Cargando…

Problematic Internet Use: A Longitudinal Study Evaluating Prevalence and Predictors

OBJECTIVE: To assess the prevalence over time and predictors of problematic internet use using the Problematic and Risky Internet Use Screening Scale (PRIUSS). We also identified an intermediate-risk PRIUSS score. STUDY DESIGN: In this longitudinal cohort study, we recruited participants using rando...

Descripción completa

Detalles Bibliográficos
Autores principales: Moreno, Megan A., Eickhoff, Jens, Zhao, Qianqian, Young, Henry N., Cox, Elizabeth D.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8300087/
https://www.ncbi.nlm.nih.gov/pubmed/34308328
http://dx.doi.org/10.1016/j.ympdx.2019.100006
_version_ 1783726392182046720
author Moreno, Megan A.
Eickhoff, Jens
Zhao, Qianqian
Young, Henry N.
Cox, Elizabeth D.
author_facet Moreno, Megan A.
Eickhoff, Jens
Zhao, Qianqian
Young, Henry N.
Cox, Elizabeth D.
author_sort Moreno, Megan A.
collection PubMed
description OBJECTIVE: To assess the prevalence over time and predictors of problematic internet use using the Problematic and Risky Internet Use Screening Scale (PRIUSS). We also identified an intermediate-risk PRIUSS score. STUDY DESIGN: In this longitudinal cohort study, we recruited participants using random selection from 2 colleges. Participants completed a yearly PRIUSS. We used multivariate logistic regression analysis to evaluate predictors of problematic internet use. We pursued receiver operating curve analysis to identify an Intermediate risk PRIUSS score. Finally, we applied Markov modeling to test the dynamics of moving through problematic internet use risk states over time. RESULTS: Of 319 participants, 56% were female, 58% were from the Midwest, and 75% were white. Problematic internet use prevalence estimates varied between 9% and 11% over the 4 years. Problematic internet use risk status from the previous time period was identified as the main predictor for problematic internet use (OR 24.1, 95% CI 12.8-45.4, P < .0001). Receiver operating curve analysis identified the optimal threshold for defining Intermediate risk was a PRIUSS score of 15. CONCLUSIONS: This longitudinal study of problematic internet use among college students found that risks were present across groups and over time. The most salient predictor of problematic internet use was being at risk at the previous time point. On the basis of these results, we propose a PRIUSS score of 15 as an intermediate-risk cut-off to better identify those at risk of developing problematic internet use.
format Online
Article
Text
id pubmed-8300087
institution National Center for Biotechnology Information
language English
publishDate 2019
publisher Elsevier
record_format MEDLINE/PubMed
spelling pubmed-83000872021-07-23 Problematic Internet Use: A Longitudinal Study Evaluating Prevalence and Predictors Moreno, Megan A. Eickhoff, Jens Zhao, Qianqian Young, Henry N. Cox, Elizabeth D. J Pediatr X Original Article OBJECTIVE: To assess the prevalence over time and predictors of problematic internet use using the Problematic and Risky Internet Use Screening Scale (PRIUSS). We also identified an intermediate-risk PRIUSS score. STUDY DESIGN: In this longitudinal cohort study, we recruited participants using random selection from 2 colleges. Participants completed a yearly PRIUSS. We used multivariate logistic regression analysis to evaluate predictors of problematic internet use. We pursued receiver operating curve analysis to identify an Intermediate risk PRIUSS score. Finally, we applied Markov modeling to test the dynamics of moving through problematic internet use risk states over time. RESULTS: Of 319 participants, 56% were female, 58% were from the Midwest, and 75% were white. Problematic internet use prevalence estimates varied between 9% and 11% over the 4 years. Problematic internet use risk status from the previous time period was identified as the main predictor for problematic internet use (OR 24.1, 95% CI 12.8-45.4, P < .0001). Receiver operating curve analysis identified the optimal threshold for defining Intermediate risk was a PRIUSS score of 15. CONCLUSIONS: This longitudinal study of problematic internet use among college students found that risks were present across groups and over time. The most salient predictor of problematic internet use was being at risk at the previous time point. On the basis of these results, we propose a PRIUSS score of 15 as an intermediate-risk cut-off to better identify those at risk of developing problematic internet use. Elsevier 2019-07-26 /pmc/articles/PMC8300087/ /pubmed/34308328 http://dx.doi.org/10.1016/j.ympdx.2019.100006 Text en © 2019 The Author(s) https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Original Article
Moreno, Megan A.
Eickhoff, Jens
Zhao, Qianqian
Young, Henry N.
Cox, Elizabeth D.
Problematic Internet Use: A Longitudinal Study Evaluating Prevalence and Predictors
title Problematic Internet Use: A Longitudinal Study Evaluating Prevalence and Predictors
title_full Problematic Internet Use: A Longitudinal Study Evaluating Prevalence and Predictors
title_fullStr Problematic Internet Use: A Longitudinal Study Evaluating Prevalence and Predictors
title_full_unstemmed Problematic Internet Use: A Longitudinal Study Evaluating Prevalence and Predictors
title_short Problematic Internet Use: A Longitudinal Study Evaluating Prevalence and Predictors
title_sort problematic internet use: a longitudinal study evaluating prevalence and predictors
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8300087/
https://www.ncbi.nlm.nih.gov/pubmed/34308328
http://dx.doi.org/10.1016/j.ympdx.2019.100006
work_keys_str_mv AT morenomegana problematicinternetusealongitudinalstudyevaluatingprevalenceandpredictors
AT eickhoffjens problematicinternetusealongitudinalstudyevaluatingprevalenceandpredictors
AT zhaoqianqian problematicinternetusealongitudinalstudyevaluatingprevalenceandpredictors
AT younghenryn problematicinternetusealongitudinalstudyevaluatingprevalenceandpredictors
AT coxelizabethd problematicinternetusealongitudinalstudyevaluatingprevalenceandpredictors