A Digital Patient Decision Aid to Increase Sexually Transmitted Infection Testing in the Emergency Department: Protocol for a Pilot Randomized Controlled Trial of the STIckER (STI Check in the Emergency Room) Study
Bibliographic record
Abstract
Background: Rising rates of sexually transmitted infections (STIs) among adolescents and young adults are concerning. Emergency department (ED) visits offer a unique opportunity to increase STI testing. However, providers in the ED may not have the time or self-efficacy to screen patients, and patients may be unable to initiate discussion on their STI care needs. A patient decision aid may improve the effectiveness and efficiency of the ED encounter for STI testing. Objective: This study aims to pilot STI Check in the Emergency Room (STIckER) app, a shared decision-making aid for urinary, oral, and rectal gonorrhea and chlamydia testing among adolescents and young adults, and assess STIckER's efficacy and implementation outcomes in an adult and pediatric ED. Methods: We are conducting a parallel-group, two-arm provider-randomized controlled pilot trial in the adult and pediatric EDs at an urban academic medical center. Fifty providers were randomized 1:1 to intervention (trained on STIckER) or control (standard of care). Adolescents and young adults aged 14-24 years, English-speaking, and sexually active within the past 6 months are recruited during eligible shifts and assigned to the study arm of their provider. The standard of care comparator consists of usual provider-initiated STI discussions and testing without access to the decision aid; control participants receive a QR code directing them to a simple landing page encouraging them to ask their provider about STI testing. The planned enrollment target was 44 providers and 140 adolescent and young adult participants. Primary outcome is preliminary efficacy, defined as the proportion of adolescents and young adults receiving gonorrhea and chlamydia testing based on electronic medical record (EMR) review. Secondary outcomes include extragenital testing uptake, STI positivity rates, decisional conflict, and perceived level of shared decision-making. Implementation outcomes include feasibility, acceptability, appropriateness (using acceptability of intervention measure, intervention appropriateness measure, and feasibility of intervention measure), and provider self-efficacy. Data will be analyzed using descriptive statistics and regression models, with mixed-effects models applied if clustering by provider is detected. Exploratory analyses will examine differences by patient age, gender, and sexual identity, and provider characteristics. Results: Between September 2023 and July 2025, we completed recruitment of 44 providers and 139 adolescent and young adult participants across both adult and pediatric EDs. Enrollment targets were met, with high fidelity to intervention delivery and strong rates of survey completion by both patients and providers. Final data cleaning and analyses are underway, and primary results are expected to be available in late 2025. Conclusions: This pilot trial will provide critical data on the feasibility, acceptability, and preliminary efficacy of a digital SDM tool to increase STI testing in the ED. Findings will inform the design of a future multisite trial and the potential for scaling STIckER to support equitable, patient-centered STI screening across diverse clinical settings.
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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 | 0.022 | 0.019 |
| Meta-epidemiology (narrow) | 0.005 | 0.003 |
| Meta-epidemiology (broad) | 0.009 | 0.004 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.006 | 0.008 |
| Insufficient payload (model declined to judge) | 0.069 | 0.009 |
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".