Typical Phone Research Articles

Self-correcting deep learning for estimating rice leaf nitrogen concentration with mobile phone images

As a pivotal role in crop development, the application of nitrogen fertilizers enhances yields, while excessive use poses environmental risks. Precision nitrogen management requires rapid crop nitrogen assessment in field conditions and mobile phone images can be a promising approach. However, few studies have investigated how arbitrary white balance and exposure value settings affect crop nitrogen diagnosis using phone photos. Therefore, a new deep learning framework: self-correcting leaf nitrogen concentration estimation network (SCLNC-Net), was proposed to explore the potential of mobile phone images for non-destructive nitrogen status monitoring. Imperfect camera metering and incorrect user operations were addressed through attention U-Net for automatic white balance and exposure correction. Then a lightweight deep learning algorithm MobileNetV3 was utilized to estimate rice leaf nitrogen concentration based on the self-corrected images. Compared with most deep learning models, SCLNC-Net has fewer parameters and higher computational efficiency, which is better suited for deployment on mobile platforms. The results revealed that SCLNC-Net enhanced image quality and acquired high accuracy in the estimation of rice leaf nitrogen concentration (R2 = 0.84, RMSE = 0.39 %, RRMSE = 13 %). Moreover, the robustness and effectiveness of the proposed SCLNC-Net remained excellent across various shooting angles, mobile phone types, and rice varieties. This study provides insights into rapid and cost-efficient nutrient assessment and precision nitrogen management.

Gender inequality in intergenerational contact after parental separation in the digital era

AbstractObjectiveThe goal of this brief report is to analyze parent‐adult child contact frequency in intact and non‐intact families by focusing on parent and child gender and the type of contact.BackgroundParental separation increases gender differences in parent–child relationships, with separated fathers having less frequent contact with their adult children compared to separated mothers. We investigate whether the father–mother gap in post‐separation contact varies according to parent–child gender mismatch and the type of contact, that is, face‐to‐face, phone, or digital (e.g., via video calls).MethodWe use data on Italian families from the Family and Social Subjects survey to examine parent–child contact frequency among 6770 adult children aged 30–55 (11,041 parent–child dyads). We estimate random and fixed effects models on the probability of having frequent contact with biological parents in intact and non‐intact families (parental separation before age 18).ResultsFathers' reduced contact frequency compared to mothers is particularly evident with daughters, more pronounced in face‐to‐face and phone contact than in digital contact, and greater among younger daughters at the time of separation. Gender differences in phone and digital contact are larger for fathers who have also less frequent face‐to‐face contact compared to mothers.ConclusionWe interpret these findings by focusing on the centrality of mother–daughter ties and the loyalty that children have with the same‐gender parent. We also suggest that different types of contact reinforce gender differences between parents and may lead to a polarization of older parents with “strong” and “weak” family ties.

On Development of a SIM-Based Prototype for Enhancing the Usability of Mobile Value-Added Services

The advent of Mobile Value-Added Services (VAS) has witnessed widespread adoption in developing regions, notably within East Africa. This surge is attributed to advancements in information and communication technology, 3G/4G proliferation, growth of mobile internet accessibility, and rising smartphone penetration. Despite this progress, a significant segment of the population continues to rely on basic phones. Studies have shown that the text-based applications used on these types of mobile phones still pose significant obstacles in delivering a user-friendly VAS experience. This paper explores the potential for improving the usability of mobile value-added services on basic phones. We employed an action research approach, utilizing quantitative and qualitative data collection methods. Questionnaires gathered feedback on end-user testing, while in-depth interviews with five industry experts provided insights into potential solutions. This multi-faceted approach ensures a comprehensive understanding of user feedback and expert insights, culminating in the design of an intuitive SIM-based user interface prototype. This highly customised prototype prioritises services and functionalities simplify the user experience through improved navigability and accessibility. The effectiveness of this prototype was quantitatively analysed using descriptive statistics, focusing on ease of use, efficiency, effectiveness, and user satisfaction. With an average ease of use score of 85.8%, a geometric mean time on task of 29.43 seconds, and a user satisfaction score of 79.5%, the prototype demonstrates impressive functionality and garners acclaim for improved navigation and information discovery from users and experts. Further, comparative analysis from expert interviews reveald a more nuanced understanding of technology preferences for basic phone usability, contrary to previous studies. Building upon these demonstrably positive results, the paper concludes by advocating for user interface standardisation and recommending user-generated content for a more inclusive VAS ecosystem.

