Developmental Trajectories of Loneliness Among Chinese Early Adolescents: The Roles of Early Peer Preference and Social Withdrawal
Bibliographic record
Abstract
This study aimed to examine distinct loneliness trajectories and to explore the roles of group-level peer preference and individual-level social withdrawal (i.e., unsociability and shyness) as predictors of these trajectories. Participants were 1134 Chinese elementary school students (Mage = 10.44 years; 565 boys). Data were collected from self-reports and peer nominations. Latent class growth analysis (LCGA) was employed to identify distinct trajectories of loneliness, and multinomial logistic regression was subsequently used to examine the relationships between these trajectories and their predictors. Results showed that three loneliness trajectories were identified: high increasing, moderate decreasing, and low decreasing. Participants at baseline with higher peer preference were more likely to belong to the low decreasing trajectory subgroup rather than the other two subgroups. Furthermore, those at Time 1 with higher unsociability had lower odds of being classified into the moderate or low decreasing trajectory subgroup compared to the high increasing trajectory subgroup. Additionally, participants at baseline with higher shyness had reduced likelihoods of following the low decreasing trajectory subgroup as opposed to the other two subgroups. These results have implications for how we understand both the different subgroups of loneliness trajectories and the predictions of peer preference and social withdrawal on these trajectories in Chinese early adolescents.
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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 | 0.000 | 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".