Smartphone-based Online Research Articles

Understanding and predicting customers’ intentions to use smartphone-based online games: A deep-learning-based dual-stage modelling analysis

Building upon flow theory, the present research empirically investigates the impact of customers' attitudes on their intention to use smartphone-based online gaming. It also examines the mediating effects of customers’ perceived flow and engagement between attitudes and customer's intention to use smartphone-based online gaming. Furthermore, customers' cognitive involvement was also examined as a moderator in between attitude and perceived flow. The data were analysed using a dual-stage hybrid method embedded with PLS-SEM and ANN. A sample of 688 smartphone-based online game players was surveyed, and the results support the notion that customers' attitudes, considered as a formative construct, significantly influence intention to use smartphone-based online gaming. The study further confirms that perceived flow and customer engagement mediate the relationship between attitudes and intention to use smartphone-based online gaming. The study also identifies the role of cognitive involvement as a significant moderator in between customers' attitudes and perceived flow. Contributions for both theory and practice are presented in the concluding sections.

Associations between light exposure and sleep timing and sleepiness while awake in a sample of UK adults in everyday life

Experimental and interventional studies show that light can regulate sleep timing and sleepiness while awake by setting the phase of circadian rhythms and supporting alertness. The extent to which differences in light exposure explain variations in sleep and sleepiness within and between individuals in everyday life remains less clear. Here, we establish a method to address this deficit, incorporating an open-source wearable wrist-worn light logger (SpectraWear) and smartphone-based online data collection. We use it to simultaneously record longitudinal light exposure (in melanopic equivalent daylight illuminance), sleep timing, and subjective alertness over seven days in a convenience sample of 59 UK adults without externally imposed circadian challenge (e.g., shift work or jetlag). Participants reliably had strong daily rhythms in light exposure but frequently were exposed to less light during the daytime and more light in pre-bedtime and sleep episodes than recommended [T. M. Brown et al., PLoS Biol. 20, e3001571 (2022)]. Prior light exposure over several hours was associated with lower subjective sleepiness with, in particular, brighter light in the late sleep episode and after wake linked to reduced early morning sleepiness (sleep inertia). Higher pre-bedtime light exposure was associated with longer sleep onset latency. Early sleep timing was correlated with more reproducible and robust daily patterns of light exposure and higher daytime/lower night-time light exposure. Our study establishes a method for collecting longitudinal sleep and health/performance data in everyday life and provides evidence of associations between light exposure and important determinants of sleep health and performance.

Use of Smartphones for Social and Sexual Networking among Transgender Women in South India: Implications for Developing Smartphone-based Online HIV Prevention Interventions.

Smartphone use is increasing among transgender women (TGW), including those who engage in sex work. Current government-supported HIV prevention interventions focus on physical venue-based outreach among TGW, missing the opportunity to reach them through smartphone-based interventions. We examined the use of smartphones among TGW, especially in relation to social and sexual networking, and explored their perspectives on their willingness to use smartphone-based HIV prevention interventions. Through an exploratory descriptive-interpretive qualitative research design, we conducted 6 focus groups with a purposive sample of 30 TGW (70% in sex work) and 4 key informant in-depth interviews in Chennai and Hyderabad, India. Data were explored using framework analysis. Through smartphones, TGW used social media (e.g., WhatsApp and Facebook) and dating applications for socialization, meeting sexual partners, and entertainment. Low-literacy TGW used voice or video messaging. TGW expressed interest in receiving short health-related videos and text messages on HIV, mental health, and gender transition. At-risk TGW could potentially be reached through smartphone-based online health promotion interventions, but those interventions need to be holistic - moving beyond HIV.

