The Predictive Validity of Clinical Ratings of the Short-Term Assessment of Risk and Treatability (START)
Bibliographic record
Abstract
With the increased need to assess and manage risk in inpatient settings, the Short-Term Assessment of Risk and Treatability (START) was implemented on a civil psychiatric unit. The goal of the present study was to examine the tool's predictive validity when completed by clinical teams as part of routine practice. Data were collected for 34 patients hospitalized for a minimum of 30 days prior to and after a START evaluation. Several challenging behaviors, such as aggression towards others, self-harm, and substance abuse were assessed using the START Outcomes Scale ( Nicholls et al., 2007 ). Results from multilevel logistic regression and Receiver Operating Characteristics analyses lend partial support for the predictive validity of the START. A limited set of START items combined was significantly better at predicting the challenging behaviors than the original total Strength and Vulnerability scales. Results are discussed in terms of the clinical use of risk assessment.
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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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".