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Accepted for/Published in: Journal of Medical Internet Research

Date Submitted: Apr 3, 2025
Date Accepted: Jan 30, 2026

The final, peer-reviewed published version of this preprint can be found here:

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

Lewis N, Reynolds J, Krause D, Reeves PM, Luster J, Stein MD, Walsh SL, Farmer A, Lofwall MR, Roberts MF, Surratt HL, Crockett BN, Stephens K, Bursey K, Mattson K, Slater MD

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

J Med Internet Res 2026;28:e75458

DOI: 10.2196/75458

PMID: 41921212

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

  • Nicky Lewis; 
  • Jennifer Reynolds; 
  • Diane Krause; 
  • Phillip M. Reeves; 
  • Jamie Luster; 
  • Michael D. Stein; 
  • Sharon L. Walsh; 
  • Amy Farmer; 
  • Michelle R. Lofwall; 
  • Monica F. Roberts; 
  • Hilary L. Surratt; 
  • Brooke N. Crockett; 
  • Kara Stephens; 
  • Kelli Bursey; 
  • Kristin Mattson; 
  • Michael D. Slater

ABSTRACT

Background:

Research on the effectiveness of online health communication campaigns is lacking. Two studies examined the platforms, tactics, and content of the campaigns employed in the HEALing (Helping to End Addiction Long-termⓇ) Communities Study (HCS) using paid media performance data.

Objective:

Two studies used click-through rate (CTR) and cost-per-click (CPC) as effectiveness outcomes of health communication campaigns. Two digital advertising methods (social media, banner/display) were compared. Performance differences by state, community type, message approach, format, and image type were assessed.

Methods:

Paid digital advertising strategies and message content factors of HCS campaigns were examined. In Study 1, we examined differences in CTR and CPC for two advertising methods (social media, banner/display) by state (KY, NY, OH) and community type (urban, rural). In Study 2, we examined differences in CTR for two advertising methods (social media, banner/display) by state (KY, MA, OH), community type (urban, rural), message approach (testimonial, information-based), format (motion graphic/GIF, video, static image), and image type (local, stock). Separate analyses were conducted for each advertising method.

Results:

Study 1

Results:

Social media (Mdn% = 0.54) had higher CTR when compared to banner/display (Mdn% = 0.13; p < .001). Social media had a statistically significant main effect for state (p < .001) but not community type (p = .67), where OH (Mdn% = 1.35) had the highest CTR. For display/banner, there were no statistically significant differences based on state or community type. Social media (Mdn = $1.61) had lower CPC when compared to banner/display (Mdn = $6.09; p < .001. Social media had a significant main effect for state (p = .002), where OH (Mdn = $1.08) had the lowest CPC. Banner/display had a significant main effect for state (p < .001) and community type (p = .008), where OH (Mdn = $11.30) and urban communities (Mdn = $6.94) had the highest CPC. Study 2

Results:

Social media (Mdn% = 0.3) had higher CTR when compared to banner/display (Mdn% = 0.08; p < .001). For social media, urban communities (Mdn% = 0.33), static format (Mdn% = 0.36), and local spokespersons (Mdn% = 0.31) had the highest CTR. There were significant pairwise differences between all pairs of states, where OH had the highest CTR (Mdn% = 1.26). For display/banner, static format (Mdn% = 0.09) and local spokespersons (Mdn% = 0.12) had the highest CTR. State and community type were not significant predictors.

Conclusions:

Results suggest that social media posts were more effective and efficient in stimulating responses to OUD messages than banner/display ads. State-to-state variation in these effects suggest the importance of pretests in any given region. Banner/display ads may be more useful for other outcomes, such as increasing awareness. Using local spokespersons versus stock spokespersons is recommended. Clinical Trial: This research was supported by the National Institutes of Health (NIH) and the Substance Abuse and Mental Health Services Administration (SAMHSA) through the NIH HEAL (Helping to End Addiction Long-termSM) Initiative under award numbers UM1DA049394, UM1DA049406, UM1DA049412, UM1DA049415, UM1DA049417 (ClinicalTrials.gov Identifier: NCT04111939). This study protocol (Pro00038088) was approved by Advarra Inc., the HEALing Communities Study single Institutional Review Board. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH, SAMHSA, or the NIH HEAL InitiativeSM.


 Citation

Please cite as:

Lewis N, Reynolds J, Krause D, Reeves PM, Luster J, Stein MD, Walsh SL, Farmer A, Lofwall MR, Roberts MF, Surratt HL, Crockett BN, Stephens K, Bursey K, Mattson K, Slater MD

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

J Med Internet Res 2026;28:e75458

DOI: 10.2196/75458

PMID: 41921212

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