Accuracy of reported service use in a cohort of people who are chronically homeless and seriously mentally ill
Bibliographic record
Abstract
BACKGROUND: Self-reported service use is an integral feature of interventional research with people who are homeless and mentally ill. The objective of this study was to investigate the accuracy of self-reported involvement with major categories of publicly funded services (health, justice, social welfare) within this sub-population. METHODS: Measures were administered pre-randomization in two randomized controlled trials, using timeline follow back with calendar aids for Health, Social, and Justice Service Use, compared to linked administrative data. Variables examined were: psychiatric admissions (both extended stays of more than 6 months and two or more stays within 5 years); emergency department visits, general hospitalization and jail in the past 6 months; and income assistance in the past 1 month. Participants (n = 433) met criteria for homelessness and a least one mental illness. RESULTS: Prevalence adjusted and bias adjusted kappa (PABAK) values ranged between moderate and almost perfect for extended psychiatric hospital separations (PABAK: 0.77; 95 % confidence interval (CI) = 0.71, 0.83), multiple psychiatric hospitalizations (PABAK = 0.50, 95 % CI = 0.41, 0.59), emergency department visits (PABAK: 0.77; 95 % CI = 0.71, 0.83), jail (PABAK: 0.74; 95 % CI = 0.68, 0.81), and income assistance (PABAK: 0.82; 95 % CI = 0.76, 0.87). Significant differences in under versus over reporting were also found. CONCLUSIONS: People who are homeless and mentally ill reliably reported their overall use of health, justice, and income assistance services. Evidence of under-reporting and over-reporting of certain variables has implications for specific research questions. ISRCTN registry: 57595077 (Vancouver at Home Study: Housing First plus Assertive Community Treatment versus congregate housing plus supports versus treatment as usual); and 66721740 (Vancouver at Home study: Housing First plus Intensive Case management versus treatment as usual).
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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 | 0.009 | 0.042 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".