To see the other types of publications on this topic, follow the link: Smartphones – Inde.
Journal articles on the topic 'Smartphones – Inde'
Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles
Consult the top 50 journal articles for your research on the topic 'Smartphones – Inde.'
Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.
You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.
Browse journal articles on a wide variety of disciplines and organise your bibliography correctly.
1
Ngoc, Ngo Thi Bich, Doan Thi Ngoc Tram, and Nguyen Thi Bich. "Association between neck and shoulder pain and smartphone usage among students of Da Nang University of Medical Technology and Pharmacy." Tạp chí Y học Dự phòng 32, no. 4 (August 1, 2022): 39–46. http://dx.doi.org/10.51403/0868-2836/2022/682.
Full textAbstract:
Smartphone addiction can lead to physical and psychological disorders in users, such as headache, lack of concentration, insomnia, fatigue, increased neck pain and disabilities with reduced range of neck flexion and extension. The main aim of this study was to investigate the association between non - specific neck and shoulder pain and the use of smartphones. A cross - sectional study among 416 undergraduate students from Danang University of Medical Technology and Pharmacy was conducted in 2019. The smartphone addiction scale - short version (SAS-SV) was used to assess smartphone addiction among students while the Neck Disability Index (NDI) scale was used to measure the severity of shoulder pain. Multivariate logistic regression models were used to seek associations between smartphone usage and students’ neck and shoulder pain. The prevalence of smartphone addiction among participants was 46.6%. The average NDI score was 5.31 ± 3.81. The results showed that daily average time using smartphones (p = 0.018) and the posture when using smartphones (p = 0.03) were significantly correlated to the severity of neck and shoulder pain. The multivariate logistic regression models indicated that the factors that have an independent impact on the student’s shoulder and neck pain were gender, school year and the addiction to smartphones. It is recommended to reduce the duration of smartphone use and maintain the proper body posture while using it such as sitting on a chair with a backrest, avoiding unfavorable positions such as lying or standing.
2
Grimaldi-Puyana, Moisés, José María Fernández-Batanero, Curtis Fennell, and Borja Sañudo. "Associations of Objectively-Assessed Smartphone Use with Physical Activity, Sedentary Behavior, Mood, and Sleep Quality in Young Adults: A Cross-Sectional Study." International Journal of Environmental Research and Public Health 17, no. 10 (May 17, 2020): 3499. http://dx.doi.org/10.3390/ijerph17103499.
Full textAbstract:
This study assesses the associations of objectively-measured smartphone time with physical activity, sedentary behavior, mood, and sleep patterns among young adults by collecting real-time data of the smartphone screen-state. The sample consisted of 306 college-aged students (mean age ± SD: 20.7 ± 1.4 years; 60% males). Over seven days of time, the following variables were measured in the participants: objectively-measured smartphone use (Your Hour and Screen Time applications), objective and subjective physical activity (GoogleFit and Apple Health applications, and the International Physical Activity Questionnaire (IPAQ), respectively), the number of hours sitting (IPAQ), mood (The Profile of Mood State (POMS)), and sleep (The Pittsburgh Sleep Quality Index (PSQI)). Multiple regressions analyses showed that the number of hours sitting per day, physical activity, and the POMS Global Score significantly predicted smartphone use (adj.R2 = 0.15). Further, participants with low levels of physical activity were more likely to increase the use of smartphones (OR = 2.981). Moreover, mood state (β = 0.185; 95% CI = 0.05, 0.32) and sleep quality (β = 0.076; 95% CI = −0.06, 0.21) predicted smartphone use, with those reporting poor quality of sleep (PSQI index >5) being more likely to use the smartphone (OR = 2.679). In conclusion, there is an association between objectively-measured smartphone use and physical activity, sedentary behavior, mood, and sleep patterns. Those participants with low levels of physical activity, high levels of sedentary behavior, poor mood state, and poor sleep quality were more likely to spend more time using their smartphones.
3
Fabio, Rosa Angela, Alessia Stracuzzi, and Riccardo Lo Faro. "Problematic Smartphone Use Leads to Behavioral and Cognitive Self-Control Deficits." International Journal of Environmental Research and Public Health 19, no. 12 (June 17, 2022): 7445. http://dx.doi.org/10.3390/ijerph19127445.
Full textAbstract:
Excessive use of smartphones has been associated with a number of negative consequences for individuals. Some of these consequences relate to many symptoms of behavioral addiction. The present study aims to investigate whether participants with high levels of smartphone usage may have difficulty with their ability to wield the self-control that is needed to restrict smartphone usage compared to participants with lower levels of smartphone addiction. Specifically, we expect that people with high levels of smartphone usage may have problems in refraining from using a smartphone. In addition, we expect people with a high level of smartphone use may show deficiencies in cognitive tasks such as memory, executive control, and visual and auditory attention. An ABA design was applied to analyze the effects of smartphone withdrawal. The first A refers to baseline measurements: Visual RT, Auditory RT, Go/No-Go RT and N-Back RT and Eriksen flanker RT. The B refers to 3 days of smartphone withdrawal, whereas the second A refers to the same measurements used in the baseline. In addition, several standardized scales were administered, among them: Smartphone addiction scale-short version (SAS-SV), Fear of missing out scale (FoMOs), Procrastination scale, and Psychological General Well-Being Index. One hundred and eleven participants took part in the study. Based on median split they were divided into two groups: high level and low level smartphone users. Moreover, thanks to an app installed on the participants’ smartphones, it was possible to measure levels of compliance with the task. Results indicate that participants with low levels of smartphone usage show less difficulty in their ability to wield the self-control needed to withdraw smartphone use and faster reaction times on cognitive tests than participants with high levels of smartphone usage. Moreover, the profile of participants with high levels of smartphone usage shows higher scores on the FoMOs and Procrastination scale, and lower scores in the Psychological General Well-Being Index. The results are discussed in light of self-regulation theory.
4
Al-Muhaydib, Ibrahim Muhaydib, Bader AbdulAziz Al-Tulihi, Osamah Saleh Alnafisah, Abdulrahman Muhaidib Almuhaidib, Ammar Abdulkareem Al-Sayegh, and Omar Muhaidib Al-Muhaidib. "The Impact of Mobile Devices on Sleep Quality among Subjects of Primary Health Care Settings in Riyadh, Saudi Arabia." Biosciences Biotechnology Research Asia 18, no. 3 (October 27, 2021): 567–74. http://dx.doi.org/10.13005/bbra/2940.
Full textAbstract:
Introduction: Smartphone use has been related to health problems. Studies have indicated that the use of smartphones is associated with Sleep disturbances. However, little is known about the association between Smartphone addiction and sleep quality in Saudi Arabia.Objective: To determine the relationship between sleep quality and the use of a smartphone, specifically before sleep.Method: A cross-sectional study was conducted at four primary healthcare centers with a total of 205 patients participated in the study using a convenience sampling technique. The Pittsburgh Sleep Quality Index (PSQI) and Smartphone Addiction Scale – Short Version (SAS-SV) were used to measure association of Sleep Quality and Smartphone addiction.Results: Two-hundred-fiveparticipants enrolled in the study, of which 99 were female (51%) with a response rate of 84%. Mean age was 36 ±13 years for all participants. Mean PSQI scores were higher among females, single, frequent smartphone users, and unemployed sub- categories; thus, they indicated poorer sleep quality. There was also a significant negative association between age and PSQI scores t(193)= -2.45, p=0.015. Finally, there was a significant positive association between mean SAS-SV score and categorical global PSQI scores t(193)= 3.4, p=0.001.Conclusion: Our study showsahigh prevalence of smartphone addiction and poor sleep quality. Younger age, being single, heavy usage hours of smartphones, and high SAS-SV are significant factors associated with poorer sleep quality.
5
Lane, Hsien-Yuan, Chin-Jui Chang, Chieh-Liang Huang, and Yun-Hsuan Chang. "An Investigation into Smartphone Addiction with Personality and Sleep Quality among University Students." International Journal of Environmental Research and Public Health 18, no. 14 (July 16, 2021): 7588. http://dx.doi.org/10.3390/ijerph18147588.
Full textAbstract:
Over the past two decades, smartphones have become common, and the accompanying devices have also become much more popular and easily accessible worldwide. With the development of smartphones, accompanied by internet facilities, excessive smartphone use or smartphone addiction may cause sleep disturbance and daily dysfunction. This study proposed examining the association between personality traits and smartphone addiction and its effects on sleep disturbance. Four hundred and twenty-two university participants (80 male and 342 female participants) with a mean age of 20.22 years old were recruited in this study. All participants were asked to complete the following questionnaires: Smartphone Addiction Inventory (SPAI), Tri-dimensional personality questionnaire (TPQ), and Chinese Pittsburgh Sleep Questionnaire Index (CPSQI). The results showed that people with a high tendency toward novelty seeking (NS) as a personality trait, compared to those with lower tendency toward NS, are more likely to become addicted to smartphone use. Moreover, those with a stronger trait of being NS and specific impulsivity factor were found to have higher total scores in the SPAI (p < 0.05). In addition, linear regression analysis showed that the individuals with higher scores for withdrawal symptoms on the SPAI and anticipatory worry factor on the TPQ tended to have higher CPSQI total scores (p < 0.05). This information may be useful for prevention in individuals with personality traits making them vulnerable to smartphone addiction and for designing intervention programs to reduce intensive smartphone use and programs to increase capability in managing smartphone use.
6
Foltran-Mescollotto, Fabiana, Érica Brito Gonçalves, Ester Moreira de Castro-Carletti, Ana Beatriz Oliveira, Elisa Bizetti Pelai, and Delaine Rodrigues-Bigaton. "Smartphone addiction and the relationship with head and neck pain and electromiographic activity of masticatory muscles." Work 68, no. 3 (March 26, 2021): 633–40. http://dx.doi.org/10.3233/wor-203398.
Full textAbstract:
Background: Excessive use of smartphones may be associated with behavioral and physical health changes and might cause musculoskeletal alterations in the head and neck region. Objective: To evaluate the prevalence of smartphone addiction in college students and its correlation with symptoms of head and neck pain and masticatory and trapezius muscle activity while resting, before and after smartphone use. Methods: Twenty university students participated in the study. They answered the Smartphone Addiction Scale and the Fonseca Anamnestic Index. Next, the participants were seated and prepared for electromyography through the placement of surface electrodes on the masseter, temporal, and trapezius muscles. Rest condition data were collected for 10 seconds before and after 30 minutes of smartphone use. Results: The results showed that 35% of the evaluated individuals were classified as smartphone addicted and 35% reported no head or neck pain in the previous 30 days. There was no association between smartphone use and head and neck pain. In the electromyography, there was an increase in RMS values after smartphone use in the right and left masseter muscles and the left trapezius. Conclusion: College students presented a high prevalence of smartphone addiction and head and neck pain, but these were not statistically associated. There was a change in muscle activity only in the right trapezius muscles before and after 30 minutes of smartphone use. These findings are contrary to the current belief that the use of smartphones correlates with pain in the neck region and changes in the electrical muscle activity, leading to fatigue in the cervical muscles.
