Abstract TMP103: Associations Between Trust in Health Information Sources and Perceptions on the Modifiability of Stroke and Dementia Risks Using a U.S. Based Cohort
Bibliographic record
Abstract
Background: Trust in healthcare information sources, specifically in healthcare professionals (HCPs) influences people’s health-related knowledge and behaviors. Epidemiological studies demonstrate that approximately 45% of dementia and 60% of stroke risks are attributable to modifiable risk factors. However, limited data exist on associations between trust levels in HCPs and people’s perceptions on the modifiability of dementia and stroke risks from a United States cohort. Methods: We developed a survey based on validated questionnaires and distributed it to a cohort of all U.S. states via the online Prolific platform in 2023. First, we described cohort characteristics and levels of trust in health information sources and mediums. We performed multivariable regression analyses between high trust of all HCPs (i.e. primary care physicians, specialists, and nurses) with the perceptions that dementia and stroke risks are modifiable, adjusting for age, sex assigned at birth, race/ethnicity, level of education, and status of knowing someone with stroke/dementia. Lastly, we performed hierarchal cluster analyses to characterize clusters of trust patterns and assessed their differences. Results: Our cohort consisted of 1,478 participants (52% females, median age 46 years [IQR:32-60], and 75% non-Hispanic Whites) with levels of trusts shown in Figure 1 . Following multivariable regression analyses, participants who highly trusted all HCPs were statistically more likely to perceive that maintaining and changing health habits can reduce the risks of stroke or dementia (adjusted odds ratios presented in Figure 2 ). Lastly, three clusters of trust patterns emerged: (i) those who highly trust most sources (n=781), (ii) those who only trust official health sources (n=540) and (iii) those who have low trust of all sources (n=103) ( Figure 3 ). Participants who have low trust of all sources (Cluster iii) were less likely to have a post-secondary degree (57% vs 67-71%, p=0.04) and to perceive that stroke (80% vs 93-94%, p<0.01) and dementia (65% vs 76-81%, P<0.01) risks are modifiable, compared to the other clusters. Conclusion: Our study identified highly trusted sources of health information, characterized trust patterns in a large U.S. cohort, and assessed their association with perceiving stroke/dementia risks as modifiable. This novel data could assist us in developing targeted interventions for risk reduction using trusted sources and mediums.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".