Related Experiment Video
Updated: Sep 17, 2025

A Novel Method for Involving Women of Color at High Risk for Preterm Birth in Research Priority Setting
Published on: January 12, 2018
CASCADE: a community-engaged action model for generating rapid, patient-engaged decisions in clinical research
1Department of Psychological Sciences, Purdue University, 703 3rd Street, West Lafayette, IN, 47906, USA. bkelleher@purdue.edu.
Background:
Integrating patient and community input is essential to the relevance and impact of patient-focused research. However, specific techniques for generating patient and community-informed research decisions remain limited. This manuscript describes a novel CASCADE method (Community-Engaged Approach for Scientific Collaborations and Decisions) that was developed and implemented to make actionable, patient-centered research decisions during a federally funded clinical trial.
Methods:
The CASCADE method was developed to facilitate decision-making, combining techniques from a variety of past methodologies with new approaches that aligned with project constraints and goals. The final result was a series of procedures that spanned seven thematic pillars (1) identifying a shared, specific, and actionable goal; (2) centering community input; (3) integrating both pre-registered statistical analyses and exploratory "quests"; (4) fixed-pace scheduling, supported by technology; (5) minimizing opportunities for cognitive biases typical to group decision making; (6) centering diversity experiences and perspectives, including those of individual patients; (7) making decisions that are community-relevant, rigorous, and feasible. The final approach was piloted within an active clinical trial, with the primary goal of describing feasibility (participation, discussion topics, timing, quantity of outputs).
Results:
The inaugural CASCADE panel aimed to identify ways to improve an algorithm for matching patients to specific types of telehealth programs within an active, federally funded clinical trial. The panel was attended by 27 participants, including 5 community interest-holders. Data reviewed to generate hypotheses and make decisions included (1) pre-registered statistical analyses, (2) results of 12 "quests" that were launched during the panel to answer specific panelist questions via exploratory analyses or literature review, (3) qualitative and quantitative patient input, and (4) team member input, including by staff who represented the focal patient population for the clinical trial. CASCADE pillars were successfully integrated to generate 18 initial and 6 final hypotheses, which were translated to 19 decisional changes.
Conclusions:
The CASCADE approach was an effective tool for rapidly, efficiently making patient-centered decisions during an ongoing, federally funded clinical trial. Opportunities for further development will include exploring best-practice structural procedures, enhancing greater opportunities for pre-panel input by community interest-holders, and determining how to best standardize CASCADE outputs.
Trial Registration:
The CASCADE procedure was developed in the context of NCT05999448.
More Related Videos
06:28E-Patient Counseling Trial E-PACO: Computer Based Education versus Nurse Counseling for Patients to Prepare for Colonoscopy
Published on: August 1, 2019
07:31Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack
Published on: May 15, 2020
Related Concept Videos
Patient-centered Care
Ethical Dilemmas II
Methods of Documentation VI: Case Management Model
For example, a patient with a chronic...
Ethical Dilemmas I
Let us explore some examples to understand the potentially complex moral decisions nurses face.
Take the case of caring for minors, particularly in areas related to reproductive...
Nursing Ethical Principles II
Consider the following scenario, which illustrates how these principles are applied in the care of Mr. John, a fifty-year-old teacher diagnosed with metastatic liver cancer.
Initially, Mr. John's...
Ethics in Research