7
Kumar, Lohith, Teja Tallam, and C. Naveen Kumar. "Assessment of Ride Quality and Road Roughness by Measuring the Response from a Vehicle Mounted Android Smartphone." IOP Conference Series: Earth and Environmental Science 982, no. 1 (March 1, 2022): 012062. http://dx.doi.org/10.1088/1755-1315/982/1/012062.
Full textAbstract:
Abstract Road surface roughness is considered as one of the most important aspect in functional condition of roads indicating to riding comfort in both transverse and longitudinal direction. For all highway projects maintaining proper surface evenness has been a mandatory requirement from the government of India. In this study, pavement unevenness was estimated using an android-based smartphone and system rely on the movement of a suspension system in response to the unevenness of the road surface travelled by a vehicle. Roughness index (RI) is an indicator to measure the standard road roughness. Conventional way of measuring RI involves usage of bump integrator, profilometer and roughometer. Present study proposes an alternative method to measure roughness using smartphones. The study was carried out in 2 different locations and 3 different smartphones to obtain the magnitude of deflections. Data collected using standard fifth wheel bump integrator is used for validation. Data collected through smartphone i.e., accelerometer sensor details was given as input to Fast Fourier transforms (FFT) to find the magnitude of deflection on the road. The results obtained from smartphones was then correlated with the existing roughness index data collected by standard fifth wheel bump integrator to establish an equation to predict RI using an android mobile.
8
Indrakusuma, Anak Agung Bagus Putra, I. Made Angga Sayoga, Stevanus Christian Surya, Agung Wiwiek Indrayani, and I. Gusti Ayu Artini. "The Association between Smartphone Addiction and Insomnia Incidence in Students of the Faculty of Medicine Udayana University Batch of 2020 during the Coronavirus Disease-19 Pandemic." Open Access Macedonian Journal of Medical Sciences 9, B (September 20, 2021): 1207–14. http://dx.doi.org/10.3889/oamjms.2021.7064.
Full textAbstract:
BACKGROUND: The use of smartphones is increasing in the coronavirus disease (COVID-19) pandemic for various purposes, this encourages smartphone addiction. In addition, the incidence of insomnia has also increased in the pandemic era. AIM: This study was conducted to find an association between smartphone addiction and the incidence of insomnia, especially among students of the Faculty of Medicine, Udayana University. METHOD: This research is a descriptive-analytic study with the cross-sectional method, using two main questionnaires, Smartphone Addiction Scale-Short Version, and Insomnia Severity Index. Questionnaires were distributed using Google forms and then collected and analyzed using software SPSS version 25. RESULT: Overall the total research respondents with the inclusion criteria in this study amounted to 364 people. The results showed that 212 respondents (58.24%) had a high level of smartphone addiction and 152 respondents (41.76%) had a low level of smartphone addiction. In addition, 187 respondents (51.37%) experienced mild insomnia, 87 respondents (23.9%) experienced moderate insomnia, 13 respondents (3.57%) experienced severe insomnia, and 77 respondents (21.15%) did not experience insomnia. Based on the results of data analysis, it was found that smartphone addiction had a significant relationship (p = 0.002) with weak and positive correlation (r = 0.162) to the incidence of insomnia. CONCLUSION: It was found that the majority of respondents experienced high levels of smartphone addiction and mild insomnia. Another finding suggests the higher addiction to the smartphones, the more severe insomnia suffered.
9
Liu, Ivan, Shiguang Ni, and Kaiping Peng. "Enhancing the Robustness of Smartphone Photoplethysmography: A Signal Quality Index Approach." Sensors 20, no. 7 (March 30, 2020): 1923. http://dx.doi.org/10.3390/s20071923.
Full textAbstract:
Heart rate variability (HRV) provides essential health information such as the risks of heart attacks and mental disorders. However, inconvenience related to the accurate detection of HRV limits its potential applications. The ubiquitous use of smartphones makes them an excellent choice for regular and portable health monitoring. Following this trend, smartphone photoplethysmography (PPG) has recently garnered prominence; however, the lack of robustness has prevented both researchers and practitioners from embracing this technology. This study aimed to bridge the gap in the literature by developing a novel smartphone PPG quality index (SPQI) that can filter corrupted data. A total of 226 participants joined the study, and results from 1343 samples were used to validate the proposed sinusoidal function-based model. In both the correlation coefficient and Bland–Altman analyses, the agreement between HRV measurements generated by both the smartphone PPG and the reference electrocardiogram improved when data were filtered through the SPQI. Our results support not only the proposed approach but also the general value of using smartphone PPG in HRV analysis.
10
Ginanjar, Rikip, and Ridho Utomo. "Sim Card Alarm for Android Smartphone." Jurnal ULTIMA InfoSys 7, no. 1 (June 15, 2017): 09–15. http://dx.doi.org/10.31937/si.v7i1.507.
Full textAbstract:
Since the first Android smartphones were released, many applications have been developed until today. One of them is security application. Security applications consist of several types of applications such as Antivirus, SIM Card Change Alarm, and Applocker. SIM Card Changed Alarm is a security application that has capability to monitor SIM Card change in Android smartphones. Although there are many SIM Card Change Alarm applications which are available in Google Playstore, there are many people who are not satisfied with this applications. It happens due to them only sends the SMS alert to the owner without locking the phone to prevent other people using it. The outcome of this research will have the same feature as SIM Card Change Alarm but with additional features such as locking the smartphone if the SIM Card has been changed, locking and unlocking remotely using SMS, triggering loud alarm, and calling-back to owner when the smartphone has been lost or stolen. The outcome expected for the Prifone Application is a userfriendly application which could be used by many people around the world and also is able to secure Android smartphones.
Index Terms – android, sim card alarm, security application
11
James, Delores C. S., and Cedric Harville. "Smartphone Usage, Social Media Engagement, and Willingness to Participate in mHealth Weight Management Research Among African American Women." Health Education & Behavior 45, no. 3 (June 13, 2017): 315–22. http://dx.doi.org/10.1177/1090198117714020.
Full textAbstract:
Background. African American women (AAW) are in a unique position to be recruited into mobile (mHealth) weight management research and programs due to their high rates of obesity and their high ownership of smartphones. Aim. This study examined smartphone usage, social media engagement, and willingness to participate in mHealth weight management among AAW in north-central Florida, United States. Methods. A self-administered survey was completed by a convenience sample of 425 smartphone owners in north-central Florida. Results. Mean age was 34.84 ± 13.74, with age distribution of 18 to 29 (45%), 30 to 50 (39%), and 51+ years (17%). Mean body mass index was 29.52 ± 8.18. Most used smartphones to access the Internet daily and were engaged with eight social media sites, such as Facebook (85%), YouTube (75%), and Google+ (57%). Compared to those 51+, those 18 to 29 were more likely to use YouTube (odds ratio [OR] = 2.52, p = .017) and Instagram (OR = 10.90, p < .0001), but they were less likely to use Google+ (OR = 0.40, p = .009). Compared to those 51+, those 30 to 50 were more likely to use Instagram (β = 1.28, OR = 3.61, p = .014) and Facebook (β = 1.04, OR = 2.84, p < .006). Most were willing to participate in research that used text messages (73%), smartwatches/fitness trackers (69%), and smartphone apps (68%). Compared to those 51+, women 18 to 29 were more likely to report willingness to use a smartphone app (OR = 5.45, p < .0001) as were those 30 to 50 (OR = 3.14, p < .0001). Conclusion. AAW’s high ownership of smartphones, use of mHealth apps and tools, and willingness to participate in mHealth research has the potential to curb the obesity epidemic by participating in mHealth weight management programs and research.
12
Rathakrishnan, Balan, Soon Singh Bikar Singh, Mohammad Rahim Kamaluddin, Azizi Yahaya, Mohd Azrin Mohd Nasir, Fauziah Ibrahim, and Zaizul Ab Rahman. "Smartphone Addiction and Sleep Quality on Academic Performance of University Students: An Exploratory Research." International Journal of Environmental Research and Public Health 18, no. 16 (August 5, 2021): 8291. http://dx.doi.org/10.3390/ijerph18168291.
Full textAbstract:
This study was conducted to examine the relationship between smartphone addiction, sleep quality, and academic performance. The study presented quantitative research on 323 students in a public university in Sabah to explore the relationship between smartphone addiction, sleep quality, and academic performance. A simple random sampling was used in the study. The Smartphone Addiction Scale Short Version (SAS-SV) and the Pittsburgh Sleep Quality Index (PSQI) were used in this study. SPSS was used as a tool of analysis for descriptive and inferential analysis. Pearson correlation was involved to test the hypothesis of the study. The result indicated that the greater the smartphone addiction, the lower the academic performance of university students. The finding also proved that students with poor sleep quality might exhibit low academic performance. Smartphone addiction was found to be associated with sleep quality where overusing smartphones was related to poor sleep quality in university students. On this basis, the problem of smartphone addiction and sleep quality should be tackled in order to improve the academic performance of university students and their overall health.
13
Ezoe, Satoko, Tadayuki Iida, Ken Inoue, and Masahiro Toda. "Smartphone Addiction and Sleep Quality Associated with Depression in University Students in Japan." International Journal of Cyber Behavior, Psychology and Learning 9, no. 4 (October 2019): 22–31. http://dx.doi.org/10.4018/ijcbpl.2019100102.
Full textAbstract:
Smartphones have developed rapidly in recent years, with their use becoming widespread and an established part of daily life. Along with the development of various applications, smartphone addiction or dependence has been routinely reported, and indicated to be associated with such conditions as sleep problems and depression. In order to examine the relationships of smartphone use, sleep quality, chronotype, and physical exercise, with a depressive state, the authors administered a self-reporting questionnaire survey, which included the Japanese version of the Smartphone Dependence Scale (J-SDS), the Pittsburg Sleep Quality Index (PSQI), the Morningness-Eveningness Questionnaire (MEQ), and the Beck Depression Inventory (BDI), to 119 university students in Japan. Results of multivariate logistic regression analysis indicated that scores for the J-SDS and PSQI were significantly related to BDI score. These findings suggest that smartphone addiction and poor sleep quality are associated with the depressive state in students in Japan.
