Barriers and facilitators of access and utilization of mental health services among forensic service users along the care pathway
Bibliographic record
Abstract
Abstract Background The verdict of Not Criminally Responsible on account of a Mental Disorder (NCRMD) is increasingly used to access specialized mental health services in Canada and elsewhere. This situation highlights the importance of ensuring timely access to services in the community to prevent violence and justice involvement. The objective of the present study is to identify individual and contextual barriers and facilitators of access to mental health services during the period preceding an offense leading to a verdict of NCRMD. Methods The sample includes 753 people found NCRMD in Québec, Canada. All episodes of mental health hospitalizations and service use before the index offense were identified using provincial administrative health data, for an average period of 4.5 years. Access was conceptualized as a function of the possibility of seeking, reaching and receiving appropriate health care services, based on Lévesque and colleagues patient-centred model of access to care. Generalized linear models were computed to identify the individual and contextual predictors of: (1) seeking mental healthcare (at least one contact with any type of services for mental health reasons); (2) reaching psychiatric care (at least one contact with a psychiatrist); (3) receiving psychiatric care, operationalized as (3a) continuity and (3b) intensity. Factors associated with volume of emergency mental health services were examined as exploratory analysis. Results Geographical considerations were highly important in determining who reached, and who received specialized mental health care – above and beyond individual factors related to need. Those who lived outside of major urban centres were 2.6 times as likely to reach psychiatric services as those who lived in major urban centres, and made greater use of emergency mental health services by 2.1 times. Living with family decreased the odds of seeking mental healthcare by half and the intensity of psychiatric care received, even when adjusting for level of need. Conclusions Findings support efforts to engage with the family of service users and highlights the importance of providing resources to make family-centred services sustainable for health practitioners. Health policies should also focus on the implementation of outreach programs, such as Forensic Assertive Community Treatment teams as part of prevention initiatives.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".