Mobile Technology Research Articles

Decídetexto: Mobile cessation support for Latino adults who smoke. A randomized clinical trial.

Latino adults experience multiple barriers to health care access and treatment that result in tobacco-related disparities. Mobile interventions have the potential to deliver smoking cessation treatment among Latino adults, the highest users of mobile technologies. Is Decídetexto, a culturally accommodated mobile health intervention, more effective for smoking cessation compared with standard care among Latinx adults who smoke? A two-arm parallel group randomized clinical trial (RCT) was conducted in Kansas, New Jersey, and New York between October 2018 and September 2021. Eligible Latino adults who smoke (n= 457) were randomly assigned to Decídetexto or a standard care group. The primary outcome was biochemically verified 7-day smoking abstinence at week 24. Secondary outcomes included self-reported 7-day smoking abstinence at weeks 12 and 24 and uptake and adherence of nicotine replacement therapy (NRT). Participants' mean age was 48.7 (SD, 11.1) years, 45.2%were female, and 50.3%smoked≥10 cigarettes per day. Two hundred twenty-nine participants were assigned to Decídetexto and 228 to standard care. Treating those lost to follow-up as participants who continued smoking, 14.4%of participants in the Decídetexto group were biochemically verified abstinent at week 24 compared with 9.2%in the standard care group (OR, 1.66; 95%CI, 0.93-2.97; P= .09). Treating those lost to follow-up as participants who continued smoking, 34.1%of the participants in the Decídetexto group self-reported smoking abstinence at week 24 compared with 20.6%of participants in the standard care group (OR, 1.99; 95%CI, 1.31-3.03; P< .001). Analyzing only participants who completed the assessment at week 24, 90.6%(174/192) of participants in the Decídetexto group self-reported using NRT for at least 1day compared with 70.2%(139/198) of participants in standard care (OR, 4.10; 95%CI, 2.31-7.28; P< .01). Among Latino adults who smoke, the Decídetexto intervention was not associated with a statistically significant increase in biochemically verified abstinence at week 24. However, the Decídetexto intervention was associated with a statistically significant increase in self-reported 7-day smoking abstinence at weeks 12 and 24 and uptake of NRT. This RCT provides encouragement for the use of Decídetexto for smoking cessation among Latino adults. ClinicalTrials.gov identifier: NCT03586596.

Enhancing 5G network performance through effective resource management with network slicing

The immense growth of mobile networks leads to versatile applications and new demands. The improved concert, transferability, flexibility, and performance of innovative network services are applied in diversified fields. More unique networking concepts are incorporated into state-of-the-art mobile technologies to expand these dynamic features further. This paper presents a novel system architecture of slicing and pairing networks with intra-layer and inter-layer functionalities in 5th generation (5G) mobile networks. The radio access network layer slices and the core network layer slices are paired up using the network slicing pairing functionalities. The physical network elements of such network slices will be logically assigned entities called softwarization of the network. Such a novel system architecture called network sliced softwarization of 5G mobile networks (NSS-5G) has shown better performances in terms of end-to-end delay, total throughput, and resource utilization when compared to traditional mobile networks. Thus, effective resource management is achieved using NSS-5G. This study will pave the way for future softwarization of heterogeneous mobile applications.