14
Cugmas, Blaž, and Eva Štruc. "Accuracy of an Affordable Smartphone-Based Teledermoscopy System for Color Measurements in Canine Skin." Sensors 20, no. 21 (October 31, 2020): 6234. http://dx.doi.org/10.3390/s20216234.
Full textAbstract:
Quality smartphone cameras and affordable dermatoscopes have enabled teledermoscopy to become a popular medical and veterinary tool for analyzing skin lesions such as melanoma and erythema. However, smartphones acquire images in an unknown RGB color space, which prevents a standardized colorimetric skin analysis. In this work, we supplemented a typical veterinary teledermoscopy system with a conventional color calibration procedure, and we studied two mid-priced smartphones in evaluating native and erythematous canine skin color. In a laboratory setting with the ColorChecker, the teledermoscopy system reached CIELAB-based color differences ΔE of 1.8–6.6 (CIE76) and 1.1–4.5 (CIE94). Intra- and inter-smartphone variability resulted in the color differences (CIE76) of 0.1, and 2.0–3.9, depending on the selected color range. Preliminary clinical measurements showed that canine skin is less red and yellow (lower a* and b* for ΔE of 10.7) than standard Caucasian human skin. Estimating the severity of skin erythema with an erythema index led to errors between 0.5–3%. After constructing a color calibration model for each smartphone, we expedited clinical measurements without losing colorimetric accuracy by introducing a simple image normalization on a white standard. To conclude, the calibrated teledermoscopy system is fast and accurate enough for various colorimetric applications in veterinary dermatology.
15
Kim, Kitai, Jeong Yee, Jee Eun Chung, Hyun Jeong Kim, Ji Min Han, Joo Hee Kim, Kyung Eun Lee, and Hye Sun Gwak. "Smartphone Addiction and Anxiety in Adolescents – A Cross-sectional Study." American Journal of Health Behavior 45, no. 5 (September 30, 2021): 895–901. http://dx.doi.org/10.5993/ajhb.45.5.9.
Full textAbstract:
Objectives: The overuse of smartphones affects physical, social, and psychological well-being. However, research on smartphone addiction and anxiety disorders is scarce. Therefore, the objective of this study was to investigate the association between anxiety and smartphone addiction risk in Korean adolescents. Methods: This study used a cross-sectional survey method. We used the Revised Children's Manifest Anxiety Scale to assess anxiety symptoms and we used the Korean Smartphone Addiction Proneness Scale index to evaluate the degree of high-risk or at-risk for smartphone addiction. Results: Analyses were performed for 1733 adolescents, including 771 boys and 962 girls. The high-risk or at-risk group for smartphone addiction accounted for 20.1% (p < .0001). Total anxiety scale score, as well as physiological anxiety, oversensitivity, and social concern categories were statistically different among levels of smartphone addiction risk (all ps < .0001). Multivariate analysis showed that poor self-reported health level, higher risk of smartphone addiction, having fewer close friends, caffeine drink consumption, female sex, and alcohol use were associated with greater anxiety. Conclusions: Management of smartphone addiction seems to be essential for proper psychological health. There is an urgent need to develop a way to prevent smartphone addiction on a social level.
16
Ibrahim, Ade Riki Harahap, and Filsi Putri Parbo. "Hubungan Antara Sikap Penggunaan Smartphone dengan Kualitas Tidur pada Siswa SMA Kartini Batam." Zona Kedokteran: Program Studi Pendidikan Dokter Universitas Batam 12, no. 3 (September 7, 2022): 254–61. http://dx.doi.org/10.37776/zked.v12i3.1031.
Full textAbstract:
Background: Smartphones have now become a special need for everyone, especially teenagers. Excessive smartphone use can interfere with sleep quality. Lack of individual ability to control the intensity of smartphone use can result in poor sleep quality. Teenagers need more bedtime no less than 8 hours every night.
Methods: The research used an observational analyticmethod by the cross sectional approach. The data collection technique used the Probability Sampling technique using the simple random sampling method with a sample of 105 students in 2021. The data collection used two questionnaires, namely the Smartphone Addiction questionnaire for the intensity of smartphone use and the Pittsburgh Sleep Quality Index (PSQI) questionnaire for sleep quality. The data were then analyzed using Fisher's exact test.
Results: There were moderate smartphone use attitudes with poor sleep quality, namely 77 people (73.3%), and high smartphone use attitudes with poor sleep quality, namely 12 people (11.4%). Based on the results of the study, none of the respondents with high smartphone use attitudes had good sleep quality (0%). Fisher's test results obtained p value = 0.028 (p <0.05).
Conclusion:According to this research, it can be concluded that there was a correlation between the smartphone usage attitude with the students’ sleeping quality at Kartini Batam Senior High School.
17
Solon Júnior, Luiz José Frota, Carlos Henrique Tomaz Ribeiro, Leonardo de Sousa Fortes, Bruno Teixeira Barbosa, and Luiz Vieira da Silva Neto. "Smartphone addiction is associated with symptoms of anxiety, depression, stress, tension, confusion, and insomnia: A cross-sectional and comparative study with physically and non-physically active adults in self-isolation during the COVID-19 pandemic." Salud mental 44, no. 4 (August 30, 2021): 193–200. http://dx.doi.org/10.17711/sm.0185-3325.2021.025.
Full textAbstract:
Introduction. During the novel coronavirus disease (COVID-19) outbreak, social media exposure and the use of electronic devices have increased; still, these behaviors may cause adverse health effects. Objective. This study assessed sleep quality, insomnia, mood, and psychological aspects among physically (n = 46) and non-physically (n = 53) active individuals during self-isolation throughout the COVID-19 pandemic and examined their association with smartphone addiction. Method. A cross-sectional study was conducted among adult Brazilian citizens in self-isolation for at least 60 days; ninety-nine volunteers from different Brazilian regions were enrolled in the online survey. The Depression, Anxiety and Stress Scale-Short Form, the Pittsburgh Sleep Quality Index, the Insomnia Severity Index, the Brunel Mood Scale, and the Smartphone Addiction Scale-Short Version were used to assess the study outcomes. Results. The results indicate moderate and large correlations of smartphone addiction with mood subscales, insomnia (r = .52), anxiety (r = .49), depression (r = .49), and stress (r = .49) symptoms. Also, it was observed that physically active participants were less addicted to smartphones than the non-physically active during self-isolation (p
18
Mengistu, Nebiyu, Endashaw Habtamu, Chalachaw Kassaw, Derebe Madoro, Wondwosen Molla, Aregahegn Wudneh, Lulu Abebe, and Bereket Duko. "Problematic smartphone and social media use among undergraduate students during the COVID-19 pandemic: In the case of southern Ethiopia universities." PLOS ONE 18, no. 1 (January 25, 2023): e0280724. http://dx.doi.org/10.1371/journal.pone.0280724.
Full textAbstract:
Background Smartphone and social media use are supposed to be integral parts of university students’ daily lives. More specifically, smartphones and social media are frequently used for communication in daily life during the COVID-19 pandemic. Nonetheless, uninterrupted and persistent use of these technologies may lead to several psychological problems. Even though smartphones and social media were used more frequently during the pandemic, there is no evidence suggesting that the studies were not undertaken in low-income countries, including Ethiopia. Therefore, the current study aimed to assess problematic smartphone use and social media use among undergraduate university students in southern Ethiopia. Methods A cross-sectional study was carried out among 1,232 university students using a simple random sampling technique. The Bergen Social Media Addiction Scale and Smartphone Application-Based Addiction Scale were used to collect data on social media and smartphone use, respectively. The Beck Depression Inventory, Generalized Anxiety Assessment Tool, Rosenberg Self-Esteem Scale, and Pittsburg Sleep Quality Index were standardized tools used to measure other independent variables. To identify factors, simple and multiple linear regression analyses were performed. A p-value of 0.05 was used to determine statistical significance. Results The overall response rate was 95%. The mean scores for problematic smartphone and problematic social media use were 17 ± 3.3/36 and 12.7 ± 2.2/30, respectively. A linear regression model revealed that being female, first-year students and poor sleep quality were significantly associated with problematic smartphone use. Factors associated with problematic social media use (PSMU) were depression, substance use, and urban residence. Conclusions This study identified significant problems with smartphone and social media use among university students. Therefore, it is preferable to provide psychological counselling, educate students about safe, beneficial, and healthy internet use, and focus on recognized high-risk groups in order to give them special attention. It is also preferable to seek counselling about substance use. It is preferable to regularly screen and treat individuals with psychological problems in collaboration with stakeholders.
19
Hammoudi, Sajida Fawaz, Hussein Walid Mreydem, Bayan Tarek Abou Ali, Nada Omar Saleh, Seockhoon Chung, Souheil Hallit, and Pascale Salameh. "Smartphone Screen Time Among University Students in Lebanon and Its Association With Insomnia, Bedtime Procrastination, and Body Mass Index During the COVID-19 Pandemic: A Cross-Sectional Study." Psychiatry Investigation 18, no. 9 (September 25, 2021): 871–78. http://dx.doi.org/10.30773/pi.2021.0120.
Full textAbstract:
Objective We aimed to investigate the association of increased smartphone screen time with insomnia, bedtime procrastination, depression, anxiety, body mass index (BMI), and physical activity during the coronavirus disease of 2019 (COVID-19) pandemic.Methods An online survey was performed for university students from all regions of Lebanon during the lockdown. The survey included questionnaires about smartphone screen time, diet, physical activity, psychological symptoms, and bedtime procrastination. We defined 6 hours of smartphone use as critical based on a survey done in United States.Results Among female students, smartphone use duration, physical activity levels, BMI, depression, anxiety, and insomnia severity were significantly higher than in male. When we stratified participants based on 6 hours of smartphone use, females, unhealthy food consumption, insomnia, anxiety, depression, and bedtime procrastination were significantly higher in the group with ≥6 hours of smartphone use. When we divided based on 7 hours, physical activity and body weight also differed between the two groups. Logistic regression analysis revealed that female, overweight, insomnia, and bedtime procrastination were significant predictors of a phone screen time of 7 hours.Conclusion Our findings suggest that adults should be more cautious and responsible when using smartphones and be more concerned about the health-related risks.
