Children’s Drawing as a Projective Measure to Understand Their Experiences of Dental Treatment under General Anesthesia
Bibliographic record
Abstract
Purpose: The overall aim of the study was to gain a deeper understanding of 3 to 10 year-old children’s experiences, main concerns, and how they manage attending hospital for dental treatment under general anesthesia (DTGA). Methods: Twelve children aged 3–10 who were scheduled for DTGA were interviewed. In addition to tape-recorded interviews, data were collected using video diaries, participant observations, and pre-, peri-, and postoperative drawings. The children’s drawings (n = 43) were analyzed using the Child Drawing: Hospital Manual (CD:H) and Vygotsky postulations for context readings, with the aim to explore what it means for children to undergo DTGA. Results: The analysis found that the main concern for children during the pre-operative period was that they were forced to prepare for an unknown experience, which elicited stress. This situation was handled during the peri-operative period by trying to recover control and to cooperate despite fear, stress, and anxiety. Drawings completed post-operatively showed the surgical mask, “stinky” smell of the anesthetic gas, and multiple extraction of teeth were the main troubling experiences for children. Several weeks after DTGA, children tried to regain normalcy in their lives again. Conclusion: This study contributed to a deeper understanding of how children as young as 3 years undergoing DTGA experience and express their lived experiences: emotional, psychological, physiological, or physical stress in the context of DTGA.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".