Rumination and alexithymia serially mediate the relationship between mindfulness and anxiety symptoms in Chinese university students
Bibliographic record
Abstract
Anxiety symptoms are highly prevalent among Chinese university students, significantly impairing psychosocial functioning. Although mindfulness has been identified as a protective psychological factor, the precise mechanisms underlying its association with anxiety symptom alleviation remain insufficiently understood. This study investigates the serial mediation effects of rumination and alexithymia in the relationship between mindfulness and anxiety symptoms. A cross-sectional study was conducted with 860 Chinese university students. Validated psychometric instruments were administered, including the Mindful Attention Awareness Scale (MAAS), Ruminative Response Scale (RRS), Toronto Alexithymia Scale (TAS-20), and Screen for Adult Anxiety Related Disorders (SCAARED). Serial mediation analyses were performed using SPSS 25.0 and Hayes’ PROCESS macro (Model 6), controlling for sex and academic grade. Higher mindfulness levels showed robust associations with lower anxiety symptom severity. This relationship was primarily linked to interconnected cognitive and affective pathways. The analysis revealed that individuals reporting higher mindfulness exhibited lower tendencies toward repetitive negative thinking (rumination), which corresponded to lower anxiety levels. Simultaneously, higher mindfulness was associated with lower alexithymia that typically co-occur with anxiety symptoms. Crucially, a sequential pathway emerged: higher mindfulness correlated with lower rumination, which in turn corresponded to fewer emotional processing difficulties (alexithymia), ultimately associating with fewer anxiety symptoms. Collectively, these indirect pathways accounted for most of mindfulness’s observed relationship with anxiety symptoms, highlighting interconnected roles of cognitive and emotional factors. Mindfulness shows protective associations with anxiety symptoms through dual correlations: correspondence with lower rumination and relationship with lower alexithymia. These findings advocate for interventions addressing both cognitive patterns and emotional regulation in culturally adapted campus mental health programs.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".