Smartphone Addiction Scale-Short Version Research Articles

Investigating the Smartphone Addiction among Undergraduate Nursing Students

In today's digital era, smartphones have become an essential part of our society. However, excessive use of smartphones can have a wide range of consequences and it affects students' physical and mental health. Nursing students should know the appropriate use of smartphones to prevent health complications. Objective: To investigate the prevalence of smartphone addiction among nursing students. Methods: A descriptive cross-sectional study design was utilized in a total of 98 nursing students of Saifee Burhani School of Nursing in Karachi, Pakistan. A convenience sampling technique was used to collect data and a Smartphone Addiction Scale short version (SAS-SV) questionnaire was utilized to collect data related to smartphone usage patterns and addiction levels among nursing students. Results: The study findings revealed that 68 nursing students (69.39%) were addicted to smartphones. Descriptive statistics, ANOVA, and independent t-independent -test were applied by Statistical Package for Social Sciences (SPSS) software version 25.0 for data analysis. Conclusions: The present study revealed that Smartphone addiction was found higher among nursing students.

Exploring the impact of smartphone addiction on decision-making behavior in college students: an fNIRS study based on the Iowa Gambling Task.

The pervasive use of smartphones, while enhancing accessibility to information and communication, has raised concerns about its potential negative effects on physical and mental health, including the impairment of decision-making abilities. This study investigates the influence of smartphone addiction on decision-making in college students. A sample of 80 individuals aged 17 to 26 was selected and divided into two groups based on their Smartphone Addiction Scale-Short Version (SAS-SV) scores. Participants underwent the Iowa Gambling Task (IGT) to evaluate their decision-making in risky and uncertain conditions, while fNIRS recorded their prefrontal cortex activity. The study found that individuals prone to smartphone addiction tend to make riskier choices in risky situations. However, when faced with decisions based on ambiguity, the smartphone addiction group showed increased brain activity in the dlPFC (specifically in channels 4, 9, and 11) compared to when making risky decisions. Despite this increased brain activation, there was no observable difference in behavior between the addiction-prone and control groups in ambiguous scenarios. Notably, the left dlPFC (e.g., channel 4) exhibited significantly higher activation in the addiction group compared to the control group. Findings suggest that smartphone addiction can detrimentally influence decision-making, behaviorally and neurologically, particularly in uncertain contexts. This study supports the classification of smartphone addiction as a genuine addiction and underscores its significance in psychiatric research. In essence, our research underscores the adverse effects of excessive smartphone use on decision-making processes, reinforcing the necessity to treat smartphone addiction as a pressing public health issue.

Comparison of musculoskeletal pain and upper extremity disability in smartphone addicts and smartphone non-addicts among university students: A cross-sectional study

ObjectiveThe aim of this study was to compare musculoskeletal pain and upper extremity disability between 'smartphone addicts' and 'non-smartphone addicts' and to assess the impact of determinants of musculoskeletal pain and upper extremity disability in both groups. MethodsThe study included 352 university students aged 18–25 years who used smartphones for at least 1 h per day in the past year. The questionnaire consisted of demographic data, the Smartphone Addiction Scale-short version (SAS-SV), the Quick Disabilities of the Arm, Shoulder, and Hand questionnaire (QuickDASH), and the Verbal Rating Scale. Participants were divided into two groups, 'smartphone addicts' and 'smartphone non-addicts', according to their SAS-SV scores (cut-off for males≥31, females≥33). ResultsParticipants had a prevalence of smartphone addiction of 38.4%. There was a statistically significant difference between the 'addicted' and 'non-addicted' groups for SAS-SV (p < 0.001), Quick DASH (p < 0.001) and daily smartphone use time (p = 0.007). The results of logistic regression analyses showed that female gender was a predictor of shoulder (OR = 0.36, 95% CI = 0.16–0.85, p = 0.01) and wrist/hand (OR = 0.43, 95% CI = 0.19–0.98; p = 0.04) pain in smartphone addicts and low back pain (OR = 0.34, 95% CI = 0.12–0.98, p = 0.04) in non-smartphone addicts. In both groups, the SAS-SV score was found to significantly predict the prevalence of musculoskeletal pain in all body regions. ConclusionsThe study showed that among university students, smartphone addicts had more musculoskeletal complaints and upper extremity disability than smartphone non-addicts. The SAS-SV score was a predictor of the prevalence of musculoskeletal pain and upper extremity disability in smartphone users among university students.

