iPICS is a multidimensional, scalable and innovative eHealth supportive intervention supplementing existing decision aid and survivorship programs. iPICS consists of three subsystems: iPICS-Inform, iPICS-Dialog, and iPICS-SNAP to provide the LPC patient population with reliable information, communication, and social support, respectively. iPICS has the potential to substantially enhance oncology care of patients with LPC by facilitating patient engagement in treatment decision-making and self-management across the survivorship continuum (diagnosis to post-treatment recovery) to reduce decision regrets and improve QOL.
Over 3.1 million men in the U.S., including over 200,000 veterans, have been diagnosed with prostate cancer. Existing programs for informing patients with localized prostate cancer about the impacts of various treatment options and assisting them during the recovery period are fragmented and limited. Most of the technology-based tools provide generic information that is not updated based on current scientific evidence, and lack personalization based on individuals’ needs and their literacy levels.
To fill these gaps in clinical practice and research, we propose a theory-based, integrated information and supportive care system, the interactive Prostate Cancer Information, Communication and Support program (iPICS), to provide tailored and personalized information about localized prostate cancer, treatment options, and their short- and long-term effects, before, during, and after treatment.
- Design and develop iPICS by adopting an iterative user-centered design approach that uses input from stakeholders (i.e., patients, caregivers, and providers) to inform content, design, functionality, and navigation schemes throughout the iPICS design and development process.
- Conduct pilot evaluation of iPICS and the study protocol using a mixed-methods design.
- Determine the feasibility and acceptability of the study protocol by analyzing enrollment, retention, data collection completion rates, and using activity tracking data to assess program interaction time and utilization.