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se ha posicionado como un centro de referencia asistencial y académica, con la proyección de conformar clínicas o centros de excelencia.Para lograr este objetivo, es indispensable que realice y se ciña a sus propias guías de práctica clínica o estándares clínicos basados en la evidencia (ECBE), que permita una adecuada y estandarizada atención de pacientes aplicando la mejor evidencia médica disponible.La obesidad es una patología de alta prevalencia en la población general, siendo uno de los motivos de consulta más

Systematic reviews and meta-analyses are essential to summarize evidence relating to efficacy and safety of health care interventions accurately and reliably. The clarity and transparency of these reports, however, is not optimal. Poor reporting of systematic reviews diminishes their value to clinicians, policy makers, and other users.Since the development of the QUOROM (QUality Of Reporting Of Meta-analysis) Statement--a reporting guideline published in 1999--there have been several conceptual, methodological, and practical advances regarding the conduct and reporting of systematic reviews and meta-analyses. Also, reviews of published systematic reviews have found that key information about these studies is often poorly reported. Realizing these issues, an international group that included experienced authors and methodologists developed PRISMA (Preferred Reporting Items for Systematic reviews and Meta-Analyses) as an evolution of the original QUOROM guideline for systematic reviews and meta-analyses of evaluations of health care interventions.The PRISMA Statement consists of a 27-item checklist and a four-phase flow diagram. The checklist includes items deemed essential for transparent reporting of a systematic review. In this Explanation and Elaboration document, we explain the meaning and rationale for each checklist item. For each item, we include an example of good reporting and, where possible, references to relevant empirical studies and methodological literature. The PRISMA Statement, this document, and the associated Web site (http://www.prisma-statement.org/) should be helpful resources to improve reporting of systematic reviews and meta-analyses.

Much biomedical research is observational. The reporting of such research is often inadequate, which hampers the assessment of its strengths and weaknesses and of a study's generalisability. The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) Initiative developed recommendations on what should be included in an accurate and complete report of an observational study. We defined the scope of the recommendations to cover three main study designs: cohort, case-control, and cross-sectional studies. We convened a 2-day workshop in September 2004, with methodologists, researchers, and journal editors to draft a checklist of items. This list was subsequently revised during several meetings of the coordinating group and in e-mail discussions with the larger group of STROBE contributors, taking into account empirical evidence and methodological considerations. The workshop and the subsequent iterative process of consultation and revision resulted in a checklist of 22 items (the STROBE Statement) that relate to the title, abstract, introduction, methods, results, and discussion sections of articles. 18 items are common to all three study designs and four are specific for cohort, case-control, or cross-sectional studies. A detailed Explanation and Elaboration document is published separately and is freely available on the Web sites of PLoS Medicine, Annals of Internal Medicine, and Epidemiology. We hope that the STROBE Statement will contribute to improving the quality of reporting of observational studies.

BACKGROUND: the analysis of microbial communities through dna sequencing brings many challenges: the integration of different types of data with methods from ecology, genetics, phylogenetics, multivariate statistics, visualization and testing. With the increased breadth of experimental designs now being pursued, project-specific statistical analyses are often needed, and these analyses are often difficult (or impossible) for peer researchers to independently reproduce. The vast majority of the requisite tools for performing these analyses reproducibly are already implemented in R and its extensions (packages), but with limited support for high throughput microbiome census data. RESULTS: Here we describe a software project, phyloseq, dedicated to the object-oriented representation and analysis of microbiome census data in R. It supports importing data from a variety of common formats, as well as many analysis techniques. These include calibration, filtering, subsetting, agglomeration, multi-table comparisons, diversity analysis, parallelized Fast UniFrac, ordination methods, and production of publication-quality graphics; all in a manner that is easy to document, share, and modify. We show how to apply functions from other R packages to phyloseq-represented data, illustrating the availability of a large number of open source analysis techniques. We discuss the use of phyloseq with tools for reproducible research, a practice common in other fields but still rare in the analysis of highly parallel microbiome census data. We have made available all of the materials necessary to completely reproduce the analysis and figures included in this article, an example of best practices for reproducible research. CONCLUSIONS: The phyloseq project for R is a new open-source software package, freely available on the web from both GitHub and Bioconductor.

