Coping as a moderator of the influence of economic stressors on psychological health
Bibliographic record
Abstract
Since 2008, there has been a decline in the economy of several European countries, including Portugal. In the literature, it is emphasized that periods of economic uncertainty propitiate the appearance of mental health problems and diminish populations’ well-being. The aim of the present study, with 729 Portuguese participants, 33.9% (n = 247) males and 66.1% (n = 482) females with an average age of, approximately, 37 years old (M = 36.99; SD = 12.81), was to examine the relationship between economic hardship, financial threat, and financial well-being (i.e., economic stressors) and stress, anxiety, and depression (i.e., psychological health indicators), as well as to test the moderation effect of coping in the aforementioned relationship. To achieve these goals, a cross-sectional design was implemented and structural equation modeling (SEM) was used to analyze the obtained data. The results showed that coping decreased the influence of economic stressors on psychological health indicators, thus protecting individuals’ psychological health from the negative consequences associated with adverse economic situations.
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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".