Assessing the Impact of a Social Marketing Campaign on Program Outcomes for Users of an Internet-Based Testing Service for Sexually Transmitted and Blood-Borne Infections: Observational Study
Bibliographic record
Abstract
BACKGROUND: While social marketing (SM) campaigns can be effective in increasing testing for sexually transmitted and blood-borne infections (STBBIs), they are seldom rigorously evaluated and often rely on process measures (eg, Web-based ad click-throughs). With Web-based campaigns for internet-based health services, there is a potential to connect campaign process measures to program outcomes, permitting the assessment of venue-specific yield based on health outcomes (eg, click-throughs per test). OBJECTIVE: This study aims to evaluate the impact of an SM campaign by the promotional venue on use and diagnostic test results of the internet-based STBBI testing service GetCheckedOnline.com (GCO). METHODS: Through GCO, clients create an account using an access code, complete a risk assessment, print a lab form, submit specimens at a lab, and get results online or by phone. From April to August 2015, a campaign promoted GCO to gay, bisexual, and other men who have sex with men in Vancouver, Canada. The campaign highlighted GCO's convenience in 3 types of promotional venues-location advertisements in print or video displayed in gay venues or events, ads on a queer news website, and ads on geosocial websites and apps. Where feasible, individuals were tracked from campaign exposures to account creation and testing using venue-specific GCO access codes. In addition, Web-based ads were linked to alternate versions of the campaign website, which used URLs with embedded access codes to connect ad exposure to account creation. Furthermore, we examined the number of individuals creating GCO accounts, number tested, and cost per account created and test for each venue type. RESULTS: Over 6 months, 177 people created a GCO account because of the campaign, where 22.0% (39/177) of these completed testing; the overall cost was Can $118 per account created and Can $533 per test. Ads on geosocial websites and apps accounted for 46.9% (83/177) of all accounts; ads on the news website had the lowest testing rate and highest cost per test. We observed variation between different geosocial websites and apps with some ads having high click-through rates yet low GCO account creation rates, and vice versa. CONCLUSIONS: Developing mechanisms to track individuals from Web-based exposure to SM campaigns to outcomes of internet-based health services permits greater evaluation of the yield and cost-effectiveness of different promotional efforts. Web-based ads with high click-through rates may not have a high conversion to service use, the ultimate outcome of SM campaigns.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".