Prevalence and associations of fatigue in psychosis: A systematic review and meta-analysis
Bibliographic record
Abstract
BACKGROUND: There is increasing interest in fatigue in people with psychotic illnesses. This systematic review and meta-analysis reviewed the evidence concerning the prevalence of fatigue and associated factors in adults with psychotic illnesses. METHODS: statistic and Egger's tests were conducted for publication bias. RESULTS: = 93 %). Eighteen studies (n = 4569 participants) were included for an analysis exploring the prevalence of antipsychotic-related fatigue, which was 20.5 % (95 % CI: 11-34 %). We found no significant difference in antipsychotic-related fatigue between studies using a valid scale (27 %, 95 % CI: 14-46, k = 7) and studies using a clinical interview (17 %, 95 % CI: 7-35 %, k = 11) p = 0.302. An Egger's test indicated no publication bias. Quality assessments for included studies revealed that 16 % were at low risk of bias, 9 % at high risk and 75 % at moderate risk. Reported associations with fatigue included sex, age, antipsychotics, distress and depression, sleep, and some negative symptoms. CONCLUSIONS: Our study revealed that a majority of people with psychosis experience fatigue. Antipsychotics, sex, and functioning may contribute to tiredness symptoms, but further research is needed.
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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 | 0.016 | 0.034 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.018 | 0.042 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".