# Trust in community as a predictor of public health measure adherence: Insights from a national Canadian survey

**Authors:** Neil Seeman, Justin Trent, Kumar Murty

PMC · DOI: 10.14745/ccdr.v51i101112a05 · Canada Communicable Disease Report · 2025-12-12

## TL;DR

This study shows that trust in the community strongly predicts adherence to public health measures, based on a survey of over 3,000 Canadians.

## Contribution

The study introduces trust as a key behavioral predictor for public health adherence, emphasizing community-level trust.

## Key findings

- Trust in community is a strong predictor of adherence to public health measures.
- Community-level adherence predicts future adherence to guidelines.
- Demographic factors like gender and education correlate with adherence behaviors.

## Abstract

Public health models often lack comprehensive behavioural data, leading to inaccurate predictions about the spread of disease and insufficient information about how to effectively build and sustain adherence to changing public health protocols.

The current study addresses this lack of comprehensive behavioural data by examining the role of trust as a predictor of adherence to public health measures.

Data were collected from an online Web intercept survey of 3,021 randomly engaged Canadians aged 16 years and older, analyzing factors such as gender, education and sources of COVID-19 information in relation to adherence to public health guidelines.

Trust, respecting someone’s expertise sufficiently to be willing to accept their counsel, emerged as a potent predictor of adherence to public health measures, highlighting the significance of trust in shaping community engagement; further, community-level adherence was found to predict anticipated future adherence.

This study emphasizes the critical role of trust, especially at the community level, in the success of public health measures, and proposes integrating trust measurement into public health models of compliance and resistance.

## Full-text entities

- **Diseases:** COVID-19 (MESH:D000086382)

## Full text

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## References

11 references — full list in the complete paper: https://tomesphere.com/paper/PMC12798833/full.md

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Source: https://tomesphere.com/paper/PMC12798833