Understanding phubbing behavior: A scoping review of qualitative and mixed-methods studies
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The use of smartphones has significantly increased in recent years, leading to the emergence of a new concept known as phubbing , which refers to being absorbed in one's smartphone while in the presence of others and neglecting interpersonal communication. Quantitative studies have highlighted the negative impacts of phubbing on, for example, relationship quality and satisfaction, as well as its predisposing factors. However, there is limited information on the experiences of those who engage in phubbing (phubbers) and those who are affected by it (phubbees). This scoping review aims to provide a comprehensive overview of the current understanding of phubbing derived from qualitative and mixed-methods studies. It follows the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines for scoping reviews. Seven databases were searched for relevant studies, from which 251 articles were found. The title and abstract screening led to the full-text review of thirty-one articles, of which thirteen were retained and assessed for quality. Data extraction and narrative synthesis were then performed on the thirteen articles included in this study. Among these, seven were qualitative and six employed mixed methods. The results were divided into seven categories: (1) study characteristics, (2) definitions, (3) negative consequences, (4) positive factors, (5) social norms and contextual factors, (6) motives, and (7) strategies. The findings of this review highlight the need for further research to clarify phubbing terminology, explore its social norms across cultures, understand its impacts, identify mitigation strategies, and investigate the factors associated with phubbing in children and adolescents.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.007 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 it