For the love of being liked: a moderated mediation model of attachment, likes-seeking behaviors, and problematic Facebook use
Bibliographic record
Abstract
Introduction: Some Facebook users have difficulty regulating the amount of time they spend online, and some Facebook features, such as likes, promote habitual use. Theoretically, attachment insecurities could be related to problematic Facebook use, but the findings of past studies were mixed with limited knowledge about potential moderators and mediators of the association between adult attachment and problematic use of Facebook.Aims: The present study used adult attachment theory to explore a moderated mediation model that examined the interaction of the two attachment dimensions of attachment anxiety and avoidance as well as the mediation role of likes-seeking behaviors.Method: A total of 2758 adolescents and young adults completed self-report questionnaires.Results: Results showed a significant interaction between the attachment dimensions, such that attachment anxiety and avoidance were each related to problematic Facebook use when the level of the other attachment dimension was low. The relations between the attachment dimensions and problematic Facebook use were mediated by likes-seeking behaviors.Conclusions: Our findings highlight the interplay between the attachment dimensions and the mediation of behaviors related to one specific Facebook feature as important risk factors of problematic Facebook use.
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.
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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".