Family-Focused Case Management: A Case Study of an Innovative Demonstration Program
Bibliographic record
Abstract
Using results from a formative evaluation, the paper describes family-focused case management (FFCM). FFCM is an innovative community mental health service designed to support both consumers/survivors and their families. The formative evaluation used a multi-informant, multi-method approach to describe FFCM services and assess their quality. Focus groups with program stakeholders produced a "program-logic model" and identified minimum standards for FFCM. Service activities and outcomes defined in the program-logic model were typical of those offered to consumers/survivors in intensive case management programs, but were supplemented with support being offered to their families. Monitoring of service activities showed that the case manager had regular contact with families and offered them a mix of direct and indirect services that corresponded, in most cases, to defined program standards. Interviews with 14 family members and 8 consumers/survivors receiving FFCM services revealed high levels of satisfaction with most aspects of the program. Overall, evaluation findings suggest that intensive case management can be expanded to include providing support to families. Future directions for developing FFCM are discussed.
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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 | 0.016 | 0.043 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.008 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".