Neurosurgeons' perspectives on psychosurgery and neuroenhancement: a qualitative study at one center
Bibliographic record
Abstract
OBJECT: Advances in the neurosciences are stirring debate regarding the ethical issues surrounding novel neurosurgical interventions. The application of deep brain stimulation (DBS) for treating refractory psychiatric disease, for instance, has introduced the prospect of altering disorders of mind and behavior and the potential for neuroenhancement. The attitudes of current and future providers of this technology and their position regarding its possible future applications are unknown. The authors sought to gauge the opinions of neurosurgical staff and trainees toward various uses of neuromodulation technology including psychosurgery and neuroenhancement. METHODS: The authors conducted a qualitative study involving in-depth interviews with 47 neurosurgery staff, trainees, and other neuroclinicians at a quaternary care center. RESULTS: Several general themes emerged from the interviews. These included universal support for psychosurgery given adequate informed consent and rigorous scientific methodology, as well as a relative consensus regarding the priority given to patient autonomy and the preservation of personal identity. Participants' attitudes toward the future use of DBS and other means of neuromodulation for cognitive enhancement and personality alteration revealed less agreement, although most participants felt that alteration of nonpathological traits is objectionable. CONCLUSIONS: There is support in the neurosurgical community for the surgical management of refractory psychiatric disease. The use of neuromodulation for the alteration of nonpathological traits is morally and ethically dubious when it is out of sync with the values of society at large. Both DBS and neuromodulation will have far-reaching and profound public health implications.
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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 | 0.022 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.019 | 0.017 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.003 | 0.009 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".