Psychological Well- Being of Healthcare Workers During The COVID-19 Pandemic
Bibliographic record
Abstract
The purpose of this study was to determine the description of the psychological well-being of health workers during the co-19 pandemic, and to find out the factors that can influence it. The informants in this study totaled 6 people. Informants were selected based on the 42-item Ryff psychological well-being scale score that had previously been distributed in advance, and could reach 96 health worker respondents. Of the 96 respondents, 6 subjects were selected based on their level of psychological well-being, namely 3 subjects with high psychological well-being, and 3 subjects with low psychological well-being. The research was conducted using a qualitative method with a phenomenological approach. Interviews were conducted using an interview guide prepared by the researcher. Data analysis was conducted using interpretative phenomenological analysis. From the results of the analysis, it was found that the psychological well-being of health workers during the Covid-19 pandemic can be influenced by the social support received, the way the subject overcomes the problems faced, and the gratitude he has for his life.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 | 0.001 |
| 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".