BACKGROUND: We recently described FastTree, a tool for inferring phylogenies for alignments with up to hundreds of thousands of sequences. Here, we describe improvements to FastTree that improve its accuracy without sacrificing scalability. METHODOLOGY/PRINCIPAL FINDINGS: Where FastTree 1 used nearest-neighbor interchanges (NNIs) and the minimum-evolution criterion to improve the tree, FastTree 2 adds minimum-evolution subtree-pruning-regrafting (SPRs) and maximum-likelihood NNIs. FastTree 2 uses heuristics to restrict the search for better trees and estimates a rate of evolution for each site (the "CAT" approximation). Nevertheless, for both simulated and genuine alignments, FastTree 2 is slightly more accurate than a standard implementation of maximum-likelihood NNIs (PhyML 3 with default settings). Although FastTree 2 is not quite as accurate as methods that use maximum-likelihood SPRs, most of the splits that disagree are poorly supported, and for large alignments, FastTree 2 is 100-1,000 times faster. FastTree 2 inferred a topology and likelihood-based local support values for 237,882 distinct 16S ribosomal RNAs on a desktop computer in 22 hours and 5.8 gigabytes of memory. CONCLUSIONS/SIGNIFICANCE: FastTree 2 allows the inference of maximum-likelihood phylogenies for huge alignments. FastTree 2 is freely available at http://www.microbesonline.org/fasttree.

Points• UK Biobank is a very large and detailed prospective study with over 500,000 participants aged 40-69 years when recruited in 2006-2010.• The study has collected and continues to collect extensive phenotypic and genotypic detail about its participants, including data from questionnaires, physical measures, sample assays, accelerometry, multimodal imaging, genome-wide genotyping and longitudinal follow-up for a wide range of health-related outcomes.• Wide consultation; input from scientific, management, legal, and ethical partners; and industrial-scale, centralised processes have been essential to the development of this resource.• UK Biobank is available for open access, without the need for collaboration, to any bona fide researcher who wishes to use it to conduct health-related research for the benefit of the public.The challenge of understanding the determinants of common life-threatening and disabling conditions is substantial.These conditions are typically caused by a combination of lifestyle, environmental, and genomic factors, with individually modest effects and complex interactions, the detection and quantification of which require studies with large numbers of disease cases.While retrospective case-control studies of particular diseases [1] or existing prospective studies of particular risk factors can help to address this challenge [2,3], a complementary approach is to establish large prospective cohorts designed to study a much wider range of known and novel risk factors for a wide range of diseases [4].Prospective studies can assess exposures before the onset and treatment of disease, diseases that are not readily investigated by

BACKGROUND: Global and regional projections of mortality and burden of disease by cause for the years 2000, 2010, and 2030 were published by Murray and Lopez in 1996 as part of the Global Burden of Disease project. These projections, which are based on 1990 data, continue to be widely quoted, although they are substantially outdated; in particular, they substantially underestimated the spread of HIV/AIDS. To address the widespread demand for information on likely future trends in global health, and thereby to support international health policy and priority setting, we have prepared new projections of mortality and burden of disease to 2030 starting from World Health Organization estimates of mortality and burden of disease for 2002. This paper describes the methods, assumptions, input data, and results. METHODS AND FINDINGS: Relatively simple models were used to project future health trends under three scenarios-baseline, optimistic, and pessimistic-based largely on projections of economic and social development, and using the historically observed relationships of these with cause-specific mortality rates. Data inputs have been updated to take account of the greater availability of death registration data and the latest available projections for HIV/AIDS, income, human capital, tobacco smoking, body mass index, and other inputs. In all three scenarios there is a dramatic shift in the distribution of deaths from younger to older ages and from communicable, maternal, perinatal, and nutritional causes to noncommunicable disease causes. The risk of death for children younger than 5 y is projected to fall by nearly 50% in the baseline scenario between 2002 and 2030. The proportion of deaths due to noncommunicable disease is projected to rise from 59% in 2002 to 69% in 2030. Global HIV/AIDS deaths are projected to rise from 2.8 million in 2002 to 6.5 million in 2030 under the baseline scenario, which assumes coverage with antiretroviral drugs reaches 80% by 2012. Under the optimistic scenario, which also assumes increased prevention activity, HIV/AIDS deaths are projected to drop to 3.7 million in 2030. Total tobacco-attributable deaths are projected to rise from 5.4 million in 2005 to 6.4 million in 2015 and 8.3 million in 2030 under our baseline scenario. Tobacco is projected to kill 50% more people in 2015 than HIV/AIDS, and to be responsible for 10% of all deaths globally. The three leading causes of burden of disease in 2030 are projected to include HIV/AIDS, unipolar depressive disorders, and ischaemic heart disease in the baseline and pessimistic scenarios. Road traffic accidents are the fourth leading cause in the baseline scenario, and the third leading cause ahead of ischaemic heart disease in the optimistic scenario. Under the baseline scenario, HIV/AIDS becomes the leading cause of burden of disease in middle- and low-income countries by 2015. CONCLUSIONS: These projections represent a set of three visions of the future for population health, based on certain explicit assumptions. Despite the wide uncertainty ranges around future projections, they enable us to appreciate better the implications for health and health policy of currently observed trends, and the likely impact of fairly certain future trends, such as the ageing of the population, the continued spread of HIV/AIDS in many regions, and the continuation of the epidemiological transition in developing countries. The results depend strongly on the assumption that future mortality trends in poor countries will have a relationship to economic and social development similar to those that have occurred in the higher-income countries.

