Problematic Internet Use: a concern for student wellbeing and academic performance

O'Brien, O, 2022. Problematic Internet Use: a concern for student wellbeing and academic performance. PhD, Nottingham Trent University.

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Abstract

Problematic Internet Use (PIU) has been linked to student loneliness, wellbeing and Fear of Missing Out (FOMO). Thus, there is a need to investigate the use of the internet and the impact of that use in universities. Reliance on self-assessment to identify PIU has generated concern in previous research, the need for measures that include assessment of actual behavior has been highlighted. This research used a method which is innovative in psychology, to gather and analyse objective data on internet activity in a university over an academic year. Student self-assessment data on PIU subtypes (general PIU, problematic smartphone use, problematic social media use, problematic internet gaming, and problematic pornography use), wellbeing, loneliness and FOMO were also gathered. The data were used to understand actual internet behavior, student assessment of that behavior and relationships with wellbeing, loneliness and FOMO.

The first and third study examined the Wifi digital traces of approximately 13,000 users at a university for an academic year. Principal component analysis identified patterns in the users’ engagement with the internet. Machine learning identified clusters of users with the same pattern of activity and enabled prediction of education activity. In the second study, the self-assessment data from 834 university students explained how users of the university WiFi assessed their internet usage behavior, wellbeing, loneliness and FOMO. A partial correlation network and variance partitioning clarified relationships between PIU subtypes, wellbeing, loneliness and FOMO. The I-PACE model (Brand et al., 2019) was used to illuminate the findings in a model of behavioral addiction.

This research contributes to understanding PIU in students and links to loneliness, wellbeing and FOMO with: (i) objective measures of actual behavior; (ii) identification of patterns of internet behavior; (iii) prediction of activity on the internet using objective data; and (iv) use of partial correlation networks, variance partitioning and the I-PACE model to clarify the relationships between PIU subtypes and wellbeing, loneliness and FOMO.

Item Type:	Thesis
Creators:	O'Brien, O.
Date:	April 2022
Rights:	Copyright © 2022 by Oonagh O’Brien. The copyright in this work is held by the author. You may copy up to 5% of this work for private study, or personal, non‐commercial research. Any re‐use of the information contained within this document should be fully referenced, quoting the author, title, university, degree level and pagination. Queries or requests for any other use, or if a more substantial copy is required, should be directed to the author.
Divisions:	Schools > School of Social Sciences
Record created by:	Linda Sullivan
Date Added:	05 May 2023 09:10
Last Modified:	05 May 2023 09:10
URI:	https://irep.ntu.ac.uk/id/eprint/48878

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