Characteristics of people on long-acting injectable antipsychotics in Australia: Data from the 2010 National Survey of High Impact Psychosis
Bibliographic record
Abstract
OBJECTIVE: This study investigates (1) the proportion of people with psychosis who are on long-acting injectable antipsychotics; (2) the difference in the demographic, clinical, substance use and adverse drug reaction profiles of people taking long-acting injectables compared to oral antipsychotics; and (3) the differences in the same profiles of those on first-generation antipsychotic versus second-generation antipsychotic long-acting injectables. METHODS: = 1049). RESULTS: Nearly a third (31.5%) of people with psychosis were on long-acting injectables, of whom 49.7% were on first-generation antipsychotic long-acting injectables and 47.9% were on second-generation antipsychotic long-acting injectables. This contrasts with oral antipsychotics where there was a higher utilisation of second-generation antipsychotics (86.3%). Of note, compared to those on the oral formulation, people on long-acting injectables were almost four times more likely to be under a community treatment order. Furthermore, people on long-acting injectables were more likely to have a longer duration of illness, reduced degree of insight, increased cognitive impairment as well as poor personal and social functioning. They also reported more adverse drug reactions. Compared to those on first-generation antipsychotic long-acting injectables, people on SGA long-acting injectables were younger and had had a shorter duration of illness. They were also more likely to experience dizziness and increased weight, but less likely to experience muscle stiffness or tenseness. CONCLUSION: Long-acting injectable use in Australia is associated with higher rates of community treatment order use, as well as poorer insight, personal and social performance, and greater cognitive impairment. While long-acting injectables may have the potential to improve the prognosis of people with psychosis, a better understanding of the choices behind the utilisation of long-acting injectable treatment in Australia is urgently 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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 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".