The lived experience of people receiving assertive community treatment: A phenomenological study
Bibliographic record
Abstract
In recent years the Assertive Community Treatment (ACT) model of service delivery, which has held considerable influence in policy and decision making in the mental health field over the past 30 years, has recently been promoted at the provincial policy level in Ontario. Previous studies on ACT have been primarily quantitative in nature and have contributed greatly to the body of knowledge that we now possess regarding the clinical outcomes produced by the ACT model. However, with the Ontario government’s financial plan to significantly increase the number of ACT programs in this province, the mental health field would benefit from the added knowledge of subjective experience that is made available through the use of qualitative methodologies. In this study, five ACT clients shared their personal experiences of receiving ACT services in order to answer the question: how do clients experience Assertive Community Treatment? The findings from this study suggest: (a) participants experience ACT as a single relationship that exists between themselves and their case manager; (b) participants experience a need to formulate goals that addressed higher order needs such as independent employment, increased self-esteem, increased income and community integration; (c) participants experience the interaction with and acceptance by non-consumer/ survivors as the most important aspect of community integration. The knowledge and understanding of the experiences of ACT clients provided by this study hold important social and professional implications for both ACT and the larger mental health system.
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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 | 0.006 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.014 | 0.016 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.003 | 0.005 |
| 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".