Are patients' attitudes towards and knowledge of electroconvulsive therapy transcultural? A multi‐national pilot study
Bibliographic record
Abstract
INTRODUCTION: Electroconvulsive therapy (ECT) is an effective, yet controversial treatment. Most patients receiving ECT have depression and it is likely that the majority having this treatment are older adults. However, attitudes towards ECT and knowledge of ECT in this population have never been studied in relation to the patients' cultural background. OBJECTIVE: To compare the attitudes and knowledge of ECT among older adults depressed patients across three culturally different populations and to explore the relationship between culture, knowledge and attitudes. METHODS: The study was conducted in one centre in each country. A semi-structured survey was used which included three sections: demographics characteristics, attitudes towards and knowledge of ECT. RESULTS: A total of 75 patients were recruited in this study: 30 patients from England; 30 patients from Argentina; and 15 patients from Canada. There was a significant difference in knowledge about ECT across the three countries. No significant difference was found in terms of attitudes. Knowledge was poor in all three countries. The most influential factor shaping subjects' attitudes and knowledge of ECT differed for the three countries. A weak correlation was found between knowledge of and attitudes towards ECT across all patients from the three different countries. CONCLUSION: Attitudes towards ECT are a very complex phenomenon. We could not find evidence that a particular cultural background affects attitudes towards ECT. Generalising the results of our study is restricted by the fact that this was a pilot study that suffered from limitations including small sample size and number of settings.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".