Alterations in white matter integrity in Egyptian youth with smartphone dependence: does DTI have a role?

BackgroundSmartphones provide various functions that facilitate our communication, organization, and entertainment in different situations. Diffusion tensor imaging (DTI) is a method measuring tissue microstructure as well as white matter integrity of the brain and detecting early changes. Several research studies recently aim to utilize conventional MRI for assessing brain structural alterations among smartphone users, but our study was aimed at identifying the DTI value while assessing white matter alterations in Egyptian youth with smartphone dependence.ResultsOur prospective case–control study involved fifty-three individuals with smart phone dependence (SPD group) as well as twenty-five volunteers who represented the control group. SPD individuals and controls were right-handed. The SPD group mean age exhibited 20.54 ± 1.56 years, while controls exhibited 26.8 ± 15.1 years. When utilizing smart phone addiction scale-short version, SPD group median total score exhibited 33. The diagnostic performance of fornix (fractional anisotropy) FA and external capsule fractional anisotropy (EC FA) regarding area under curve (AUC) exhibited significant increase as opposed to all other tested regions, with a sensitivity of 90.6% as well as a specificity of 96%. While regarding the mean diffusivity (MD), the greatest (AUC) was for EC (0.927, p < 0.001), in which the MD value = 0.825 was the cutoff value and able to diagnose the smart phone dependency with a sensitivity of 92.5% as well as a specificity of 76%.ConclusionsQuantitative DTI parameters (FA, MD) in different white matter regions can diagnose and detect white matter changes in excessive smartphone users even when conventional MRI data are normal. This study demonstrates the recent noninvasive MRI technique value while revealing covered brain white matter alterations in Egyptian youth due to smartphone overuse.

Childhood Adversity and Adolescent Smartphone Use Across Sexual Orientation and Gender Expression

Nonheterosexual and gender-nonconforming (GNC) individuals tend to report adverse childhood experiences (ACEs) more frequently compared with heterosexual and gender-conforming individuals, and individuals who have experienced ACEs, identify as nonheterosexual, or exhibit moderate to high levels of GNC are more prone to engaging in problematic smartphone use (PSU). However, there is limited school-based data among adolescents regarding this matter. To explore the associations between ACEs and PSU among adolescents across different sexual orientation and gender expression groups. Using data from the 2021 School-Based Chinese Adolescents Health Survey, this cross-sectional study includes participants from 288 public high schools across 8 provinces in China. Statistical analysis was performed from October 2023 to February 2024. Data on ACEs, sexual orientations, and gender expressions (high, moderate, and low GNC) were collected. PSU was assessed using the 10-item Smartphone Addiction Scale-Short Version (SAS-SV). Weighted linear, logistic, or Poisson regression models were used. Among the 85 064 adolescents included (mean [SD] age, 14.92 [1.77] years), 42 632 (50.1%) were female, 70 157 (83.2%) identified as Han Chinese, and 14 208 (16.8) identified as other ethnicities (Miao, Hui, Yi, Dai, and other ethnic groups). The prevalence of PSU among participants was 35.4%. Weighted Poisson regression models indicated that the interaction between GNC and ACE was significant (adjusted prevalence ratio [APR], 0.98; 95% CI, 0.97-0.99). Further stratified analysis demonstrated homosexual adolescents who experienced 4 or more ACEs showed a significantly increased prevalence of PSU (APR, 1.79; 95% CI, 1.64-1.96). Similarly, a markedly higher prevalence of PSU was observed among bisexual individuals with 4 or more ACEs (APR, 1.60; 95% CI, 1.41-1.80). Regarding gender expression categories, a significantly higher prevalence of PSU was noted among high GNC adolescents with 4 or more ACEs (APR, 1.78; 95% CI, 1.60-1.98) compared with low GNC adolescents without ACEs. Furthermore, experiencing any 3 ACE categories (abuse, neglect, and household dysfunction) was associated with an increased prevalence of PSU across different sexual orientation and gender expression subgroups. In this cross-sectional study, the amalgamation of elevated ACE scores with nonheterosexual orientations or GNC identities was significantly associated with increased PSU prevalence. These findings underscore that preventing ACEs may be beneficial in mitigating PSU among adolescents, particularly for nonheterosexual adolescents and those with high levels of GNC.