Cellulose acetate/MOF film-based colorimetric ammonia sensor for non-destructive remote monitoring of meat product spoilage

Herein, we designed an on-site and portable colorimetric assay using cellulose acetate polymeric films incorporated with HKUST-1 metal-organic framework while immersed in a solution of methyl red and brilliant cresyl blue organic dyes as an indicator for monitoring ammonia levels. Ammonia serves as a significant biomarker of food spoilage which falls under the category of volatile organic compounds (VOCs). The designed colorimetric solid-state sensor was comprehensively characterized using FE-SEM, EDS-mapping, XRD, FTIR, and contact angle analyses. The results confirmed the superior stability, water permeability, good crystallinity and desirable morphology of the prepared sensor platform. Additionally, customized smartphone was developed and applied for online signaling and colorimetric analysis. The findings demonstrated two linear ranges: 1–100 ppb and 0.1–1340 ppm with a detection limit of 0.02 ppm. The solid-state sensor exhibited high selectivity in the presence of other VOCs such as methanol, ethanol, acetone, 2-propanol, toluene, humidity, and hexane. It displayed acceptable repeatability in both inter-day (RSD = 3.38 %) and intraday (RSD = 3.86 %), long-term stability over 4 days as well as reusability over 3 cycles. We successfully applied this sensing platform for ammonia monitoring in spoiled meat foods including veal, fish and chicken. The results indicated favorable percentage recovery and repeatability, confirming the feasibility and potential applicability of this intelligent packaging system for monitoring freshness. The platform allows for real-time monitoring and data analysis via smartphone-based online signaling, providing a convenient and effective method for ensuring food quality.

A smartphone-based online platform for clinical skills training and assessment with standardized patients: platform development and pilot study outcomes

ABSTRACT There are limitations and difficulties in the management of traditional in-person standardized patient (SP) practice. The latest developments in online communication tools and the COVID-19 pandemic have promoted the needs for online clinical skills training objectively. However, existing commercial online platforms may not meet the requests for SP-based medical simulation. This paper described the methodology applied to develop a smartphone-based online platform for the management of clinical skills training and assessment with remote SPs, and aimed to determine whether this new platform is acceptable or useful through a pilot run in September 2020. The post-run survey including questionnaire inspired by technological acceptance model and determinants of the perceived ease of use was used to assess the acceptability and usefulness of the platform. Twenty four-year students of clinical medicine participated in the pilot study with twenty SPs and ten faculties. Data from the post-run survey showed that there was a general recognition that the platform is easy to use among all the users. Two questions regarding the usefulness of the platform showed significant differences between the SPs/faculties and the students. More SPs found the platform useful as a training method than the students did. The faculties showed more attempts than the students to use this platform for clinical skills training in the future. This smartphone-based online platform was widely accepted among the tested students, SPs and faculties, which meets the requests and challenges of the new era. It provides an effective approach for clinical skills training and assessment with remote SPs.

High monkeypox vaccine acceptance among male users of smartphone-based online gay-dating apps in Europe, 30 July to 12 August 2022.

We assess monkeypox vaccination acceptance among male adults in the European Region. We conducted an online survey through two dating apps targeting men who have sex with men, from 30 July to 12 August 2022. We developed Bayesian hierarchical logistic regression models to investigate monkeypox vaccination acceptance. Overall crude vaccination acceptance was 82% and higher in north-western compared to south-eastern European regions. Acceptance strongly rose with perception of increased disease severity and transmission risk, and in individuals linked to healthcare.

Surveying Spontaneous Mass Protests: Mixed-mode Sampling and Field Methods

Protest survey is a standard tool for scholars to understand protests. However, although protest survey methods are well established, the occurrence of spontaneous and leaderless protests has created new challenges for researchers. Not only do their unpredictable occurrences hinder planning, their fluidity also creates problems in obtaining representative samples. This article addresses these challenges based on our research during Hong Kong’s Anti-Extradition Law Amendment Bill Movement. We propose a mixed-mode sampling method combining face-to-face survey and smartphone-based online survey (onsite and post hoc), which can maximize sample sizes while ensuring representativeness in a cost-effective manner. Test results indicate that key variables from the survey modes are not statistically different in a consistent manner, except for age. Our findings show mixed-mode sampling can better capture protesters’ characteristics in contemporary protests and is replicable in other contexts.