20
Citó, Erika Brasil Cavalcante, Delane Viana Gondim, Jorge Luiz Moreira Freire Júnior, Patrícia Silveira Damasceno, Maria Caroline Sousa Queiroz Pereira de Oliveira, and Ana Karine Macedo Teixeira. "Smartphone addiction in COVID-19 pandemic times." Revista da ABENO 22, no. 2 (January 21, 2022): 1–12. http://dx.doi.org/10.30979/revabeno.v22i2.1547.
Full textAbstract:
This study aimed to evaluate smartphone addiction, sleep quality, quality of life and depression among dental students before and during the first wave COVID-19 pandemic lockdown and explore how smartphone addiction influences the other variables. 57 dental students answered the smartphone addiction inventory, Pittsburg sleep quality index, WHOQOL-bref and research diagnosis criteria for temporomandibular disorders axis II questionnaires before and during lockdown. Statistical analysis was conducted using Wilcoxon test, Mann-Whitney U test, Spearman tests and linear regression models considering the smartphone addiction inventory total score as the independent variable. The high mean scores on smartphone addiction on both times are remarkable. The smartphone addiction prevalence was also high on both times (68.66% and 71.92% respectively). Overall sleep quality improved. However, there was no significant change on overall smartphone addiction, quality of life and depression grade during lockdown. Tolerance using smartphones increased during lockdown, especially for women. Smartphone addiction showed negative correlation to quality of life and positive correlation to depression, subjective sleep quality and sleep medication use. Smartphone addiction was a predictor to total WHOQOL-bref score, all WHOQOL bref domains, sleep medication use and to depression on both times, before and during lockdown. Smartphone addiction was directly affecting quality of life. Despite the growing smartphone use among university students due to the pandemic restrictions, this study showed that the overall smartphone addiction, quality of life and depression grade were not influenced by the lockdown restrictions. However, it was observed an improvement on sleep quality during this period among dental students.
21
Wah, Saw Wah, Uraiwan Chatchawan, Thiwaphon Chatprem, and Rungthip Puntumetakul. "Prevalence of Static Balance Impairment and Associated Factors of University Student Smartphone Users with Subclinical Neck Pain: Cross-Sectional Study." International Journal of Environmental Research and Public Health 19, no. 17 (August 28, 2022): 10723. http://dx.doi.org/10.3390/ijerph191710723.
Full textAbstract:
The aim of this study was to assess the prevalence of static balance impairment in university student smartphone users with subclinical neck pain and identify the associated risk factors. Because of rapid and widespread smartphones use, and the subsequent effect on neck pain in university students, it is essential to determine the prevalence of balance impairment and associated factors in this population. Simple random sampling was completed among eighty-one participants in this cross-sectional study. A self-reported questionnaire, fitted precisely for smartphone users, was used prior to clinical assessment by the Balance Error Scoring System. Both simple and multiple logistic regressions were used to analyze the prevalence of static balance impairment and associated factors. The prevalence of static balance impairment in university student smartphone users with subclinical neck pain was 74.07% (95% CI: 64.32 to 83.82). The significant risk factors were “daily smartphone use ≥ 4 h’’ (AOR: 19.24 (95% CI 4.72 to 78.48) p = 0.000), “≥4 years of smartphone use” (AOR: 5.01 (95% CI 1.12 to 22.38) p = 0.035), and “≥7 neck disability index score’’ (AOR: 12.91 (95% CI 2.24 to 74.45) p = 0.004). There was a high prevalence of static balance impairment in university smartphone users with subclinical neck pain. University student smartphone users with subclinical neck pain who met at least one of the risk factors should realize their static balance impairment.
22
Zhou, Haowen, Ruoqing Zhu, Anita Ung, and Bruce Schatz. "Population analysis of mortality risk: Predictive models from passive monitors using motion sensors for 100,000 UK Biobank participants." PLOS Digital Health 1, no. 10 (October 20, 2022): e0000045. http://dx.doi.org/10.1371/journal.pdig.0000045.
Full textAbstract:
Many studies have utilized physical activity for predicting mortality risk, using measures such as participant walk tests and self-reported walking pace. The rise of passive monitors to measure participant activity without requiring specific actions opens the possibility for population level analysis. We have developed novel technology for this predictive health monitoring, using limited sensor inputs. In previous studies, we validated these models in clinical experiments with carried smartphones, using only their embedded accelerometers as motion sensors. Using smartphones as passive monitors for population measurement is critically important for health equity, since they are already ubiquitous in high-income countries and increasingly common in low-income countries. Our current study simulates smartphone data by extracting walking window inputs from wrist worn sensors. To analyze a population at national scale, we studied 100,000 participants in the UK Biobank who wore activity monitors with motion sensors for 1 week. This national cohort is demographically representative of the UK population, and this dataset represents the largest such available sensor record. We characterized participant motion during normal activities, including daily living equivalent of timed walk tests. We then compute walking intensity from sensor data, as input to survival analysis. Simulating passive smartphone monitoring, we validated predictive models using only sensors and demographics. This resulted in C-index of 0.76 for 1-year risk decreasing to 0.73 for 5-year. A minimum set of sensor features achieves C-index of 0.72 for 5-year risk, which is similar accuracy to other studies using methods not achievable with smartphone sensors. The smallest minimum model uses average acceleration, which has predictive value independent of demographics of age and sex, similar to physical measures of gait speed. Our results show passive measures with motion sensors can achieve similar accuracy to active measures of gait speed and walk pace, which utilize physical walk tests and self-reported questionnaires.
23
Anto, Lie, Herlyani Khosama, and Mieke Kembuan. "The relationship between smartphone addiction and sleep quality in college students of the faculty of medicine, Sam Ratulangi university." International Journal of Research in Medical Sciences 10, no. 3 (February 25, 2022): 580. http://dx.doi.org/10.18203/2320-6012.ijrms20220504.
Full textAbstract:
Background: Excessive smartphone use affects sleep quality. The purpose of this study was to see the relationship between smartphone usage and sleep quality.Methods: Respondents were selected consecutively and asked to fill out the smartphone addiction scale-short version (SAS-SV), Pittsburgh sleep quality index (PSQI) questionnaires via google form and measure sleep quality objectively with sleep tracker (Fitbit charge 2™). Datas were analyzed using SPSS version 25.Results: There were 62 subjects included in this study, the majority were women (74.2%), the average age was 21 years old. A total of 69.4% are addicted to smartphones. Assessment with PSQI found that 71% showed poor sleep quality, while with Fitbit charge 2™, good sleep quality was obtained, namely sleep latency (100%), sleep efficiency (75.8%), light sleep (61.3%), and deep sleep (82.3%). Waking 5 minutes (50%) is uncertain. Poor sleep quality, namely wake after sleep onset (WASO) by 77.4% and rapid eye movement (REM) by 59.7%. The relationship between smartphone addiction and subjective sleep quality (PSQI) was significant at p=0.007. Smartphone addiction and sleep quality measured by objective parameters seemed insignificant (wake up 5 minutes p=0.884, WASO p=0.848, sleep efficiency p=701, light sleep p=0.629, deep sleep p=0.240, REM p=0.638).Conclusions: There is a relationship between smartphone addiction and sleep quality using subjective measurement (PSQI), but not with a sleep tracker.
24
Chovatiya, Nandani K., Hardi S. Chaudhary, and Nisha S. Kanabar. "Correlation of smartphone addiction with musculoskeletal discomfort and neck disability among college students." International Journal Of Community Medicine And Public Health 8, no. 9 (August 27, 2021): 4357. http://dx.doi.org/10.18203/2394-6040.ijcmph20213536.
Full textAbstract:
Background: The nearly universal availability of smartphones in present cultures has resulted in smartphone addiction. The main purpose of the study was to assess risk of musculoskeletal discomfort and neck disability among college students who are smartphone addicted and assumes faulty posture with prolong smartphone use.Methods: The study examined 100 healthy students of a college in Ahmedabad and Gandhinagar by random sampling based on self-administered questionnaires that consist of Smartphone addiction scale (SAS), Cornell musculoskeletal discomfort questionnaire (CMDQ), Neck disability index (NDI) in the age group of 18-25 years. Pearson correlation coefficient was used to correlate between SAS and CMDQ, and SAS and NDI.Results: There was a predominance of females over males (females- 78, males- 22). Mean±SD of SAS, NDI and CMDQ was 92.74±21.33. 8.6±9.56 and 88±14.84 (CMDQ frequency), 30.5±7.77 (CMDQ discomfort), 27±4.24 (CMDQ interference) respectively. Pearson correlation coefficient showed a significant moderate positive correlation between SAS and NDI (r=0.44) and it showed a significant moderate positive correlation between both SAS and CMDQ (frequency) (r=0.50) and SAS and CMDQ (discomfort) (r=0.40), while it showed weak correlation between SAS and CMDQ (interference) (r=0.38). Conclusions: The study indicated that there was a moderate positive correlation between neck disability and Smartphone addiction, while there was mild to moderate correlation between musculoskeletal disorders and smartphone addiction.
25
Malik, Rifkind, Rhandyka Rafli, Salmi Salmi, and Yasinta Allisya Noer. "Relationship of Sleep Quality and Oxidative Stress Level in Smartphone Users; Study in Faculty of Medicine Student, Universitas Baiturrahmah." Open Access Macedonian Journal of Medical Sciences 10, B (February 21, 2022): 501–5. http://dx.doi.org/10.3889/oamjms.2022.8593.
Full textAbstract:
BACKGROUND: Excessive smartphones can affect sleep quality, reducing sleep duration. This lack of sleep will impact various health and increase levels of free radicals in the body, affecting various cell functions. AIM: The aim of the study was to measure the relationship between sleep quality due to smartphone use and serum malondialdehyde (MDA) levels. MATERIALS AND METHODS: This was a quasi-experimental with pre- and post-test group study. Sleep quality was assessed with Pittsburgh Sleep Quality Index (PSQI), and the smartphone addiction was assessed based on Smartphone Addiction Scale (SAS) score. The subjects were divided into four groups (n = 6) based on their PSQI and SAS score. The first group was the subjects with normal sleep and non-smartphone addict. The second group was the subjects with normal sleep but smartphone addict. The third group was the subjects with abnormal sleep and non-smartphone addict. Furthermore, fourth was the subjects with abnormal sleep and smartphone addiction. All the subjects were asked to sleep usually and used the smartphone as necessary a day before the study started. Blood plasma was collected from the subject before and after the study for MDA measurement. Plasma MDA was determined using the thiobarbituric acid test. RESULTS: Smartphone use can reduce sleep quality and duration, resulting in sleep deprivation. There was no increase in MDA concentration (p > 0.05) in the ordinary and non-addictive or smartphone-addicted sleep group. Meanwhile, the group that stayed up late and was neither addictive nor addictive showed an increase in MDA levels and was statistically significant (p < 0.05). CONCLUSION: Adequate sleep can reduce blood serum MDA levels and smartphone use does not affect MDA levels.
