Perception of Radiation Exposure and Risk among Patients, Medical Students, and Referring Physicians at a Tertiary Care Community Hospital
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: It is important for physicians to be aware of the radiation doses as well as the risks associated with diagnostic imaging procedures that they are ordering. METHODS: A survey was administered to patients, medical students, and referring physicians from a number of specialties to determine background knowledge regarding radiation exposure and risk associated with commonly ordered medical imaging tests. RESULTS: A total of 127 patients, 32 referring physicians, and 30 medical students completed the survey. The majority of patients (92%) were not informed of the radiation risks associated with tests that they were scheduled to receive and had false perceptions about the use of radiation and its associated risks. Physicians and medical students had misconceptions about the use of ionizing radiation in a number of radiologic examinations; for example, 25% and 43% of physicians and medical students, respectively, were unaware that interventional procedures used ionizing radiation, and 28% of physicians were unaware that mammography used ionizing radiation. Computed tomographies and barium studies were thought to be associated with the least ionizing radiation among physicians. CONCLUSION: There is a need for educating the public, medical students, and referring physicians about radiation exposure and associated risk so that (1) patients receiving multiple medical imaging tests are aware of the radiation that they are receiving and (2) physicians and future physicians will make informed decisions when ordering such tests to limit the amount of radiation that patients receive and to promote informed consent among patients.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it