A smartphone-based online system for fall detection with alert notifications and contextual information of real-life falls

BackgroundFalls are a leading cause of accidental deaths and injuries worldwide. The risk of falling is especially high for individuals suffering from balance impairments. Retrospective surveys and studies of simulated falling in lab conditions are frequently used and are informative, but prospective information about real-life falls remains sparse. Such data are essential to address fall risks and develop fall detection and alert systems. Here we present the results of a prospective study investigating a proof-of-concept, smartphone-based, online system for fall detection and notification.MethodsThe system uses the smartphone’s accelerometer and gyroscope to monitor the participants’ motion, and falls are detected using a regularized logistic regression. Data on falls and near-fall events (i.e., stumbles) is stored in a cloud server and fall-related variables are logged onto a web portal developed for data exploration, including the event time and weather, fall probability, and the faller’s location and activity before the fall.ResultsIn total, 23 individuals with an elevated risk of falling carried the phones for 2070 days in which the model classified 14,904,000 events. The system detected 27 of the 37 falls that occurred (sensitivity = 73.0 %) and resulted in one false alarm every 46 days (specificity > 99.9 %, precision = 37.5 %). 42.2 % of the events falsely classified as falls were validated as stumbles.ConclusionsThe system’s performance shows the potential of using smartphones for fall detection and notification in real-life. Apart from functioning as a practical fall monitoring instrument, this system may serve as a valuable research tool, enable future studies to scale their ability to capture fall-related data, and help researchers and clinicians to investigate real-falls.

Understanding Smartphone-based Online Shopping Experiences and Behaviors of Blind Users

Understanding Smartphone-based Online Shopping Experiences and Behaviors of Blind Users

The effectiveness of a smartphone-based online peer group on type II diabetes mellitus patients self-empowerment in a primary healthcare center in Indonesia

Objective: Self-empowerment is an important factor that influences a person's ability to perform effective diabetes management. One effort that can be done to improve self-empowerment is by providing a smartphone-based online peer-group. This research determined the effect of smartphone-based online peer groups on type 2 diabetes mellitus (T2DM) patients self-empowerment in four primary healthcare centers in Indonesia. Methods: This quasi-experimental research was conducted in four healthcare centers in Indonesia. The total sample was 71 divided into two groups (control and intervention). The control group received standard education from the healthcare center, whereas the intervention group underwent an online peer-group. Self-empowerment was measured before and after intervention using the Diabetes Empowerment Scale-Short Form (DES-SF) questionnaire (Indonesian version). General Linear Model was used in statistical analysis. Results: The mean age of respondents was 56.4 ± 8.8 and 56.9 ± 7.1 years old, 59.5%, and 76.5% had good family support, and 70.3% and 50% of respondents had not received diabetes education for the control and intervention groups, respectively. The average pretest self-empowerment score was 27.03 ± 3.73 and 27.59 ± 3.53 (diff. 0.56; 95%CI -1.16; 2.29), and the post-test score was 27.43 ± 4.13 and 32.76 ± 4.38 (diff. 5.33; 95%CI 3.32; 7.35) for the control and intervention groups, respectively. Online peer-group improve self-empowerment significantly in the intervention group. Conclusion: Smartphone-based online peer-group can improve self-empowerment in patients with T2DM.

A smartphone-based online tool for prehospital self-triage of COVID-19.

The COVID-19 epidemic has swept across China and spread to other countries. The rapid spreading of COVID-19 and panic combined with the lack of a hierarchical medical system in China have resulted in a huge number of hospital visiting which are overwhelming local medical system and increasing the incidence of cross infection. To meliorate this situation, we adopted the management concept of the system of Tiered Diagnosis and Treatment and developed an online tool for self-triage based on the mostly used multi-purpose smartphone app Wechat in China. This online tool helps people perform self-triage so that they can decide whether to quarantine at home or visit hospital. This tool further provides instructions for home quarantine and help patients make an appointment online if hospital visiting suggested. This smartphone application can reduce the burden on hospitals without losing the truly COVID-19 patients and protect people from the danger of cross infection.

QUIZLET: APLIKASI PEMBELAJARAN BERBASIS SMARTPHONE ERA GENERASI MILENIAL

Millennials are a generation that is familiar with the use of technology and the internet in everyday life. This generation can spend hours using internet technology through cellular phones or mobile phones that are more practical and easy to use. The process of education and learning in this generation certainly needs to apply some appropriate learning methods by using mobile phones based on smartphones so students are more interested and enthusiastic in participating in learning. Quizlet is a smartphone-based online learning device that can be used for all subjects and for all ages. Quizlet can be accessed by students through mobile phones based on Android or iOS. The purpose of this study is to explain the advantages of the Quizlet application that can be used in the millennial generation learning process. Literature studies are used to explain the advantages offered by the Quizlet application through the analysis of theory and literature that has been obtained.