Selection of disassembly schemes for multiple types of waste mobile phones based on knowledge reuse and disassembly line balancing

The growing number of waste mobile phones (WMPs) have made recycling an urgent issue. Different disassembly schemes demonstrate varying effectiveness in the large-scale disassembly of WMPs. It is necessary to consider both economic benefits and efficiency improvement comprehensively. This paper applies knowledge reuse and disassembly line balancing to the automated disassembly of multiple types of WMPs. In this regard, descriptive standards for mobile phone disassembly knowledge at different workstations are established based on the theory of knowledge reuse. In light of mobile phone disassembly characteristics, workstation thresholds, threshold intervals, and excessively small thresholds are introduced to improve the selection of disassembly line schemes. Based on a quantitative analysis of disassembly line balancing, the selection schemes for disassembling different batches of phones have been optimized. Case studies are conducted on Android and iOS system smartphones to verify the proposed method. The experimental results demonstrate that our proposed method, which incorporates disassembly knowledge, judgment thresholds, and selection schemes, substantially enhances the accuracy of disassembly line selection. For iOS system phones, designing two lines can disassemble all models of WMPs. For Android system phones, the retirement time of mobile phones influences the selection of lines in the disassembly process. Phones with earlier retirement times are more likely to be selected for simpler disassembly lines. Based on disassembly line balancing, two proposed cases for disassembling different batches of phones increase the overall disassembly efficiency by 48.4 % and 46.7 %, respectively.

Healthcare professionals' willingness to utilize a mobile health application for adverse drug reaction reporting in a limited resource setting: An input for digital health, 2023

BackgroundAdverse drug reactions (ADRs) are a significant public health concern, particularly in limited resource settings where underreporting is prevalent due to various challenges. Mobile health applications (mHealth apps) offer a promising solution to enhance pharmacovigilance by facilitating easier and more efficient ADR reporting. However, despite the increasing availability and use of mHealth apps, there is a lack of evidence on healthcare professionals' willingness to adopt them for ADR reporting in resource-constrained environments. Therefore, this study aimed to assess the willingness of healthcare professionals in Ethiopia to utilize mobile health applications for adverse drug reaction reporting and identify associated factors. MethodsWe carried out a cross-sectional study involving 422 healthcare professionals working in institutional settings. We gathered data through a pretested questionnaire that participants completed themselves. We inputted the data using Epi Data V.4.6 and analyzed it using SPSS V.26. Our analysis involved conducting multivariable logistic regression to identify the factors influencing the likelihood of healthcare professionals using mobile applications to report adverse drug reactions. ResultsThe study involved 389 healthcare professionals. Approximately 301 (77.4 %) of them expressed willingness to utilize mobile applications for reporting adverse drug reactions. The willingness to utilize mobile applications was significantly associated with the type of mobile phone (smart: AOR 3.56; 95 % CI 2.15–5.67), basic computer training (AOR 4.43; 95 % CI 2.27–8.64), mobile health-related training (AOR 1.96; 95 % CI 1.01–3.79), attitude (AOR 4.01; 95 % CI 2.19–7.35), perceived ease of use (AOR 2.91; 95 % CI 1.59–5.23), and perceived usefulness (AOR 2.10; 95 % CI 1.15–3.85). ConclusionsOverall, there was a high proportion of healthcare professionals willing to use mobile devices for reporting drug adverse reactions. Their willingness correlated with factors such as the type of mobile phone, perceived ease of use, attitude, training, and perceived usefulness of mobile applications. With the increasing use of smartphones, motivation among healthcare professionals is rising. Basic computer and mHealth-related training are crucial for enhancing the acceptability of such applications and should be incorporated into future implementations. Taking these factors into account could offer insights into the design and implementation of mobile applications for adverse drug reactions in Ethiopia.

Implementing a Pharmacist-Led Primary Care Pharmacogenomics Medication Management Service.