Smart Phone and Internet Addiction among Undergraduate Medical Students

Background: Smartphone is an indispensable miracle of artificial intelligence in the hands of global netizens. The internet and smartphones have a strong potential for addiction. Excessive usage of these technologies can have adverse effects on physical, social, and psychological well-being of the users.Objective: To assess the prevalence of Smartphone and Internet addiction and the associated factors amongmedical students.Methodology: Cross-sectional study was conducted among 202 undergraduate medical students. Data wascollected using pre-tested and pre-designed proforma after taking informed consent on voluntary basis. Smartphone addiction scale - short version (SAS-SV) and Internet addiction test (IAT) was used to assess smartphone and internet addiction respectively. Descriptive statistics and Chi-Square test and odds ratio was applied.Results: Among 202 undergraduate medical students 41.58% were addicted towards smartphone. 55.45% were having internet addiction, of which 39.60% and 15.35% were having mild and moderate level. 53.75% who were addicted to smartphone were having moderate and mild levels of internet addiction. This finding was found to be statistically significant (χ2 = 57.609, df = 1, p = 0.0001, OR= 13.4429)Conclusion: Smartphone addiction and internet addiction are related proportionally. It is necessary to createawareness regarding the ill health effects and to promote physical, social, and mental well-being among students from the undergraduate level.

Cyberchondria and smartphone addiction: A correlation survey among undergraduate medical students in Egypt

BackgroundThere is an increase in smartphone usage globally. Cyberchondria (CYB) is characterized by excessive Internet searches for health information. Smartphone addiction is constantly rising among medical students together with CYB as a collateral emerging risk, yet there is limited research available on the topic.MethodsThis cross-sectional study explores the rising phenomenon of smartphone addiction and its potential role in CYB among medical students in seven Egyptian universities. A total of 1435 medical students participated in completing online questionnaires that assessed smartphone addiction and CYB using the Smartphone Addiction Scale-Short Version (SAS-SV) and Cyberchondria Severity Scale (CSS-12). Multivariable regression analysis was applied to assess predictors of smartphone addiction and CYB.ResultsBased on the used scales, 57.6% of students were suffering from smartphone addiction, and 85.8% exhibited a moderate degree of CYB. There was a significant positive correlation between smartphone addiction scores and CYB (p < 0.05). The multivariable regression models revealed that four factors including using Facebook, using WhatsApp, increasing time spent on the Internet per day, and a higher CYB score increase the probability of smartphone addiction. The factors that increase the probability of CYB are using Facebook, an increase in the frequency of Internet searches, a higher degree of worry about one’s health or a family member’s health, and being a smartphone addict.ConclusionSmartphone addiction among undergraduate medical students is prevalent. Social media use, time spent online, and smartphone addiction were linked with the risk of CYB. Regular physical activity decreases the probability of smartphone addiction. Awareness programs and increased mental and physical activities are required to help reduce smartphone addiction among youth.

IJCM_357A: Smartphone addiction and physical activity among students of a Medical College in Bengaluru-a cross-sectional study

Background: Smartphones have become an indispensable necessity for medical students because of their various demands and comforts. The excessive use of smartphones may lead to addiction which can negatively affect physical and mental health including physical activity. The relationship between smartphone addiction and physical activity needs exploration. Hence this study was undertaken to assess the magnitude of smartphone addiction and to explore its association with physical activity among students of a medical college in Bengaluru. Objective: To assess smartphone addiction and its association with physical activity among students of a medical college in Bengaluru. Methodology: A cross-sectional study was conducted among students of Bangalore Medical College and Research Institute. Based on a study done in Maharashtra(p=46.15%), the sample size was calculated as 382. Study subjects were recruited by stratified random sampling and probability-proportional to size sampling was used to select study participants across various strata. Data was collected using a pretested semi-structured questionnaire. Smartphone addiction was assessed by smartphone addiction scale-short version (SAS-SV) and physical activity by international physical activity questionnaire-short form (IPAQ-SF). The data collected was entered in MS Excel and analyzed using SPSS 21.0. Results: Among 382 students 164(43%) were found to have smartphone addiction. The primary use of smartphones was for social networking. Physical activity, duration of smartphone usage, and use of the smartphone right before sleeping were associated significantly with smartphone addiction. Conclusion: The problem of smartphone addiction has reached an alarming level. There is a need to create awareness about the problem and plan effective strategies to address it.