26
ADENIYI, Wasiu. "Psycho-demographic Characteristics as Predictors of Smartphone Addiction among Undergraduates of Obafemi Awolowo University, Ile-Ife, Nigeria." Journal of Research in Psychology 3, no. 1 (May 30, 2021): 68–87. http://dx.doi.org/10.31580/jrp.v3i1.1976.
Full textAbstract:
The thrust of the study was to investigate the use and prevalent of smartphone addiction among undergraduates of Obafemi Awolowo University, Ile-Ife, Nigeria as well as examining the influence of psycho-demographic characteristics on students’ smartphone addiction. The survey research design was employed for the study. A sample of 600 undergraduates and six faculties were selected from the university using a multistage sampling technique. An adapted questionnaire titled “Questionnaire on Smartphone Addiction among Undergraduates” (QSAU) was used to collect the data from the participants. The reliability test result of the instrument after trial-tested was 0.71% at a 0.05 level of significance. Percentages, Relative Significance Index (RSI), ranking order, t-test, One-Way Analysis of Variance, and multiple regressions were employed to analyse the data collected. The results showed a high prevalence rate of smartphone addiction among 124(20.7%) undergraduates. Educative information (0.801), charting (0.787) and sports and recreation (0.778) were the frequently information undergraduates sourced from their smartphones. Again, the results showed a significant influence of personality characteristics (F(5,546) = 51.870, p < 0.05); sex (the t-test = 0. -2.612; df = 598, p > 0.05) age (F(2,596) = 9.533; p < 0.05), students’ level (F(4,594); = 57.209, p < 0.05) and smartphone addiction among the students. Finally, the result showed that all variables contributed 65.3%. This indicated psycho-demographic variables greatly contributed to students’ smartphone addiction (R2 = 0.653; F = 57.209, p < 0.05). The study concluded psycho-demographic variables predisposed undergraduates to smartphone addiction.
27
Aakash Kumar B. and R. Latha. "Nomophobia and the psycho-physiological effects of PUBG gaming on medical college student’s health and academic performance." Biomedicine 42, no. 3 (July 3, 2022): 567–73. http://dx.doi.org/10.51248/.v42i3.965.
Full textAbstract:
Introduction and Aim: Nomophobia is a psychological condition, where people have a fear of being detached from mobile phone connectivity. The medical college students are suffering from PUBG addiction which affects their psycho-physiological parameters. The aim is to assess the prevalence of nomophobia in the medical college students, to assess the stress and anxiety in the absence of smartphone and correlate it with the conduction velocity of median nerve. Materials and Methods: A cross-sectional study was conducted in the physiology department of a tertiary care teaching hospital for a period of 2 months involving 169 medical students using smartphones. For studying nomophobia, the students in the study group were divided into groups A and B according to their smartphone usage and on the basis of a Smartphone Addiction Scale (SPAS) Questionnaire. Results: Out of the 169 students, 80 were subjected for the assessment of the variability in the median nerve conduction velocity as a quantitative measurement to detect the decrease in the terminal latency index, motor distal latency and the conduction velocity due to excessive gaming or chronic smartphone usage. As per our hypothesis 94.37 % of the study sample had decreased terminal latency index and about 85.62 % of students had a decreased nerve conduction velocity. Conclusion: The prevalence of nomophobia in our study was 37.39 % as per the ICD-10 diagnostic criteria for dependence syndrome. Hence medical education to school-going children, teenagers and adolescents about the risks of excessive smartphone usage should be given as they are the most vulnerable to this disorder.
28
Wang, Fan, Yukun Lan, Jiang Li, Junming Dai, Pinpin Zheng, and Hua Fu. "Patterns, influencing factors and mediating effects of smartphone use and problematic smartphone use among migrant workers in Shanghai, China." International Health 11, Supplement_1 (October 30, 2019): S33—S44. http://dx.doi.org/10.1093/inthealth/ihz086.
Full textAbstract:
Abstract Background With the popularization of smartphones in China, the conditions of smartphone use (SU) and problematic smartphone use (PSU) among migrant workers are unknown. This study explored the patterns and influencing factors of SU and PSU in migrant workers in Shanghai, China. Furthermore, the mediation effects of PSU in the link between SU and some psychological factors were also examined. Methods Questionnaires containing the Mobile Phone Addiction Index, Patient Health Questionnaire, World Health Organization Five-item Well-being Index and other items, including demographics, sleep quality, job stress and SU, were distributed to 2330 migrant workers by trained investigators in six districts of Shanghai from June to September 2018. Results Of the 2129 returned questionnaires, 2115 were valid. SU and PSU varied according to certain demographics. Many demographics, psychological factors, sleep quality and main smartphone applications were influencing factors for SU and PSU. PSU played a mediating role in the link between daily SU time and psychological factors, including depression, mental health and job stress. Conclusions The health influences of SU and PSU on migrant workers in Shanghai merit significant attention. Additionally, it is necessary to develop and target intervention strategies according to the workers’ various characteristics and SU patterns.
29
Stanislaus, Sharleny, Maj Vinberg, Sigurd Melbye, Mads Frost, Jonas Busk, Jakob Eyvind Bardram, Maria Faurholt-Jepsen, and Lars Vedel Kessing. "Daily self-reported and automatically generated smartphone-based sleep measurements in patients with newly diagnosed bipolar disorder, unaffected first-degree relatives and healthy control individuals." Evidence Based Mental Health 23, no. 4 (August 24, 2020): 146–53. http://dx.doi.org/10.1136/ebmental-2020-300148.
Full textAbstract:
Objectives(1) To investigate daily smartphone-based self-reported and automatically generated sleep measurements, respectively, against validated rating scales; (2) to investigate if daily smartphone-based self-reported sleep measurements reflected automatically generated sleep measurements and (3) to investigate the differences in smartphone-based sleep measurements between patients with bipolar disorder (BD), unaffected first-degree relatives (UR) and healthy control individuals (HC).MethodsWe included 203 patients with BD, 54 UR and 109 HC in this study. To investigate whether smartphone-based sleep calculated from self-reported bedtime, wake-up time and screen on/off time reflected validated rating scales, we used the Pittsburgh Sleep Quality Index (PSQI) and sleep items on the Hamilton Depression Rating Scale 17-item (HAMD-17) and the Young Mania Rating Scale (YMRS).Findings(1) Self-reported smartphone-based sleep was associated with the PSQI and sleep items of the HAMD and the YMRS. (2) Automatically generated smartphone-based sleep measurements were associated with daily self-reports of hours slept between 12:00 midnight and 06:00. (3) According to smartphone-based sleep, patients with BD slept less between 12:00 midnight and 06:00, with more interruption and daily variability compared with HC. However, differences in automatically generated smartphone-based sleep were not statistically significant.ConclusionSmartphone-based data may represent measurements of sleep patterns that discriminate between patients with BD and HC and potentially between UR and HC.Clinical implicationDetecting sleep disturbances and daily variability in sleep duration using smartphones may be helpful for both patients and clinicians for monitoring illness activity.Trial registration numberclinicaltrials.gov (NCT02888262).
30
Shamsi, Rafia Farrukh, Aisha Sadeeqa, Asma Afzal Khan, Fizah Mahnoor Khan, Aruba Saeed, and Syeda Nayab Sheeraz. "CORRELATION OF SMARTPHONE ADDICTION WITH TEXT NECK SYNDROME DURING COVID-19 PANDEMIC." Rehabilitation Journal 06, no. 04 (December 31, 2022): 442–45. http://dx.doi.org/10.52567/trj.v6i04.148.
Full textAbstract:
Background: Smartphones pervasiveness has captured people with the ability to search for information, communicate more easily, and make our day-to-day jobs easier. On the other hand, excessive smartphone use can also lead to serious musculoskeletal consequences including neck pain and disability. Objective: To determine the correlation of Text-Neck-Syndrome with smartphone addiction during the COVID-19 pandemic. Methods: The cross-sectional study was conducted on n=500 participants of both genders between 20 to 30 years olds. The study population were assessed for text next syndrome with Neck disability index, and neck pain on Visual analogue scale (VAS) and Smartphone addiction scale short version (SAS-SV) to find problematic smartphone usage. The spearmen test was used to determine the correlation between the Text neck syndrome and smartphone addiction during Covid-19 pandemic. Results: The mean age of the participants was 22.8±2.47 years. A total of n=418(83.6%) were female and remaining n=82(16.4%) was male participated in the study. The results showed that there is significant mild to moderate positive significant correlation (p<0.05) between individual item and total score of SAS-SV with pain and neck disability. Conclusion: It was concluded that the excessive use of smart phone during COVID 19 caused neck pain and related functional impairment. Keywords: Addiction, neck disability, neck pain, text neck syndrome, VAS
31
Cankurtaran, Damla, Zeynep Aykin Yigman, Fatih Yigman, and Gulnur Celik. "How does smartphone usage affect the severity of neck pain, neck-pain related disability, and cervical lordosis? A pilot study." Medical Science and Discovery 8, no. 4 (April 18, 2021): 254–59. http://dx.doi.org/10.36472/msd.v8i4.527.
Full textAbstract:
Objective: Long-term and repetitive use of smartphones may cause musculoskeletal symptoms such as neck pain. This pilot study aimed to examine the effect of smartphone usage on neck pain, disability, and cervical lordosis.
Material and Methods: Seventy-eight patients were enrolled in this cross-sectional pilot study. The level of smartphone use was evaluated with the Smartphone addiction scale-short version (SAS-SV). Neck Bournemouth Questionnaire (NBQ), Neck Disability Index (NDI), and 100 mm Visual Analog Scale (VAS) were used to assess pain and disability. Cervical lordosis angle was measured using the Cobb method.
Results: A positive significant correlation with low correlation coefficient (r= 0.277, p=0.014; r: 0.295, p=0.009) was determined between SAS-SV and NBQ, and NDI. However, no correlation was found between SAS-SV and cervical lordosis angle (p>0.05). When applying simple linear regression modeling to predict neck pain severity, the SAS-SV total score alone explained 7.7% of the variance of the NBQ and 9.0% of the variance of the NDI total score.
Conclusion: We concluded that it would be beneficial to question the frequency and position of smartphone use, to recommend to use it less, and to avoid prolongation in neck flexion for patients with chronic neck pain.
