Parental neglect, anxious attachment, perceived social support, and mental health among Chinese college students with left‐behind experience: A longitudinal study
Bibliographic record
Abstract
The harm of childhood parental neglect to emerging adults' maladjustment has garnered empirical support. For college students who have left-behind experience (LBE), this relationship is rarely discussed and the psychological process underlying this relationship is not well understood. Using a longitudinal study and guided by the Risky Families model, this study aimed to explore the mediating roles of anxious attachment and perceived social support in the link between parental neglect and maladjustment of LBE college students. We used two-wave longitudinal data, with a time lag of 3 months, collected among Chinese college students with LBE in Chongqing (N = 391). The results revealed that parental neglect in wave one was positively associated with maladjustment (depression, anxiety, and stress) in wave two. Anxious attachment and perceived social support in wave two separately mediated the relationship between parental neglect in wave one and maladjustment in wave two. Anxious attachment and perceived social support in wave two only sequentially mediated the pathway from parental neglect to later depression. These findings emphasize the importance of anxious attachment and social support in resilience and have significant implications for LBE college students' social work practice in China.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".