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Record W7135608609

Current trends in electroconvulsive therapy

2022· dissertation· cs· W7135608609 on OpenAlexaboutno aff
Jakub Opelka

Bibliographic record

VenueDigital Repository (National Repository of Grey Literature) · 2022
Typedissertation
Languagecs
FieldMedicine
TopicElectroconvulsive Therapy Studies
Canadian institutionsnot available
Fundersnot available
KeywordsElectroconvulsive therapyCognitionElectroencephalographySeizure thresholdDepression (economics)Cognitive impairment
DOInot available

Abstract

fetched live from OpenAlex

This bachelor thesis focuses on electroconvulsive therapy from a research and clinical perspective. Special emphasis is placed on cognitive impairment as one of the most serious side effects of electroconvulsive therapy. It also briefly summarizes the historical development and current good practice in electroconvulsive therapy. It presents several hypotheses on the mechanism of action of electroconvulsive therapy and briefly discusses the technical aspect of this treatment method. Future perspectives and new variants of convulsive methods are described with emphasis on Low Amplitude Seizure Therapy. The proposed research aims to compare the degree of cognitive impairment when using electroconvulsive therapy and its new variant Low Amplitude Seizure Therapy. A sub-objective is to map the profile of cognitive impairment with Low Amplitude Seizure Therapy alone, as no such research exists to date. A battery of cognitive tests consisting of the Montreal Cognitive Assessment, the MATRICS Consensus Cognitive Battery, and the Columbia University Autobigraphical Memory Interview - Short Form was constructed for research purposes. Keywords electroconvulsive therapy, Low Amplitude Seizure Therapy, cognitive function, retrograde amnesia, major depressive disorder, MATRICS Consensus Cognitive Battery

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 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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesMeta-epidemiology (narrow)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.253
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0030.003
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.003
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 head0.011
GPT teacher head0.299
Teacher spread0.289 · 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; both teacher heads agree on what is shown here.

Study designObservational
Domainnot available
GenreEmpirical

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

Citations0
Published2022
Admission routes1
Has abstractyes

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