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The Psychological Assessment of Candidates for Spinal Cord Stimulation for Chronic Pain Management

2004· article· en· W2142371871 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenuePain Practice · 2004
Typearticle
Languageen
FieldMedicine
TopicPain Management and Treatment
Canadian institutionsMcGill University
Fundersnot available
KeywordsPsychosocialMedicineSpinal cord stimulationSpinal cord stimulatorPhysical therapyChronic painPsychotherapistSpinal cordIntensive care medicinePsychiatryPsychology

Abstract

fetched live from OpenAlex

It is known that, in spite of meeting appropriate clinical criteria for spinal cord stimulation (SCS) and having undergone flawless procedures, a significant number of patients who fail the therapy continues to exist. It is the purpose of this article to focus on the development of psychosocial indicators of success for SCS, if any. Referring to specialist literature authors present a review of what is known, what is not known, and what remains controversial on this topic. After reading this article we hope the reader will understand the importance of a psychological evaluation as part of the development of standards for identifying appropriate patients for this therapy. To improve treatment outcomes of SCS, seems to be essential to perform psychosocial evaluations on all persons clinically indicated for SCS to exclude those patients, who most probably, on a psychosocial level, will fail the procedure. To maximize treatment efficacy, authors believe spinal cord stimulation for chronic pain control must be part of a comprehensive program. An accurate preoperative psychosocial assessment and a course of psychological assistance both before and after therapy seems to be crucial for improving outcomes.

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 imitation

Not 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.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.918
Threshold uncertainty score0.327

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.047
GPT teacher head0.437
Teacher spread0.390 · 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