Psychological Resource as a Necessary Condition for Students’ Mental Health and Study Adjustment
Bibliographic record
Abstract
Drawing on the conservation of resource (COR) theory, this study examines individual psychological resource as a necessary condition for students’ mental health and study adjustment during the Covid-19 pandemic. We further examine how international and domestic students differ in their resources, mental health and study adjustment. Employing partial least squares structural equation modeling (PLS-SEM), the study tests the hypothesized effects of psychological resources utilizing online survey data from 2,136 domestic and international students across five countries. The necessary condition analysis demonstrates psychological resources as necessary but not sufficient conditions for mental health and study adjustment. Additionally, one-way analysis of variance reveals that international students surpass domestic students in psychological resources, mental health, and adjustment. This research makes a novel contribution to the COR theory by proposing the “necessary resource principle,” which underscores that certain resources constitute necessary conditions in the event of significant losses of other resources. It provides evidence that individual psychological resources are not only desirable but also indispensable for students’ mental health and study outcomes during stressful periods. Furthermore, it contributes to adjustment theory by emphasizing the pivotal role of mental health in students’ adjustment. The implications for management and higher education are discussed.
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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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".