• Diagnostic Performance of a Multiantigen Print ImmunoAssay (MAPIA) for Antibody Detection in Human Neurocysticercosis

  Toribio, Luz M.; Guzman, Carolina; Vasquez, Alessandra; Saavedra, Herbert; Gonzales, Isidro; Bustos, Javier A.; García, Hector H. (Oxford University Press, 2026-01-01)

  Background Neurocysticercosis (NCC) is the most prevalent helminth infection affecting the human central nervous system. Although neuroimaging is required for definitive diagnosis, serology supports case confirmation and clarifies diagnostic doubts. Serology gold standard is antibody detection using the enzyme-linked immunoelectrotransfer blot assay, which uses 7 antigenic lentil-lectin purified parasite glycoproteins (LLGP-EITB). LLGP-EITB is poorly accessible to low-resource settings due to its technical complexity and costs, and it is inaccessible in many settings in which parasitic material to produce antigens is not readily available. We recently developed a 3-Antigen multiantigen print immunoassay (MAPIA) based on recombinant/synthetic antigens (rGP50, rT24H, and sTs14), corresponding to the 3 principal diagnostics antigenic families from LLGP-EITB, that is simpler and does not require parasite-derived materials. Methods MAPIA performance was evaluated using a well-defined set of serum samples from NCC patients confirmed by imaging, including 73 samples from subarachnoid NCC, 72 with >5 parenchymal cysts, 59 with 3-5 parenchymal cysts, 95 with 1-2 parenchymal cysts, and 77 healthy negative controls and compared it with the LLGP-EITB performance. Results Overall, our MAPIA presented a sensitivity of 97.7% and a specificity of 97.4%. Subgroup analyses by NCC type demonstrated a sensitivity of 100% for subarachnoid and parenchymal NCC with >5 cysts and a slight decrease for the groups with 3-5 cysts (96.6%) and 1-2 cysts (94.7%). Observed agreement with the LLGP-EITB assay was 98.33%. Conclusions Our 3-Antigen MAPIA obtained comparable results to LLGP-EITB and emerges as a simpler, reproducible, and easy-Access alternative tool for antibody diagnosis in NCC.
• Taenia solium neurocysticercosis: lts current epidemiological, diagnostic, therapeutic, and control landscapes

  Bustos, Javier A.; Coyle, Christina M.; Thakur, Kiran T.; Guzman, Carolina; Toribio, Luz M.; Arroyo, Gianfranco; Saavedra, Herbert; Mwape, Kabemba E.; Rajshekhar, Vedantam; Garcia, Hector H.; the Cysticercosis Working Group in Peru (cwgp) (Public Library of Science, 2026-02-01)

  Neurocysticercosis is the most common helminthic parasitic disease affecting the human central nervous system and is pleomorphic in its presentation. It is frequently encountered in daily practice in most parts of the world, and also commonly seen in industrialized countries in immigrant populations. In the past decade, new treatment (combined anti-parasitic drugs, increased attention to reducing treatment-associated inflammation and damage, new surgical strategies), and diagnostic (more specific antigen and antibody detection concepts and tools, more sensitive magnetic resonance imaging sequences) approaches, new animal models, and data on control of transmission have emerged. Still, diagnostic challenges persist and treatment approaches for some types of disease may differ, affecting clinical practice. This review provides clinicians in endemic and non-endemic countries with a comprehensive and practical reference to understand the variabilities in clinical expression of the disease and the optimal diagnostic and treatment approaches.
• On the need for patient-centered approaches to Helicobacter pylori management in geriatric populations

  Badell, Camila S.; Ruiz, Eloy F. (Ediciones Doyma, S.L., 2026-03-01)

  El artículo examina críticamente la pertinencia de adoptar enfoques centrados en el paciente en el tratamiento de la infección por Helicobacter pylori en adultos mayores, subrayando la necesidad de integrar variables clínicas, comorbilidades y factores de calidad de vida en la toma de decisiones terapéuticas.
• Oncoplastic Approach to Juvenile Giant Fibroadenoma: A Case Series

