Interaction of Depressive Status and Cognitive Ability Predicts Psychological Resilience of Young Adults in Taiwan
Bibliographic record
Abstract
Abstract Associations among cognitive ability, depressive symptoms, and psychological resilience have been found, but the interaction among these variables remains unclear, especially for young adults. The current study aimed to investigate how these variables interact in young adults in Taiwan. A total of 192 participants (97 female) with a mean age of 21.84 years (range 19–30 years) were analyzed for this study. Participants’ cognitive ability was assessed by the Taiwanese version of the Montreal Cognitive Assessment. Depressive status was evaluated by the revision of Beck Depression Inventory-II. Participants with a score of 14 or above were defined as mild-to-severe-depressed (MSD). Otherwise, they were defined as minimal-depressed (MD). For the psychological resilience measurement, a Chinese version of the Resilience Scale for Adults (RSA) was used. A linear regression model was applied to investigate the interaction of cognitive ability and depressive status on psychological resilience after adjusting for the covariates of gender and age. The interaction of BDI-II and MoCA was significantly associated with the RSA score (B = -6.519, p = .044) and other effects were not significant. The results indicated that a negative relationship between cognitive ability and psychological resilience was only observed in MSD young adults but not in MD. This study had a limited number of participants in the MSD group. Young adults with higher cognitive ability reported lower psychological resilience when they had mild-to-severe depression. In contrast, cognitive ability does not relate to psychological resilience among young adults with minimal depression.
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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 | 0.000 | 0.001 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".