- Title
- Testing the spectrum hypothesis of problematic online behaviors: a network analysis approach
- Creator
- Baggio, Stéphanie; Starcevic, Vladan; Billieux, Joël; King, Daniel L.; Gainsbury, Sally M.; Eslick, Guy D.; Berle, David
- Relation
- Addictive Behaviors Vol. 135, Issue December 2022, no. 107451
- Publisher Link
- http://dx.doi.org/10.1016/j.addbeh.2022.107451
- Publisher
- Elsevier
- Resource Type
- journal article
- Date
- 2022
- Description
- The validity of the constructs of problematic Internet or smartphone use and Internet or smartphone addiction has been extensively debated. The spectrum hypothesis posits that problematic online behaviors (POBs) may be conceptualized within a spectrum of related yet distinct entities. To date, the hypothesis has received preliminary support, and further robust empirical studies are still needed. The present study tested the spectrum hypothesis of POBs in an Australian community sample (n = 1,617) using a network analysis approach. Psychometrically validated self-report instruments were used to assess six types of POBs: problematic online gaming, cyberchondria, problematic cybersex, problematic online shopping, problematic use of social networking sites, and problematic online gambling. A tetrachoric correlation matrix was computed to explore relationships between online activities and a network analysis was used to analyze relationships between POBs. Correlations between online activities were positive and significant, but of small magnitude (0.051 ≤ r ≤ 0.236). The community detection analysis identified six distinct communities, corresponding to each POB, with strong relationships between items within each POB and weaker relationships between POBs. These findings provide further empirical support for the spectrum hypothesis, suggesting that POBs occur as distinct entities and with little overlap.
- Subject
- behavioral addictions; network analysis; problematic online behaviors
- Identifier
- http://hdl.handle.net/1959.13/1487619
- Identifier
- uon:52198
- Identifier
- ISSN:0306-4603
- Rights
- © 2022 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
- Language
- eng
- Full Text
- Reviewed
- Hits: 1201
- Visitors: 1249
- Downloads: 54
| Thumbnail | File | Description | Size | Format | |||
|---|---|---|---|---|---|---|---|
| View Details Download | ATTACHMENT02 | Publisher version (open access) | 525 KB | Adobe Acrobat PDF | View Details Download |