  Chávez Díaz, Marcelo; de La Cruz Ku, Gabriel; Cedrón Lenci, Carla Carina; Cueva Perez, Maria del Rosario (Galenos Publishing House, 2026-04-01)

  Juvenile giant fibroadenoma (GFA) is defined as a benign tumor larger than 5 cm, 500 grams, and/or involving at least 80% of the breast. It typically occurs in young patients and causes breast deformity and asymmetry. Surgical treatment involves resection of the tumor (enucleation), rearrangement of the skin envelope, and repositioning of the nipple-areola complex. However, the expected re-expansion of the breast following tumor removal, often managed through periareolar approaches, can be unpredictable and prolonged in certain cases. For this reason, oncoplastic surgery techniques have been developed, which allow for immediate partial reconstruction and are now among the available therapeutic options. This report describes three cases in which an oncoplastic approach was used for the treatment of GFA.
• CLO26-131: Hematologic-IHC Prognostic Score for Therapeutic Prioritization in Breast Cancer: Multicenter Validation in Peru (2010-2020)

  Malpartida, Robert; Benites, Vladimir; Malpartida, Jesús Miguel; Matos, Joseph; Leiva, Silvia; Arroyo, Jorge Luis (Journal of the National Comprehensive Cancer Network : JNCCN, 2026-03-31)

  Introduction: Early treatment selection in breast cancer is often delayed in Latin America due to limited access to advanced biomarkers. We propose an accessible score based on baseline complete blood count and standard immunohistochemistry (IHC) to stratify risk at first consultation. Objective: To internally develop and validate a hematologic–IHC prognostic score to estimate 5-year overall survival. Methods: Multicenter retrospective cohort across four public hospitals in Lima-Peru (2010–2020). A total of 883 patients with histologic confirmation, baseline blood counts and complete IHC (ER, PR, HER2, Ki-67) were included. The Hematologic–IHC Prognostic Score (SPHIQ) integrates six routinely available clinicopathologic and hematologic parameters, yielding a total score ranging from 0 to 12 points: PIV: <250 (0), 250–399 (1), ≥400 (2); PLR: <150 (0), 150–199 (1), ≥200 (2); Hemoglobin (g/dL): >12 (0), 11–12 (1), ≤11 (2); Stage: I–II (0), III (1), IV (2); Histologic grade: G1 (0), G2 (1), G3 (2); Molecular subtype: Luminal A (0), Luminal B (1), HER2+/HR- or TNBC (2). The cumulative SPHIQ score reflects tumor biological aggressiveness, where higher scores correlate with poorer prognosis. This integrated index enables early pre-consultation risk stratification by combining systemic inflammation, hematologic status, and molecular subtype into a single, reproducible prognostic tool. Risk groups: low 0–4, intermediate 5–8, high 9–12. Statistics: Kaplan–Meier, log-rank, multivariate Cox, bootstrap, AUC and C-index. Results: Risk distribution: low n=290 (32.8%), intermediate n=394 (44.6%), high n=199 (22.5%). 5-year OS: 83%, 61% and 34% (log-rank p<0.001). Independent predictors of lower OS: * PIV≥310 aHR 4.94 (95%CI 1.59–15.38; p=0.006) * PLR≥150 aHR 2.33 (95%CI 1.22–4.44; p<0.05) * Triple-negative and HER2+ HR-negative with worst prognosis Model performance: C-index 0.72, AUC 0.71. Calculation time: <5 minutes in clinic. Conclusion: SPHIQ enables immediate prognostic stratification using standard CBC and IHC, optimizing therapeutic prioritization and resource allocation in Latin American healthcare systems.
• Safety and clinical outcomes of mechanical thrombectomy for acute stroke in pregnant patients: A systematic review

