Evidence mapPaperPMID 41915903Full record

ArticleOnline journal of public health informatics2026

Persona Development in Washington State: Mixed Methods Approach Using Statewide Survey Data.

Jordan M Garcia, Rebecca A Hills, Debra Revere, Jaewon Lim, Adam S Elder, Chris Baumgartner, Bryant T Karras, Janet G Baseman

Abstract read
In one paragraph

Article in Online journal of public health informatics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Jordan M GarciaSchool of Social Work, University of Washington, Seattle, WA, United States.ORCID https://orcid.org/0009-0001-8083-3947
Rebecca A HillsDepartment of Epidemiology, School of Public Health, University of Washington, Seattle, WA, United States.ORCID https://orcid.org/0000-0002-4305-5373
Debra RevereDepartment of Health Systems & Population Health, School of Public Health, University of Washington, Seattle, WA, United States.ORCID https://orcid.org/0000-0002-3863-7774
Jaewon LimDepartment of Biostatistics, School of Public Health, University of Washington, Seattle, WA, United States.ORCID https://orcid.org/0000-0002-4677-3805
Adam S ElderDepartment of Epidemiology, School of Public Health, University of Washington, Seattle, WA, United States.ORCID https://orcid.org/0000-0003-1665-2639
Chris BaumgartnerWashington State Department of Health, Tumwater, WA, United States.ORCID https://orcid.org/0009-0000-7807-2467
Bryant T KarrasWashington State Department of Health, Tumwater, WA, United States.ORCID https://orcid.org/0000-0001-5452-9362
Janet G BasemanDepartment of Epidemiology, School of Public Health, University of Washington, Seattle, WA, United States.ORCID https://orcid.org/0000-0002-1974-8196

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPersonas, fictional profiles representing user segments, play an important role in human-centered design, ensuring tools are tailored to the needs of users. Although public health organizations often develop information systems to promote population health, human-centered design methods and personas are generally underused in public health informatics projects.

objectiveThis study aims to present a novel, mixed methods approach to developing data-driven personas for use in public health information system design, leveraging 2 statewide surveys conducted in Washington State. The aim is to produce realistic, representative, and actionable personas that reflect the diversity of a state population and support user-centered design in public health initiatives.

methodsQuantitative (cluster analysis) and qualitative (thematic review and quote extraction) methods were applied to 2 statewide survey datasets: (1) a statewide knowledge, attitudes, and practices survey (N=1103) which used random, address-based sampling, and (2) a subset of the knowledge, attitudes, and practices respondents (N=143), which included more targeted questions on opinions and preferences related to public health information systems. Characteristics examined included demographics, technological readiness, opinions about public health policies, and experience using online health tools.

resultsK-prototype clustering resulted in 5 clusters. These 5 clusters were studied using both quantitative and qualitative analysis of key factors of the Washington State population to build 13 personas. Each persona represents a different population demographic, varying levels of technological readiness and attitudes toward public health policies, and differing experiences with online health tools. Persona descriptions are further elucidated with a short profile and 2-3 quotes.

conclusionsThis study offers a scalable and adaptable framework for persona development in public health, demonstrating how existing datasets can be transformed into effective design tools. Through a mixed methods approach, personas that reflect the diverse needs, preferences, and behaviors of Washington State residents were created. These personas can enhance the design, development, and evaluation of public health information systems by centering on user experience. Persona development and the methods described here can be used in future public health informatics projects to assist in formative research, guide design and development, inform usability testing, and shape communication strategies. By bridging the gap between large-scale data and user-centered design, this approach provides a practical model for making public health technologies more aligned with community needs.

Indexed as

cluster analysisinformation system designpersonaspublic health informaticsqualitative datauser-centered design

Identifiers

PMID41915903
PMCPMC13080291

What Socratic holds

Textmetadata
LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.