KIERUNKI ROZWOJU APLIKACJI MOBILNYCH W DIAGNOSTYCE I TERAPII SZUMÓW USZNYCH: PRZEGLĄD LITERATURY NAUKOWEJ

IntroductionTinnitus is a condition that requires multidisciplinary care and monitoring. Widespread use of mobile devices and ready access to the internet offers a possible solution since smartphones can run apps programmed for a particular health problem. The aim of the article is to assess the scale and direction of how mobile apps are being created and used to diagnose and treat tinnitus.Material and methodsPublications in Google Scholar, PubMed, and ResearchGate were searched for the years 2010–2023. The results of the review were organized by themes.ResultsHits were organized into the following themes: (1) existing mobile apps for tinnitus, (2) apps supporting the diagnosis of tinnitus, (3) apps supporting tinnitus therapy, (4) a look to the future – sensors built-in or connected to mobile devices, wearables, artificial intelligence (AI), and big data systems.ConclusionsSmartphone-based apps with ecological momentary assessment methods and the possibilities of using wearable diagnostic devices might be useful in better understanding the variability of tinnitus and perhaps its causes. Mobile crowdsensing and central databases with big data and artificial intelligence support appear to be a valuable resource for new scientific research. There are now mobile apps providing a variety of therapies – sound therapy, self-help psychology, and educational training. Equally important for tinnitus therapy are smart devices managed by mobile apps – hearing aids, cochlear implants, and other hearables. In the future, development of mobile technologies and artificial intelligence will help create smart therapy platforms for tinnitus.

Does Fintech Affect Bank Profitability? Empirical Insights from Malaysia

Objectives: This study investigates the influence of Fintech on the profitability of Malaysian banks. It aims to assess both accounting measures, such as Return on Assets (ROA) and Net Interest Margin (NIM), and market performance measures, including Tobin's Q. The research utilizes bank-level metrics like the intangible asset ratio and the ATM-to-branch ratio, along with a country-level Fintech index that combines data on ATM, smartphone usage, and internet penetration. The study seeks to understand the complex dynamics between Fintech investments and bank profitability, providing insights for various stakeholders, including policymakers, banks, investors, and consumers. Methods: The research employs a panel regression analysis to explore the relationship between Fintech developments and bank profitability. The analysis covers publicly listed banks in Malaysia from 2010 to 2022. Key variables include the intangible asset ratio as a proxy for IT investment in Fintech, the ATM-to-branch ratio, and a comprehensive Fintech index at the country level. The study also considers market risk exposure, using Value at Risk (VaR) as an indicator. The approach is grounded in the resource-based view theory, suggesting that Fintech can provide competitive advantages through data analytics, mobile technology, and enhanced cybersecurity. Results: The findings reveal that Fintech investments at the bank level, indicated by the intangible asset ratio, have a positive impact on NIM. This supports the notion that technology-driven innovations can enhance profitability. However, the study also uncovers a contrasting effect at the country level, where broader Fintech development appears to negatively impact bank profitability. This suggests a more complex interplay between technological advancement and market dynamics, including increased competition from digital payment systems and peer-to-peer lending platforms. Additionally, the research highlights that banks with higher exposure to market risk, as indicated by VaR, tend to achieve better profitability metrics, such as ROA, NIM, and Tobin's Q. Conclusion: The study concludes that while Fintech investments at the bank level can enhance profitability, broader Fintech development in the country may pose challenges to traditional banking profitability due to increased competition and market disruption. The results underscore the importance of strategic agility, advanced risk management, and innovation in banking practices to navigate the evolving financial landscape. The findings offer valuable insights for stakeholders, emphasizing the need for tailored regulatory approaches, strategic investments in technology, and innovations that focus on consumer needs. This nuanced understanding of the Fintech-bank profit nexus can help guide more informed decision-making in the industry.

Climate change awareness and information utilisation and dissemination in rural areas of Nsanje district

Background: Climate information communication is the heart of climate service delivery which provide knowledge to help guide individuals and other stakeholders to make climate smart decisions. Therefore, this study explored awareness, utilization and dissemination of climate information in rural areas of Nsanje district. Methods: The study used both quantitative and qualitative research design that does not involve the designing of an experiment. This focuses much on the descriptive research design. The advantage of using this research design in this study was that the participants’ accuracy was clearly depicted. Finding: The results showed that 63 percent of the people in rural areas access climate information through radio and 33 percent do not use it at all. Multinomial logistic regression indicate that floods and crop pests are significant predictors of the location of an individual whether lives in flood prone area or not with p-values of 0.02 and 0.04 respectively, and this shows that people understand climate change based on the impacts felt. This also shows that crop pests are more prevalent in flood prone zones. Conclusion: The study concluded that there is a need to adopt climate communication channels that are more interactive and recruit more extension workers who are agents to promote the use of climate information. Novelty/Originality of this article: This study proposes developing a community-based interactive climate communication model that integrates mobile technology and local extension worker networks to improve the accessibility and understanding of climate information in rural areas.