Smartphone Addiction and the Associated Factors of Adolescents and Purposes and Pattern of Smartphone Use

Background: Smartphone addiction is the failure to control excessive smartphone use, in spite of its negative impacts on social, psychological, physical, and economic aspects of life. The smartphones, as multifunctional device have become essential in daily life, particularly among adolescents, but excessive reliance on them can lead to behavioural addiction. Objectives The study aimed to examine the association between smartphone addiction and the characteristics of adolescents and purposes and patterns of smartphone use. Methodology: The study adopted a descriptive correlation design among 209 adolescents (105 boys and 104 girls) selected from high schools using multi-stage random sampling. Data was collected regarding the general characteristics of the adolescents as well as the pattern of usage and purposes for which they use smartphones. The level of smartphone addiction was assessed by using Smartphone Addiction Scale—Short Version (SAS-SV). The association between smartphone addiction and study variables was tested using the chi-square test. Results: Majority of adolescents (66.99%) were found at high risk for smart phone addiction, while 27.75% were addicted to smart phones. The study found a significant correlation between smartphone addiction and adolescents' gender, class/standard, purpose for use of smartphone viz educational activities, mobile games, social networking, internet browsing and pattern of smartphone usage including types of ownership of smartphone, duration of smartphone use, report of recent change in eye sight/vision, internet packages and self-perceived overuse of smartphone at the 0.05 level of significance. Conclusion: The study reveals a significant relation between socio-demographic characteristics and smartphone addiction among adolescents aged 13–16 years of both gender, class, purposes and patterns of smartphone use. Smartphone use was be influenced by the socio-cultural environments in which adolescents live as well as the reasons for which they use their smartphones. Smartphone addicts spend considerable time using their smartphones, which is significantly influenced by the daily duration and purposes and patterns of smartphone usage. Keywords: Smartphone addiction; associated factors of adolescents; purposes of smartphone use; patterns of smartphone use.

Exploring the Relationship between Smartphone Addiction, Quality of Life, and Personality Traits in University Students.

Objective: This study aimed to explore the dynamics of the relationship among smartphone addiction, quality of life, and personality characteristics in university students. Method : This correlational and descriptive research was conducted to investigate the relationship between smartphone addiction, quality of life, and personality traits among university students. Using a nonprobability random sampling method, 496 university students were selected. Data collection involved the Student Information Form, Smartphone Addiction Scale, Symptom Checklist (SCL-90-R), Revised Eysenck Personality Questionnaire-Abridged Form (EPQR-A), and the WHO Quality of Life Scale-Short Form (WHOQOL-BREF). Statistical analysis was conducted with SPSS 25.0, utilizing Chi-square tests, independent sample t-tests, and Pearson's correlation analysis. Results: Out of 496 students (average age of 20.52), 59.87% were identified as smartphone addicts based on the Smartphone Addiction Scale-Short Version. A notable difference was found by study year (P = 0.009) and socioeconomic status (P = 0.003). Participants with smartphone addiction registered higher SCL-90-r scores for conditions like Obsessive Compulsive Disorder, Interpersonal Sensitivity, and Psychoticism. The Eysenck Personality Inventory highlighted that the Psychoticism score was significantly higher in the group with smartphone addiction (P = 0.001). A negative correlation between smartphone addiction scores and general health (WHOQoL) was identified, whereas a positive correlation with SCL-90-R's Psychoticism dimension score was observed (P < 0.001). Conclusion: Smartphone addiction is widespread among university student population. The study indicates that smartphone addiction not only impacts the individual's quality of life but also is associated with personality disorders, and these problems intensify with the severity of addiction. The findings underscore the need for interventions and educational programs to address smartphone addiction in this population.

Smartphone use and social media addiction in undergraduate students

Background Children’s use of social media has increased significantly over the past decade. As a result, they are susceptible to smartphone addiction. In particular, parents' and children's well-being and behaviors are negatively affected by smartphone addiction. Such addiction likely affects both physical performance and lifestyle. Adolescents utilize their smartphones while performing other tasks. The secondary task might divert attention away from the primary task. Reaction time is the combination of brain processing and muscular movement. Texting or communicating on a smartphone while performing another task may affect reaction time. Thus, the purpose of this study was to explore the influence of smartphone use on reaction time in undergraduate students who were addicted to smartphones. Methods The Smartphone Addiction Scale-Short Version (SAS-SV) was used to assign 64 undergraduate students to the smartphone addiction group (n = 32) and the control group (n = 32). The reaction time (RT) of an organism is used to determine how rapidly it responds to stimuli. All participants were examined on the RT test under three conditions: no smartphone use (control), texting, and chatting on a smartphone. Participants were questioned by smartphone through text message or chat with the support of a researcher during the texting and conversation conditions. While responding to the questions, the participant was administered an RT test. Results The results showed that smartphone addiction tends to have a reduced influence on reaction time when compared to the control group. Also, texting or conversing on a smartphone while doing other work had a substantial impact on reaction time in the undergraduates. Conclusions Combining smartphone use with other activities tends to reduce undergraduate students' reaction time.

