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Electroconvulsive therapy in young people and the pioneering spirit of Lauretta Bender

2010· article· en· W6940886237 on OpenAlexaff

Bibliographic record

VenueResearchOnline - ND (The University of Notre Dame Australia) · 2010
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicMycorrhizal Fungi and Plant Interactions
Canadian institutionsDalhousie University
Fundersnot available
KeywordsElectroconvulsive therapyPunishment (psychology)CohortYoung adult

Abstract

fetched live from OpenAlex

From antiquity up to the middle of the 20th century, with few exceptions, childhood psychiatric disorders were at best ignored and at worst considered manifestations of ‘badness’ or poor upbringing. Thus, it is not surprising that the treatments administered were generally of little clinical benefit or, applying today's standards, more akin to punishment than treatment. In this context, the initial use of electroconvulsive therapy (ECT) in young people in the 1940s provided a welcome breakthrough. ECT was first used in children and adolescents early in that decade by Heuyer and colleagues in Paris, with positive results (1), but what remains the largest published cohort of young recipients of the treatment was that reported by Lauretta Bender in 1947 (2). In that year, Bender described the use of ECT at New York's Bellevue Hospital in 98 children younger than 12 years of age and, while acknowledging that complete remission occurred in only a few patients, Bender suggested that ECT was of benefit in all but two or three of the young recipients. Bender considered the children as having ‘childhood schizophrenia’. However, using contemporary criteria, they would more likely qualify for a diagnosis of developmental disorder or disruptive behaviour disorder.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.770
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0020.000

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 head0.022
GPT teacher head0.250
Teacher spread0.228 · 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 teacher head, not a consensus.

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
Published2010
Admission routes1
Has abstractyes

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