O-07 - Adapting ACT to serve culturally diverse communities: a comparison of a japanese and a canadian ACT team
Bibliographic record
Abstract
The Assertive Community Treatment (ACT) teams of Mount Sinai Hospital in Toronto and the KUINA Center, Hitachinaka, Japan, were compared with regard to ACT fidelity, organizational structure, populations served, and treatment outcomes. Ethnocultural adaptations to the ACT model made by both teams included enhanced family support and intervention, culturally and linguistically matched staff and patients when possible, culturally informed therapy, routine cultural assessments, culturally matched housing and community support, and flexible funding models. Data were gathered by chart reviews (66 patients in Toronto and 40 patients in Japan), a satisfaction measure, a standard measure of ACT fidelity, a pre-post measure of treatment outcomes (the Brief Psychiatric Rating Scale), and hospitalization days. Both teams achieved good fidelity to ACT and reductions in hospitalization and symptom severity. Family satisfaction scores were high. With culturally informed adaptations, ACT can be effective in a Canadian mixed ethnocultural population and a homogeneous Japanese population.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".