The digital health dilemma: Exploring cyberchondria, well-being, and smartphone addiction in medical and non-medical undergraduates

Background: The Internet is a popular source of health information, but too much research can cause anxiety (cyberchondria). Medical and non-medical personnel interpret information differently, leading to varying rates of cyberchondria. Smartphone addiction may also contribute to cyberchondria and impact mental health. Methods: The study was an epidemiological survey-based investigation with a cross-sectional design involving undergraduate students (aged 18 years or older) from Indian universities or colleges. The study utilized the Cyberchondria Severity Scale-Short Form (CSS-12), WHO-5 well-being index, and Smartphone Addiction Scale-Short Version (SAS-SV). Results: A total of 1033 participants (53.1% females and 46.4% males) were recruited in the survey. Of the participants, 58.5% were pursuing medical or paramedical courses, while the remaining 41.5% belonged to the non-medical group. High-severity cyberchondria was present in about 4.4% of the students. The medical cohort demonstrated a significantly lower cumulative CSS in comparison to the non-medical cohort (t = - 3.90; P &lt; 0.01). Smartphone addiction was observed in 57.2% of individuals in the medical group and 55.9% of individuals in the non-medical group (P = 0.68). Medical students had a significantly lower mean well-being score compared to non-medical students (58.4 vs. 59.6; P &lt; 0.01). There was a positive correlation between cyberchondria severity and smartphone addiction, which was consistent across both groups. Conclusion: Medical students have less cyberchondria than non-medical students. Cyberchondria severity is linked to smartphone addiction. Non-medical students with cyberchondria have higher subjective well-being.

Association between Health Anxiety, Smartphone Addiction, and Cyberchondria

Abstract Introduction: Online health information seeking is one of the single most popular platforms in which people gather health-related information. Many sources provide ambiguous and unauthorized health information, which is part of the digital era. Cyberchondria refers to prolonged and repetitive online health searches and negative emotional and physiological responses that occur due to online searches. Health anxiety due to COVID-19 also contributed to online health information seeking. This current study assesses the association between health anxiety and smartphone use with cyberchondria among young adults. Methods: The study sample consisted of 356 individuals aged 18–25 years. We used an online survey for study participants with the Cyberchondria severity scale-12 (CSS-12), Health Anxiety Questionnaire, and the Smartphone Addiction Scale-Short Version. Results: The mean age of participants was 22 years (standard deviation: 2.13). Sixty-two percent of participants used the information obtained by the online platform to diagnose themselves. Excessiveness was more among all other subscales of cyberchondria. The results of linear regression analysis indicated that health anxiety (P &lt; 0.001) and smartphone addiction (P &lt; 0.001) significantly contributed to cyberchondria. Conclusion: This study shows the association between health anxiety and smartphone addiction with cyberchondria. This finding implies the need for a community-level conscientization on cyberchondria. There is a need to carry out promotional and preventive programs regarding the health usage of technology.

Relationship between smartphone addiction, loneliness, and depression in adolescents: A correlational structural equation modeling study

PurposeThis study was aimed to investigate the relationship between smartphone addiction, loneliness, and depression in adolescents. Design and methodsThis study was designed in a correlational-cross-sectional-descriptive model and was conducted with 1041 adolescents attending high schools in a provincial center in Eastern Turkey. The data were collected through face-to-face interviews using a personal information form, Smartphone Addiction Scale-Short Version for Adolescents, UCLA Loneliness Scale, and Kutcher Adolescent Depression Scale. ResultsThe average scores for smartphone addiction were found to be higher among females, individuals with low academic success, and those with a high-income level. Similarly, the average scores for loneliness were higher among individuals residing in broken families and those with parents who have limited literacy. Additionally, the mean scores for depression were higher among individuals with low academic success and those with a high-income level. Furthermore, a significant positive correlation was observed between the duration of smartphone use and levels of smartphone addiction, loneliness, and depression. ConclusionSmartphone addiction, loneliness, and depression were found to be prevalent above the moderate level in adolescents. Additionally, a significant positive correlation was observed between the depression and loneliness scores of adolescents. Practice implicationsPediatric and school nurses should assess children's phone use. Nurses are well-positioned to establish a follow-up program aimed at monitoring adolescents' efforts in managing smartphone use, offering continuous support, and providing guidance when necessary. The implementation of such programs enables prompt intervention in addressing any arising issues.