Background: Pharmacogenomics (PGx) is a tool to guide optimal medication selection. Increased demand for personalized medicine and the growing occurrence of chronic diseases are drivers for pharmacogenomic medication management services. A review of implementation models identified a paucity of models delivering these services utilizing pharmacists in primary care. Lack of standardization of this process remains a barrier to widespread implementation within health systems. Purpose: Describe the process of developing an institutional guidance document and applying it to implement a pharmacogenomics medication management service at clinic sites within an integrated health system in the United States. Measure the growth in the number of PGx visits completed. Method: A task force of pharmacists reviewed literature, guidelines, and institutional policies to create a comprehensive guidance document. The document included six minimum practice requirements for implementation in the primary care setting, and six additional recommendations. A retrospective chart review of all face to face, phone and eConsult PGx visit types occurring from January 1, 2022 through September 30, 2022 was conducted. Results: A pharmacist-led pharmacogenomics medication management service is now offered at all primary care sites within the health system. During the study timeframe, 1378 patients had a PGx visit, resulting in 1939 PGx visits. Of those visits, 1777 (92%) were referred by a primary care provider and 1675 (86.7%) were conducted by a primary care pharmacist. Twenty-nine primary care pharmacists offered the PGX service and 25 (89%) completed at least one visit. Patients were referred by providers from 56 of the 64 (87.5%) primary care departments. Conclusions: Developing an institutional process and guidance document for the implementation of a new pharmacist-led pharmacogenomics medication management service at clinic sites within an integrated health system was beneficial in developing and standardizing the workflow. Dissemination of workflow expectations to the primary care providers and pharmacists resulted in adoption of the service.

Identifying Patterns of Smoking Cessation App Feature Use That Predict Successful Quitting: Secondary Analysis of Experimental Data Leveraging Machine Learning.

Leveraging free smartphone apps can help expand the availability and use of evidence-based smoking cessation interventions. However, there is a need for additional research investigating how the use of different features within such apps impacts their effectiveness. We used observational data collected from an experiment of a publicly available smoking cessation app to develop supervised machine learning (SML) algorithms intended to distinguish the app features that promote successful smoking cessation. We then assessed the extent to which patterns of app feature use accounted for variance in cessation that could not be explained by other known predictors of cessation (eg, tobacco use behaviors). Data came from an experiment (ClinicalTrials.gov NCT04623736) testing the impacts of incentivizing ecological momentary assessments within the National Cancer Institute's quitSTART app. Participants' (N=133) app activity, including every action they took within the app and its corresponding time stamp, was recorded. Demographic and baseline tobacco use characteristics were measured at the start of the experiment, and short-term smoking cessation (7-day point prevalence abstinence) was measured at 4 weeks after baseline. Logistic regression SML modeling was used to estimate participants' probability of cessation from 28 variables reflecting participants' use of different app features, assigned experimental conditions, and phone type (iPhone [Apple Inc] or Android [Google]). The SML model was first fit in a training set (n=100) and then its accuracy was assessed in a held-aside test set (n=33). Within the test set, a likelihood ratio test (n=30) assessed whether adding individuals' SML-predicted probabilities of cessation to a logistic regression model that included demographic and tobacco use (eg, polyuse) variables explained additional variance in 4-week cessation. The SML model's sensitivity (0.67) and specificity (0.67) in the held-aside test set indicated that individuals' patterns of using different app features predicted cessation with reasonable accuracy. The likelihood ratio test showed that the logistic regression, which included the SML model-predicted probabilities, was statistically equivalent to the model that only included the demographic and tobacco use variables (P=.16). Harnessing user data through SML could help determine the features of smoking cessation apps that are most useful. This methodological approach could be applied in future research focusing on smoking cessation app features to inform the development and improvement of smoking cessation apps. ClinicalTrials.gov NCT04623736; https://clinicaltrials.gov/study/NCT04623736.

Multiple Table Models Based on Queuing Theory for Firefighting Traffic Problems

With the development of global urbanization, urban planning has been a hot spot of most concern. Since the traditional urban fire station setting method has been gradually unable to meet the emergency needs of a city. In this paper, a series of methods are developed to achieve the best balance between economic expenditure and reliability. According to the heat maps about emergency calls in a city in recent years, different types of alarm phones have obvious regional distribution characteristics. Inspired by the Queuing Theory algorithm, we abstract this complex problem into a parallel multi-server waiting queuing model to find each average queue length of three kinds of alarm calls and success in converting the multiplicity problem into solving the vehicle number and location problems respectively. Based on this planning problem, new combinations with different numbers of vehicles can be gotten. Then based on the assignment model, the optimal deployment plan can also be different with different numbers and geographical locations of the three kinds of stations. Our method significantly improves the firefighting traffic problems and can be applied in the actual situation.

