Longitudinal Associations Between Depressive Symptoms and Preference for Solitude Among Chinese Early Adolescents: Separating Between-Person from Within-Person Effects
Bibliographic record
Abstract
The goal of this study was to explore longitudinal associations between preference for solitude (PFS) and depressive symptoms among early adolescents in mainland China, with a focus on separating between-person and within-person effects using a random intercept cross-lagged panel model (RI-CLPM). Participants were N = 1039 Chinese early adolescents ( M age = 12.37, 46.1% girls, at Time 1), who completed annual self-reports of depressive symptoms and peer-nominations of PFS over a 3-years period. Results revealed that fluctuations in depressive symptoms consistently predicted fluctuations in PFS 1 year later, but not vice versa, supporting a symptoms-driven model. Findings are discussed in terms of the role of depressive symptoms in promoting subsequent PFS among 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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".