A Systematic Review of Knowledge, Attitude, and Perception Towards Electroconvulsive Therapy (ECT) in Africa
Bibliographic record
Abstract
Background: Despite growing evidence showing ECT’s efficacy and efficiency in the management of severe mental health conditions, the knowledge, attitude, and perceptions (KAP) towards ECT vary around the globe. However, KAP guarantees the extent to which ECT is accepted and administered efficiently. This review sheds light on the KAP toward ECT in Africa. Methods: This review included studies that presented results on KAP towards ECT in Africa based on relevant searches from various databases ( Ovid, PubMed, Web of Science , and African Journal Online ) using appropriate key words from the start until September 2023. Results: Only 13 of the 867 retrieved articles were included in the review. The studies show a reliance on different sources of information, including healthcare professionals, mass media, and the Internet. Moreover, African individuals demonstrated varying levels of knowledge, with many having a limited understanding of ECT. Additionally, attitudes and perceptions toward ECT vary across the continent and depend on exposure and medical qualification. Conclusion: The review of KAP of ECT in Africa reveals a complex landscape characterized by diverse sources of information, varying levels of knowledge among healthcare professionals and students, and a spectrum of attitudes and perceptions towards ECT. The findings underscore the importance of addressing knowledge gaps, dispelling myths, and promoting informed perspectives to enhance the acceptability and utilization of ECT in mental health care. Keywords: electroconvulsive therapy, ECT, knowledge, attitude, perception, Africa
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 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 | 0.007 | 0.034 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.011 | 0.013 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".