Relationships between Stages of Change and Self-Efficacy for Effective Stress Management in Chinese College Students
Bibliographic record
Abstract
The Transtheoretical Model of Behavior Change (TTM) has the potential to explain how Chinese collegestudents can initiate and maintain effective stress management (any form of healthy activity, which is practicedto manage stress for at least 20 minutes per day). The TTM regards the process as progression through thefollowing five stages of change: precontemplation (not ready), contemplation (getting ready), preparation (ready),action, and maintenance. Self-efficacy (confidence to manage stress effectively even under tempting situations)is assumed to increase with stage progression. Previous studies have found such relationships, but no study hasexamined these relationships with Chinese college students. The purpose of this study was to examine therelationship between stages of change and self-efficacy for effective stress management. The participantsincluded 366 male and 505 female Chinese college students. The Chinese language version of Pro-Change’sself-efficacy measure was developed based on item response theory. A single scale of 10 items was replicated.Self-efficacy was significantly higher in action and maintenance than in precontemplation and contemplation.Self-efficacy was also significantly higher in men than in women. These results provide initial evidence that theself-efficacy measure can be applied to stress management with Chinese college students.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".