The Communication of Neurological Bad News to Parents
Bibliographic record
Abstract
Communicating disappointing or unexpected neurological news to parents is often both difficult and emotionally unwelcome. At the same time, it is important that transfer of such information is done well and, indeed, if done well, can be a very rewarding experience. Limited references are available for physicians regarding the proper communication of neurological bad news to parents. This paper attempts to provide general guidelines regarding this process. The review is based on the available medical literature, detailed discussions with many senior physicians from different medical systems and the authors personal experience. The manner in which neurological bad news is conveyed to parents can significantly influence their emotions, their beliefs and their attitudes towards the child, the medical staff, and the future. This review of the literature, combined with clinical experience, attests to the fact that most families describe emotional shock, upset, and subsequent depression after the breaking of news of a bad neurological disorder. However, the majority find the attitude of the news giver, combined with the clarity of the message and the news giver's knowledge to answer questions as the most important aspects of giving bad news.
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 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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.006 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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 itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
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".