  Calisaya-Madariaga, Irving Gabriel; Carbajal-Galarza, Meiling; Castillo-Granda, Jhosely Ibeth; Abanto-Florez, Leonardo Marcelo; Navarro Salcedo, Maria Fernanda; Suárez Rodríguez, José Alejandro; Ramos Maguiña, Edward Sebastian; Meca-Bayona, Matias Daniel; Pacheco-Barrios, Niels; Acurio-Ortiz, Karlos (BMJ Publishing Group, 2026-01-01)

  Mechanical thrombectomy (MT) is an established and guideline-endorsed treatment for acute ischemic stroke (AIS) due to large vessel occlusion. Intravenous thrombolysis (IVT) with alteplase remains the first-line therapy within the approved time window, often used alone or as a bridging strategy before MT. However, both interventions have been systematically understudied in pregnant patients, as this population has been excluded from most pivotal clinical trials. This systematic review critically evaluates the procedural feasibility, safety, and maternal-fetal outcomes of MT in pregnant patients experiencing AIS. A comprehensive literature search using PubMed, Embase, and Web of Science yielded 16 studies encompassing 26 cases. In 20 of these, the occlusions involved the M1 segment of the middle cerebral artery, with 58% receiving combined IVT and MT, and 42% undergoing MT alone. Successful reperfusion (TICI 2b-3) was attained in 84% of cases. The median times were 120 min from onset to hospital arrival, 92 min from arrival to puncture, and 330 min from onset to recanalization. Favorable maternal outcomes (mRS 0-1) were observed in 91% of cases at follow-up, and no direct MT-related fetal mortalities occurred. Radiological protection practices, though inconsistently reported, commonly included abdominal shielding and optimized fluoroscopic protocols. Despite limited high-level evidence, MT in pregnancy appears technically feasible and clinically beneficial, warranting prompt multidisciplinary coordination and robust imaging protocols. Future prospective research is essential to better define safety parameters and optimize guidelines for this vulnerable subgroup of patients.
• Exploring the Seismic Performance of Confined Brick Masonry Walls via Diverse Toothing Connections: A Numerical Investigation

  Shandilya, A. N.; Haldar, A.; Yacila, Jhair; Mandal, S. (American Society of Civil Engineers (ASCE), 2026-02-01)

  Confined brick masonry (CBM) combines masonry walls with reinforced concrete ties for enhanced structural integrity. The wall-to-tie connection is essential for effective load transfer, preventing out-of-plane failure, and enhancing ductility. Introducing tie-columns into masonry walls through various toothing connections is crucial. However, previous research and guidelines do not provide clear insights into their specific contributions, making it difficult to accurately assess their impact. Addressing this gap, our study employed a robust numerical approach, utilizing an integrated finite element macromodel that treated wall and tie members as a single entity, thereby improving computational efficiency. Additionally, the study applied the concrete damage plasticity model to predict damage progression in CBM walls and performed pushover analysis to evaluate the seismic performance of various toothing schemes in CBM walls. An extensive parametric study was conducted to compare various toothing schemes, evaluate the optimal horizontal and vertical projections of tooth, assess the impact of height-to-thickness ratio on toothing schemes, and investigate the effect of openings on the performance of toothing schemes in CBM walls. This research also assessed the severity of damage encountered by CBM walls, providing insights into crack propagation and distribution and emphasizing the significance of its design. This study highlights the critical role of toothing schemes in the seismic performance of CBM walls, with the machine-made toothing schemes demonstrating superior results. These schemes significantly enhanced ultimate strength, stiffness, and energy absorption compared to handmade, horizontal reinforcement, and no-tooth options. The research also quantified the positive correlation between increased wall thickness and improved structural resilience, particularly when paired with machine-made toothing. Furthermore, the study identified the adverse effects of wall openings on seismic performance, emphasizing the importance of precise tooth size and arrangement. Notably, a 100-mm vertical projection was shown to offer the most effective seismic performance, providing valuable, data-driven guidelines for the design of earthquake-resistant CBM structures.
• Enhancing Minimarket Customer Experience Through YOLOv8-Powered Checkout Systems