Efficient smartphone-based measurement of phosphorus in water

Agricultural runoff is one of the main sources of excess phosphorus (P) in different water bodies, subsequently leading to eutrophication and harmful algal blooms. To effectively monitor P levels in water, there is a need for simple measurement tools and extensive public involvement to enable regular and widespread sampling. Several smartphone-based P measurement methods have been reported, which extract red-green-blue (RGB) values from colorimetric reactions to build statistical regression models for P quantification. However, these methods typically require meticulous light conditions, involve initial equipment investment, and have undergone limited testing for large-scale applications. To overcome these limitations, this study developed a smartphone-based, equipment-free and facile P colorimetric analysis method. Following the standard procedure of the ascorbic acid approach, colorimetric reactions were captured by a smartphone camera, and RGB values were extracted using Python code for modeling. Different indoor light conditions, phone types, containers, and types of water samples were examined, resulting in a collection of 1922 images. The best regression model, employing random forest with RGB values and container types as inputs, achieved an R2 of 0.97 and an RMSE of 0.051 for P concentrations ranging from 0.01 to 1.0 mg P/L. Additionally, the optimal classification model could estimate the level of P below 0.1 mg P/L with an accuracy of 95.2 (or 77.4 % for <0.05 mg P/L). The strong performance of the developed models, which are also available freely online, suggests an easy and effective tool for more frequent P measurement and greater public involvement.

Do baseline participant characteristics impact the effectiveness of a mobile health intervention for depressive symptoms? A post-hoc subgroup analysis of the CONEMO trials.

To ascertain whether sociodemographic and health-related characteristics known from previous research to have a substantive impact on recovery from depression modified the effect of a digital intervention designed to improve depressive symptoms (CONEMO). The CONEMO study consisted of two randomized controlled trials, one conducted in Lima, Peru, and one in São Paulo, Brazil. As a secondary trial plan analysis, mixed logistic regression was used to explore interactions between the treatment arm and subgroups of interest defined by characteristics measured before randomization - suicidal ideation, race/color, age, gender, income, type of mobile phone, alcohol misuse, tobacco use, and diabetes/hypertension - in both trials. We estimated interaction effects between the treatment group and these subgroup factors for the secondary outcomes using linear mixed regression models. Increased effects of the CONEMO intervention on the primary outcome (reduction of at least 50% in depressive symptom scores at 3-month follow-up) were observed among older and wealthier participants in the Lima trial (p = 0.030 and p = 0.001, respectively). There was no evidence of such differential effects in São Paulo, and no evidence of impact of any other secondary outcomes in either trial. NCT02846662 (São Paulo, Brazil - SP), NCT03026426 (Lima, Peru - LI).

Exploring social influence effect on mobile marketing behaviors of young consumers in the USA and Mexico

Purpose This study aims to investigate the effect of social influence and value-driven mobile marketing activities on consumers’ acceptance of mobile marketing offers. Design/methodology/approach The method used is survey questionnaire. A proposed model was tested by using structural model analysis and data gathered from 356 Mexico consumers and 346 US consumers. Findings The study shows the number of peers and providing information are the main predictor variables of consumer acceptance of mobile marketing offers in both countries. These results suggest that social value factors are important variables for explaining consumers’ responses to mobile marketing offers across two countries characterized by dissimilar macro-environmental conditions. Research limitations/implications The study’s overall implication about standardization vs adaptation is that social value messages can be standardized across countries. However, the marketing tools and touch points required to communicate any message appeal must be adapted across countries. One limitation in this study is the use of a convenience sample of undergraduate college students. This study did not control for different types of mobile phones and the screen sizes of mobile phones. Practical implications The overall implication of standardization vs adaptation from the study results is that social value messages can be standardized across countries. However, the marketing tools and touch points required to communicate any message appeal must be adapted across countries. Originality/value Unlike previous studies where the emphasis is to explicate the effect of value-oriented mobile activity, this study examines the combined effect of social influence and value-driven mobile activities on acceptance of mobile marketing.

The Advancement of Electronic Gadgets in 21st Century

The 21st Century was full of innovation when it came to the Tech Sector alone, be it the introduction of the Iphone, or the launch of the big conglomerates such as Facebook and Twitter. The 21st Century gave rise to the concepts of the Curved Displays on phones and the Foldable phones. There were numerous problems which were associated with the flat screen displays, and the shortcomings have been overcome by the Curved Displays and the Foldable phones as discussed in the paper. They have revolutionized the Technological market since their launch. Many Conglomerates such as Samsung, Honor, Xiaomi have invested millions of dollars in availing this new technology. However, currently Samsung has the lead over all its Chinese competitors, and with different companies investing in the new technology, the competition is predicted to become more intense. This will surely give customers a huge variety of phones to choose from. However, this technology did not come without its drawbacks. There were multiple issues associated with the Foldable Phones such as the weight associated with the phone when folded, the tensile strength of the Foldable phones is very low, and the User Interface is not something one could get excited about. Similar issues existed with Curved Displays as well, including costly repair costs, and it is harder to get a grip on compared to the Foldable phones due to the thinning of the edges. The paper discusses in depth the shortcomings of all the types of Phones, as well as which would be the best fit for the user, along with the current trend of the users, and what the Future holds for this segment of Technology.

