Dataset Information

Development of the Smartphone Addiction Risk Rating Score for a Smartphone Addiction Management Application.

ABSTRACT: Smartphone usage characteristics are useful for identification of the risk factors for smartphone addiction. Risk rating scores can be developed based on smartphone usage characteristics. This study aimed to investigate the smartphone addiction risk rating (SARR) score using smartphone usage characteristics. We evaluated 593 smartphone users using online surveys conducted between January 2 and January 31, 2019. We identified 102 smartphone users who were addicted to smartphones and 491 normal users based on the Korean Smartphone Addiction Proneness Scale for Adults. A multivariate logistic regression analysis was used to identify significant risk factors for smartphone addiction. The SARR score was calculated using a nomogram based on the significant risk factors. Weekend average usage time, habitual smartphone behavior, addictive smartphone behavior, social usage, and process usage were the significant risk factors associated with smartphone addiction. Furthermore, we developed the SARR score based on these factors. The SARR score ranged between 0 and 221 points, with the cut-off being 116.5 points. We developed a smartphone addiction management application using the SARR score. The SARR score provided insights for the development of monitoring, prevention, and prompt intervention services for smartphone addiction.

SUBMITTER: Park J

PROVIDER: S-EPMC7517726 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Development of the Smartphone Addiction Risk Rating Score for a Smartphone Addiction Management Application.

Park Jihwan J Jeong Jo-Eun JE Park Seo Yeon SY Rho Mi Jung MJ

Frontiers in public health 20200911

Smartphone usage characteristics are useful for identification of the risk factors for smartphone addiction. Risk rating scores can be developed based on smartphone usage characteristics. This study aimed to investigate the smartphone addiction risk rating (SARR) score using smartphone usage characteristics. We evaluated 593 smartphone users using online surveys conducted between January 2 and January 31, 2019. We identified 102 smartphone users who were addicted to smartphones and 491 normal us ...[more]

PMID: 33042938

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Project description:The data were collected to test the hypothesis that problematic smartphone use, defined as the risk of smartphone addiction, is positively related to the type/purpose of device use (hedonic, meaning pleasure/gratification) and perceived stress, while it is negatively related to life satisfaction. The data were collected online between October 2020 and January 2021, using Qualtrics online research platform. The participants were aged 18 years or over, had a good command of the English language. They were recruited by posting the survey link on popular social media platforms, such as Facebook, LinkedIn, and Twitter, as well as by using applications such as WhatsApp and Instagram. Participation was voluntary, anonymous, and without material compensation. In addition to demographic questions (age, gender, level of education), respondents completed three questionnaires, including the Smartphone Application-Based Addiction Questionnaire (SABAS), Satisfaction with Life Scale (SWLS), Perceived Stress Scale (PSS), and answered two questions about the proportion of time they use their smartphone to access the Internet and the proportion of time they use smartphone for hedonic purposes. In the course of the data analysis, our aim was to predict the risk of smartphone addiction by the type or purpose of smartphone use, perceived stress, life satisfaction, age, and gender. The reuse potential of the data lies in the possibility to examine the relationships between the hedonic use of smartphones and other variables in the dataset. Researchers could also examine differences of gender or education level in the specific components of smartphone addiction, since each item of the SABAS represents a distinct component in the 'Components model' of addiction [4]. Furthermore, since we have data on Internet access via a tablet, laptop, and desktop computer, it is possible to analyse the relationships of the dependent variables with these paths of accessing the Internet.

Project description:PurposeInformation technology (IT)-based interventions, especially mobile health (mHealth), possess a great potential for promoting self-management in patients with chronic diseases, including diabetes type II. The present study was aimed to design and develop a smartphone-based application (app) for nutrition management in patients with type II diabetes and evaluation of its usability.MethodsIn this study, a three-phase research approach was followed; (1) To determine the information content and functionalities of the app, a five-point Likert scale checklist including six parts was developed based on reviews of clinical practice guidelines and specialized databases. The checklist was then given to ten experts in endocrinology and metabolism, internal medicine, and nutrition, and those items with a mean score higher than 3.75 were approved. (2) In Android Studio, the app was designed and developed using Java language. (3) The Questionnaire for User Interaction Satisfaction (QUIS) was used to assess the app's usability by 21 patients with type II diabetes, ten IT experts, and seven endocrinologists, internal medicine practitioners, and nutritionists over one month. Mean scores were divided into three levels: weak (0-3), average (3-6), and good (6-9).ResultsAccording to experts' view, 17 out of 22 educational content and 17 out of 27 functionalities were approved. The app's most important educational content was the timing of meals for insulin patients and the definition of diabetes and its complications. The designed app had the following functionalities: providing educational information, recording information, performing calculations, representing data graphically, setting reminders, and communicating with physicians. The most important features of the app were the insulin dose calculation, reminders for doctors' appointments, setting times for tests and blood glucose measurements, and also tracking weight, blood glucose levels, and blood pressure. In terms of usability evaluation, the app was rated "good" level by diabetic patients (7.83 ± 0.74), IT experts (8.1 ± 0.66), and physicians (8.03 ± 0.95).ConclusionGiven the desirable evaluation of the app by patients, physicians, and IT experts, it can be concluded that the developed app has the required functionalities for nutrition management of patients with type II diabetes. Smartphone-based apps appear to be able to improve self-management, the quality of care and health in patients with diabetes, and reduce many of their unnecessary visits to healthcare centers, and costs.Supplementary informationThe online version contains supplementary material available at 10.1007/s40200-022-01140-x.

Project description:Research into the neurogenetic basis of addiction identified and characterized by Reward Deficiency Syndrome (RDS) includes all drug and non-drug addictive, obsessive and compulsive behaviors. We are proposing herein that a new model for the prevention and treatment of Substance Use Disorder (SUD) a subset of RDS behaviors, based on objective biologic evidence, should be given serious consideration in the face of a drug epidemic. The development of the Genetic Addiction Risk Score (GARS) followed seminal research in 1990, whereby, Blum's group identified the first genetic association with severe alcoholism published in JAMA. While it is true that no one to date has provided adequate RDS free controls there have been many studies using case -controls whereby SUD has been eliminated. We argue that this deficiency needs to be addressed in the field and if adopted appropriately many spurious results would be eliminated reducing confusion regarding the role of genetics in addiction. However, an estimation, based on these previous literature results provided herein, while not representative of all association studies known to date, this sampling of case- control studies displays significant associations between alcohol and drug risk. In fact, we present a total of 110,241 cases and 122,525 controls derived from the current literature. We strongly suggest that while we may take argument concerning many of these so-called controls (e.g. blood donors) it is quite remarkable that there are a plethora of case -control studies indicating selective association of these risk alleles ( measured in GARS) for the most part indicating a hypodopaminergia. The paper presents the detailed methodology of the GARS. Data collection procedures, instrumentation, and the analytical approach used to obtain GARS and subsequent research objectives are described. Can we combat SUD through early genetic risk screening in the addiction field enabling early intervention by the induction of dopamine homeostasis? It is envisaged that GARS type of screening will provide a novel opportunity to help identify causal pathways and associated mechanisms of genetic factors, psychological characteristics, and addictions awaiting additional scientific evidence including a future meta- analysis of all available data -a work in progress.

Dataset Information

Development of the Smartphone Addiction Risk Rating Score for a Smartphone Addiction Management Application.

Publications

Development of the Smartphone Addiction Risk Rating Score for a Smartphone Addiction Management Application.

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