Evidence map›Paper›PMID 41921212›Full record

ArticleJournal of medical Internet research2026

Health Communication Campaign Performance During the HEALing Communities Study: Cross-Sectional Examination of Digital Advertising Methods.

Nicky Lewis, Jennifer Reynolds, Diane Krause, Philip M Reeves, Jamie Luster, Michael D Stein, Sharon L Walsh, Amy Farmer, Michelle R Lofwall, Monica F Roberts and 6 more

Abstract read
In one paragraph

Article in Journal of medical Internet research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

16 authors.

Nicky LewisIndiana University Bloomington, 601 E Kirkwood Avenue, Bloomington, IN, 47405, United States, 1 812 855 6106.ORCID http://orcid.org/0000-0003-1753-9101
Jennifer ReynoldsHealth and Resilience Strategies, Oak Ridge Associated Universities, Oak Ridge, TN, United States.ORCID http://orcid.org/0009-0002-6860-2238
Diane KrauseHealth and Resilience Strategies, Oak Ridge Associated Universities, Oak Ridge, TN, United States.ORCID http://orcid.org/0009-0008-5413-9397
Philip M ReevesHealth and Resilience Strategies, Oak Ridge Associated Universities, Oak Ridge, TN, United States.ORCID http://orcid.org/0000-0003-2684-604X
Jamie LusterThe Ohio State University College of Medicine, Columbus, OH, United States.ORCID http://orcid.org/0000-0002-8484-1215
Michael D SteinBoston University School of Public Health, Boston, MA, United States.ORCID http://orcid.org/0000-0002-2466-5192
Sharon L WalshUniversity of Kentucky, Lexington, KY, United States.ORCID http://orcid.org/0000-0002-9722-5681
Amy FarmerThe Ohio State University College of Medicine, Columbus, OH, United States.ORCID http://orcid.org/0009-0007-4154-9664
Michelle R LofwallUniversity of Kentucky, Lexington, KY, United States.ORCID http://orcid.org/0000-0002-5911-0752
Monica F RobertsUniversity of Kentucky, Lexington, KY, United States.ORCID http://orcid.org/0009-0006-3462-0920
Hilary L SurrattUniversity of Kentucky, Lexington, KY, United States.ORCID http://orcid.org/0000-0003-4027-7840
Brooke N CrockettThe Ohio State University College of Medicine, Columbus, OH, United States.
Kara StephensHealth and Resilience Strategies, Oak Ridge Associated Universities, Oak Ridge, TN, United States.ORCID http://orcid.org/0009-0005-9359-4868
Kelli BurseyHealth and Resilience Strategies, Oak Ridge Associated Universities, Oak Ridge, TN, United States.ORCID http://orcid.org/0009-0009-8901-1454
Kristin MattsonHealth and Resilience Strategies, Oak Ridge Associated Universities, Oak Ridge, TN, United States.ORCID http://orcid.org/0009-0003-9347-7683
Michael D SlaterThe Ohio State University College of Medicine, Columbus, OH, United States.ORCID http://orcid.org/0000-0003-4279-346X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Research on the effectiveness of digital health campaign strategies is lacking. Understanding performance outcomes is essential for the successful implementation of campaigns. Two studies examined platforms, tactics, and content of digital health campaigns using paid media performance data. Objective: This analysis compared 2 digital advertising methods (social media and banner or display) using click-through rate (CTR) and cost-per-click (CPC) as performance measures. Performance differences by state, community type, message approach, format, and image type were assessed. CTR and CPC served as measures in determining performance differences between social media and banner or display. Methods: This cross-sectional secondary analysis examined campaign performance for the HEALing (Helping to End Addiction Long-Term) Communities Study, which served 85,875,105 impressions. Data were collected from media buy reports, entered into templates that included method (display or banner and social media) and key performance indicators (impressions, clicks, and media spend), and CTR and CPC were calculated. Study 1 assessed differences in CTR and CPC for social media and banner or display by state (KY, NY, MA, and OH) and community type (urban and rural). Study 2 assessed differences in CTR for social media and banner or display by state (KY, NY, MA, and OH), community type (urban and rural), message approach (testimonial and information-based), format (motion graphic or graphics interchange format, video, and static image), and image type (local and stock). Separate analyses were conducted for each advertising method. Results: Study 1 found significant differences between advertising methods, where social media had higher CTR compared to banner or display. Social media had a significant main effect for state, where OH had the highest CTR. There was a statistically significant difference in CPC based on advertising method, where social media had a lower CPC compared to banner or display. Social media had a significant main effect for state, where OH had the lowest CPC. Banner or display had a significant main effect for state and community type, where OH and urban communities had the highest CPC. Study 2 found significant differences between advertising methods, where social media had higher CTR than banner or display. For social media, urban communities, static format, and local spokespersons had the highest CTR. There were significant differences between all pairs of states, where OH had the highest CTR. For display or banner, static format and local spokespersons had the highest CTR. Conclusions: This analysis provides guidance for digital health campaigns. It examined the performance of opioid use disorder campaigns using CTR and CPC measures, demonstrating utility in future campaign evaluations. Social media was more related to stimulating responses to campaign messages compared to banner or display. State-to-state variations emphasized the importance of message pilot testing. Using local spokespersons versus stock spokespersons is recommended.

Indexed as

AdvertisingHealth CommunicationHealth PromotionCross-Sectional StudiesDigital MediaHumansMedia ExposureSocial Mediabuprenorphine evidence-based practicecommunicationsmethadonenaloxoneopiate overdosesocial stigma

Identifiers

PMID41921212
PMCPMC13043076

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.