Precision-medicine findings from the FACE-SZ cohort to develop motivation-enhancing programs in real-world schizophrenia
Bibliographic record
Abstract
Background In people with schizophrenia, major areas of everyday life are impaired, including independent living, productive activities, social relationships and overall quality of life. Enhanced understanding of factors that hinder real-life functioning is vital for treatments to translate into more positive outcomes.Aim The goal of the present study was to identify factors associated with motivation deficits in real-life schizophrenia, and to assess its contribution to impaired functioning and quality of life.Methods Based on previous literature and clinical experience, several factors were selected and grouped into factors potentially explaining motivation deficits. Some of these variables were never investigated before in relationship with motivation deficits.Results In 561 patients with schizophrenia of the national FACE-SZ cohort living in the community, 235 (41.9%) reported severe motivation deficits. These deficits were found to be significantly associated with impaired socially useful activities, psychological and physical quality of life (in almost all domains), alcohol use disorder (aOR = 2.141, p = 0.021), severe nicotine dependence (aOR = 2.906, p < 0.001) independently of age and sex. No significant association was found for body mass index, metabolic syndrome or physical activity level. In the second model, we identified the following modifiable factors associated with motivation deficits: history of suicide attempt (aOR = 2.297, p = 0.001), positive symptoms (aOR = 1.052, p = 0.006), current major depressive episode (aOR = 2.627, p < 0.001), sleep disorders (aOR = 1.474, p = 0.024) and lower medication adherence (aOR = 0.836, p = 0.001) independently of gender, current alcohol use disorder, second-generation antipsychotics and akathisia. No significant association was found for negative symptoms, childhood trauma and inflammation. These results were maintained after removing patients with schizoaffective disorders or those with major depressive disorder.Interpretation Motivation deficits are frequent and remain persistent unmet need in real-world schizophrenia that should be addressed in future guidelines. Based on our results, literature and clinical experience, we recommend to address in priority major depression, sleep, suicide, positive symptoms (when present and as early as possible) and medication adherence to improve motivation deficits of schizophrenia.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".