratio is known, although this ratio can vary and does not always increase linearly, as it is influenced by various ecological and evolutionary factors. Thus, this ratio presents challenges and complexities in the context of pelagic species conservation. To delve deeper into these challenges, firstly, we recall the diverse types of effective population sizes, including contemporary and historical sizes, and their implications in conservation biology. Secondly, we outline current knowledge about the influence of life history traits on the N e/N c ratio in the light of examples drawn from large and abundant pelagic fish species. Despite efforts to document an increasing number of marine species using recent technologies and statistical methods, establishing general rules to predict N e/N c remains elusive, necessitating further research and investment. Finally, we recall statistical challenges in relating N e and N c emphasizing the necessity of aligning temporal and spatial scales. This last part discusses the roles of generation and reproductive cycle effective population sizes to predict genetic erosion and guiding management strategies. Collectively, these sections underscore the multifaceted nature of effective population size estimation, crucial for preserving genetic diversity and ensuring the long-term viability of populations. By navigating statistical and theoretical complexities, and addressing methodological challenges, scientists should be able to advance our understanding of the N e/N c ratio.

A Study on Market Share and Size Estimation through Expressway Rest Area Business Analysis(Conducting Research using The Modified Huff Model)

A Study on Market Share and Size Estimation through Expressway Rest Area Business Analysis(Conducting Research using The Modified Huff Model)

Estimation of DNA content and genome size of some orchids using flow cytometry

Flow cytometry technique is used extensively in plant sciences to reveal the deviation of genomic size to better identify or resolve the closely related organisms or groups. In this study, extracted nuclei from the leaf tissue of ten Dendrobium species were analyzed for their DNA content. A flow cytometer was used to measure DNA content after extracting and specific staining of nuclei. Direct comparison was performed using chicken erythrocyte nuclei (1C DNA = 1.25 pg) as a standard. The calculated amount of DNA content showed the variation in the amount, ranging from 3.78 to 8.75pg, equivalent to a genomic size of 1852.20 to 4287.50 Mbp, respectively. There was no correlation between elevation and quantity of genome of studied Dendrobium species. It was observed that the quantity of a particular species DNA was inversely proportional to the size of their flowers and positively correlated with the plant height and leaf length. An ANOVA test among the four variables was performed and to identify the subsets that were distinct from one another, we performed Tukey’s HSD test. A pair-wise comparison was performed and among the six compressions, only the stem length significantly differed (mean = 97.873, p&lt; 0.001) from other three variables.

On the estimation of population size-A comparison of capture-recapture and multiplier-benchmark methods.

Approaches to population size estimation are of importance across a wide spectrum of disciplines, especially when census and simple random sampling are impractical. The capture-recapture method and the multiplier-benchmark method are two commonly used approaches that use data that partially capture the target population and overlap in a known way. Due to similarities in required data structures, the approaches are often used interchangeably without a critical appraisal of the underlying assumptions, especially in the two-sample case. Here, we describe the similarities and differences of the sampling mechanisms and assumptions underlying both approaches. We emphasize that the capture-recapture method assumes data sources as random samples and describes two-way inclusion histories, while in multiplier-benchmark method, one source captures a fixed sub-population, and the one-way inclusion histories are modeled. We also discuss the implications of these differences through simulation and real data to guide the choice of method in practice. A careful study of the data structures, relationships, and data generation processes is crucial for assessing the appropriateness of using these methods.

Periodontitis and Oral Health-Related Quality of Life: ASystematic Review and Meta-Analysis.

To investigate the association between periodontitis and oral health-related quality of life (OHRQoL) in adults, and to compare OHRQoL across different severities of the disease. Searches were conducted in five electronic databases up to December 2023. Observational studies that provided a clear definition of periodontitis and used validated measures of OHRQoL were included. Meta-analyses were performed both overall and based on factors that could explain heterogeneity between studies. Sixty studies comprising 14,851 individuals were included in the review. Meta-analyses showed that periodontitis was associated with impaired OHRQoL: any OHRQoL instruments (n = 33 studies; SMD: 0.75, 95% CI: 0.53-0.93), solely using the OHIP-14 (n = 26 studies; MD: 5.14, 95% CI: 3.64-6.64), and risk assessment (n = 9 studies; adjusted RR: 1.42, 95% CI: 1.12-1.78). Stages III-IV periodontitis had a greater impact than Stages I-II periodontitis. Subgroup and meta-regression analyses indicated smaller effect size estimates for individuals with comorbidities. Periodontitis negatively impacts OHRQoL, with a positive score-response relationship found between periodontitis severity and poorer OHRQoL. However, the magnitude of this association appears to be diminished in individuals with comorbidities.

