P.027 KNOW BRAIN EMBRACE CARE: A study investigating young adult stroke patients’ knowledge and behaviour around lifestyle
Bibliographic record
Abstract
Background: Stroke incidence is rising among younger adults (≤65yrs). Modifiable and behavioural risk factors are linked to stroke; however, limited understanding of knowledge and behaviour exists around preventative/lifestyle medicine (LSM) among this patient population. Study aim was to assess younger adult stroke patients’ lifestyle knowledge, habits, and barriers. Methods: A cross-sectional design was employed. Data were collected through an online, self-reported survey following a routine stroke prevention clinic visit and analyzed using descriptive and inferential statistics. Results: Sample included 103 participants (56.3% women, 60% white, mean age 47.6, 54.5% prior stroke). Majority (63%) understood current healthy lifestyle recommendations around blood pressure, sleep, and alcohol use, but fewer (<24.3%) around exercise and diet. Almost 70% ate processed food weekly, with emotions and social/family situations influencing eating habits. Interestingly, despite not understanding the current recommendations, >80% exercised moderately (3.5d/wk) with work and family responsibilities as main barriers. Over 50% slept <7hrs/night, had moderate to high stress levels, and implemented different coping strategies (food, TV, video games, and exercise). Majority (82.4%) reported willingness to change habits. Conclusions: Our findings provide valuable insight on young adult stroke patients’ preventative/LSM-related knowledge, habits, and barriers and provide new opportunities for the development of brain care-related initiatives.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".