There is increasing concern that most current published research findings are false. The probability that a research claim is true may depend on study power and bias, the number of other studies on the same question, and, importantly, the ratio of true to no relationships among the relationships probed in each scientific field. In this framework, a research finding is less likely to be true when the studies conducted in a field are smaller; when effect sizes are smaller; when there is a greater number and lesser preselection of tested relationships; where there is greater flexibility in designs, definitions, outcomes, and analytical modes; when there is greater financial and other interest and prejudice; and when more teams are involved in a scientific field in chase of statistical significance. Simulations show that for most study designs and settings, it is more likely for a research claim to be false than true. Moreover, for many current scientific fields, claimed research findings may often be simply accurate measures of the prevailing bias. In this essay, I discuss the implications of these problems for the conduct and interpretation of research.

Advances in modern sequencing technologies allow us to generate sufficient data to analyze hundreds of bacterial genomes from a single machine in a single day. This potential for sequencing massive numbers of genomes calls for fully automated methods to produce high-quality assemblies and variant calls. We introduce Pilon, a fully automated, all-in-one tool for correcting draft assemblies and calling sequence variants of multiple sizes, including very large insertions and deletions. Pilon works with many types of sequence data, but is particularly strong when supplied with paired end data from two Illumina libraries with small e.g., 180 bp and large e.g., 3-5 Kb inserts. Pilon significantly improves draft genome assemblies by correcting bases, fixing mis-assemblies and filling gaps. For both haploid and diploid genomes, Pilon produces more contiguous genomes with fewer errors, enabling identification of more biologically relevant genes. Furthermore, Pilon identifies small variants with high accuracy as compared to state-of-the-art tools and is unique in its ability to accurately identify large sequence variants including duplications and resolve large insertions. Pilon is being used to improve the assemblies of thousands of new genomes and to identify variants from thousands of clinically relevant bacterial strains. Pilon is freely available as open source software.

The Illumina DNA sequencing platform generates accurate but short reads, which can be used to produce accurate but fragmented genome assemblies. Pacific Biosciences and Oxford Nanopore Technologies DNA sequencing platforms generate long reads that can produce complete genome assemblies, but the sequencing is more expensive and error-prone. There is significant interest in combining data from these complementary sequencing technologies to generate more accurate "hybrid" assemblies. However, few tools exist that truly leverage the benefits of both types of data, namely the accuracy of short reads and the structural resolving power of long reads. Here we present Unicycler, a new tool for assembling bacterial genomes from a combination of short and long reads, which produces assemblies that are accurate, complete and cost-effective. Unicycler builds an initial assembly graph from short reads using the de novo assembler SPAdes and then simplifies the graph using information from short and long reads. Unicycler uses a novel semi-global aligner to align long reads to the assembly graph. Tests on both synthetic and real reads show Unicycler can assemble larger contigs with fewer misassemblies than other hybrid assemblers, even when long-read depth and accuracy are low. Unicycler is open source (GPLv3) and available at github.com/rrwick/Unicycler.