Characteristics of medical students with problematic smartphone use: a cross-sectional study

Background: Excessive smartphone use is common among university students and can negatively affect students’ mental health, but data from Middle-East countries is scarce. Objective of the study was to determine the characteristics of medical students affected by and the prevalence of problematic smartphone use in a sample of Iranian medical students. Methods: This cross-sectional study was conducted in a large Iranian medical university. A convenience sample of 356 students of different years of medical training were recruited. Data on socio-demographic characteristics, daily estimated average time using a smartphone, and main motivations to use a smartphone were collected through a self-reported questionnaire. Problematic smartphone use (PSU) was evaluated using the smartphone addiction scale – short version (SAS-SV) questionnaire. Backward logistic regression analysis was used to understand independent factors associated with PSU. Results: Overall, two-thirds of Iranian medical students were affected by PSU, including 68.5% of male and 64% of female students. Students who lived alone had significantly higher SAS-SV scores than those who lived with their families (p=0.007). Additionally, students with daily smartphone use &gt;4 hours were 3.2 times more likely to be diagnosed with PSU (p&lt;0.001). Social media use was the main motivation that strongly predicted the presence of PSU among medical students (adjusted OR: 2.87, 95% CI: 1.68-4.89). Conclusions: Main motivation to use and duration of phone use are the most important factors predicting problematic smartphone use among medical students.

Relationship Between Alexithymia, Smartphone Addiction, and Psychological Distress Among University Students: A Multi-country Study.

Increasing dependence on smartphones results in the appearance of psychological problems, especially among young people. This study aims to determine the rates of alexithymia and its relationship with smartphone addiction and psychological distress in university students. A total of 2616 students (mean age = 22.5±3.5 years; 73.1% female) from universities in Egypt, Oman, and Pakistan were included in a cross-sectional and comparative study conducted through a web survey during the COVID-19 pandemic from October to December 2021. The following scales were used: Toronto Alexithymia Scale (TAS-20), Depression Anxiety Stress Scale (DASS-21), and Smartphone Addiction Scale-Short Version (SAS-SV). The survey also included questions related to sociodemographic and smartphone usage patterns.

The Association between Smartphone Addiction and Headache among Adults

Background: Limited studies that adequately explain the cause-and-effect relationships have linked mobile phone use to various health consequences. Several studies have examined how exposure to mobile phones may affect various symptoms. To find out an association between smartphone addiction and headaches among adults. Methods: In this cross-sectional survey, data was collected through a non-probability sampling technique from 400 adults of either gender aged between 18 to 35 years from Rawalpindi, Islamabad and Taxila. Data was collected via the Smartphone Addiction Scale Short Version (SAS-SV), Headache Disability Index (HDI) and Visual Analogue Scale (VAS). The data were analyzed using the SPSS version 23. Results: There were 400 participants, n=187(46.8%) male and n= 213(53.3%) female, with mean age (23.20±4.41) years. The descriptive statistics of the study population were Functional HDI (21.10±11.62), Emotional HDI (19.99±12.47), HDI-Sum (41.09±22.90) and SAS-Sum (33.48±11.35). The correlation of smartphone addiction with pain (r=0.258, p=0.000), Functional HDI (r=0.349, p=0.000), Emotional HDI (r=0.364, p=0.000), and HDI-Sum (r=0.375,p=0.000) respectively. Conclusion: Headache due to smartphone addiction affects adults because of unrestricted usage of smartphones. Keywords: Headache, Pain, Smart Phones, Young Adults.

