Exploring the association between khat use and psychiatric symptoms: a systematic review
Bibliographic record
Abstract
Objectives Consumption of the drug khat is high across East Africa and the South-Western Arabian Peninsula despite evidence for its adverse psychiatric effects. This systematic review aims to explore cross-sectional research in the field to determine the strength of the association between khat use and psychiatric symptoms Methods Six databases were searched in October 2021—Ovid Medline, Embase, APA PsycINFO, CINAHL, Scopus and Proquest—using the following search terms: “khat” OR “qat” OR “qaad” OR “catha” OR “miraa” OR “mairungi” AND “depression” OR “anxiety” OR “mania” OR “psych*” OR “schiz*” OR “mental” OR “hallucinations” OR “delusions” OR “bipolar”. Eligible studies were cross-sectional studies of any population or setting comparing the prevalence of psychiatric symptoms in long term or dependent khat users with non-users. The quality of each study was appraised by the Newcastle-Ottawa scale. A meta-analysis was planned using a random effects model to produce an OR with 95% CIs—using the Mantel-Haenszel method—alongside an I 2 statistic to represent heterogeneity. The quality of this meta-analysis was appraised using the Grading of Recommendations, Assessment, Development and Evaluations (GRADE) scoring system. Results 35 studies were eligible for inclusion (total participants=31 893), spanning 5 countries (Ethiopia, Somalia, Kenya, Saudi Arabia, UK). Meta-analysis suggests that khat use is associated with an 122% increased prevalence of psychiatric symptoms (OR 2.22, 95% CIs 1.76 to 2.79, p<0.00001, GRADE score: ‘very low’). Conclusions The high heterogeneity of the meta-analysis is likely due to the wide variation between the studies within the evidence base. To perform a more accurate systematic review, further primary studies are needed with standardised measurements of variables, particularly khat consumption. PROSPERO registration number CRD42020224510.
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 | 0.006 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.008 |
| Bibliometrics | 0.009 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 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".