Assessment of everyday functioning in Swedish forensic mental health services
Bibliographic record
Abstract
Individuals in forensic mental health services (FMHS) commonly exhibit greater cognitive deficits and unmet health needs than those in general psychiatric care. Despite the central role of functional disability in FMHS treatment objectives, the assessment in this domain remains underexplored. This study examines current practices of functional assessment in Swedish FMHS through the combination of a survey and analysis of register data. The survey covered the presence and content of procedure manuals regarding functional assessment and the clinical use of assessment results. Frequency of assessment and relation to individual factors (age, gender, place of birth, psychiatric diagnosis, and history of addiction) and contextual factors (FMHS site, size and security level at the site, and administrated risk assessment) were investigated through statistical analysis of register data. Results indicate significant variability in functional assessment practices across different FMHS sites. Contextual factors such as site and the use of risk assessment instruments demonstrate a positive association with assessment frequency. Functional assessments were primarily used with in-patients, raising concerns about applicability beyond hospital settings and preparation for community re-entry. Despite professionals’ belief in the potential benefits of functional assessment for tailoring interventions, its impact on individual treatment plans was limited. The study underscores the need for improved assessment accuracy and ongoing monitoring of functioning, particularly considering the disparate practices observed across FMHS sites. Moreover, there is a call for national coordination and evidence-based guidelines to enhance functional assessment practices in Swedish FMHS.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".