Recombination is an important process in the evolution of RNA viruses. For viruses with segmented genomes, recombination can occur by reassortment of entire genomic segments. This process has played a significant role in the adaptation and spread of influenza viruses with novel genomic combinations, i.e. , antigenic shifts. Reassortment is usually identified by discrepancies between the topologies of trees reconstructed from different genomic segments, e.g. , subtree prune and regraft (SPR) rearrangements. However, this phylogenetic discordance can also result from errors in tree reconstruction due to insufficient information. The objective of this study was to evaluate the contribution of phylogenetic reconstruction error to the inference of reassortment events from influenza A virus (IAV) genomes from avian hosts. We curated a dataset of 11,795 complete avian H5Nx IAV genomes and sampled subsets of HA sequences with different expected levels of reconstruction error. Next, we simulated molecular evolution along the trees reconstructed from these HA samples, varying rates of evolution and sequence lengths to correspond to the other genomic segments. Because these simulations had no reassortment, any phylogenetic discordance identified from the resulting trees must be caused by reconstruction error. We found that simulations from random samples yielded about 32% as many SPRs as obtained from real data. This false positive rate was reduced to 4% when simulating trees from the most genetically divergent subset of HA sequences. By modifying the simulated trees with SPR rearrangements, we observed a false negative rate of 8.5%, which increased with the number of SPRs per tree. Overall, we found that reassortment can be substantially overestimated from phylogenetic discordance, underscoring the need to account for phylogenetic uncertainty and sampling design when analyzing IAV datasets for reassortment.

Host–parasite coevolution is expected to generate strong selection for resistance and infectivity that has the potential to erode genetic variation. Despite this, natural populations often retain extensive genetic variation in these traits. Genotype-by-genotype interactions on fitness can generate negative frequency-dependent selection, which helps maintain this variation by preventing any host or pathogen genotype from retaining a permanent advantage. Because these interactions place genetic variance in the interaction term rather than in additive differences among hosts or pathogens, that variance is masked from directional selection and can remain ‘cryptic’. Here we combine coevolutionary modelling with large‑scale experimental infection assays to quantify how host-pathogen interactions structure fitness variance in a vertically transmitted virus system, Drosophila melanogaster and sigma virus. Simulations show that coevolution typically erodes additive genetic variance in host and pathogen fitness, concentrating variance in host-virus interaction terms. Consistent with these predictions, experiments spanning 90 host-virus genotype combinations reveal that transmission, viral load, and virulence are overwhelmingly governed by host-virus genetic interactions rather than host or virus main effects. As a result, neither host resistance alleles nor viral genotypes confer consistently higher fitness across genetic backgrounds. Interactions tend to be sex‑specific, further limiting heritable fitness variation. Our results demonstrate that coevolution can substantially mask heritable genetic variation from directional selection by rendering fitness context-dependent. This extensive cryptic genetic variation may be revealed either when ecological or evolutionary conditions shift, or when the process of coevolution itself alters the direction of selection. This demonstrates the need to account for genotype-specific interactions when forecasting evolutionary responses.

Deep-learning-based holographic reconstruction requires numerical data with reliable ground truth for training and quantitative evaluation. Experimental hologram acquisition and pixel-level phase annotation can be difficult to control, making physically defined numerical cases useful as reproducible benchmarks. Here, three analytically specified phase targets—a smooth Gaussian distribution, a four-level step distribution, and a radially structured Siemens Star—are used to generate off-axis digital holograms with known phase ground truth. A frequency-domain filtering procedure is applied before inverse Fourier reconstruction, followed by DCT-based global phase unwrapping. Reconstruction quality is quantified using root mean square error (RMSE), mean absolute error (MAE), correlation coefficient, and profile-based error analysis. The results show that reconstruction errors are comparatively small in smooth regions and increase near abrupt or high-spatial-frequency phase transitions. The three cases are therefore presented as controlled benchmark examples for algorithm verification and baseline comparison, not as a complete substitute for experimental holographic datasets or as a complete training corpus for deep-learning models.

The development of an efficacious vaccine against Plasmodium vivax malaria remains a top global health priority. P. vivax forms hypnozoites, dormant forms of the parasite in the liver that can become reactivated after a few months or even years, causing relapse malaria and enhancing transmission. Therefore, targeting antigens expressed during the pre-erythrocytic stages offers the potential to prevent clinical malaria from both primary and relapse infections. The circumsporozoite protein (CSP) is the leading pre-erythrocytic vaccine candidate and forms the basis for the current P. falciparum malaria vaccines RTS, S and R21/Matrix M. Studies have shown that in P. vivax , CSP attributes limited protection, highlighting the need to identify additional pre-erythrocytic antigens to improve vaccine efficacy. Evaluation of new candidates often requires human volunteers, making initial screening complex and highlighting the need for robust preclinical models. In this study, we generated transgenic P. berghei parasite lines as research tools to investigate the potential efficacy of two P. vivax pre-erythrocytic vaccine candidates, SSP3 and SPECT1. The chimeric Pb-Pv SSP3 and Pb-Pv SPECT1 lines showed normal development throughout the parasite life cycle, in both mice and mosquitoes. Antisera raised against recombinant Pv SSP3 and Pv SPECT1 using TitreMax Gold adjuvant exhibited reduction in sporozoite invasion of hepatocytes in vitro , with mean inhibitions of 27% and 14%, respectively. In vivo sporozoite challenge studies showed sterile protection in 10% of mice immunized with r Pv SPECT1, whereas r Pv SSP3 provided no detectable protection. Although substantial protection was not observed for either antigen under the conditions tested, the transgenic P. berghei lines generated in this study serve as useful platforms for evaluating the efficacy of these antigens as vaccine candidates across different delivery systems and adjuvanted formulations.