An alternative flood measurement approach: Flood Meter

Flash floods commonly occur in urban areas due to a short period of heavy rainfall associated with the large impervious area and inadequate drainage system. An increase in the uncertainty of predicting flash floods, especially due to climate change, reduces the accuracy of the existing flood forecasting system. In such cases, the affected zone’s actual flood level data is required for more effective flood management and incident response. This study aims to develop a mobile application called Flood Meter to identify flood levels in real-time. It measured the flood level based on object scale and images taken by mobile phones. Although the validation using an actual flood event with three different types of mobile phones shows lack of accuracy but by considered the maximum flood level only 0.17 m and the result keep improving when flood level increase, it shows a potentially good agreement compared with manual measurement. The application can become an alternative method to disseminate accurate real-time flood situations as well as flood data collection for future flood risk management.

“It is a different type of policing than in the bush”: Police officers’ perceptions of the differences in enforcement of the phone use while driving legislation in rural and urban areas

Mobile phone use while driving continues to be a significant road safety concern, despite the severe legal countermeasures to reduce this behaviour. Phone use while driving-related crashes have been demonstrated to be an issue in rural areas, yet research into the impact of legal sanctions on phone use while driving has primarily focussed on urban areas. Therefore, this study aimed to investigate differences in enforcement of phone use while driving between rural and urban environments as reported by police officers. In addition, to provide necessary context, this study aimed to explore how the police officers perceive differences in drivers’ engagement in phone use while driving between rural and urban environments. To address these aims, a total of 26 police officers from Queensland, Australia (18 with both rural and urban experience, 6 with only rural experience and 2 with only urban experience) completed an interview. A total of seven themes were developed from the data. Several differences between rural and urban environments were identified concerning different types of phone offending behaviour, as well as different resources, management and infrastructure that can impact police enforcement. For example, it was suggested that drivers in rural areas have less reasons to use their phone while driving. Nevertheless, when this behaviour does occur, it is more challenging to enforce this law in rural compared to urban environments. The results not only provide important contextual information for phone use while driving research, but also suggest that enforcement strategies for this behaviour may need to be recontextualised to incorporate the more nuanced aspects of rural policing.

An Early Wake-up and Access Barring Scheme for Improving the Probability of NDP in BLE Networks

IoT (Internet of Things) has become attractive and ubiquitous in recent years. BLE (Bluetooth Low Energy) is a protocol widely used in IoT. For BLE, it has low cost, low energy consumption, and is supported on most types of mobile phones. BLE Beacon which is widely applied in many situations, such as shopping malls and indoor navigation, is an application based on the BLE network. This paper is aimed at proposing a feasible scheme to enhance the performance of the BLE Beacon application. communications in BLE networks involve the neighbor discovery process (NDP) in the first phase to create a connection or exchange information with neighbors. When more people with mobile devices simultaneously send requests to the BLE Beacon, the success probability of the NDP decreases and then the latency of the NDP increases. It leads to poor customer experience. Therefore, we propose an Early Wake-Up and Access Barring (EWAB) scheme to improve the NDP performance among an advertiser and multiple scanners. The scheme makes good use of the information that can be contained in the advertising packet to adjust the scan interval and the backoff window dynamically. The results show that EWAB provides better performance in terms of the probability of successful discovery, the mean discovery latency, and power consumption in the BLE networks.

MARKETING STRATEGY ANALYSIS IN INCREASING PRODUCT SALES AT LAKITA CELL IN MAKASSAR CITY

Strategy is a tool to achieve objectives. Marketing is a process influenced by various social, cultural, political, economic, and managerial factors. There are three systematic marketing strategy steps, starting with market segmentation strategy, target market determination strategy, and market positioning strategy. The marketing mix also includes marketing strategies, comprising four crucial points: product, price, place, and promotion. The purpose of this research is to analyze marketing strategies in increasing product sales at Lakita Cell in the city of Makassar. This study adopts a qualitative research design. Primary and secondary data sources are utilized for data collection. Data collection techniques consist of observation, interviews, and documentation. Data analysis involves three stages: data collection, data analysis, and decision-making. The research findings indicate that segmentation influences sales levels due to varying network quality in each area, while targeting does not significantly affect profits as sales levels fluctuate. Positioning has a significant impact on sales, profits, and company growth as Lakita Cell not only focuses on internet voucher sales but also provides services like interbank ATM transfers, digital money top-ups, and various types of mobile phone and electronic device essentials.

