Validation of a New Scale for Measuring Problematic Internet Use: Implications for Pre-employment Screening
Bibliographic record
Abstract
The current study introduced a theory-driven, multidimensional measure of problematic Internet use: the Online Cognition Scale (OCS). Undergraduate students (n = 211) in an industrial/organizational psychology course completed the OCS, along with measures of procrastination, rejection sensitivity, loneliness, depression, and impulsivity. A confirmatory factor analysis indicated that problematic Internet use consists of four dimensions: diminished impulse control, loneliness/depression, social comfort, and distraction. As hypothesized, the OCS predicted all of the study variables in the expected directions. Representing a departure from previous research in this area, the current article focused on procrastination, impulsivity, and social rejection as key elements of problematic Internet use. Furthermore, interactive applications (e.g., chat) were most related to problematic Internet use, and scores on the OCS predicted being reprimanded at school or work for inappropriate Internet use. As a result, the utility of the OCS for both clinical assessment of Internet addiction and as an organizational preemployment screening measure to identify potential employees who are likely to abuse the Internet in the workplace (also known as "cyberslacking") were discussed.
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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 | 0.019 | 0.034 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".