Advancing the reporting of pediatric EEG data: Tools for estimating reliability, effect size, and data quality metrics

EEG studies play a crucial role in enhancing our understanding of brain development across the lifespan. The increasing clinical and policy implications of EEG research underscore the importance of utilizing reliable EEG measures and increasing the reproducibility of EEG studies. However, important data characteristics like reliability, effect sizes, and data quality metrics are often underreported in pediatric EEG studies. This gap in reporting could stem from the lack of accessible computational tools for quantifying these metrics for EEG data. To help address the lack of reporting, we developed a toolbox that facilitates the estimation of internal consistency reliability, effect size, and standardized measurement error with user-friendly software that facilitates both computing and interpreting these measures. In addition, our tool provides subsampled reliability and effect size in increasing numbers of trials. These estimates offer insights into the number of trials needed for detecting significant effects and reliable measures, informing the minimum number of trial thresholds for the inclusion of participants in individual difference analyses and the optimal trial number for future study designs. Importantly, our toolbox is integrated into commonly used preprocessing pipelines to increase the estimation and reporting of data quality metrics in developmental neuroscience.

COMPARATIVE ANALYSIS OF METHODS AND MODELS FOR ESTIMATING SIZE AND EFFORT IN DESIGNING MOBILE APPLICATIONS

Mobile applications have long become an integral part of everyday life and have gained popularity among ordinary users, small companies, and large enterprises. However, this is a completely separate area of software. We can say that this is a whole separate ecosystem. Creating functional software for this ecosystem comes with new requirements, constraints, and characteristics that were not used in previous software metrics evaluation methods such as desktop programs or web applications. Mobile applications have new features, limitations and capabilities that are different from other software. Estimating the size and effort helps the software development team approximate the costs needed to more successfully develop a software product such as a mobile application. An early estimate of size and effort is necessary to identify resources that can help in the early stages of implementation a software project within budget and on time. The reliability of the assessment is also of great importance. Low reliability can lead to overestimation or underestimation, which can have bad consequences for any software development company, especially mobile applications. However, the suitability of methods and models for measuring size and efforts that are used for traditional software (PC applications and web applications) do not always provide sufficient reliability for mobile applications.The main goal of this article is to analyze the usage of various methods and models for estimating size and effort the development of mobile applications, including for the Android OS at the initial stages of their design. There is a brief description of the main and widespread methods and models that are used to estimate the size and effort, such as: Lines of Code (LOC), Function Points (FP), COCOMO and COCOMO 2, COSMIC, FiSMA, application of regression analysis for construction of mathematical models. The methods and models proposed by various authors are directly analyzed.

Assessing the Impact of Visual Arts Teaching on Critical Thinking and Behavior Regulation

Background: Visual arts education has been suggested to influence cognitive and behavioral outcomes, yet its specific effects on critical thinking and behavior regulation remain underexplored. The effect of visual arts education on these domains forms the topic of the present study, which employs a mixed approach research design. Aim: To assess the impact of visual arts education on the improvement of critical thinking and self-regulation in students. Methodology: A quasi-experimental approach was employed with 80 individuals, with 40 in the experimental group Report Phrase receiving education in visual arts and 40 in the control group receiving non-visual arts education. CTST and BRI assessment tools were used to acquire quantitative data about the participants, utilizing the independent and paired sample T-tests. Data collected from participants include interviews, focus group discussions, self-administered, and thematic analysis. A repeated measures ANOVA was used to analyse the data. Result: Statistical findings depicted improvements in the quantitative aspect; critical thinking skills improved from 70.0 to 75.3 with p&lt;0.001 and behavior regulation improved from 65.0 to 69.2 with p&lt;0.001 in the experimental-group in contrast to the control-group. The thematic analysis found striking increases in attention, impulse control, task completion, creativity, collaboration, affect expression, and self-esteem of experimental-group participants. Based on the findings of the Repeated Measures ANOVA, significant enhancements were observed in both domains for critical thinking and behavior regulation with effect size estimates of 0.40 and 0.30, respectively. Conclusion: The development of critical thinking and behavior control in students is greatly impacted by art instruction. Quantitative and qualitative data both support the utility of using visual arts interventions for cognitive and behavioral development and inform practice in art education.