Words used by children and their primary caregivers for private body parts and functions.
Bibliographic record
Abstract
BACKGROUND: Effective patient-physician communication requires the use of words that are clearly understood by both parties. We conducted this study to compile a list of words used by children and caregivers to describe "private" anatomical structures and physiological functions, to document the frequency of such usage and to examine the relation between correct word usage and caregiver's level of education. METHODS: In a large urban pediatric emergency department, a convenience sample of 156 children at least 3 years old were asked to name the body parts (penis, testes, vagina, buttocks, breasts) pointed to in 4 simple, explicit line drawings of an unclothed boy or girl, and to name the bodily functions (vomiting, defecation, urination) depicted in 3 drawings of children. Eighty-seven patients sufficiently fluent in English were included in the study. Their caregivers were asked separately what words they currently use with their child and with other adults for these body parts and functions and what words they remembered using as children. RESULTS: The children used a mean of 1.2 correct anatomical and physiological terms out of a possible 8 to describe the private parts and functions in the drawings. The mean number of correct words used by the caregivers was 2.3 when talking with their children, 3.6 when talking with their peers and 1.5 when they were children. There was no correlation between the caregiver's level of education and the frequency of correct word usage by their children. We identified slang words used by at least 5% of the respondents; however, some used the same slang words to refer to different body parts. INTERPRETATION: Given the variety of slang words used by children and their caregivers to describe private parts and functions, the meaning of the words should be clarified during history taking.
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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.000 |
| 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".