  Arana-Del-Carpio, Sebastian; Becerra-Bisso, Luis; Ugarte, Willy (Springer Science and Business Media Deutschland GmbH, 2026-01-01)

  In Lima, Peru, minimarkets are vital, providing essential goods to a growing population. However, slow payment processes lead to long lines and frustrated customers, impacting satisfaction and profitability. The main issue is the slow, error-prone manual item scanning at the checkout. Addressing this inefficiency can enhance economic impact, customer satisfaction, and operational efficiency. Despite the benefits, implementing object detection technology faces challenges such as technological complexity, integration issues, diverse product ranges, and high costs. Previous solutions failed due to inadequate technology, high costs, poor integration, and user resistance. This paper proposes using YOLOv8, a state-of-the-art object detection model, for its precision, real-time processing, cost-effectiveness, and easy integration. This work includes custom hardware, an integration layer, and a user interface, with the aim of reducing checkout times, achieving over 94% product recognition accuracy, and improving customer satisfaction. Initial tests show promising results in speed, accuracy, and customer feedback.
• IoT System Based on Deep Learning for the Identification and Feedback of Work Postures When Using a Computer

  Caballero-Lara, Eduardo; Camargo-Ramirez, Enzo; Ugarte, Willy (Springer Science and Business Media Deutschland GmbH, 2026-01-01)

  It is common for office workers, mostly dedicated to IT, to present musculoskeletal pain in the back, neck and shoulders due to poor posture practices they adopt while doing their work in front of the computer for long periods, this is known as forced postures. Our main work seeks to implement an IoT system with force sensors, model RP-S40-ST, based on the use of classification algorithms and deep learning techniques for the identification and correction of postures through feedback. Ten classification algorithms were used for training and validation of the model, with the Logistic Regression algorithm achieving the highest accuracy rate being .8794 and .9052 respectively.
• Mitigating Information Leakage in Tech-Sector SMEs: Implementing ISO 27001:2022 for Comprehensive Security

  Quispe, Gabriel O.; Zuloaga, Cesar K.; Castañeda, Pedro S. (Springer Science and Business Media Deutschland GmbH, 2026-01-01)

  This paper presents a model for implementing an Information Security Management System (ISMS) based on ISO 27001:2022 tailored to the needs of small and medium-sized enterprises (SMEs) in the technology sector in Lima Metropolitana. The model focuses on mitigating data leakage, a critical issue exacerbated by the increasing digitization of business operations. The proposed framework integrates controls from ISO 27001 aligned with NIST SP 800-53 to enhance information security practices. Results from applying the model to two technology SMEs indicate that one company (Company A) achieved a 94.44% Critical Control Implementation Index (IICC), a 70% Critical Vulnerability Resolution Rate (TRVC), and an 85% Policy Compliance Rate (TCPS), while the second company (Company B) achieved significantly lower rates of 50%, 40%, and 60%, respectively. These findings highlight both strengths in technological controls and weaknesses in organizational security management. This research contributes to the field by providing a practical, scalable approach for SMEs to enhance their information security posture, addressing both human and technological factors.
• Unveiling Injustice: Analyzing Child Mortality Inequality across decades in Peru (1981–2017)

  Huaroto, César; Francke, Pedro; Vivas, Claudia (Elsevier Ltd, 2026-01-01)

  Peru is a developing country that has significantly improved the average of almost all health indicators. Specifically, in the past four decades, child mortality decreased tenfold. However, the same is not necessarily true of equality, which remains a challenge. Using microdata from Peru's population censuses in 1981, 1993, 2007, and 2017, we estimate the inequality in child mortality across different social groups. We estimate differences between ethnic groups, education levels, wealth quintiles, regions, and urban–rural groups and find that although inequality has decreased, it remains significantly high. The data show that inequality in child mortality increased between 1981 and 1993, declined between 1993 and 2007, and then increased between 2007 and 2017. Differences in education are the most crucial factor, associated with 45 % of the inequality in 1981 and 58 % in 2017. Differences between Lima and rural areas account for 27 % to 30 % of the inequality, while ethnicity contributes only 6 % in 1981 and 10 % in 2017.
• A Thorough Evaluation of Demand Prediction Models: Machine Learning, Deep Learning, and Statistical Techniques for Import Businesses