The relationship between smartphone addiction and fear of missing out: phubbing as the mediator in students at a university’s faculties

Background: Smartphone addiction is a public health problem. The aim of this study was to investigate the relationship between smartphone addiction with fear of missing out and phubbing. Methods: The universe of this cross-sectional study consisted of all students studying at Fırat University Faculties. 582 students were reached. A questionnaire was used as data collection tools. The questionnaire consists of demographic information form, questions about smartphone use, Smartphone Addiction Scale-Short Version, Fear of Missing Out Scale, and Phubbing Scale. SPSS PROCESS macro version 3.5 (Model 4) was used to test the mediation effect. Results: 51.5% of the students were women and the mean age of all students was 22.06 ± 2.99. Smartphone addiction score was higher in women (p &amp;lt; 0.05). A significant negative correlation was found between smartphone addiction and age (r = -0.10). A significant positive correlation was found between smartphone addiction and daily smartphone usage frequency (r = 0.31) and daily smartphone usage duration (r = 0.44). Fear of missing out and phubbing were significant positive predictors of smartphone addiction. Phubbing had a mediating effect on the effect of fear of missing out on smartphone addiction. Conclusion: Phubbing as a mediator increases the impact of fear of missing out on smartphone addiction.

Smartphone addiction prevalence, patterns of use, and experienced musculoskeletal discomfort during the COVID-19 pandemic in a general Iranian population

BackgroundSmartphone usage is an essential everyday tool in Iran, however problematic use has escalated and become a concern for the Iranian health policy system, particularly during and following the COVID-19 Pandemic. This study’s aim was investigation of the prevalence of smartphone addiction, patterns of use, and the relationship to specific demographic characteristics and associated musculoskeletal disorders during the COVID-19 pandemic.MethodsA descriptive-analytical correlational study recruited participants from a population of convenience (n = 2344) who were smartphone owners with > 1 year of use. For demographic information an electronic self-report questionnaire collected age, sex, marital status, usage for daily hours, and patterns. To assess addiction levels, the ‘Smartphone Addiction Scale-short version’ (SAS-SV) patient-reported outcome measure was used (cut-off = 31). For experienced discomfort, the Extended Nordic Musculoskeletal Questionnaire (ENMQ) was used.ResultsThe participants (female = 66.6%, n = 1561, mean age = 29.07 ± 12.34 years, range 6–60 years) smartphone use averaged 5.75 ± 3.44 h/day. The general prevalence of smartphone addiction was 46.16% (females = 46.06%, males = 46.36%; married = 44.5%, single = 47.63%). School students had the greatest addiction (53.2%) and those with a higher education to or above a Master’s degree were the lowest (39.38%). The highest pattern of use was for social networks at 89.1% of participants (female = 88.34%, male = 90.54%). The areas of highest reported discomfort were the eyes (43.5%) and neck (43.3%). A significant correlation was found between smartphone addiction and hours of daily usage, and the amount of usage increased during the COVID-19 pandemic period.ConclusionA high level of smartphone addiction in the Iranian population was found to have occurred during the COVID-19 pandemic. Those most affected were unmarried individuals and school students, with the predominant areas being the eyes and neck. Health decision-makers should consider these findings when developing recommendations and plans for public health, particularly those focused on students.

Effects of aerobic exercise or Tai Chi Chuan interventions on problematic mobile phone use and the potential role of intestinal flora: A multi-arm randomized controlled trial

BackgroundProblematic use of mobile phones (PMPU) has been described as a serious public health issue. MethodsThis study was a parallel three-arm randomized controlled trial and has completed registration (ClinicalTrials.gov Identifier: NCT05843591). Ninety college students with PMPU were randomly assigned to the aerobic exercise group (AE group, n = 30), the Tai Chi Chuan group (TCC group, n = 30), or the wait-list control group (WLC group, n = 30). At the end of the intervention, stool samples from the study participants were collected for biological analysis based on 16 S rDNA amplicon sequencing technology. The primary outcome was addiction symptoms assessed by the Smartphone Addiction Scale-Short Version (SAS-SV). The secondary outcomes are emotional symptoms, physical symptoms, and flora species. ResultsCompared with the WLC group, the AE and TCC groups showed reductions in PMPU levels, physical and mental fatigue, but there was no difference between the two groups. Moreover, the effect of increasing self-esteem embodied in the TCC group was not present in the AE group. Compared to the WLC group, the relative abundance of Bacteroidaceae and Bacteroides were lower in the AE group, while the relative abundance of Erysipelotrichaceae and Alistipes were lower in the TCC group. And the relative abundance of Bacteroidaceae, Bacteroides, and Alistipes were significantly and negatively correlated with the decline in PMPU scores. ConclusionAE or TCC is an effective, safe and efficient intervention for college students with PMPU, providing some physiological and psychological benefits and having some impact on their intestinal flora.