Insights into the microscopic heterogeneity of whey proteins between yak colostrum and mature milk based on 4D lable-free quantitative phosphoproteomics

This study aimed to reveal the change patterns of the phosphorylation modification status of yak whey phosphoproteins during lactation and their physiological effects. Herein, we comprehensively characterized whey phosphoproteome in yak colostrum and mature milk using an ultra-high throughput phosphoproteomics approach incorporating trapped ion mobility technology. A total of 344 phosphorylation sites from 206 phosphoproteins were identified, with individual site modification predominating. Notably, 117 significantly different phosphorylation sites were distributed on 89 whey phosphoproteins. Gene ontology analysis indicated that these significantly different whey phosphoproteins (SDWPPs) were mainly annotated to carbohydrate metabolic process, membrane, extracellular region and calcium ion binding. Metabolic pathway enrichment analysis demonstrated that SDWPPs were critically involved in protein processing in endoplasmic reticulum, NOD-like receptor signaling pathway and N-glycan biosynthesis. Our results elucidate the phosphorylation profiles of yak whey phosphoproteins at different lactations and their adaptive regulatory role in meeting the nutritional requirements of yak calves during development.

Artificial intelligence and electrocardiography: A modern approach to heart rate monitoring

The integration of Artificial Intelligence (AI) in Electrocardiography (ECG) and Photoplethysmography (PPG) signifies AI's profound influence on heart rate monitoring and analysis. ECG traditionally offers critical insights into cardiac health, necessitating expert interpretation. This study introduces an AI framework with Fast Fourier Transformation Analysis for swift, human-like interpretation of complex ECG signals. A multilayer AI Network accurately detects intricate features, enhancing ECG analysis precision. Leveraging comprehensive datasets, AI models proficiently identify heart dysfunctions like atrial fibrillation and hypertrophic cardiomyopathy, and can estimate age, sex, and race. The proliferation of mobile ECG technologies has spurred AI-based ECG phenotyping, impacting clinical and population health. This research explores AI's role in enhancing cardiac health assessment and clinical decision-making using MATLAB, acknowledging its transformative potential and inherent limitations.

High-temperature relaxation and microwave dielectric response of (1-x)BaNd1.76Bi0.24Ti5O14-xBa0.6Sr0.4La4Ti4O15 compounds with adjustable medium-high dielectric constant

Dielectric ceramics in the microwave band are one of the crucial materials for mobile communication technology, and the studying of their phase evolution and defect behavior can help to understand and reduce dielectric loss. In this work, (1-x)BaNd1.76Bi0.24Ti5O14-xBa0.6Sr0.4La4Ti4O15 (x = 0.2, 0.4, 0.6 and 0.8, (1-x)BNT-xBSLT) ceramics were synthesized by solid-state reaction method. X-ray diffraction (XRD) and Raman spectra analysis reveal that tungsten bronze and hexagonal perovskite phases coexist in the ceramics, and BaNd2Ti3O10 is indexed as the main crystalline phase at x = 0.4, 0.6, leading to a deterioration of the microwave dielectric properties. The defect-related relaxation behavior and its effect on microwave dielectric properties were analyzed by dielectric temperature spectrum and thermally stimulated depolarization current (TSDC). The relationship between the dielectric constant and the electric field distribution was solved using the eigenmode of the high frequency structure simulator. In short, the (1-x)BNT-xBSLT ceramics at x = 0.8 exhibit excellent microwave dielectric properties: εr = 47.2, Q×f = 16,800 GHz, and τf = −4.6 ppm/°C. The microwave dielectric response of BNT-BSLT composite ceramics is closely related to the phase composition and defects, which is informative for the development of low dielectric loss ceramics.

