Self-Monitoring Platform for Cancer Medication Safety
This study is testing an online platform to help people with lung, colorectal, breast, or prostate cancer track their medications and any concerns they have. Many people taking cancer medicines at home face challenges with complex schedules and side effects. This platform aims to help you become a "vigilant partner" in managing your medications and reporting any issues to your care team. We want to see how easy the platform is to use and how helpful you find it over six months. To join, you need to be an adult (18+) with one of these cancers, currently receiving active treatment, managing your own cancer medications, and have access to a smartphone, tablet, or computer. The study is looking for 80 participants, but its current status is unclear.
- Study design
- This study is an interventional study, meaning participants will receive an intervention. It plans to enroll 80 participants.
- What's involved
- You would use an online self-monitoring platform to track your medication experiences and concerns. You will also receive educational materials and follow-up contact.
- Compensation
- Not stated in the trial record.
- Follow-up
- You will be followed for up to 6 months to assess the platform's usability and usefulness.
AI-generated from the public study record. Only the study team can confirm whether you're eligible — confirm details with them before making decisions.
A Self-Monitoring Platform for Tracking Medication Safety and Concerns in Cancer Patients
At a glance
Conditions
Where it's being run
1 sites across 1 statesStudy leadership
- Yun Jiang · PRINCIPAL_INVESTIGATOR · University of Michigan Rogel Cancer Center
- Yang Gong · PRINCIPAL_INVESTIGATOR · UTHealth Houston McWilliam School of Biomedical Informatics
Who to contact
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Do you actually qualify for this trial?
Add a private profile and we'll compare every criterion below against your situation — and tell you which ones are met, uncertain, or excluding.
Inclusion
Exclusion
What this trial measures
- Self-reported system usabilityUp to 6 months
Self-reported system usability will be assessed using the 10-item System Usability Scale. Will use descriptive statistics, such as mean and standard deviation for continuous variables, and frequency and percentage for categorical variables.
- Perceived usefulnessUp to 6 months
Qualitative data, including brief interview data will be analyzed and summarized through content analysis.
- Ease of useUp to 6 months
Qualitative data, including brief interview data will be analyzed and summarized through content analysis.
- Attitudes toward useUp to 6 months
Qualitative data, including brief interview data will be analyzed and summarized through content analysis.
- Intention to use and continuous use of the system over timeUp to 12 months
Qualitative data, including brief interview data will be analyzed and summarized through content analysis.
- Self-reported patient engagementUp to 6 months
Self-reported patient engagement will be measured by the 9-item Twente Engagement with Ehealth Technologies Scale (TWEETS), including three dimensions, behavioral engagement, cognitive engagement, and affective engagement. Will use the overall TWEETS score to evaluate patient engagement in this study, rather than analyzing each dimension separately. Will use descriptive statistics, such as mean and standard deviation for continuous variables, and frequency and percentage for categorical variables. Will use repeated measures analysis of variance to assess the changes in mean scores of patient engagement. Univariate associations between baseline personal and clinical factors and patient engagement at each time point will be assessed using correlation analyses (Pearson or Spearman), Chi-square tests, or non-parametric Mann-Whitney U tests, depending on the variable types. Multiple linear regressions will be conducted to assess associations between patient engagement and outcomes.
- System usage over timeUp to 12 months
Will be objectively recorded by the system logs and analyzed using Google Analytics (dashboard only), including parameters like the number of logins, number of tab pages clicked, number of events or concerns self-tracked, and more. Will use descriptive statistics, such as mean and standard deviation for continuous variables, and frequency and percentage for categorical variables.
- Patient activation levelsUp to 6 months
Patient activation levels will be measured by the Short Form of Patient Activation Measure. Will use descriptive statistics, such as mean and standard deviation for continuous variables, and frequency and percentage for categorical variables.
- Medication self-management abilityUp to 6 months
Medication self-management ability will be measured by the Measure of Medication Self-Management. Will use descriptive statistics, such as mean and standard deviation for continuous variables, and frequency and percentage for categorical variables.
- Symptom distressUp to 6 months
Symptom distress will be measured by the 19-item MD Anderson Symptom Inventory. Will use descriptive statistics, such as mean and standard deviation for continuous variables, and frequency and percentage for categorical variables.
- Health related quality of lifeUp to 6 months
Health-related quality of life will be measured by the 27-item Functional Assessment of Cancer Therapy - General. Will use descriptive statistics, such as mean and standard deviation for continuous variables, and frequency and percentage for categorical variables.
- Number of emergency room visitsUp to 12 months
Will be measured by both self-report and chart review. Will use descriptive statistics, such as mean and standard deviation for continuous variables, and frequency and percentage for categorical variables.
- Number of hospitalizationsUp to 12 months
Will be measured by both self-report and chart review. Will use descriptive statistics, such as mean and standard deviation for continuous variables, and frequency and percentage for categorical variables.
- User experiences with the systemUp to 6 months
Participants' user experiences with the system, such as perceived facilitators or barrios to system use, along with their suggestions for system improvement, will be collected through a brief individual interview. Qualitative data, including brief interview data will be analyzed and summarized through content analysis.