Economic diversification is commonly modeled using co-occurrence-based measures of relatedness that quantify pairwise overlap among activities in a capability network. Although such measures are derived from network structure, they operate at the level of first-order neighborhood relations and summarize proximity through local co-occurrence. They do not explicitly encode higher-order structural context, such as indirect connectivity patterns or global positional similarity, into a continuous representation of entities and activities. We develop an embedding-based framework that learns such representations from network topology, enabling the construction of interpretable geometric features, including capability alignment, displacement, and portfolio entropy, that extend standard measures used in economic complexity. We apply this framework to two systems: international trade (1998–2023) and public procurement firms (2009–2024). The resulting representations reveal different structural organization across scales: firms exhibit modular clustering patterns, whereas countries occupy broader, nested capability configurations. In predictive tasks for product and activity specialization, embedding-derived features provide additional explanatory power beyond relatedness in several settings, particularly when forecasting variation in the magnitude of comparative advantage. For country-level entry events, however, persistence remains the strongest predictor. Our results show that relatedness remains the dominant predictor of entry events. In contrast, embedding-derived features become more informative in specific settings, particularly for modeling variation in specialization magnitude and in low-relatedness regimes. More broadly, the findings indicate that diversification depends on structural signals that are both prediction-target-dependent and scale-dependent, with relatedness and embedding-derived features capturing different aspects of the capability space (local overlap vs. structural position).

Effective malaria control and elimination require continuous monitoring of vector control interventions, entomological indicators, and their relationship with malaria case incidence. This implementation case study describes data fragmentation and develops a unified, granular profile of malaria burden and vector control at the district level in mainland Tanzania. By integrating data on malaria burden, vector control interventions, and intervention coverage, the study complements existing stratification approaches and generates actionable insights to inform policy and strategic decision-making on effective interventions at the council level. We extracted monthly council-level malaria incidence data (2018–2022) from DHIS2. Insecticide-treated net (ITN) access was estimated using ITN distribution and population data through a stock-and-flow model, assuming a Tanzania-specific median net lifespan of 2.15 years. Data on indoor residual spraying (IRS) implementation and entomological monitoring reports (2011–2022) were reviewed. Rainfall data were summarized and visualized as overlapping monthly time series. According to the annual vector control report (AVCR) for 2021 and 2022, the mean modeled council-level population access to ITNs was 63.9% in 2021 and 65.2% in 2022. Across 184 councils, 17.4% had low ITN access (<50%), 59.2% had moderate access (51–80%), and 23.4% achieved sufficient access (>80%). Councils with ITN access above 80% consistently reported lower malaria incidence rates, whereas those with access below 50% were generally associated with higher malaria burden. Higher ITN access was associated with lower malaria incidence, underscoring the importance of accurate quantification and timely distribution of insecticide-treated nets. In areas where Anopheles arabiensis predominates, complementary outdoor vector control interventions may be needed to address residual outdoor transmission. District-level vector control profiling can enhance the effectiveness of malaria programmes by supporting evidence-based resource allocation and adaptive intervention strategies.

