Missed opportunities: childhood learning disabilities as early indicators of risk among homeless adults with mental illness in Vancouver, British Columbia
Bibliographic record
Abstract
OBJECTIVES: It is well documented that early-learning problems and poor academic achievement adversely impact child development and a wide range of adult outcomes; however, these indicators have received scant attention among homeless adults. This study examines self-reported learning disabilities (LD) in childhood as predictors of duration of homelessness, mental and substance use disorders, physical health, and service utilisation in a sample of homeless adults with current mental illness. DESIGN: This study was conducted using the baseline sample from a randomised controlled trial (RCT). SETTING: Participants were sampled from the community in Vancouver, British Columbia. PARTICIPANTS: The total sample included 497 adult participants who met criteria for absolute homelessness or precarious housing and a current mental disorder based on a structured diagnostic interview. Learning disabilities in childhood were assessed by asking adult participants whether they thought they had an LD in childhood and if anyone had told them they had an LD. Only participants who responded positively to both questions (n=133) were included in the analyses. OUTCOME MEASURES: Primary outcomes include current mental disorders, substance use disorders, physical health, service utilisation and duration of homelessness. RESULTS: In multivariable regression models, self-reported LD during childhood independently predicted self-reported educational attainment and lifetime duration of homelessness as well as a range of mental health, physical health and substance use problems, but did not predict reported health or justice service utilisation. CONCLUSIONS: Childhood learning problems are overrepresented among homeless adults with complex comorbidities and long histories of homelessness. Our findings are consistent with a growing body of literature indicating that adverse childhood events are potent risk factors for a number of adult health and psychiatric problems, including substance abuse. TRIALS REGISTRATION NUMBER: This trial has been registered with the International Standard Randomised Control Trial Number Register and assigned ISRCTN42520374.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 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".