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Record W4416376911 · doi:10.1080/00207411.2025.2576946

The adverse effects of electroconvulsive therapy beyond memory loss: an international survey of recipients and relatives

2025· article· en· W4416376911 on OpenAlexaff
John Read, Sue Cunliffe, Sarah Hancock, Chris Harrop, Lucy Johnstone, Lisa Morrison

Bibliographic record

VenueInternational Journal of Mental Health · 2025
Typearticle
Languageen
FieldMedicine
TopicElectroconvulsive Therapy Studies
Canadian institutionsTraffic Injury Research Foundation
Fundersnot available
KeywordsAdverse effectElectroconvulsive therapyMEDLINEDepression (economics)

Abstract

fetched live from OpenAlex

Research into the safety of electroconvulsive therapy (ECT) usually focuses on memory loss. Studies asking patients directly reveal a broader range of adverse effects. This paper reports the responses of 747 ECT recipients and 201 relatives/friends, from 37 countries, to a question about 25 possible adverse effects, in an online survey. Seventeen of the 25 were reported by more than half of both the ECT recipients and the relatives/friends. Eight were reported by more than 67% of both groups: Losing train of thought, Difficulty concentrating, Fatigue, Emotional blunting, Relationship problems, Loss of independence, Difficulty navigating and Loss of vocabulary. The first four of these were described as ‘severe’ by at least 30% of both groups. Several individual adverse effects were positively related to recipients receiving more courses of ECT and more total individual ECTs, to being female, and having bilateral electrode placements. More recent ECT was not, as often claimed, associated with fewer adverse effects. Researchers and mental health staff should pay attention to a broader range of potential adverse effects than memory loss, so as to facilitate fully informed consent, the minimization or those effects where possible, and, where not possible, referral to rehabilitation programmes.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.177
Threshold uncertainty score0.368

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0000.000

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 head0.363
Teacher spread0.352 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations3
Published2025
Admission routes1
Has abstractyes

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