  Julca-Mejia, Wilson; Julca-Mejia, Annie (Springer Science and Business Media Deutschland GmbH, 2026-01-01)

  Nowadays, managing demand in companies is crucial to avoid storage overcosts, stockouts and to improve the service level of companies. To address this scenario, demand predictions through models and algorithms emerge. Therefore, this research aims to evaluate the performance of seven prediction techniques applying machine learning, deep learning, and statistical methods. To validate our experiments, we used Dickey–Fuller, Shapiro–Wilk, Friedman, and Wilcoxon post-hoc statistical tests on the predictions of the models using demand records from a Peruvian import company. The results indicated that deep learning and statistical models have significantly better predictions than machine learning models. In particular, the LSTM, CNN, ARIMA, and Holt-Winters models significantly improve accuracy compared to the Ridge Regression, Random Forest Regressor, and Decision Tree Regressor models. Compared to machine learning models, statistical and deep learning models improve accuracy in a range from 66.01 to 86.10%. These results highlight the statistical advantage of deep learning and statistical models in demand prediction, with the LSTM model showing the lowest error.
• Patients with Chronic Kidney Disease and Advance Health Care Directive Registration

  Díaz-Cárdenas, David; Gallardo-Echenique, Eliana (Springer Science and Business Media Deutschland GmbH, 2026-01-01)

  Advance healthcare directives planning entails the development of an understanding, reflection and communication process among patients, family members and healthcare team to accurately clarify patients’ preferences and identify surrogates, especially in end-of-life scenarios. The purpose of this study was to analyse the perceptions of patients with chronic kidney disease undergoing haemodialysis at Hospital Abraham Godoy Peña de Lautaro regarding the intention to register their advance healthcare directive. A phenomenological approach was applied to understand the meaning of the experiences of the subjects involved. Theoretical sampling was used, and 14 semi-structured interviews were conducted. Data were processed using thematic analysis. Patients with stage 5 chronic kidney disease undergoing haemodialysis were aware of the importance of advance healthcare directive registration; however, the registration process and should be guided by values-based education techniques. Interviewees prefer therapies aligned with their lifestyles, family impact, psychological comfort, and inclusion, rather than focusing solely on clinical results.
• Empirical Experiment to Validate Guidelines for Video Game Users With ADHD

  Diaz, Eduardo; Morante Castaneda, Augusto; Ignacio Panach, Jose (Education Society of IEEE (Spanish Chapter), 2026-01-01)

  Current video game designs often include features that distract users, a problem exacerbated for individuals with Attention Deficit Hyperactivity Disorder (ADHD). To mitigate distractions for this population, specific design guidelines have been proposed. This study evaluates the benefits of applying such guidelines in the software development process of video games for users with ADHD. A controlled experiment was conducted with 16 subjects interacting with two versions of a video game: one designed according to the guidelines and another without them. Metrics analyzed include perceived effort and user satisfaction, measured through Perceived Ease of Use (PEOU), Perceived Usefulness (PU), and Intention to Use (ITU). Results indicate statistically significant differences in effort and satisfaction; users engaging with the guided design reported lower cognitive effort and higher satisfaction. These findings suggest that integrating ADHD-focused design guidelines enhances game accessibility and improves user experience for this demographic.
• Influence of economic globalisation on growth and environmental quality in Pacific Alliance countries

  Gómez Sánchez Torres, Carlos Daniel; Peña Takeuchi, Ayumi Abigail; Ponce Gomez, Maureen Daniela; Cusihuallpa Fernandez, Giovana Angélica; Suárez Ramos, Pilar Inés; Rodríguez Sánchez, Leonardo Valentino; Moscoso Cuaresma, Julio Ricardo; Azabache Morán, Carlos Alberto (Cogent OA, 2026-01-01)

