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Informed Consent

Principal Investigator: Dr. Linda Pescatello
Co-Investigators: Dr. Yin Wu, Dr. Gregory Panza, and Shiqi Chen.

Title of Study: Evaluating the Feasibility and Preliminary Efficacy of an Evidence-Based Algorithm to Prescribe Exercise for Adults with Cardiovascular Disease Risk Factors

You are invited to participate in a research study. This form includes information about the study and contact information if you have any questions.

Purpose of Research

The Prioritize Personalize and Prescribe Exercise (P3-EX) algorithm, developed by Dr. Linda Pescatello at the University of Connecticut (UConn), is an evidence-based clinical decision support system clinicians can use to prescribe exercise to their patients. Using the P3-EX algorithm, you will be able to design individualized exercise prescriptions for your patients in 5 minutes or less without prior training. The purpose of this study is to obtain your impressions of the P3-EX algorithm for use when prescribing exercise to patients with cardiovascular disease (CVD) risk factors. The CVD risk factors include hypertension, dyslipidemia (high cholesterol), diabetes mellitus, and obesity. If you agree to participate, you will complete an evaluation survey to answer questions about your job, professional training, and your opinions of the P3-EX algorithm after using it with a case study that we will provide. We will use the feedback we receive to further improve how the P3-EX algorithm will work.

Duration of Participation and Procedures

This evaluation survey is entirely online and will take you 15-20 minutes to complete. You will first visit a UConn website (which is where you are right now) and read instructions on how to complete the survey. Then you will use the P3-EX algorithm to design an individualized exercise prescription for a case study that we will provide you on the website. You will then complete the evaluation survey to provide your opinions about the P3-EX algorithm.

The survey will take you 10-15 minutes to complete. In the survey, you will answer questions in three different sections. In the first section, you will answer questions about your background and professional experience prescribing exercise to patients. In the second section, you will answer questions regarding your impression about the P3-EX algorithm regarding if it is easy to read and understand; easy to use without prior training and correct errors if/when they occur; time-efficient; acceptable to use at work to prescribe exercise to patients; and do you want to use it and will continue to use it. In the third section, you will answer questions regarding your additional impressions about the P3-EX algorithm such as if the functions of the P3-EX algorithm are unique; and if your patients will become healthier when the P3-EX algorithm exercise prescriptions are put into action by your patients. We ask that you complete the survey in one sitting because if you exit the survey before completing it, you will lose information that you have already entered. You can skip any questions you do not want to answer by leaving them blank. If you have not completed the survey in 7 days after you have received the invitation to participate, we will send you a reminder via email to complete it. After the first reminder, if you still have not completed the survey in 14 days after you received the invitation to participate, we will send you a second and last reminder via email. You will receive a $10 Amazon gift card after completing this study. The gift card will be sent to you via email.

Based on the evaluation survey results, we will integrate the feedback received from all respondents to improve the functionality of the P3-EX algorithm. We will then be performing a follow up evaluation survey on the improved P3-EX algorithm following the same steps as the first evaluation survey. For the follow up evaluation survey, we may be contacting you again to participate and collect your opinions on the improved P3-EX algorithm. If you decide to participate and complete the follow up evaluation survey, you will receive another $10 Amazon gift card.

Please check here at the bottom of this page to indicate if you wish to be contacted for the follow up evaluation survey. Please note that this question is only about if you are willing to be contacted again, it does not indicate if you are or are not willing to participate in the initial evaluation survey.

You should also know that the UConn Institutional Review Board (IRB) and the Office of Research Compliance may investigate study records, but these investigations will only focus on the researchers and not on your responses or involvement. The IRB is a group of professionals who review research studies to protect the rights and welfare of research participants like you.

Risks

We believe that the risks of your participation in this study are minimal.

Benefits

You may not benefit directly from this research. However, the benefits of your participation may impact society by increasing knowledge about the feasibility (do you like it, want it, will you continue to use it) and efficacy (does it help the users, does it improve the health of your patients) of the P3-EX algorithm. A potential benefit is knowing that you will have the opportunity to provide input about the P3-EX algorithm.

Confidentiality

Any data collected during this research study will be kept confidential by the researchers. Your identifying information (email) will be destroyed when the study has been completed. We will do our best to protect the confidentiality of the information we gather from you, but we cannot guarantee 100% confidentiality. Your confidentiality will be fully maintained to the degree that is permitted by the technology we used. Specifically, no guarantees can be made regarding the interception of data sent via the Internet by any third parties.

You do not have to be in this evaluation survey study if you do not want to. You do not have to answer any question that you do not want to answer for any reason. We will be happy to respond to any questions you have about this study.

If you have other questions about this project or if you have a research-related problem, you may email or call the Principal Investigator, Dr. Linda Pescatello, at Linda.Pescatello@uconn.edu or 860-486-0008. You may also email or call the graduate research assistant, Shiqi Chen, at shiqi.chen@uconn.edu or 860-771-8325.

If you have any questions about your rights as a research participant, you may contact the University of Connecticut IRB at 860-486-8802.