Is Smartphone Usage Truly Smart? A Qualitative Investigation of IT Addictive Behaviors
Bibliographic record
Abstract
Defined as the dependency to a technology that results in its excessive and compulsive use, IT addiction is seen as increasingly prevalent in today's societies. Recent research has revealed that IT addictive behaviors are creating serious problems for individuals and organizations alike. In this paper, we report the results of a qualitative study that aimed at investigating smart phone addictive usage. Building on 11 in-depth interviews and answers to 183 exploratory written questionnaires, we used a grounded theory approach to investigate this phenomenon. Our results reveal four smarphone user profiles. In two of these profiles, users are exhibiting addictive behaviors. In the first group, the users' profile corresponds to that of other types of additions. In the second group, known definitions of addiction do not apply and the characteristics of these users are very different. Our results thus suggest that adopting traditional conceptualizations of addiction will not be sufficient to define, understand and manage IT addictive behaviors.
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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 | 0.008 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.006 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".