A Predictive Research on the Posttraumatic Improvement of Emergency Health Employees
Bibliographic record
Abstract
Traumatic incidents are defined as despair people are in when they face fears, weaknesses and vulnerabilities. The purpose of the present research is determining the mental problems faced by emergency health workers while performing their jobs and how they deal with these problems. For this purpose, “The Hopelessness Scale, Locus of Control Scale, Problem Solving Inventory, Multidimensional Scale of Perceived Social Support, Post Traumatic Growth Inventory, Peritraumatic Dissociative Experiences Questionnaire, The Posttraumatic Diagnostic Scale and Beck Depression Inventory were used as data collection tools. The present research was designed in accordance with general screening model, which is a descriptive research method. With this model, how the independent variable affected the dependent variable was investigated and the regression analysis was conducted for the relationship between the variables. The research was carried out on the employees of the Department of Emergency Health Services in Erzincan and data were collected from 400 emergency health workers. The statistical analysis of the data was done by SPSS 20.00 package program and .05 was taken as the significance level. According to the regression analysis results hopelessness, negative effects of events on life, social support and dissociation were significantly related with stress symptoms and depressive mood levels. It was found that the effects of event and dissociation predict posttraumatic stress symptoms positively; and social support negatively. It was observed that hopelessness and post-traumatic stress symptoms predicted the level of depression positively and social support negatively. According to the findings of the research, it was recommended that psychosocial support units may be useful in emergency health services and psycho-education and psychological counseling services provided by the psychosocial unit can be useful for the stress, posttraumatic stress disorder and other problems that may be experienced.
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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".