Very low neighbourhood income limits participation post stroke: preliminary evidence from a cohort study
Bibliographic record
Abstract
BACKGROUND: Neighbourhood income level is associated with the incidence of stroke and stroke-related mortality. It has also been linked to receipt of appropriate services, post discharge motor recovery and functional status following a stroke. We examined the impact of neighbourhood income on participation among community-dwelling stroke survivors during the two years following the stroke. METHODS: Secondary analysis of data from a prospective cohort study. Participants were 67 individuals who were treated in acute care or rehabilitation following a first ever stroke, and were discharged to the community with FIM™ scores of at least 3 for comprehension, memory and problem solving. On this functional independence measure, these scores indicate that assistance is needed with related tasks up to 50 % of the time. Participation at 6, 9, 12, 18 and 24-months post stroke was measured using the Reintegration to Normal Living Index (RNLI). Income was measured by median neighbourhood annual family income according to postal code. The impact of very low neighbourhood income (median family income $20,000 Cdn or less) on participation at each follow-up period was determined controlling for potential confounders. RESULTS: Six (9.0 %) of the participants lived in very low-income neighbourhoods. These participants had average RNLI scores approximately 25 % lower at each follow-up period. While there was a trend for increasing participation with time among those in higher income neighbourhoods, this was not seen among very low-income neighbourhood participants. Very low me neighbourhood income had an independent effect on participation after controlling for discharge FIM™, 2-min walk test, gender, self-rated health, age, and emotional well-being at all follow-up periods. CONCLUSIONS: Our results indicate that very low neighbourhood income is linked with decreased participation during the first two years following stroke. Our findings indicate the need for further investigation of this relationship, and the importance of close follow-up of stroke survivors living in very low-income contexts.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".