Public university students’ use of smartphone-based online social network and family relationship

Public university students’ use of smartphone-based online social network and family relationship

The Effects of Smartphone-based Online Interactions: Teacher-Student, Peer, and Small Group Feedback on University Students’ Speaking Performance

The Effects of Smartphone-based Online Interactions: Teacher-Student, Peer, and Small Group Feedback on University Students’ Speaking Performance

Content Analysis and User Characteristics of a Smartphone-Based Online Support Group for People Living with HIV.

Although there is growing interest in mobile applications and online support groups to enhance chronic disease self-management, little is known about their potential impact for people living with HIV (PLWH). We developed an innovative online support group delivered through a community message board (CMB) within a clinic-affiliated smartphone application Positive Links (PL). We analyzed characteristics of posters and nonposters to the CMB and evaluated content posted to the CMB. For this study, 38 HIV-infected patients received cell phones with the PL application that included the opportunity to interact with other users on a CMB. Logistic regressions investigated associations between participant characteristics and posting. CMB messages were downloaded and analyzed qualitatively. 24 participants posted to the CMB; 14 did not. Participants had lower odds of posting if they were white (p = 0.028) and had private insurance (p = 0.003). Participants had higher odds of posting if they had unsuppressed viral loads (p = 0.034). Of the 840 CMB messages over 8 months, 62% had psychosocial content, followed by community chat (29%), and biomedical content (10%). Psychosocial content was most prevalent on this CMB, in contrast to other online forums dominated by informational content. Participants who posted expressed support for each other, appreciation for the community, and a perception that the app played a positive role in their HIV self-management. This CMB on a clinic-affiliated mobile application may reach vulnerable populations, including racial/ethnic minorities and those of lower socioeconomic status, and provide psychosocial support to PLWH.

Smartphone-Based Online and Offline Speech Recognition System for ROS-Based Robots

Speech recognition is one of the fundamental requirements for fully autonomous robotic systems nowadays. The objective of the presented work is to offer a smartphone based speech recognition system for ROS (Robot Operating System) based autonomous robotic systems. The proposed recognition process consists of three steps, namely acquisition, preprocessing, and result extraction. In the contribution we also present a comparison by applying the proposed recognition process using Online and Offline speech servers. The Online method uses Google speech server whereas the Offline uses Simon speech server. The speech recognition and the robotic controlling system work under a server-client architecture. For the evaluation of the Online, we used an Android smartphone, a Pioneer-3DX robot, and Google speech server. For the Offline recognition evaluation, an Android smartphone, a Pioneer-3AT and a standalone Simon speech server are used. The applications running on the smartphone act like clients and communicate with both speech server and robotic system. The contribution provided in this paper is two fold: One using smartphone with Offline speech recognition server Simon recognition feature with robotic navigation on ROS platform. DOI: http://dx.doi.org/10.5755/j01.itc.43.4.5980

A smartphone-based online social network trust evaluation system

The number of smartphone users has increased significantly over the last decade. The number of people using social networking sites is also increasing, and these platforms offer many features through which individuals can communicate with their contacts. The digital sphere is an opportunity for communication, but it is also an unprecedented arena for malicious attacks. The high quantity of personal and/or sensitive data, coupled with the large number of users, is one of the main motivations of malicious actors. We introduce in this paper a novel trust indicator for evaluating the contacts of an online social network user. This analysis is particularly important since the security policy of online social networks rests on the principle that a user’s contact is a person of trust. This assumption, not always verified as true, gives any number of people access to personal information. To address this problem, we propose applying a multi-layer model and extend it by proposing overlapping features that highlight the level of overlap of a contact belonging to the set of social networking friends of a smartphone user. We prove the efficiency of these features in evaluating trust using a case study with Facebook and Twitter.