Child maltreatment between knowledge, attitude and beliefs among Saudi pediatricians, pediatric residency trainees and medical students
Bibliographic record
Abstract
BACKGROUND: Child maltreatment is not included in Saudi medical schools and pediatric residency curriculums, which might limit knowledge and spread misconceptions. Additionally, physicians might have different attitudes regarding reporting child abuse and neglect. In this study, we hypothesize that medical students and pediatric trainees have limited knowledge, oblivious attitude and misbeliefs regarding child maltreatment in comparison to experienced pediatricians. But, medical students and trainees might hold higher motives and willingness to learn about child maltreatment and their consequences. METHODS: A self reported questionnaire was distributed after a pilot study to include pediatricians, pediatrics trainees and medical students in all main areas of pediatrics services: pediatrics wards, pediatrics outpatient clinics, critical care and pediatrics emergency. RESULTS: In disregard to their level of training, medical students and physicians believed that child maltreatment happens within the kingdom and is common. They were familiar with the child maltreatment definition, although only one third thought it is subject to culture sensitivity. However, experienced physicians were more knowledgeable especially about neglect. Moreover, female participants were more likely to report despite being more skeptical of readiness of Saudi law system to deal with cases of maltreatment. In general, knowledge about reporting was clearly deficit at all levels. Fortunately, all participants requested and were enthusiastic to receive further training. CONCLUSION: Saudi medical students, pediatrics trainees and pediatricians have good basic knowledge, positive attitude and willingness to learn more to provide a safe environment for children in Saudi Arabia. However, knowledge in regards to reporting child maltreatment is a major observed defect. Still, further education and training are needed to combat CAN in Saudi Arabia.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".