Background In sub-Saharan Africa, child mortality remains a critical public health challenge, with Zambia exhibiting some of the highest rates in the region. While survival analysis has identified key risk factors, these methods often fail to capture complex non-linear interactions and the dynamic, time-varying nature of longitudinal markers like birth intervals. This study aimed to develop and compare predictive survival models to improve risk stratification for under-five mortality using the 2024 Zambia Demographic and Health Survey (ZDHS). Methods A cohort of 35,610 live births was initially identified, with a final analytic sample of 9,362 singleton births and 1,236 mortality events (13.2%) after applying exclusion criteria for maternal age and data completeness. We compared four modeling frameworks for predictive comparison: Cox Proportional Hazards (Cox PH), Lasso Cox regression, Random Survival Forests (RSF), and Gradient Boosting Machines (GBM), alongside a Bayesian Joint Model for inference on the birth interval and mortality association. The proportional hazards assumption was assessed using Schoenfeld residuals, and stratified Cox models were employed to address time-varying effects. Model performance was evaluated using nested cross-validation with mother-level outer folds and time-dependent Concordance Indices (C-index) and Area Under the Curve (AUC) metrics across a 48-month follow-up period. Results Under nested cross-validation, the four survival models demonstrated comparable predictive performance, with C-indices ranging from 0.745 (Cox PH) to 0.750 (Gradient Boosting Machine) and Integrated Brier Scores ranging from 0.095 to 0.096; pairwise comparisons across models were not statistically significant (DeLong’s test: all p > 0.05). The Bayesian Joint Model revealed a significant association between the longitudinal birth interval process and the hazard of death ( α = 0.035 , 95% CI: 0.023–0.048, p < 0.001), supporting the maternal depletion hypothesis. Variable importance analysis identified birth interval and maternal age as the most influential predictors of child survival, followed by previous child deaths. Stratified analysis of the Cox model revealed significant effects for maternal education (Secondary: HR = 0.426, 95% CI: 0.318–0.570) and previous child deaths (HR = 1.648, 95% CI: 1.529–1.777). Conclusion Advanced survival modeling using joint modeling techniques provides deeper biological insights into child mortality dynamics, and machine learning and traditional survival models offered equivalent predictive discrimination and calibration in this analysis. These findings support targeted public health interventions focusing on birth spacing, maternal age, and enhanced monitoring for high-risk families as critical strategies for reducing under-five mortality in Zambia.

Chronic obstructive pulmonary disease (COPD) is a complex and common condition with significant health, social, and economic burdens, especially due to frequent hospitalizations and comorbidities. International research shows current care for COPD is limited by delayed diagnosis, poor coordination among providers, and inconsistent adherence to treatment guidelines, which negatively impacts patient outcomes. Clinical pathways offer a promising solution by improving care coordination, aligning treatment with evidence-based guidelines, and enhancing both patient experiences and system efficiency; however, questions remain about how, for whom, and in which contexts they are most effective. Using a realist evaluation approach, our study will evaluate how, for whom, and in which circumstances an integrated clinical pathway for COPD works in Saskatchewan, Canada. First, we will develop initial program theories based on literature and stakeholder input. Second, we will test these theories using administrative data and realist interviews with healthcare staff, managers, providers, COPD patients, and caregivers. Third, we will refine our theories based on data collected. Fourth, we will translate our findings to enhance future implementation. These phases will be repeated over a three-year span to continuously improve pathway implementation processes and monitor improvements in patient outcomes. Findings will be shared through integrated knowledge translation with system decision-makers and patients. Findings will also be disseminated to the broader research community through conference presentations and peer-reviewed publications.

The main purpose of this study was to determine the differences in executive function performance levels of esports players who play First-Person Shooter (FPS) and Multiplayer Online Battle Arena (MOBA) game types compared to non-video game players (NVGPs). Other purposes of the study are to examine the relationships of executive function components and their relationships with in-game rank and total game play time variables. The study groups consisted of ninety volunteer participants, all of whom were male young adults between the ages of 18 and 34, 30 of whom actively played FPS video games, 30 of whom actively played MOBA video games, and 30 of whom NVGPs. Corsi Block-Tapping Test (CBT), Wisconsin (Berg) Card Sorting Test (WCST), and Stroop Test Çapa Form (ST) were used as data collection tools. According to the findings of the study; FPS players had significantly higher scores than NVGPs (p < 0.001, F = 8.55) in CBT and less error percentage than the NVGPs (p < 0.01, F = 5.58) and MOBA players had significantly less interference time than NVGPs in the ST (p < 0.001, F = 7.66). In addition, there was a significant negative correlation between CBT and ST interference times for all players (p < 0.05; r = −0.28) and a significant negative correlation between in-game skill and ST interference times for FPS players (p < 0.05; r = −0.41). These findings suggest that digital video game experience shapes cognitive profiles based on genre-specific demands; while FPS gameplay primarily enhances visuospatial working memory capacity, MOBA gameplay fosters stronger inhibition control, with higher in-game skill level reflecting superior inhibitory control in FPS gameplay, and relationship of visuospatial working memory and inhibition components demonstrating an underlying interrelated structure.