Predictors of length of time in service: Characteristics of people in intensive case management for longer than 5 years.
Bibliographic record
Abstract
OBJECTIVE: The purpose of this study was to examine the characteristics of people who stay in intensive case management (ICM) for longer than 5 years. METHOD: = 289). RESULTS: People who were older and those with psychotic disorder, co-occurring substance use disorder, dual diagnosis (with developmental disability), chronic medical condition, and also in another program in the same agency were more likely to be in ICM for longer than 5 years. People who were returning ICM clients and those who completed the ICM program (rather than withdrawing or disengaging) were more likely to be in ICM for 5 years or less. Higher dose of ICM (in contacts) predicted a shorter time in ICM. CONCLUSIONS AND IMPLICATIONS FOR PRACTICE: People with serious mental illness, dual diagnosis, concurrent substance use, and chronic medical conditions and those who are older may need additional supports within ICM and when transitioning out of ICM. People in ICM for a longer time have lower numbers of contacts, indicating that a less intense service may meet their needs. (PsycInfo Database Record (c) 2025 APA, all rights reserved).
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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 | 0.000 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".