The Effects of Attachment, Temperament, and Self-Esteem on Technology Addiction: A Mediation Model Among Young Adults
Bibliographic record
Abstract
Excessive use of technology has become a worldwide problem due to its high prevalence, fast growth rate, and undesirable consequences. However, little is known about underlying psychological mechanisms that maintain excessive use of technology. We investigated the mediating role of self-esteem, novelty seeking, and persistence on the relationship between attachment dimensions and technology addiction among young adults. Data were collected from 727 young adults (females, N = 478; 66.3 percent), aged 23.44 ± 3.02 years. Participants completed self-report measures of secure and insecure attachment dimensions, personality, and temperament characteristics (i.e., self-esteem, novelty seeking, and persistence), technology addiction and frequency of technology use (i.e., own technology use, perceived use by peers and parents). The mediation model was tested through a path analysis. The effects of attachment insecurity on technology addiction were partially mediated by the levels of persistence and self-esteem, whereas the effects of attachment security on technology addiction were fully mediated. The effects remained robust even after controlling for the frequency of technology use. The model was gender and age invariant, suggesting that the mediation worked in a similar way for both men and women and across ages. Findings suggest that attachment dimensions exert not only a direct but also an indirect effect on technology addiction through self-esteem and persistence. Such findings may help to develop psychosocial interventions that are sensitive to young adults' attachment, personality, and temperament characteristics.
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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 | 0.004 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".