Characterizing movement disorders and their associations with substance use and psychosis in adults living in precarious housing or homelessness
Bibliographic record
Abstract
Background: Many individuals who are precariously housed or homeless live with multimorbid conditions, including substance use, psychotic, and neurological disorders. Despite high levels of susceptibility, movement disorders are understudied in these socially marginalized people. The general objective of the current dissertation was to characterize movement disorders in relation to substance use and psychosis, and also to examine their longitudinal characteristics. Methods: Participants were recruited from an impoverished neighborhood of downtown Vancouver, Canada. Data were collected on the diagnosis of psychiatric disorders, severity of signs of movement disorders and symptoms of psychosis, and recent use of drugs and substances. Cross-sectional and longitudinal mixed-effects regression analyses were used to examine the associations in question. Results: Among different types of substance use examined, methamphetamine was most consistently associated with movement disorders, including parkinsonism and dyskinesia, and the association was stronger in older female participants. Moreover, underlying psychotic disorders were associated with higher odds of clinically relevant signs of movement disorders as a result of methamphetamine and cannabis use. In turn, movement disorders were associated with impaired psychosocial functioning, greater symptoms of psychosis (negative, disorganized, and excited symptoms), and poorer cognitive functioning, especially in participants with underlying psychotic disorders. Furthermore, there were temporal relationships between movement disorders and cardinal psychotic symptoms, where preceding delusions and unusual thought content were associated with subsequent parkinsonism, and preceding dyskinesia was associated with subsequent conceptual disorganization. Lastly, parkinsonism was commonly observed in all age groups of precariously housed and homeless participants relative to the general population. The proportion affected by parkinsonism rapidly increased during the peak of the opioid epidemic, although urine fentanyl detection was not associated with parkinsonism. On the other hand, the proportion affected by dyskinesia decreased during the post-declaration period, and urine fentanyl detection was associated with lower severity of orofacial dyskinesia. Conclusions: Overall, these results suggest that movement disorders are important neurological complications in precariously housed and homeless individuals, and future studies should aim to reveal the mechanisms underlying substance use-associated movement disorders (e.g., neuroimaging markers), differentially diagnose parkinsonism (e.g., idiopathic Parkinson’s disease), and establish intervention and prevention strategies for these signs and symptoms.
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 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".