Dataset Information

Social networking and fear of missing out (FOMO) among medical students at University of Khartoum, Sudan 2021.

ABSTRACT:

Background

With students becoming more involved in the internet and social networking sites, they become more prone to their consequences. This study focuses on measuring the social networking intensity and the fear of missing out among the medical students of University of Khartoum, then examining the association between them.

Methods

Facility-based, descriptive, cross-sectional study was conducted at Faculty of Medicine, Khartoum University between January and March 2021. A total of 333 students were selected by simple random sampling. Data was collected from the participants using a structured self-administered questionnaire that involved the social networking intensity (SNI) scale and fear of missing out (FOMO) scale. The data was analyzed by the Statistical Package for Social Science (SPSS) software version 26.

Results

Moderate positive correlation between social networking intensity and fear of missing out was found (p-value < 0.01). Of the total participants; 51 participants (15.4%) experienced low SNI and low FOMO. Another 78 participants (23.6%) had moderate SNI and moderate FOMO and only 16 Participants (4.8%) showed high SNI and high FOMO. There were no significant differences in SNI or FOMO scores among the different socio-demographic variables, except for the SNI score which was positively correlated to the monthly income.

Conclusion

An association between SNI and FOMO was found. SNI was not affected by socio-demographic factors except for the monthly income.

SUBMITTER: Mohammed AAA

PROVIDER: S-EPMC10693061 | biostudies-literature | 2023 Dec

REPOSITORIES: biostudies-literature

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Publications

Social networking and fear of missing out (FOMO) among medical students at University of Khartoum, Sudan 2021.

Mohammed Abdalla Abbas Abdalla AAA Osman Mohammedahmed M MM Ali Mohammednour Mukhtar Mohammednour MMM Adam Mohammed O MO Mustafa Mohamed Esameldeen Elsayed MEE Babikir Anab M AM Abdulsamad Ahmed M I AMI Abo Mohamed Elhadi Abdelrahim MEA Yasein Yasein Abdelmoneim Mohamed YAM Abdelgader Mohamed Sati Shampool MSS Hasabo Elfatih A EA Ibrahim Mohammed Elsir ME

BMC psychology 20231201 1

<h4>Background</h4>With students becoming more involved in the internet and social networking sites, they become more prone to their consequences. This study focuses on measuring the social networking intensity and the fear of missing out among the medical students of University of Khartoum, then examining the association between them.<h4>Methods</h4>Facility-based, descriptive, cross-sectional study was conducted at Faculty of Medicine, Khartoum University between January and March 2021. A tota ...[more]

PMID: 38041160

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Project description:This paper reports a two-part study examining the relationship between fear of missing out (FoMO) and maladaptive behaviors in college students. This project used a cross-sectional study to examine whether college student FoMO predicts maladaptive behaviors across a range of domains (e.g., alcohol and drug use, academic misconduct, illegal behavior). Participants (N = 472) completed hard copy questionnaire packets assessing trait FoMO levels and questions pertaining to unethical and illegal behavior while in college. Part 1 utilized traditional statistical analyses (i.e., hierarchical regression modeling) to identify any relationships between FoMO, demographic variables (socioeconomic status, living situation, and gender) and the behavioral outcomes of interest. Part 2 looked to quantify the predictive power of FoMO, and demographic variables used in Part 1 through the convergent approach of supervised machine learning. Results from Part 1 indicate that college student FoMO is indeed related to many diverse maladaptive behaviors spanning the legal and illegal spectrum. Part 2, using various techniques such as recursive feature elimination (RFE) and principal component analysis (PCA) and models such as logistic regression, random forest, and Support Vector Machine (SVM), showcased the predictive power of implementing machine learning. Class membership for these behaviors (offender vs. non-offender) was predicted at rates well above baseline (e.g., 50% at baseline vs 87% accuracy for academic misconduct with just three input variables). This study demonstrated FoMO’s relationships with these behaviors as well as how machine learning can provide additional predictive insights that would not be possible through inferential statistical modeling approaches typically employed in psychology, and more broadly, the social sciences. Research in the social sciences stands to gain from regularly utilizing the more traditional statistical approaches in tandem with machine learning.

