A Study on the Psychological Status of Hospitalized Children and Their Perceptions of Hospital and Sickness Through Drawings
Bibliographic record
Abstract
Objective: Sickness and hospitalization may have negative influences on the development and psychological status of children. It is important to understand children’s perceptions of sickness and hospital in order to reduce and eliminate the negative effects of hospitalization experiences on the psychological well-being of the children. From this perspective, the aim of this study was to examine the hospitalized children’s psychological status and their perceptions of hospital and sickness.Material and Methods: The study was based on a both descriptive and content analysis approach. The study group consisted of 31 children between the ages of 5 and 16 years who were recruited from a public hospital in North Cyprus. The children’s experiences were examined through their family and hospital drawings and draw-and-tell interviews.Results: Anxiety, depression, and the representation of the hospital as unsafe, need for a well-structured environment, problems with social relations, difficulties with holding onto life and lack of quality in the drawings were found to be the common findings in the drawings. When the drawings of each child were evaluated individually, it was found that regression increases in the hospital drawings. Conclusion: The findings of this study may be helpful in understanding the hospitalization experiences from the children’s perspective and might have clinical implications for practice in terms of supporting children in the hospitalization process.
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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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".