  This article examines the dual impact of economic globalisation on economic growth and environmental quality within the Pacific Alliance—Chile, Colombia, Mexico and Peru—between 1990 and 2022. Employing a quantitative longitudinal approach, it applies panel data econometric techniques, specifically Fixed Effects models, complemented by robustness checks using Random Effects and Pooled Ordinary Least Squares estimations. Panel unit root tests (Levin–Lin–Chu; Im–Pesaran–Shin) confirmed data stationarity, and the Hausman test validated the suitability of the Fixed Effects estimator. The results show that trade openness exerts a positive and statistically significant effect on real economic growth, suggesting that deeper integration into global markets enhances productive efficiency, diversifies exports and improves resource allocation. By contrast, foreign direct investment does not exhibit a significant relationship with growth, owing to institutional weakness, limited infrastructure and the shallow financial systems that characterise the region. Regarding environmental outcomes, trade openness increases carbon dioxide emissions, indicating that liberalisation stimulates production while exacerbating environmental degradation in contexts with insufficient regulatory capacity. Foreign direct investment likewise shows no significant effects, possibly due to sectoral heterogeneity. The study concludes that the Pacific Alliance must strengthen environmental governance and guide trade and investment towards sustainable development.
• Model for Monitoring the Pest Carmenta Foraseminis in Cocoa Crops Through Environmental Parameters

  Huaman, Kevin Guerra; Chavez, Heyul; Trujillo, Carlos Silvestre Herrera; Zapata, Gianpierre; Raymundo, Carlos (Springer Science and Business Media Deutschland GmbH, 2026-01-01)

  Cocoa consumption has increased in recent years as it has a significant impact on the food and cosmetic sector. It is therefore important to maintain and improve agricultural productivity, which makes it urgent and necessary to improve management techniques, including fertilization and crop and plantation protection practices. However, intensive cocoa production in Peru and South America faces challenges for cocoa production. The most decisive is the attack of the “mazorquera” pest (Carmenta foraseminis), which infests the fruit inside without giving the possibility of early detection and, consequently, the quality and intensity of the harvest is often diminished. The objective of this work is the development and implementation of a method to monitor and detect the “mazorquera” pest in the cocoa crop, by obtaining data in real time and analyzing them. In this sense, the proposal involves the use of sensors to monitor certain environmental variables that correlate with the behavior of the pest “mazorquera” from certain artificial intelligence algorithms. The use of intelligent algorithms decreases the analysis time, the error rate and increases the accuracy in the decision-making process. The proposed method proves to have the relevant correlation between environmental conditions and the behavior with crop pests, allowing its timely detection to intervene quickly and effectively. The proposed procedure is not limited to the improvement in crop management, it also creates the conditions for improved traceability of information, improving cocoa production, making it more competitive and sustainable.
• The KUYUY Accelerograph and SIPA System: Towards Low-Cost, Real-Time Intelligent Seismic Monitoring in Peru

  Ortiz, Carmen; Alva, Jorge; Raucana, Roberto; Chipana, Michael; Oliden, José; Huarcaya, Nelly; Riveros, Grover; Valverde, José (Multidisciplinary Digital Publishing Institute (MDPI), 2026-01-01)

  Accelerographs are essential instruments for quantifying strong ground motion, serving as the foundation of modern earthquake engineering. In Peru, the first accelerographic station was installed in Lima in 1944; since then, various institutions have promoted the expansion of the national network. However, this network’s spatial coverage and instrumentation remain insufficient to properly characterize strong motion and support seismic risk reduction policies. In this context, the KUYUY accelerograph is presented as a low-cost, low-noise device equipped with real-time telemetry and high-performance MEMS sensors. Its interoperability with the Intelligent Automatic Processing System (SIPA) enables real-time monitoring and automated signal analysis for seismic microzonation studies and rapid damage assessment, contributing to seismic risk reduction in Peru. The validation process included static gravity calibration, field comparison with a reference accelerograph, and an initial deployment in Lima and Yurimaguas. The results demonstrate the proposed accelerograph’s linear response, temporal stability, and amplitude consistency with respect to high-end instruments, with differences below 5–10%.
• IoT-based air pollution monitoring system: A case study in Artisanal Brick Kilns

