Understanding Mental Health First Aid for Psychosis
Bibliographic record
Abstract
Throughout this guide, we have tried to explain all parts of a first episode of psychosis in a detailed way. But what happens if you know someone who may be experiencing an episode of psychosis and you have to act fast or help them get into treatment? This last chapter includes advice on how to provide mental health “first aid” to those who may be experiencing an episode of psychosis. These guidelines were developed by and reprinted here with permission from Professor Anthony Jorm and Ms. Betty Kitchener from the University of Melbourne and ORYGEN Research Centre in Melbourne, Victoria, Australia. As a result of an extensive process, they are based on the agreement of a panel of patients, family members, and mental health professionals from Australia, Canada, New Zealand, the United Kingdom, and the United States. For more information on their Mental Health First Aid program, please visit www.mhfa.com.au. The remainder of this chapter is organized around nine questions that are addressed to help people who may need to provide “first aid” to someone experiencing psychosis. The purpose of these guidelines is to help members of the public to provide first aid to someone who may be experiencing psychosis. The role of the first aider is to assist the person until he or she receives appropriate professional help or the crisis resolves. These guidelines are a general set of recommendations about how you can help someone who may be experiencing psychosis. Each individual is unique, and it is important to tailor your support to that person’s needs. So, these recommendations will not be appropriate for every person who may have psychosis. It is important to learn about the early warning signs of psychosis and the symptoms of psychosis so that you can recognize when someone may be developing psychosis. Although some of these signs may not be very dramatic on their own, when you consider them together, they may suggest that something is not quite right. It is important not to ignore or dismiss such warning signs or symptoms, even if they appear gradually and are unclear.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.023 | 0.008 |
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".