Balancing Technological Innovation and Environmental Sustainability: A Lifecycle Analysis of 6G Wireless Communication Technology

Wireless communication has revolutionized the evolution of humankind. The rapid growth and development of mobile communication has created an ecosystem better than what has been before. However, issues such as ample energy consumption and resulting carbon emissions, a lack of proper disposal mechanisms for large amounts of electronic waste, and the recycling of electronic materials interrupt growth. When the world is waiting for the implementation of 6G mobile communication technology, it is mandatory to resolve these issues for the sustainability of 6G technology. In this review, we present the superiority of 6G over previous generations accompanied by issues that cause extensive damage to the environment. To mitigate this adverse effect, we present a lifecycle analysis of 6G wireless communication technology from production to disposal, focusing on issues surrounding electronic waste, energy consumption, and environmental impact. This study explains the intricacies of electronic parts, toxic compounds, and the dangers of incorrect disposal techniques. It also investigates energy consumption issues specific to 6G technology, such as manufacturing processes and network infrastructures that require considerable energy. We also present a quantitative evaluation of the 6G lifecycle in detail. In addition, we present a comprehensive strategy and insights to make 6G sustainable. Furthermore, we suggest an ecological policy for all stakeholders for the sustainability of 6G. We also present political and commercial implications for 6G. As the process of 6G development continues, we show the impact of network fragmentation on standardization, which helps improve sustainability. Finally, we conclude that while the existing research has made significant advances in 6G, there is a need for correct disposal techniques to refine the key government policies for managing e-waste. New cooling technologies and renewable energy sources must be adopted to reduce the current greenhouse emission of 200 g of CO2 and energy consumption of 2.5 kWh per GB for 6G networks.

Strategi Manajemen Memori pada Sistem Operasi Android untuk Smartphone Kelas Menengah

In the context of rapidly evolving mobile technology, memory management has become an important aspect that determines the efficiency and effectiveness of Android operating systems, particularly on mid- range smartphones. The objective of this research is to identify, analyze and develop memory management strategies that can improve the performance of the Android operating system on resource-constrained devices. Using an experimental approach, this study evaluates various memory management techniques, including the use of optimized caches, memory compression, and page replacement algorithms, to determine the most effective combination to improve system responsiveness and performance. The results show that the implementation of appropriate memory management strategies can significantly improve operating system performance and user experience while extending battery life. These findings provide valuable information for application developers and device manufacturers to optimize their products for mid-range smartphone competition.

Enhancing Driving Safety through User Experience Evaluation of the C-ITS Mobile Application: A Case Study of the DARS Traffic Plus App in a Driving Simulator Environment.

The paper evaluates the DARS Traffic Plus mobile application within a realistic driving simulator environment to assess its impact on driving safety and user experience, particularly focusing on the Cooperative Intelligent Transport Systems (C-ITS). The study is positioned within the broader context of integrating mobile technology in vehicular environments to enhance road safety by informing drivers about potential hazards in real time. A combination of experimental methods was employed, including a standardised user experience questionnaire (meCUE 2.0), measuring quantitative driving parameters and eye-tracking data within a driving simulator, and post-experiment interviews. The results indicate that the mobile application significantly improved drivers' safety perception, particularly when notifications about hazardous locations were received. Notifications displayed at the top of the mobile screen with auditory cues were deemed most effective. The study concludes that mobile applications like DARS Traffic Plus can play a crucial role in enhancing road safety by effectively communicating hazards to drivers, thereby potentially reducing road accidents and improving overall traffic safety. Screen viewing was kept below the safety threshold, affirming the app's efficacy in delivering crucial information without distraction. These findings support the integration of C-ITS functionalities into mobile applications as a means to augment older vehicle technologies and extend the safety benefits to a broader user base.