32
Choi, Younggeun, Hayoung Jung, Jangwoon Park, and Heecheon You. "Development of an Ergonomic Method for Determination of Smartphone Hard Key Locations." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 62, no. 1 (September 2018): 1022–26. http://dx.doi.org/10.1177/1541931218621236.
Full textAbstract:
The present study proposed a design method for determination of optimal hard key locations based on analysis of preferred grip posture and preferred hard key control area, and examined the effectiveness of the method by applying it to a smartphone with 5.0” screen. 45 participants were involved for analysis of preferred grip postures and another 44 participants were recruited for measurement of preferred hard key control area. Smartphone mock-ups which allow participants to adjust the locations of hard keys in their preference were developed having similar specification of real smartphone. L (left) 3 - R (right) 1 - K (back) 1 grip posture (82.6%) that the back side of the device is supported by the index finger and L (left) 4 - R (right) 1 grip posture (11.9%) that all five fingers contribute to grasp the device hardly were the most preferred for the smartphone with 5.0” screen. The optimal hard key locations were found 77 ~ 96 mm area from the bottom for the 20 mm right hard key and 88 ~ 97 mm area from the bottom for the 10 mm left hard key. A verification with real smartphones in various use contexts is needed to apply the results to the product design since the experiments were conducted in a laboratory setting with mock-ups.
33
Aleadelat, Waleed, and Khaled Ksaibati. "Estimation of Pavement Serviceability Index Through Android-Based Smartphone Application for Local Roads." Transportation Research Record: Journal of the Transportation Research Board 2639, no. 1 (January 2017): 129–35. http://dx.doi.org/10.3141/2639-16.
Full textAbstract:
The Wyoming Technology Transfer Center is in the process of developing a pavement management system (PMS) for county paved roads in Wyoming. This PMS uses the present serviceability index (PSI) as a main pavement performance parameter. This PMS depends on pavement condition index, international roughness index, and pavement rutting as explanatory variables to estimate PSI. This study researched new explanatory variables measured by using smartphones’ sensors to estimate PSI. It was found that the variance of the signals (time series acceleration data) acquired by smartphones’ accelerometers could work as a very good explanatory variable to estimate PSI. Two models were developed with high significance ( R2 higher than .9) to predict PSI using the variance of smartphone signals. The initial validation results suggested that using these models could predict, with high certainty, the actual PSI values. The difference between the predicted and the actual PSI values was not statistically different. The study was performed on 20 roadway segments extracted from the Wyoming county roads’ PMS database. In addition, the selected segments had various lengths and geometric features reflecting various roadway segments under any PMS. The proposed methodology is intended to lower the cost of measuring county roads’ pavement conditions by estimating PSI directly without the reliance on the direct measurement of pavement condition parameters.
34
Qanash, Sultan, Faisal Al-Husayni, Haneen Falata, Ohud Halawani, Enas Jahra, Boshra Murshed, Faris Alhejaili, Ala’a Ghabashi, and Hashem Alhashmi. "Effect of Electronic Device Addiction on Sleep Quality and Academic Performance Among Health Care Students: Cross-sectional Study." JMIR Medical Education 7, no. 4 (October 6, 2021): e25662. http://dx.doi.org/10.2196/25662.
Full textAbstract:
Background Sleep quality ensures better physical and psychological well-being. It is regulated through endogenous hemostatic, neurogenic, and circadian processes. Nonetheless, environmental and behavioral factors also play a role in sleep hygiene. Electronic device use is increasing rapidly and has been linked to many adverse effects, raising public health concerns. Objective This study aimed to investigate the impact of electronic device addiction on sleep quality and academic performance among health care students in Saudi Arabia. Methods A descriptive cross-sectional study was conducted from June to December 2019 at 3 universities in Jeddah. Of the 1000 students contacted, 608 students from 5 health sciences disciplines completed the questionnaires. The following outcome measures were used: Smartphone Addiction Scale for Adolescents–short version (SAS-SV), Pittsburgh Sleep Quality Index (PSQI), and grade point average (GPA). Results The median age of participants was 21 years, with 71.9% (437/608) being female. Almost all of the cohort used smartphones, and 75.0% (456/608) of them always use them at bedtime. Half of the students (53%) have poor sleep quality, while 32% are addicted to smartphone use. Using multivariable logistic regression, addiction to smartphones (SAS-SV score >31 males and >33 females) was significantly associated with poor sleep quality (PSQI >5) with an odds ratio of 1.8 (1.2-2.7). In addition, male gender and older students (age ≥21 years) were significantly associated with lower GPA (<4.5), with an odds ratio of 1.6 (1.1-2.3) and 2.3 (1.5-3.6), respectively; however, addiction to smartphones and poor sleep quality were not significantly associated with a lower GPA. Conclusions Electronic device addiction is associated with increased risk for poor sleep quality; however, electronic device addiction and poor sleep quality are not associated with increased risk for a lower GPA.
35
Mohapatra, Dipti, Syed Bilal Ali, Lipilekha Patnaik, and Tapaswini Mishra. "A cross-sectional study on the effect of bedtime smartphone usage on sleep quality, sleep duration and daytime sleepiness in medical students." Journal of Associated Medical Sciences 56, no. 1 (January 2, 2023): 19–25. http://dx.doi.org/10.12982/jams.2023.003.
Full textAbstract:
Background: Sleep is a physiological phenomenon. It is a condition of unawareness that the body regulates homeostatic. Sleep is essential because it plays a leading role in mental and physical function, removing toxins, preventing diseases, etc. Reduced sleep among young adults is becoming a significant health problem worldwide. Several factors have been shown to lead to poor sleep quality, but the reason smartphone use creates sleep disorders in young adults has attracted great curiosity for a few years. The study aimed to assess sleep quality, duration, and daytime sleep dysfunction among medical students who use their smartphones at bedtime. Materials and methods: This cross-sectional study included 109 medical students. The data was collected using a pre-validated questionnaire about bedtime mobile phone usage and Pittsburgh sleep quality index (PSQI). The means were calculated, and the association was determined using statistical analysis. Results: In the study, 60% of participants indicated poor sleep quality was due to prolonged bedtime smartphone usage. The average global PSQI score was 5.4±2.5. Conclusion: This study concluded that participants had poor sleep quality measured by PSQI. In addition, prolonged smartphone usage during bedtime was strongly co-related to poor sleep latency.
36
Dutta, Arindam, Ekta Sardar, Sarbani Dutta, Sushmita Saha, Rupak Chakraborty, Moloy Dhar, Sourish Mitra, and Biswajit ChakiChoudhur. "Identification of Cancerous Cell from Noisy Images." International Journal for Research in Applied Science and Engineering Technology 10, no. 6 (June 30, 2022): 4055–57. http://dx.doi.org/10.22214/ijraset.2022.44765.
Full textAbstract:
Abstract: Over the last decades, the incidence of skin cancer, melanoma and non-melanoma,has increased at a continuous rate. In particular for melanoma, the deadliest type of skin cancer, early detection is important to increase patient prognosis. Recently, deep neural networks (DNNs) have become viable to deal with skin cancer detection. In this work, we present a smartphone-based application to assist on skin cancer detection. This application is based on a Convolutional Neural Network (CNN) trained on clinical images and patients demographics, both collected from smartphones. Also, as skin cancer datasets are imbalanced, we present an approach, based on the mutation operator of Differential Evolution (DE) algorithm,to balance data. In this sense, beyond provides a flexible tool to assist doctors on skin cancer screening phase, the method obtains promising results with a balancedaccuracy of 85% and a recall of 96%. Index Terms—skin cancer detection, smartphone application, deep learning, convolutional neural network
37
Kim, Do Hyun, Sung Won Kim, and Se Hwan Hwang. "Diagnostic value of smartphone in obstructive sleep apnea syndrome: A systematic review and meta-analysis." PLOS ONE 17, no. 5 (May 19, 2022): e0268585. http://dx.doi.org/10.1371/journal.pone.0268585.
Full textAbstract:
Objectives To assess the diagnostic utility of smartphone-based measurement in detecting moderate to severe obstructive sleep apnea syndrome (OSAS). Methods Six databases were thoroughly reviewed. Random-effect models were used to estimate the summary sensitivity, specificity, negative predictive value, positive predictive value, diagnostic odds ratio, summary receiver operating characteristic curve and measured the areas under the curve. To assess the accuracy and precision, pooled mean difference and standard deviation of apnea hypopnea index (AHI) between smartphone and polysomnography (95% limits of agreement) across studies were calculated using the random-effects model. Study methodological quality was evaluated using the QUADAS-2 tool. Results Eleven studies were analyzed. The smartphone diagnostic odds ratio for moderate-to-severe OSAS (apnea/hypopnea index > 15) was 57.3873 (95% confidence interval [CI]: [34.7462; 94.7815]). The area under the summary receiver operating characteristic curve was 0.917. The sensitivity, specificity, negative predictive value, and positive predictive value were 0.9064 [0.8789; 0.9282], 0.8801 [0.8227; 0.9207], 0.9049 [0.8556; 0.9386], and 0.8844 [0.8234; 0.9263], respectively. We performed subgroup analysis based on the various OSAS detection methods (motion, sound, oximetry, and combinations thereof). Although the diagnostic odds ratios, specificities, and negative predictive values varied significantly (all p < 0.05), all methods afforded good sensitivity (> 80%). The sensitivities and positive predictive values were similar for the various methods (both p > 0.05). The mean difference with standard deviation in the AHI between smartphone and polysomnography was -0.6845 ± 1.611 events/h [-3.8426; 2.4735]. Conclusions Smartphone could be used to screen the moderate-to-severe OSAS. The mean difference between smartphones and polysomnography AHI measurements was small, though limits of agreement was wide. Therefore, clinicians should be cautious when making clinical decisions based on these devices.
38
Kim, Youngkyu, Woo June Choi, Jungmin Oh, and Jun Ki Kim. "Compact Smartphone-Based Laser Speckle Contrast Imaging Endoscope Device for Point-of-Care Blood Flow Monitoring." Biosensors 12, no. 6 (June 9, 2022): 398. http://dx.doi.org/10.3390/bios12060398.