Project description:This communication reports on the Mycetoma Research Centre of the University of Khartoum, Sudan experience on 6,792 patients seen during the period 1991-2014.The patients were predominately young (64% under 30 years old) males (76%). The majority (68%) were from the Sudan mycetoma belt and 28% were students. Madurella mycetomatis eumycetoma was the most common type (70%). In 66% of the patients the duration of the disease was less than five years, and 81% gave a history of sinuses discharging mostly black grains (78%). History of trauma at the mycetoma site was reported in 20%. Local pain was reported in 27% of the patients, and only 12% had a family history of mycetoma. The study showed that 57% of the patients had previous surgical excisions and recurrence, and only 4% received previous medical treatment for mycetoma. Other concomitant medical diseases were reported in 4% of the patients. The foot (76%) and hand (8%) were the most commonly affected sites. Less frequently affected sites were the leg and knee (7%), thigh (2%), buttock (2%) and arm and forearm (1%). Rare sites included the chest wall, head and neck, back, abdominal wall, perineum, oral cavity, tongue and eye. Multiple sites mycetoma was recorded in 135 (2%) of cases. At presentation, 37% of patients had massive lesions, 79% had sinuses, 8% had local hyper-hydrosis at the mycetoma lesion, 11% had regional lymphadenopathy, while 6% had dilated tortuous veins proximal to the mycetoma lesions. The diagnosis of mycetoma was established by combined imaging techniques and cytological, histopathological, serological tests and grain culture. Patients with actinomycetoma received a combination of antimicrobial agents, while eumycetoma patients received antifungal agents combined with various surgical excisions. Surgical excisions in the form of wide local excision, debridement or amputation were done in 807 patients, and of them 248 patients (30.7%) had postoperative recurrence. Different types of amputations were done in 120 patients (1.7%).

Project description:BackgroundSocial media addiction (SMA) is known to be associated with excess use of social media. However, few studies have focused on the links of self-presentation on social media, fear of missing out (FoMO) and SMA. The present study investigated the relationships of self-presentation, FoMO and SMA among university students.MethodsOnline survey was conducted with 2,744 respondents, who completed online survey including social media use, FoMO and SMA. Self-presentation on social media and privacy information protection were assessed via researcher-designed questionnaires. Self-presentation on social media was composed of basic information shown on social media and expression willingness. Privacy information protection contained information viewed by others and privacy settings in social media platforms.ResultsThe most common information posted on social media were gender, hobby, age, personal photos, videos, and birthday. The most common social platforms with privacy setting were QQ zone (62.2%), WeChat (60.1%), and QQ (40.3%). FoMO (OR = 2.852, P = 0.000), information viewed by others (OR = 4.261, P = 0.000), managing a personal homepage (OR = 1.339, P = 0.002), accept a stranger's "friend request" (OR = 1.251, P = 0.028) and undergraduate students and above (OR = 1.439, P = 0.001) predicted expression willingness. FoMO (OR = 5.278, P = 0.000), information viewed by others (OR = 9.673, P = 0.000), privacy setting in QQ (OR = 0.817, P = 0.002) and in Tik Tok (OR = 0.536, P = 0.019) and female (OR = 0.588, P = 0.004) significantly influenced basic information shown on social media. Furthermore, FoMO (OR = 4.165, P = 0.000), expression willingness (OR = 1.645, P = 0.000), and information viewed by others (OR = 1.406, P = 0.000) positively affected the level of SMA. Risk of SMA increased as time spent on social media per day. However, basic information shown on social media did not significantly influence SMA.ConclusionIn general, students with higher level of FoMO and expression willingness are more likely to experience SMA. These results highlight individual behaviors on social media should be considered as essential elements for assessing problematic engaging to social media.

Dataset Information

Social networking and fear of missing out (FOMO) among medical students at University of Khartoum, Sudan 2021.

Background

Methods

Results

Conclusion

Publications

Social networking and fear of missing out (FOMO) among medical students at University of Khartoum, Sudan 2021.

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