Rolling optimal scheduling for urban parcel crowdsourced delivery with new order insertion

The rapid development of mobile information technology has introduced numerous new solutions for delivery companies to enhance profits. One such solution employed by some companies is crowdsourced delivery. In this paper, we focus on rolling optimal scheduling for urban parcel crowdsourced delivery by utilizing private cars that will be in passing with the incorporation of new order insertion. The bonus incentive strategy is introduced to enhance the delivery probability of private car drivers. A static model and a rolling optimization model to maximize profits and the number of parcels delivered by private cars are established. To address the NP-hard problem, a hybrid genetic algorithm and insertion algorithm are designed. Numerical experiments are carried out to verify the proposed method in different scenarios, including the scattered network, clustered network, Dalian network, and Foursquare network. The computational results demonstrate that the method enhances the matching ratio and increases profits. Utilizing private cars that will be in passing for urban parcel delivery reduces the need for dedicated vehicles, mitigating traffic growth and alleviating traffic congestion. Increasing the private car-parcel ratio improves profits and the matching ratio while reducing traffic growth. Raising the incentive coefficient for bonuses increases the matching ratio and detour distance, but profits first increase and then decrease, and delivery distance by dedicated vehicles decreases. Our research findings offer a more rational basis for green urban parcel delivery decision-making by companies.

Highly reliable DHR-based polar compilation code communication method

The advent of fifth-generation mobile communication technology, 5G, has raised the bar for data transmission rates, information security, and reliability. Polar codes, the channel coding scheme in the 5G communication standard, encounter issues of singularity, limitations, and passivity in the face of unknown attacks. Therefore, this study introduces a highly reliable DHR-based polar coding communication approach. Drawing parallels between cyber attacks and channel noise, the method incorporates reconfigurable executors, decoding decisions, strategy scheduling, and other mechanisms to enable active defense. The True Relatively Axiom (TRA) is employed to theoretically validate the method’s heterogeneity, redundancy, and dynamics. Comparative simulation experiments with traditional polar decoding algorithms, such as SCL, SC, BP, SCAN, and SSC decoding algorithms, demonstrate that the proposed method not only improves secure transmission efficiency but also guarantees secure and reliable transmission across various attack scenarios. Our code is available at https://github.com/yuluzi/my-code.git.

INVESTIGATION OF HIGH SCHOOL STUDENTS’ EXPOSURE TO PHUBBING BEHAVIOR

Technological behavioral disorders have become prevalent issues nowadays. Uncontrolled and excessive time spent on the internet, along with the addictive use of mobile phones, brings along problems in social relationships, feelings of deprivation, and situations such as mobile device or technology addiction. The situation of being unable to live without a phone and consciously ignoring people around oneself has begun to be defined as 'Phubbing'. The main aim of this study is to examine high school students' instances of displaying Phubbing behavior concerning various demographic variables such as school type, gender, grade level, family relationships, and friendships. It is believed that this study will create an awareness of Phubbing behavior and contribute to the literature by providing insights into situations negatively affecting interpersonal communication, thereby enabling necessary precautions to be taken. The aim of this study is to examine Phubbing behavior among high school students concerning various demographic variables (school type, gender, grade level, family relationships, friendship relationships, duration of internet usage). The study was conducted based on a quantitative research method using a survey design. The 'General Phubbing Scale’ was employed as the data collection instrument. A total of 353 students from both private and public high schools in a province in the Central Anatolia region participated in the research during the 2022-2023 academic year. In addition to descriptive statistics for the analysis of quantitative data obtained from the scale, tests examining differences between means, such as independent sample t-Test and one-way analysis of variance (ANOVA), were utilized. Upon examination of the findings from the study, no significant difference was found concerning Phubbing behavior based on gender. However, significant differences were observed in demonstrating Phubbing behavior among students based on school type, phone usage durations, and family and friendship relationships. The research concludes with some recommendations.