Full textAbstract:
Laser speckle contrast imaging (LSCI) is a powerful visualization tool for quantifying blood flow in tissues, providing simplicity of configuration, ease of use, and intuitive results. With recent advancements, smartphone and camera technologies are suitable for the development of smartphone-based LSCI applications for point-of-care (POC) diagnosis. A smartphone-based portable LSCI endoscope system was validated for POC diagnosis of vascular disorders. The endoscope consisted of compact LED and laser illumination, imaging optics, and a flexible fiberscope assembled in a 3D-printed hand-held cartridge for access to body cavities and organs. A smartphone’s rear camera was mounted thereto, enabling endoscopy, LSCI image acquisition, and processing. Blood flow imaging was calibrated in a perfused tissue phantom consisting of a microparticle solution pumped at known rates through tissue-mimicking gel and validated in a live rat model of BBN-induced bladder cancer. Raw LSCI images successfully visualized phantom flow: speckle flow index showed linearity with the pump flow rate. In the rat model, healthy and cancerous bladders were distinguishable in structure and vasculature. The smartphone-based low-cost portable mobile endoscope for monitoring blood flow and perfusion shows promise for preclinical applications and may be suitable for primary diagnosis at home or as a cost-effective POC testing assay.
39
Pichon, Leo, James Taylor, and Bruno Tisseyre. "Using smartphone leaf area index data acquired in a collaborative context within vineyards in southern France." OENO One 54, no. 1 (March 10, 2020): 123–30. http://dx.doi.org/10.20870/oeno-one.2020.54.1.2481.
Full textAbstract:
Aim: The objective of this short communication is to study the opportunity of using a smartphone application for leaf area index (LAI) observations within vineyards in southern France in a farmsourcing context, i.e. when several operators make parallel acquisitions over the same area. In this context, several sources of variability are likely to affect measurement quality, such as the smartphone model or the operator. Understanding these sources of variability will enhance the ability to properly interpret LAI observations to produce relevant information for decision-making.Methods and material: A study was specifically designed to evaluate the ability of a smartphone application to differentiate sites with different LAI and to determine the origin and the relative importance of different sources of variation in a context of farmsourcing data collection. This focused on the VitiCanopy application, which has been developed specifically for viticulture LAI measurements. Measurements were performed by 18 operators with 11 different smartphone models, on three different vines presenting controlled canopy size to evaluate the ability of the smartphone application to differentiate sites under varying acquisition conditions. Controlled repetitions over seven vines by seven operators with seven smartphone models were performed to further determine the sources of variation and their relative importance.Results: LAI estimations made with VitiCanopy were consistent with the different levels of controlled vine size in the experiment. The operator and the smartphone model had a significant effect on the variance of the estimated LAI. The variance caused by the observation protocol was relatively low compared to the variability between plants within the observation site (seven vines).Conclusions: This study showed that the VitiCanopy application was relevant for ordering or classifying vines according to LAI. In an operational context, the results of this study support the use of this smartphone application for relative measurements. However, the best results were achieved when smartphone model differences were minimised or avoided and with homogeneous acquisition conditions between operators. This last condition will require the organisation of group training sessions to minimise an observed operator effect on measurement variability.Significance and impact of the study: This short communication demonstrated the potential of LAI observations collected with smartphones by several operators for decision-making in a context of farmsourcing. The results showed that this new source of observations, which is inexpensive to collect, made it possible to characterise vine size (LAI) differences in vineyards of southern France. This shows the potential of this app for large production areas such as cooperatives. Further investigations are needed to understand how different training systems may affect the measurement. This source of observations could be complementary to other information sources that are more precise or more accurate, but also more expensive (i.e. destructive methods).
40
Gupta, Rajshree, Santosh Kumar Sant, Rajesh Kumar Gupta, Raveendra Singh Rajpoot, Amit Kant Singh, Kirti Jaiswal, Naresh Pal Singh, et al. "DETERMINING PATTERN OF SMARTPHONE USAGE AND ASSOCIATION OF ACADEMIC STRESS WITH SLEEP QUALITY OF FIRST-YEAR MEDICAL UNDERGRADUATE STUDENTS - A CROSS-SECTIONAL STUDY." International Journal of Advanced Research 10, no. 10 (October 31, 2022): 479–87. http://dx.doi.org/10.21474/ijar01/15514.
Full textAbstract:
Introduction:Medical students, encounter considerable stress during prolonged study periods,especially during their exams, and together with excessive smartphone usage for studies and social networking are vulnerable to lack of sleep. Humans require adequate sleep to survive, as it greatly influences ones capacity for productive and effective daily performance. According to several studies, sleep-deprived students may experience headaches, muscle aches, sweating, palpitations,insomnia, nightmares, difficulties falling asleep, etc. Methods:Methods for gathering data included a pre-structured &pre-designed questionnaire for Smartphone Usage, Perceived Academic Stress (PAS) Scale & Pittsburgh Sleep Quality Index (PSQI). Surveyed 184 first-year medical students of U.P.U.M.S., Saifai, Etawah. Results:Out of 184 students (116 male and 68 female) the Screen time of Smartphones exceeds 3 hours in 44.6% (82) students, 168 students (91.3%) used their smartphone after 10 pm and 51 students (27.7%) students reported difficulty in eyes or refractive error due to smartphone usage. 86 students (46.7%) think smartphone usage has a negative impact on their sleep quality. The Mean±Standard Deviation of the Perceived Academic Stress (PAS) Scale for all Subjects was 60.11 ± 11.29(>60 is High Academic Stress and that of Global PSQI Scores was 9.15 ± 0.58 (>5 associated with poor sleep quality). The association between the variables was determined by analysis of variance that is the value of significance or the p-value was p = 0.0001. Conclusion: The findings of this study led us to the significant association between academic stress with sleep quality. There is high academic stress among the studentsand the pattern of their smartphone usage has a negative impact on their sleep quality.
41
Jamalova, Maral, and Constantinovits Milán. "The Comparative Study of the Relationship Between Smartphone Choice and Socio-Economic Indicators." International Journal of Marketing Studies 11, no. 3 (July 12, 2019): 11. http://dx.doi.org/10.5539/ijms.v11n3p11.
Full textAbstract:
The aim of the current study is to measure the influence of the socio-economic indicators on consumers’ purchase decision about smartphones based on the operating system. For this purpose, indicators as GDP per capita, Gross Savings, Inflation, ICT Development Index, Unemployment and Human Development Index were chosen. Excluding cultural, psychological and personal factors (which mainly should be analyzed on microeconomic level), therefore mentioned socio-economic variables are the same for all citizens of the country. These indicators create an overview of the general situation on the global level and in the developing/developed countries. Also, it makes a sense to identify the relationship between variables not only on the global level but also in the context of income level. So, research is essential to determine the above-mentioned trends in the smartphone market.
42
Coe, Mary, and Jan Wright. "Looking for needles in a haystack: how do ebook reader applications handle active indexes? Part 4 - smartphones." Indexer: The International Journal of Indexing: Volume 39, Issue 1 39, no. 1 (March 1, 2021): 15–34. http://dx.doi.org/10.3828/indexer.2021.3.
Full textAbstract:
Indexes in ebooks can be ‘active’, with hyperlinks into the text. Should these links go to the page, paragraph, line or word level? This is a complex question, but the main concern may be the user interface in ebook reader applications. In this last article of a four-part series, Mary Coe and Jan Wright report on their investigation of how active ebook indexes are handled by applications on smartphones. They conclude that smartphone applications perform reasonably well but do not handle all levels of locator specificity with precision and that small smartphone screens can lead to problems with index display and use. They also conclude the series with a summary of their findings across all ereading applications and devices. (See also the other articles in this series - the first part on Web-based browser ereader applications in The Indexer 37(2), pp. 125-40; the second part on dedicated ereader devices in The Indexer 38(1), pp. 29-44; and the third part on tablet devices in The Indexer 38(3), pp. 271-89.)
43
Kadhim Rashid, Muayad, Saad Ahmed Ali Jadoo, Adil Hassan Alhusseiny, and Ismail Ibrahim Latif. "Prevalence of text neck syndrome among Iraqi medical students: a cross-sectional study." Journal of Ideas in Health 5, Special1 (July 17, 2022): 693–99. http://dx.doi.org/10.47108/jidhealth.vol5.issspecial1.229.
Full textAbstract:
Background: Excessive use of portable electronic devices causes neck flexion and the emergence of text neck syndrome (TNS). This study aims to explore the prevalence of TNS among medical students during the COVID-19 lockdown in Iraq. Methods: A prospective cross-sectional web-based study was conducted from 1st to 20th March 2021 at the faculty of medicine, Diyala University, Iraq. A self-administered questionnaire was distributed among the medical students using Google Form through social media (WhatsApp group). The semi-structured questionnaire included the sociodemographic, the valid smartphone addiction scale-short version (SAS-SV), and the neck disability index (NDI). Univariate, bivariate, and multiple logistic regression were used to analyze the data. SPSS version 16. The statistical significance is considered at less than 0.05. Results: Out of 273 medical students included in the study, 59.3% were males, unmarried (88.3%), and from the 1st year (21.6%). The mean age of students was 21.27 ± 1.74 years. The prevalence of text neck syndrome was 64.5%. About two-thirds (61.5%) of students were addicted to their smartphones and used them more than five h/daily (63.7%). Factors associated with neck disability were the students who did not warm up neck muscles before using the smartphone (OR = 8.796, 95% CI: 1.724 to 24.884), addicted to the smartphone (OR = 6.803, 95% CI: 3.455 to 13.397), experienced increase in daily hours using the smartphone during the COVID-19 related quarantine (OR = 5.370, 95% CI: 2.523 to 11.427), maintained smartphone use five hours and more daily (OR = 2.818, 95% CI: 1.422 to 5.587), had neck pain (OR = 2.876, 95% CI: 1.356 to 6.098), the female gender (OR = 2.756, 95% CI: 1.221 to 6.221), and those who did not have a frequent break when using the smartphone (OR = 2.693, 95% CI: 1.329 to 5.454). Conclusion: In conclusion, the prevalence of neck disability was high among the surveyed medical students. Addiction and excessive smartphone use with a lack of attention to warm up the neck muscles before usage was the most prominent predictors of neck disability.
44
Cho, Jay, and Kiseok Sung. "Identifying the boundaries of screen edge and screen corner gestures based on thumb and index finger interactions on a small touch screen." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 61, no. 1 (September 2017): 1062–65. http://dx.doi.org/10.1177/1541931213601870.
Full textAbstract:
Due to the increasing complexity and number of additional features now found in smartphones, it is important for smartphone designers to provide users an efficient way to access these features. This study examines the potential of performing gestures that start at the screen corners (rather than the middle of the edges), by drawing the trajectories and identifying the boundaries of screen edge and screen corner gestures based on the thumb and index finger interactions. Eleven participants were required to perform screen edge and screen corner gestures using their thumb with one hand or index finger while holding the device with their other hand. Kernel density estimations were plotted based on interaction method and gesture. Paired t-tests showed that screen corners will not interfere with the commonly used screen edge gestures and could be a viable region for a new set of gestures. A primary contribution of this study is to present a baseline for screen corner gesture design guidelines.
