Identifying barriers to mental health system improvements: an examination of community participation in assertive community treatment programs
Bibliographic record
Abstract
BACKGROUND: Integrating the best available evidence into program standards is essential if system-wide improvements in the delivery of community-based mental health services are to be achieved. Since the beginning of the Assertive Community Treatment (ACT) program movement, program standards have included a role for the community. In particular, ACT program standards have sought to ensure that members of the local community are involved in governance and that former clients participate in service delivery as "Peer Support Specialists". This paper reports on the extent to which ACT program standards related to community participation have been implemented and identifies barriers to full compliance. METHODS: Qualitative and quantitative data were collected through a telephone survey of ACT Program Coordinators in Ontario, Canada, using a census sample of the existing 66 ACT programs. A thematic approach to content analysis was used to analyze respondents' qualitative comments. Quantitative data were analyzed using SPSS 16.0 and included means, frequencies, independent t-tests and Pearson Correlations. RESULTS: An 85% response rate was achieved. Of the 33 program standards, the two that received the lowest perceived compliance ratings were the two standards directly concerning community participation. Specifically, the standard to have a functioning Community Advisory Body and the standard requiring the inclusion of a Peer Support Specialist. The three major themes that emerged from the survey data with respect to the barriers to fully implementing the Community Advisory Body were: external issues; standard related issues; and, organizational/structural related issues. The three major themes concerning barriers to implementing the Peer Support Specialist role were: human resource related issues; organizational/structural related issues; and, standard related issues. CONCLUSIONS: The reasons for low compliance of ACT programs with community participation standards are complex and are tied to structural and human resources barriers (both internal and external to the ACT programs) as well as to the requirements of the standards themselves. In order for improvements to the mental health system to be achieved there is a need to identify and address these barriers. Failure to do so will result in less than optimal client, family and economic efficiency outcomes.
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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 | 0.010 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".