Somatic health perception among in-patients with severe mental illness: a comparison of self-rated and clinically assessed health
Bibliographic record
Abstract
PURPOSE: To investigate somatic health burden and self-rated health (SRH) among forensic psychiatric (FP) patients and the concordance between these two health measurements. Additionally, the study evaluates how different binary groupings of SRH responses impact concordance. METHODS: In a cross-sectional study, 67 inpatients from two Danish forensic psychiatric hospitals were assessed. SRH was measured using a single-item question from the validated and widely used SF-12 scale, and clinical evaluation was performed by a general physician using the Clinical Frailty Scale (CFS). SRH responses were dichotomised in two different ways to test concordance with clinical assessment, and detailed somatic health data were collected from consultations with health care professionals and patient records. RESULTS: Seventy-nine percent of FP patients assessed their own health as "good" or better despite the presence of risk factors such as history of smoking (median pack years = 20) and 25% having hypertension, 84% being overweight, and 55% having metabolic syndrome when assessed by a physician. We found a total of 195 somatic diagnoses with no clear trend in either diagnosis or organ system. Regardless of grouping, concordance between self-reported health and clinician-rated CFS remained low, ranging from 58 to 61%. CONCLUSION: This study reveals discrepancies between forensic psychiatric patients' subjective and clinically assessed health. The findings underscore the need to interpret SRH with caution in populations with severe mental illness, where discrepancies between SRH, physician-rated health and diagnoses burden are pronounced. Clinicians and researchers should approach SRH critically to avoid underestimating patients' health risks.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".