A Systematic Research Review of Internet Addiction and Identity
Bibliographic record
Abstract
A small but growing body of research documents how internet misuse can lead to negative outcomes for individuals. One particularly important area of public concern is the connection between addictive internet usage and human identity. This study addressed the connection between excessive internet use on real-world and virtual-world identity. This systematic research review synthesized research studies conducted between 2008 to 2018 on the influence of internet addiction on identity. Findings revealed that the majority of published studies focused on young individuals aged 9-30 years old (89%) and that the connection between excessive internet use on real-world identity and virtual-world identity was complex and multi-faceted. Online gaming addiction was identified as a leading theme within the published research (30%). Based on study findings, recommendations are made for greater future research attention to internet addiction among adults, comprehensive studies of the relationship between online and offline identity to internet addiction, and the inclusion of internet addiction as a multifaceted disorder in future editions of DSM, which includes online gaming addiction among other forms of online addiction.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.014 | 0.083 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.007 |
| Bibliometrics | 0.020 | 0.019 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".