45
Agus Suprayitno, Eko, Akhmad Setiawan, and Rohman Dijaya. "Design of Instrumentation in Detecting Blood Sugar Levels with Non-Invasive Technique Base on IoT (Internet of Things)." International Journal of Engineering & Technology 7, no. 4.15 (October 7, 2018): 440. http://dx.doi.org/10.14419/ijet.v7i4.15.25252.
Full textAbstract:
Diabetes mellitus is a disease with metabolic disorders that result from defects in insulin secretion, which results in hyperglycemia with impaired carbohydrates, fats and body proteins. Diabetes mellitus can be known by measuring blood sugar levels which are generally done by injuring the body (Invasive) for blood. Normal blood sugar values range from 70 - 200 mg/dL. For people with diabetes mellitus, checking blood sugar is an important thing to do to maintain their body condition. In this study made Instrumentation detection of blood sugar levels non-invasive (does not hurt the body). This study uses the MAX30100 sensor as a non-invasive measure of blood sugar levels, because to determine blood sugar levels is only done by attaching the index finger to the sensor, and does not hurt the fingers. The value of blood sugar levels in this instrumentation is displayed on LCD and Android smartphones. For serial communication, Instrumentation with Android smartphones is done with IoT (Internet Of Things) technology to make it easier for medical officers to monitor the condition of diabetics through remote Android smartphones. From the results of testing Non-invasive blood sugar detection instrumentation with industry standard blood sugar measurement (Invasive), the accuracy of blood sugar readings was 90.3% with a deviation of 1.2 - 39.6 mg/dL. Tests were carried out on 14 Normal patients and people with diabetes mellitus. Reading distance reading Non-invasive blood sugar detection instrumentation with an Android Smartphone can reach a distance of 823 Km as long as Instrumentation is connected to the internet. Tests have been carried out in several cities including Sidoarjo, North Jakarta, Sidoarjo-Lamongan, Sidoarjo-Kediri.
46
Lee, Yushin, Joong Hee Lee, Yong Min Kim, Jihwan Lee, Sanghyun Kwon, Hyungmin Sim, and Myung Hwan Yun. "The Effects of Curvature of Edge Screen on Subjective Feelings in Smartphone Usage." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 61, no. 1 (September 2017): 1269–70. http://dx.doi.org/10.1177/1541931213601798.
Full textAbstract:
As the penetration rate of Smartphone grows high and the market gets saturated, the technological and aesthetic progress for manufacturers are heavily demanded to sustain their market share. To meet such demands, manufacturers continuously improve the design of their products. As the design of smartphone varies by manufacturers, there have been many existing researches to identify the relationships between various physical dimensions of smartphones and how users feel (Chowdhury, A., & Kanetkar, M., 2017; Lee, S., Kyung, G., Lee, J., Moon, S. K., & Park, K. J., 2016; Pereira, A., Miller, T., Huang, Y. M., Odell, D., & Rempel, D., 2013; Sung, K., Cho, J., & Freivalds, A., 2016). Recently, in accordance with the development and improvement of flexible displays, curved displays have been applied on smartphones with various curvatures. The popular one among them is the “edge screen” on smartphones, which refers to curved display implemented either on one single side or both sides. Considering that physical dimensions such as shape and size are the important features for customer satisfaction (Hwang, 2012; Ling, C., Hwang, W., and Salvendy, G., 2007), curvature of edge screen can influence on user comfort when the users carry out their tasks on their smartphones. However, such issue hasn’t been dealt in previous studies. Therefore, as a preliminary study, this study aimed to identify the relationships between curvatures of edge screens and subjective feelings in smartphone usage with various usage patterns using subjective evaluation experiment. In this laboratory study, 47 subjects assessed their subjective feelings (grip comfort, control comfort, stability, front visibility, side visibility) towards given samples with four different kinds of usage patterns. The samples were designed with a 5.5-inch flat display of 16:9 ratio (Samsung Galaxy Note 2) as a main screen along with a curved display of different radii of curvatures (R, unit: mm) on the right edge as an edge screen: 4R, 6R, 8R, and 10R. The usage patterns were defined according to which hands were used for grip and control: Grip with right hand and control with right thumb (usage pattern (a)), Grip with left hand and control with right index finger (usage pattern (b)), Grip with both hands and control with both thumbs (usage pattern (c)), and Grip with right hand without control (usage pattern (d)). The statistically significant results of one-way analysis of variance (ANOVA) and post hoc analysis (Duncan’s test) showed that the sample with 4R curvature belonged to the third homogeneous subset (in descending order) for the front visibility while it belonged to the second homogeneous subset for the control comfort in usage pattern (b) and (c). Whereas the sample with 6R curvature belonged to the second homogeneous subset for the front visibility and the second homogeneous subset for the control comfort in usage pattern (b) and (c). In case of the sample with 8R curvature, it was within the first homogeneous subset throughout all analyses conducted. Lastly, the sample with 10R curvature was within the second homogeneous subset for the grip comfort in usage pattern (d). Therefore, it is concluded that the optimal radius of curvature for edge screens is 8R. Although there were some samples evaluated better than the 8R sample in descriptive manner, however, such results were not statistically significant. This study is expected to contribute towards the design of smartphones with edge screens in terms of better subjective feeling by various usage patterns. However, this study is yet a preliminary study which is based on a subjective evaluation. In the future research, more criteria of subjective feeling are needed to be evaluated to decide more precise optimal curvature. In addition, objective evaluation method such as analysis of muscle activity, motion tracking analysis, or behavior analysis could be applied to verify the reliability and validity of the result of this study.
47
Horbiński, Tymoteusz, Paweł Cybulski, and Beata Medyńska-Gulij. "Web Map Effectiveness in the Responsive Context of the Graphical User Interface." ISPRS International Journal of Geo-Information 10, no. 3 (March 3, 2021): 134. http://dx.doi.org/10.3390/ijgi10030134.
Full textAbstract:
The main objective of this article was to determine the effectiveness of a web map GUI (Graphical User Interface) layout designed specifically for desktop monitors and smartphones. A suitable design of buttons for the graphical user interface is vital for the effectiveness of web maps. This article presents a study of three rules that prevail in GUI map design in terms of responsiveness, which was analyzed on two devices: a smartphone and a PC screen. The GUI effectiveness study, based on six variants of web maps, was conducted by means of eye-tracking on a group of 120 participants. An additional goal was to find an index (based on eye movements, mouse tracking, and time) that would be assessing the effectiveness of the GUI layout on both devices. The main motivation for conducting the research described in the article was the desire to find a synthetic measure based on more than one factor (time) in the context of determining the effectiveness of the GUI.
48
Lee, Sungchul, Eunmin Hwang, Yanghee Kim, Fatih Demir, Hyunhwa Lee, Joshua J. Mosher, Eunyoung Jang, and Kiho Lim. "Mobile Health App for Adolescents: Motion Sensor Data and Deep Learning Technique to Examine the Relationship between Obesity and Walking Patterns." Applied Sciences 12, no. 2 (January 14, 2022): 850. http://dx.doi.org/10.3390/app12020850.
Full textAbstract:
With the prevalence of obesity in adolescents, and its long-term influence on their overall health, there is a large body of research exploring better ways to reduce the rate of obesity. A traditional way of maintaining an adequate body mass index (BMI), calculated by measuring the weight and height of an individual, is no longer enough, and we are in need of a better health care tool. Therefore, the current research proposes an easier method that offers instant and real-time feedback to the users from the data collected from the motion sensors of a smartphone. The study utilized the mHealth application to identify participants presenting the walking movements of the high BMI group. Using the feedforward deep learning models and convolutional neural network models, the study was able to distinguish the walking movements between nonobese and obese groups, at a rate of 90.5%. The research highlights the potential use of smartphones and suggests the mHealth application as a way to monitor individual health.
49
Aharony, Noa, and Avi Zion. "Effects of WhatsApp's Use on Working Memory Performance Among Youth." Journal of Educational Computing Research 57, no. 1 (January 23, 2018): 226–45. http://dx.doi.org/10.1177/0735633117749431.
Full textAbstract:
The current study seeks to shed light on the usage habits of the WhatsApp application among teenagers, exploring the effect of mobile instant messaging distractions on pupils' working memory performance. Research was conducted in Israel during 2016 school year. The study sample was divided into two groups randomly—a control group and an experimental group. Researchers used six questionnaires to gather personal details, execution assessment questionnaire, and Working Memory Index from the Wechsler Intelligence Scale for Children-IV. The main findings show that WhatsApp's distractions, transmitted via smartphones, decrease pupils' performance of working memory. In addition, students are aware of the difficulty WhatsApp causes while performing a learning task and of the decrease in learning effectiveness. The present study displays a unique experiment that explored the direct effect of the distractions stemming from a new technological platform— WhatsApp—on young pupils' working memory. Further, it suggests that instructors and teachers should be aware of the potential damage of multitasking caused by smartphone use during learning tasks.
50
Maldonado-Romo, Javier, and Mario Aldape-Pérez. "Sustainable Circular Micro Index for Evaluating Virtual Substitution Using Machine Learning with the Path Planning Problem as a Case Study." Sustainability 13, no. 23 (December 4, 2021): 13436. http://dx.doi.org/10.3390/su132313436.
Full textAbstract:
Due to the problems resulting from the COVID-19 pandemic, for example, semiconductor supply shortages impacting the technology industry, micro-, small-, and medium-sized enterprises have been affected because the profitability of their business models depends on market stability. Therefore, it is essential to propose alternatives to mitigate the various consequences, such as the high costs. One attractive alternative is to replace the physical elements using resource-limited devices powered by machine learning. Novel features can improve the embedded devices’ (such as old smartphones) ability to perceive an environment and be incorporated in a circular model. However, it is essential to measure the impact of substituting the physical elements employing an approach of a sustainable circular economy. For this reason, this paper proposes a sustainable circular index to measure the impact of the substitution of a physical element by virtualization. The index is composed of five dimensions: economic, social, environmental, circular, and performance. In order to describe this index, a case study was employed to measure the path-planning generator for micro aerial vehicles developed using virtual simulation using machine-learning methods. The proposed index allows considering virtualization to extend the life cycle of devices with limited resources based on suggested criteria. Thus, a smartphone and the Jetson nano board were analyzed as replacements of specialized sensors in controlled environments.