Examination of the relationship between smartphone addiction and cyberchondria in adolescents

Köse, Selmin; Murat, Merve

doi:10.1016/j.apnu.2021.08.009

Cited by 19 publications

(21 citation statements)

References 38 publications

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“…A study conducted during the pandemic reported that people with severe cyberchondria tended to search for information online in an addictive manner (Seyed Hashemi et al, 2020 ). In a similar study, a significant relationship was found between cyberchondria levels and conducting online searches two or more times per week (Köse & Murat, 2021 ). Some studies concluded that smartphone, internet and/or social media addiction was related to the severity of cyberchondria (Khazaal et al, 2021 ).…”

Section: Discussionmentioning

confidence: 83%

Cyberchondria and COVID-19 anxiety and internet addiction among nursing students

et al. 2022

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This study was conducted to determine the relationship between cyberchondria and COVID-19 anxiety and internet addiction in nursing students. This cross-sectional study was conducted with 843 students studying in the nursing department of Adnan Menderes University. The mean age of the students was 20.8 ± 1.72 years and 61.2% were female. The Cyberchondria Severity Scale-Short Form, Coronavirus Anxiety Scale, and the Young Internet Addiction Test-Short Form were used to collect data. The study found a positive association between internet addiction, cyberchondria severity, and anxiety about COVID-19. It was found that the anxiety of COVID-19 had a mediating role in the association between internet addiction and cyberchondria severity. It was found that the use of the internet as a source of information on health problems and trusting the health information found had a significant effect on high cyberchondria levels ( p < 0.05). Taken together, the findings of previous studies and this study on the role of the association between internet addiction and cyberchondria exacerbating anxiety due to the pandemic provide further evidence for healthcare professionals that greater focus is needed on the problems of the new era related to people-internet interaction. To reduce the negative effects of the current health crisis and future health crises, interventions for nursing students to control their internet use and cyberchondria behaviors should be prioritized.

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Section: Discussionmentioning

confidence: 83%

Cyberchondria and COVID-19 anxiety and internet addiction among nursing students

et al. 2022

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“…Data from [18], mobile cellular users globally in 2016 reached 7 billion users. According to [19], many people have always checked and used mobile phones in recent times that can be concluded that most people use mobile phones or smartphones. Using a mobile application as a garbage detector is very practical because the broader community worldwide uses mobile phones.…”

Section: Introductionmentioning

confidence: 99%

The Development of Real-Time Mobile Garbage Detection Using Deep Learning

Fathurrahman

Ma’arif

Chin

2022

Jurnal Ilmiah Teknik Elektro Komputer Dan Informatika

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The problem of garbage in the world is a serious issue that must be solved. Good garbage management is a must for now and in the future. Good garbage management is accompanied by a system of classification and sorting of garbage types. This study aims to create a mobile-based application that can select the type of garbage and enter the garbage data into a database. The database used is a Google SpreadSheet that will accommodate data from the output issued by the garbage detection mobile application. The image data used in this study amounted to 10108 images and was divided into six different garbage classes. This study uses a deep learning platform called densenet121 with an accuracy rate of 99.6% to train the image data. DenseNet121 has been modified and added an optimization based on a genetic algorithm. The genetic algorithm applied in the optimization uses four generations. The model resulting from the training of the two approaches is converted into a model that mobile applications can access. The mobile application based on a deep learning model accommodates the detection data of the type of garbage, the level of detection accuracy, and the GPS location of the garbage. In the final experiment of the mobile application, the delay time in sending data was very fast, which was less than one second (0.86s).

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“…Excessive social media and PSU during COVID-19 home quarantines ( Hallauer et al, 2021 ; Hu et al, 2021 ; Köse and Murat, 2021 ; Saiful et al, 2021 ; Zhang et al, 2021 ) are associated with having urban residence, watching television, irregular physical exercise, and poor sleep and psychological well-being. Functional impairment is associated with behavioral addictions such as PSU that mediates the link between COVID-19-related exposure and post-traumatic stress disorder (PTSD) symptoms.…”

Section: Introductionmentioning

confidence: 99%

Smartphone addiction risk, technology-related behaviors and attitudes, and psychological well-being during the COVID-19 pandemic

et al. 2022

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COVID-19 pandemic-related perceived risk of infection, illness fears, acute stress, emotional anxiety, exhaustion, and fatigue, psychological trauma and depressive symptoms, and sustained psychological distress can cause smartphone addiction risk and lead to technology-related cognitive, emotional, and behavioral disorders, thus impacting psychological well-being. Behavioral addiction of smartphone users can result in anxiety symptom severity, psychiatric symptoms, and depressive stress. We carried out a quantitative literature review of the Web of Science, Scopus, and ProQuest throughout June 2022, with search terms including “smartphone addiction + COVID-19” + “stress,” “anxiety,” “depression,” “psychological distress,” “screen time,” and “fear.” As we analyzed only articles published between 2020 and 2022, 288 papers met the eligibility criteria. By excluding sources with similar titles, having unclear findings or unsupported by replication, or displaying inconsistent content, we selected 64, mainly empirical, sources. We used layout algorithms (VOSviewer) and bibliometric mapping (Dimensions) as data visualization tools. Assessing the Methodological Quality of Systematic Reviews (AMSTAR), a systematic review and literature review software (Distiller SR), Mixed Methods Appraisal Tool (MMAT), and Systematic Review Data Repository (SRDR) were employed as methodological quality assessment tools. As limitations, we analyzed only articles published between 2020 and 2022 in scholarly outlets indexed in the Web of Science, Scopus, and ProQuest databases. The scope of our study also does not advance the inspection of sources covering vulnerable individuals suffering from certain diseases or specific generations. Subsequent analyses should develop on smartphone use and addiction among children and adolescents. Future research should thus investigate problematic smartphone use and addiction across generations Z and Alpha. Attention should be directed to their personality traits and psychopathological symptoms.

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Examination of the relationship between smartphone addiction and cyberchondria in adolescents

Cited by 19 publications

References 38 publications

Cyberchondria and COVID-19 anxiety and internet addiction among nursing students

Cyberchondria and COVID-19 anxiety and internet addiction among nursing students

The Development of Real-Time Mobile Garbage Detection Using Deep Learning

Smartphone addiction risk, technology-related behaviors and attitudes, and psychological well-being during the COVID-19 pandemic

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