Increasing the value of digital phenotyping through reducing missingness: a retrospective review and analysis of prior studies

BackgroundDigital phenotyping methods present a scalable tool to realise the potential of personalised medicine. But underlying this potential is the need for digital phenotyping data to represent accurate and precise...

Development of a Fuzzy Model and Usability Test of a Recommended Interface Design for Mobile Phones for Elderly Users

Although mobile phone application developers aim to design software to be user-friendly, elderly users report having problems with flexible user interfaces. The purpose of this study was to examine a range of flexible user interface designs for mobile phones with the aim of locating and addressing the limitations reported by elderly users. Accordingly, a fuzzy model drawing on a range of variables was developed from an age/vision impaired related data set for the development of a variety of basic design elements for user interfaces. The model was tested to assess the preciseness and accuracy of its functions, achieving a Mean Absolute Error (MAE) close to 0 and an Effectiveness Index (EI) close to 1, giving the model a high value for effectiveness. A subsequent usability test of the generated design interfaces using four types of mobile phones (18 screens in all) was conducted among 25 elderly users with vision impairment. The findings showed that the size and shape of both numeric and function buttons was a significant factor in assessing phone usability both for communication and for social media use, as was text and number size, although, significantly, the latter was qualified by screen size. Recommended numeric and dial function button sizes are 15.6mm and 16.2 mm, respectively. Likewise, recommended text and numbers sizes are 14 and 25 points, respectively. Furthermore, square-shaped buttons with rounded-edge buttons are the most suitable for elderly users, as is a background in a light shade, with texts and icons in dark colors. The model demonstrates that it is possible to design user interfaces with particular groups in mind such as the elderly and vision-impaired, in order to enhance mobile phone usability for these groups.

The dynamism of communication technology adoption, market information and welfare: Evidence from Nile perch (Lates niloticus) fish market, Mwanza, Tanzania

AbstractDespite the growing importance of digital technology in modern society, its adoption in some sectors and regions has been slow. One such sector is fishing in developing countries, where the potential benefits of technology have yet to be fully realized. This study examines the adoption of communication technology among Nile perch fishers on Lake Victoria in Mwanza, Tanzania. Using a Probit model and Ordinary Least Square (OLS) estimations with Robust Standard Errors (OLSR), the study analyzes the impact of technology adoption on fishers' welfare, with a focus on income. The results suggest that the type of mobile phone, fishing experience, and the desire to exploit digital marketing are key factors in technology adoption among fishers. Furthermore, the study finds that technology adoption has a significant positive impact on fishers' welfare, indicating that digitalization can increase market competitiveness, openness, and improve livelihoods. To capitalize on these benefits, the study recommends that the government should support the digitalization of the fishing market and make accurate and timely market information readily available to fishers.

The National Wealth Score in the Brazilian National Survey on Child Nutrition (ENANI-2019).

The National Wealth Score (IEN) is a synthetic household index that assesses socioeconomic conditions. This study aims to present the methods used to update the IEN using data from the Brazilian National Survey on Child Nutrition (ENANI-2019). The following items were included: the education level of the mother or caregiver of the child; the number of bedrooms and bathrooms, TV sets, and cars in the household; and the presence of a radio, refrigerator or freezer, washing machine, microwave oven, telephone line, computers, air conditioner, media player devices, cable or satellite TV, cell phone ownership and type of service, cell phone internet, and internet at the household. Principal component analysis (PCA) was used to estimate the IEN with and without incorporating the complex sampling design (CSD). Thus, the IEN validation considered proxy indicators of socioeconomic status and living conditions. The first component of the PCA explained 31% and 71% of the variation with and without incorporating the CSD, respectively. The coefficients of variation of the IEN were 53.4% and 2.6% with and without incorporating the CSD, respectively. The mean IEN score was lower in households without access to a sewage system, those that received benefits from Brazilian Income Transfer Program, those with some degree of food insecurity, and those with stunted children. Adding ENANI-2019 items to the calculation of IEN to capture technological advances resulted in a better fit of the model. Incorporating the CSD increased PCA performance and the IEN precision. The new IEN has an adequate performance in determining the socioeconomic status of households with children aged under five years.