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Record W2061751949 · doi:10.4061/2011/871874

A Review of Social and Relational Aspects of Deep Brain Stimulation in Parkinson's Disease Informed by Healthcare Provider Experiences

2011· review· en· W2061751949 on OpenAlexafffund
Emily Bell, Bruce Maxwell, Mary Pat McAndrews, Abbas F. Sadikot, Éric Racine

Bibliographic record

VenueParkinson s Disease · 2011
Typereview
Languageen
FieldMedicine
TopicNeurological disorders and treatments
Canadian institutionsMcGill UniversityMontreal Neurological Institute and HospitalUniversité de MontréalMontreal Clinical Research Institute
FundersSocial Sciences and Humanities Research Council of CanadaCanadian Institutes of Health ResearchNovo Nordisk Fonden
KeywordsDeep brain stimulationParkinson's diseasePsychologyDiseaseHealth carePsychiatryMedicinePolitical science

Abstract

fetched live from OpenAlex

Background. Although the clinical effectiveness of deep brain stimulation (DBS) in Parkinson's disease is established, there has been less examination of its social aspects. Methods and Results. Building on qualitative comments provided by healthcare providers, we present four different social and relational issues (need for social support, changes in relationships (with self and partner) and challenges with regards to occupation and the social system). We review the literature from multiple disciplines on each issue. We comment on their ethical implications and conclude by establishing the future prospects for research with the possible expansion of DBS for psychiatric indications. Conclusions. Our review demonstrates that there are varied social issues involved in DBS. These issues may have significant impacts on the perceived outcome of DBS by patients. Moreover, the fact that the social impact of DBS is still not well understood in emerging psychiatric indications presents an important area for future examination.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0040.005
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.066
GPT teacher head0.363
Teacher spread0.297 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreReview

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".

Quick stats

Citations45
Published2011
Admission routes2
Has abstractyes

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