  Barrientos-Mauricio, Rogger Gustavo; Medrano-Jacobo, Alejandro Quiros; Carrera-Salas, Ernesto Adolfo (Taylor and Francis Ltd., 2026-01-01)

  The rapid growth of industrial activities has led to a significant increase in environmental pollution. Exposure to these air pollutants negatively impacts health, quality of life, and contributes to climate change. It is essential to develop accessible and low-cost mechanisms for controlling polluting emissions. This study presents an IoT-based air pollution monitoring system implemented in an artisanal brick kiln, where manual processes and the use of fossil fuels generate emissions that can severely affect nearby communities, particularly due to the high concentration of fine particulate matter such as PM2.5, known to cause respiratory and cardiovascular problems. The system uses the SPS30 sensor to measure PM2.5 and PM10, connected to an ESP32 microcontroller, which transmits data using the MQTT protocol to the AWS IoT Core service, where they are processed and visualized in real time through a web application. During its validation, the system demonstrated high accuracy, obtaining a correlation of r = 0.95 for PM2.5 and r = 0.99 for PM10 compared to an official monitoring station. The experiment at the artisanal brick kiln confirmed that on 100% of the days monitored, PM2.5 concentrations exceeded the limit of 75 µg/m³, while PM10 exceeded 150 µg/m³ on 30% of the days evaluated. The system generates automatic alerts for excessive pollutants, facilitating a timely response and the implementation of corrective measures when pollution levels reach critical levels. The proposal presents a scalable and low-cost solution to improve environmental management across various industrial sectors.
• When Virality Builds Brands: The Power of eWOM in Digital Campaigns

  Irala, Valeria; Arbaiza, Francisco (Springer Science and Business Media Deutschland GmbH, 2026-01-01)

  This study analyzes the effectiveness of experiential marketing and the strategies of buzz marketing, Word of Mouth (WOM), and electronic Word of Mouth (eWOM) in Burger King’s 2024 “Kiss Day” campaign, aimed at improving brand perception and fostering consumer engagement. Using a qualitative case study approach, the research examined consumer experiences and perceptions through semi-structured interviews and social media content analysis. The findings show that the combination of positive emotions and active participation was associated with greater campaign’s virality and improved brand recall. However, the initiative demonstrated limited effect on long-term loyalty among non-regular customers. The study concludes that integrating experiential marketing with digital strategies can expand the reach and effectiveness of campaigns, offering key insights for future advertising efforts in the fast-food industry.
• Guidelines for Adapting a Corruption Peruvian Survey into the Ecuadorian Context

  Freundt-Thurne, Úrsula; Bernal-Suarez, Juan David; Gallardo-Echenique, Eliana (Springer Science and Business Media Deutschland GmbH, 2026-01-01)

  This study aimed to adapt the “Corruption Normalization Scale”, created for, and applied among Peruvian university students, to the Ecuadorian university context. To achieve this, cultural, idiomatic, and linguistic particularities of the latter country were considered. This is a cross-cultural adaptation study, through content validation and expert judgment. Ten multidisciplinary experts from different areas of knowledge were chosen. The experts agree on the relevance of the four criteria evaluated: Sufficiency, Clarity, Coherence, and Relevance. The results showed that a group of experts found it difficult to delimit the scope of the three dimensions (Fraud, Criollada, and Transgression). It is recommended to contemplate the idiomatic particularities of each country or area where the Scale is to be applied, to clearly and correctly transmit what is to be evaluated.

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