ArticleJMIR human factors2024
Lessons Learned From Developing Dashboards to Support Decision-Making for Community Opioid Response by Community Stakeholders: Mixed Methods and Multisite Study.
Article in JMIR human factors, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT04111939 (HEALing Communities Study), which is not on this map. Cited by 9 papers.
What it found
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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.
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.
HEALing Communities Study: Developing and Testing an Integrated Approach to Address the Opioid Crisis
Who cites it
9 citing papers in PubMed.
- Nursing Perceptions of the Intended Use of Artificial Intelligence to Prevent Medication Errors: A Qualitative Descriptive Study.Journal of clinical nursing · 2026Article
- Understanding Data Use in Community Coalitions: Insights from a CFIR 2.0-Informed Study of the Ohio HEALing Communities Initiative.Community mental health journal · 2026Article
- Customizing and fine-tuning opioid overdose machine learning models for community-specific dashboards.Journal of big data · 2026Article
- Barriers to Population Data Use in Overdose Fatality Reviews: Observational and Interview Study of Dashboard Deployment.JMIR human factors · 2026Observational
- Implementation Outcomes of Low Threshold Care for Persons with Opioid Use Disorders.Journal of general internal medicine · 2026Article
- Building Public Health Data Dashboards: Tutorial Playbook.JMIR public health and surveillance · 2026Article
- Designing a Substance Misuse Data Dashboard for Overdose Fatality Review Teams: User-Centered Design Approach.JMIR human factors · 2026Article
- The Practical, Robust Implementation and Sustainability (PRISM)-capabilities model for use of Artificial Intelligence in community-engaged implementation science research.Implementation science : IS · 2025Article
- Data Dashboard Acceptability, Use, and Perceived Effectiveness in Disseminating Local Overdose Data and Resources in a Rural New York State County: A Cross-Sectional Study.Online journal of public health informatics · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
19 authors.
Funding
Abstract
backgroundData dashboards are published tools that present visualizations; they are increasingly used to display data about behavioral health, social determinants of health, and chronic and infectious disease risks to inform or support public health endeavors. Dashboards can be an evidence-based approach used by communities to influence decision-making in health care for specific populations. Despite widespread use, evidence on how to best design and use dashboards in the public health realm is limited. There is also a notable dearth of studies that examine and document the complexity and heterogeneity of dashboards in community settings.
objectiveCommunity stakeholders engaged in the community response to the opioid overdose crisis could benefit from the use of data dashboards for decision-making. As part of the Communities That HEAL (CTH) intervention, community data dashboards were created for stakeholders to support decision-making. We assessed stakeholders' perceptions of the usability and use of the CTH dashboards for decision-making.
methodsWe conducted a mixed methods assessment between June and July 2021 on the use of CTH dashboards. We administered the System Usability Scale (SUS) and conducted semistructured group interviews with users in 33 communities across 4 states of the United States. The SUS comprises 10 five-point Likert-scale questions measuring usability, each scored from 0 to 4. The interview guides were informed by the technology adoption model (TAM) and focused on perceived usefulness, perceived ease of use, intention to use, and contextual factors.
resultsOverall, 62 users of the CTH dashboards completed the SUS and interviews. SUS scores (grand mean 73, SD 4.6) indicated that CTH dashboards were within the acceptable range for usability. From the qualitative interview data, we inductively created subthemes within the 4 dimensions of the TAM to contextualize stakeholders' perceptions of the dashboard's usefulness and ease of use, their intention to use, and contextual factors. These data also highlighted gaps in knowledge, design, and use, which could help focus efforts to improve the use and comprehension of dashboards by stakeholders.
conclusionsWe present a set of prioritized gaps identified by our national group and list a set of lessons learned for improved data dashboard design and use for community stakeholders. Findings from our novel application of both the SUS and TAM provide insights and highlight important gaps and lessons learned to inform the design of data dashboards for use by decision-making community stakeholders.
trial registrationClinicalTrials.gov NCT04111939; https://clinicaltrials.gov/study/NCT04111939.
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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 OpenQuestion graph.