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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 teacher head, 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".