Awareness, facilitators, barriers, and behaviours surrounding brain health: a large-scale cross-sectional survey of adults across UK and Ireland
Bibliographic record
Abstract
BACKGROUND: Almost half of all dementia cases could theoretically be delayed or prevented by addressing risk factors at the population level. However, dementia risk reduction requires awareness of, and action on, modifiable risk factors. This study aimed to explore public awareness of brain health, and the facilitators for, and barriers to, engaging in preventative action to reduce dementia risk, across the UK and Ireland. METHODS: The Brain Health and Lifestyle Survey (BHLS) was a co-developed and evidence-informed online survey, underpinned by behaviour change frameworks. The BHLS was distributed via convenience sampling to individuals aged ≥ 40 years living in the UK and Ireland. It comprised 31 main questions on awareness, beliefs and behaviour change surrounding brain health and took approximately 20-25 min to complete. Ethical approval was obtained from Queen's University Belfast [Ref: MHLS20_162]. RESULTS: A total of 6816 respondents (75% UK; 25% Ireland) completed the BHLS between February and June 2021. Most respondents were aged 50-74 years (78%), female (79%), white (99%), overweight (59%) and highly educated (64%). The majority of respondents rated their brain health as good (79%) and there was high awareness of protective factors, including cognitively stimulating activities (91%) and physical exercise (88%). However, awareness of risk factors such as hypertension (62%), midlife obesity (61%), air pollution (50%) and hearing loss (35%) was lower. Awareness differed according to demographic factors, with lower awareness among respondents aged 40-49 years, and those with lower educational attainment. The identified barriers to adopting a brain-healthy lifestyle were implementing changes which were not enjoyable (44%), lack of self-motivation (33%), and a lack of trusted information (27%). Facilitators for adopting a brain-healthy lifestyle included: noticing problems with brain health (70%) and receiving personalised advice (51%). CONCLUSION: Understanding of brain health and dementia risk reduction was variable in this large sample of UK and Irish citizens. There were identified gaps in awareness of risk factors relating to cardiometabolic health, hearing loss, and air pollution. These findings highlight the need for credible sources of accessible and relevant information to improve awareness and behaviours surrounding brain health.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| 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 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".