Report · Health

Admitting past mistakes would build trust in public health

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About a third of Americans (35%) say the public health field could best build greater trust by publicly acknowledging its past missteps and changing practices based on what it learns, according to a November 2025 Verasight survey.

Another 23% point to building community partnerships that emphasize learning, and 15% say they don't know. Smaller shares name training in transparent and empathetic communication (13%), changing organizational incentives to reward transparency (8%), and leadership modeling openness and self-reflection (7%).

Topline

single choice

Topline distribution

Admitting past mistakes would build trust in public health.

What would most help the public health field build greater trust?

  • Publicly acknowledge and change practices based on learnings from past missteps 34.7%
  • Building community partnership that emphasize learning 22.7%
  • I don't know 15.3%
  • Training in transparent and empathetic communication 12.9%
  • Changing organizational incentives to reward transparency 7.6%
  • Leadership modeling openness and self-reflection 6.7%

2025 · base n 1,000 · +/- 3.2%

Module 2

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Methodology

Full methodology
Mode
Verasight panel recruited via random address-based sampling, random person-to-person text messaging, and dynamic online targeting
Field dates
2025-11-14 → 2025-11-20
Base (unweighted)
1,000
Margin of error
+/- 3.2%
Module
Module 2

Source

Citation

Verasight APHA Omnibus Survey #2025-148, fielded November 14-20, 2025, N=1,000 US adults age 18+, +/- 3.2%.

https://reports.verasight.io/r/verasight-apha-2025

Verasight survey methodology

How Verasight conducts surveys.

This page describes the Verasight general survey contract, separate from how the Data Library packages it. When a wave report is published, its field dates, sample sizes, and module breakdown are listed in that report.

Mode
Verasight panel recruited via random address-based sampling, random person-to-person text messaging, and dynamic online targeting.
Population
US adults age 18+.
Sample design
Surveys are run as omnibus or single-topic waves. Omnibus waves are split into modules with their own respondent set, typically around one thousand respondents per module.
Field window
Each wave specifies its own field dates. Most omnibus waves field across roughly two weeks.
Weighting
Per-module weighting to CPS targets including age, race and ethnicity, sex, income, education, region, and metropolitan status.
Partisanship benchmark
Pew Research Center's NPORS benchmarking surveys, three-year running average.
Vote benchmark
2024 presidential vote population benchmarks.
Margin of error
Typically about plus or minus 3.4 to 3.6 percent per module at standard module sizes. Question-level MoE is recomputed when a base shrinks materially below the module baseline.
Reporting
The canonical report hub is reports.verasight.io. Verified legacy reports remain on their original hosts, and unpublished reports are marked pending.
Transparency
Verasight is a member of the American Association for Public Opinion Research Transparency Initiative.

The canonical report hub is reports.verasight.io; older reports may remain on verified legacy hosts.