POSSIBLE PSYCHOLOGICAL EFFECTS OF LIVING CONDITIONS THAT CHANGED THROUGH THE COVID-19 ON YOUNG INDIVIDUALS
Bibliographic record
Abstract
Objective: Aim of this study was to investigate the possible effects of changing living conditions due to COVID-19 in young adult individuals. Methods: The study was conducted as a descriptive relation-seeker-type. A total of 551 young people were reached. Questionnaire, Perceived Stress Scale, Health Anxiety Scale-Short Form and Maudsley Obsessive Compulsive Question List were used. For Analysis was used number, percentage, mean, standard deviation, chi-square, t test, ANOVA, Tukey-HSD and Pearson correlation tests. Results: The average age of the participants was 22.60 ± 3.49 years. 74% are women, 88.6% are single, 53.4% are students (health). The average stress score of individuals is 30.44±7.86, the average HAS-1 is 14.32±6.22, the average HAS-2 is 3.43±2.34 and the average MOCQ is 17.79±7.19. In terms of obsessive-compulsive disorder, 10% (n=55) of the participants showed low trends, 29.9% (n=165) moderate, and 60.1% (n=331) showed a high level of trend.It was determined that individuals’ perceived stress, anxiety and obsessive-compulsive behavior levels changed according to variables such as age, gender, marital status, occupation, presence of chronic disease, smoking and quarantine status (p<0.05). Conclusion: It was determined that young people experienced psychological problems due to the COVID-19 outbreak, and these problems changed according to demographic characteristic.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".