October 2016 VOL 7, NO 9

← Back to Issue

Category VII: Clinical Research

44. Decision-Making in Cancer Research

Barbara Biedrzycki, PhD, CRNP, AOCNP
Johns Hopkins 

Background: Cancer clinical research is essential to producing evidence-based clinical care that offers better treatment outcomes. Yet the recruiting and consenting process for cancer clinical trials can be challenging and lead to slow-accruing clinical research and dissatisfaction. Respect for autonomy and fear of unduly influencing the research participation decision may hinder our involvement with the decision-making process. A conceptual model of the research decision-making process would be helpful to identify the factors associated with research decision-making and to generate future research.

Objectives: Describe the factors associated with research decision-making. Define decision-making preferences. Discuss the Research Decision-Making Model.

Methods: Cross-sectional, descriptive research of mailed surveys to 197 patients with advanced gastrointestinal cancer who were invited to participate in a treatment-based cancer clinical trial. Prior to receiving the surveys, potential research participants were invited to participate by a mailed introductory letter along with an opt-out return postcard. If the postcard was not received in 2 weeks, the surveys and stamped return envelope were mailed. If surveys were not received within 2 weeks, a second mailing was sent with a return postcard that provided the options to decline research participation or request a second set of surveys and stamped envelope. Each mailing reminded participants of the voluntary nature of research and that the surveys do not need to be completed at one time. Research participants were sent a $20 gift card and hand-written thank you note on receipt of surveys. This study was IRB approved.

Results: Response rate was 46%, guided by the Dillman Method for survey research. Statistical analysis of age, gender, cancer diagnosis, and cancer stage indicated no statistical difference between survey responders and those 54% who did not respond. Through logistic regression analysis, all 13 variables of the Research Decision-Making Model (cancer stage, symptom burden, age, educational level, race, sex, hope, quality of life, trust in healthcare system, trust in healthcare professional, preference for research decision control, perceived risks and benefits, and adequacy of research information) together predicted cancer clinical trial participation (P = .032) and satisfaction with the research decision (P = .007). Individual predictors were age for clinical trial participation (P = .009); and hope (P = .019) and trust in the healthcare system (P = .003) for decision satisfaction. Most research participants (163/197; 83%) preferred shared (also known as collaborative) decision-making.

Conclusions: Research decision-making is a multifactorial process conceptualized and validated by the Research Decision-Making Model. Shared decision-making preference is an unrecognized factor for cancer clinical research decision-making. Patient and nurse navigators’ awareness of the many factors impacting the decision-making process and the patient’s decision-making preference may facilitate optimal navigation within clinical research. Interventional research is needed to determine the impact of decision-making support on clinical trial accrual, satisfaction, and quality of life, and to further test the Research Decision-Making Model.

Related Articles
Category II: Psychosocial Support, Seventh Annual AONN+ Conference Abstracts - September 23, 2016

7. Financial Navigation: Justification, Benefits, and Program Management

Objectives: Define financial toxicity in cancer patients; determine the value of financial navigators (FNs) to patients; evaluate costs/benefits of financial navigation to healthcare organizations; evaluate the utility of toolsets for [ Read More ]

Category III: Quality, Outcomes, and Performance Improvement, Seventh Annual AONN+ Conference Abstracts - September 23, 2016

13. Creating a Scorecard to Monitor Program Growth and Evaluate Navigation Metrics in a Multiple-Market Navigation Program

Objectives: The creation of a defined navigation model, clear navigation metrics, and proof of navigation return on investment (ROI) are essential for “continued development and success of oncology navigation programs.”1 [ Read More ]