Quantum-attack-resilience OTP-based multi-factor mutual authentication and session key agreement scheme for mobile users

Due to rapid advancements in hardware and mobile communication technologies, the usage of various mobile-based online applications is increasing tremendously. However, security and privacy are two of the most essential features of wireless communication. Using a Mutual Authentication and Session Key Agreement (MASK) scheme, an authorized mobile user can login to a remote server over the Internet. In quantum contexts, many of the MASK schemes are not secure. This paper proposes a One-Time Password (OTP) and biometric-based Multi-Factor MASK (OTP-MF-MASK) scheme for mobile users. We used Peikert’s authentication and reconciliation mechanism, defined for the post-quantum environments. The OTP-MF-MASK scheme used a password, mobile device, biometric, and OTP as login credentials. To avoid the biometric acquisition problem, we used the fuzzy extractor in the OTP-MF-MASK scheme. We proved that the OTP-MF-MASK scheme is semantically secure in the Random Oracle Model (ROM) based on the hardness assumption of the Ring Learning With Errors (RLWE) problem. The OTP-MF-MASK scheme is compared with state-of-the-art schemes to justify the attack-resilience and computation efficiencies in quantum environments.

Handover for V2V communication in 5G using convolutional neural networks

Vehicle communication is one of the most vital aspects of modern transportation systems because it enables real-time data transmission between vehicles and infrastructure to improve traffic flow and road safety. The next generation of mobile technology, 5G, was created to address earlier generations' growing need for high data rates and quality of service issues. 5G cellular technology aims to eliminate penetration loss by segregating outside and inside settings and allowing extremely high transmission speeds, achieved by installing hundreds of dispersed antenna arrays using a distributed antenna system (DAS). Huge multiple-input multiple-output (MIMO) systems are accomplished via DASs and huge MIMO systems, where hundreds of dispersed antenna arrays are built. Because deep learning (DL) techniques employ artificial neural networks with at least one hidden layer, they are used in this study for vehicle recognition. They can swiftly process vast quantities of labeled training data to identify features. Therefore, this paper employed the VGG19 DL model through transfer learning to address the task of vehicle detection and obstacle identification. It also proposes a novel horizontal handover prediction method based on channel characteristics. The suggested techniques are designed for heterogeneous networks or horizontal handovers using DL. In the designated surrounding regions of 5G environments, the suggested detection and handover algorithms identified vehicles with a success rate of 97 % and predicted the next station for handover.

‘Watch the closing doors’- material interpellation, mobility affordance, and passenger sensations

The multi-sensorial and embodied experiences of ‘being transported’ as passengers are an important, but at times underemphasized, theme in transport policy and planning. Asking the key question ‘how does it feel?’ seems straight forward and yet still hard to accommodate in the realm of planning and transport policies. However, if the ‘way that we feel’ is what attunes us to be attracted (or the opposite) to different modes of transport, then the affective, embodied, and sensorial qualities of buses, subways, airplanes, and ferries is more than an issue of ‘comfort’ and competitive advantage (even though this is a central concern for public transport agencies in the post-covid 19 context). Rather, we should understand how the enrolment of human bodies into infrastructural systems and mobility technologies shape our experiences in the everyday life. This paper hones in on a few theoretical concepts developed under the umbrella of ‘mobilities design’. Seen as a field of ‘material pragmatism’ it presents concepts such as ‘material interpellation’, ‘mobility affordance’, ‘extended bodies’, and ‘osmosis’ as part of a vocabulary enabling a more granular understanding of how we experience the world as passengers.

Using Multimodal Assessments to Reevaluate Depression Designations for Spine Surgery Candidates.

