This clinical trial compares the impact of the Smart Symptom Tracking ALEX application (app) to standard symptom-tracking practices in tracking and monitoring gastrointestinal (GI) symptoms in young adults. Rates of early-onset colorectal cancer are rising sharply and it is projected to become the leading cause of cancer-related death in young adults. Despite this, adults under 45 still face barriers to diagnosis, including access to screening, unclear guidance on the impact of GI symptoms and dismissal of symptoms by healthcare providers. Current screening guidelines lack guidance on monitoring early symptoms in younger adults. The Smart Symptom Tracking ALEX tool is a digital platform that uses artificial intelligence to provide prompts for symptoms, coaching, reminders and education. Standard of care clinical practices include paper-based logs to report symptoms. Using the Smart Symptom Tracking ALEX app may provide more detailed symptom reports and increase self-reported symptom communication compared to standard symptom-tracking practices in young adults concerned about their GI health.
Ages 18-44 years
Concerned about their GI health
Able to speak and read English
Willing to complete a four-week symptom tracking protocol
Unable to understand the informed consent or comply with protocol requirements
Parallel
Artificial Intelligence-based Intervention
Other interventionEngage with the Smart Symptom Tracking ALEX app
Best Practice
Other interventionComplete paper logs
Communication Intervention
Other interventionReceive reminders
Questionnaire Administration
Other interventionAncillary studies
Change in gastrointestinal self-advocacy
Will use a 4-items self-report "How confident are you in..." scale and chart-verified data to assess baseline and post-intervention self-advocacy. Questions are answered on a 5-point scale where 1=not at all confident and 5=extremely confident. Higher scores indicate greater self-advocacy confidence. Will compare mean change between arms using analysis of covariance (ANCOVA) or linear regression adjusting for baseline scores. Will estimate effect sizes (Cohen's d) and 95% confidence intervals. Sensitivity analysis will use mixed-effects models for repeated measures.
Symptom-tracking frequency
Will be defined as the number of entries logged (ALEX application or pencil-paper logs).
Symptom-report detail and quality
Will be assessed by qualitative review of report detail (e.g., presence of descriptors, specificity, and red-flag indicators). Will be reported using descriptive summaries of coding categories.
Communication readiness and symptom-disclosure confidence
Will be measured by 4 self-report questions answered on a Likert-type scale where 1=not at all confident, 2=slightly confident, 3=moderately confident, 4=somewhat confident, and 5=extremely confident. Higher scores indicate greater confident in readiness to communication symptoms with confidence.
Intervention acceptability and usability (ALEX arm only)
Will be measured using the 2-question System Usability Scale (answered on a scale of 1-5 where 1=strongly disagree and 5=strongly agree) or other study-specific acceptability measures. Will be reported using descriptive statistics of acceptability and usability scores.
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