Depression is common in spine surgery candidates and may influence postoperative outcomes. Ecological momentary assessments (EMAs) can overcome limitations of existing depression screening methods (e.g., recall bias, inaccuracy of historical diagnoses) by longitudinally monitoring depression symptoms in daily life. In this study, we compared EMA-based depression assessment with retrospective self-report (a 9-item Patient Health Questionnaire [PHQ-9]) and chart-based depression diagnosis in lumbar spine surgery candidates. We further examined the associations of each depression assessment method with surgical outcomes. Adult patients undergoing lumbar spine surgery (n = 122) completed EMAs quantifying depressive symptoms up to 5 times daily for 3 weeks preoperatively. Correlations (rank-biserial or Spearman) among EMA means, a chart-based depression history, and 1-time preoperative depression surveys (PHQ-9 and Psychache Scale) were analyzed. Confirmatory factor analysis was used to categorize PHQ-9 questions as somatic or non-somatic; subscores were compared with a propensity score-matched general population cohort. The associations of each screening modality with 6-month surgical outcomes (pain, disability, physical function, pain interference) were analyzed with multivariable regression. The association between EMA Depression scores and a depression history was weak (rrb = 0.34 [95% confidence interval (CI), 0.14 to 0.52]). Moderate correlations with EMA-measured depression symptoms were observed for the PHQ-9 (rs = 0.51 [95% CI, 0.37 to 0.63]) and the Psychache Scale (rs = 0.68 [95% CI, 0.57 to 0.76]). Compared with the matched general population cohort, spine surgery candidates endorsed similar non-somatic symptoms but significantly greater somatic symptoms on the PHQ-9. EMA Depression scores had a stronger association with 6-month surgical outcomes than the other depression screening modalities did. A history of depression in the medical record is not a reliable indication of preoperative depression symptom severity. Cross-sectional depression assessments such as PHQ-9 have stronger associations with daily depression symptoms but may conflate somatic depression symptoms with spine-related disability. As an alternative to these methods, mobile health technology and EMAs provide an opportunity to collect real-time, longitudinal data on depression symptom severity, potentially improving prognostic accuracy. Diagnostic Level III. See Instructions for Authors for a complete description of levels of evidence.

Influence of Tiktok video content on youth people's online shopping intention for fashion items

This study delves into the influence of TikTok video content factors - Entertainment, Information, Usefulness, and Interaction - on the online purchase intention of fashion items among young consumers. Drawing upon the Integrated Theory of Planned Behavior, ABC model (Attitude, Behavior, Context), and Mobile Technology Acceptance Model framework, the research examines how these factors shape consumer behavior on popular social media platforms. A quantitative approach was employed, utilizing survey data collected from 620 young respondents in Vietnam. The findings reveal that Entertainment, Information, Usefulness, and Interaction significantly impact online purchase intention, with Usefulness and Interaction emerging as the primary drivers. However, the study also acknowledges several limitations, including sample size constraints and potential biases inherent in self-reported data. Future research directions include longitudinal studies to explore the dynamic nature of consumer behavior on TikTok and comparative studies across different demographic groups to enhance generalizability. This study contributes valuable insights for marketers and advertisers seeking to leverage TikTok as a platform for engaging young consumers and driving online purchase behavior in the fashion industry.

The Development of the Smartphone Proficiency Questionnaire for Chinese Older Adults (SPQ-COA).

While mobile technology is rapidly evolving, it remains a challenge for some older adults to use smartphones worldwide. To address this issue through tailored skill training and product design, this study developed a questionnaire to assess the smartphone proficiency of older adults. The Smartphone Proficiency Questionnaire for Chinese Older Adults (SPQ-COA) assessed proficiency based on 30 up-to-date tasks (e.g., mobile payment), that covered common operations in daily life of Chinese older adults. The questionnaire was distributed to 452 older adults (age ≥60), as well as 100 young adults (age: 18-30) as a control group. The questionnaire performed well in terms of reliability, difficulty, and discrimination. Among older adults, higher scores were associated with lower age, longer daily use duration, more years of use, higher monthly income, and higher education level, further validating the questionnaire. Overall, the SPQ-COA is a valid tool for evaluating Chinese older adults' smartphone usage skills.