SRFP080: Presenting Information to Promote Vaccines

Shyam Bhatt, MPH, MD Candidate; John Epling, MD, MSEd; Cara Spivey, MS

Abstract

Context: Framing effect and agency attribution are cognitive biases that influence patient decision making. Framing effect describes a tendency for people to alter their decision-making based on whether information is presented as gain or loss. Patients’ understanding of how much agency they have over becoming ill may also play a role in health decisions. These effects were studied in a clinical setting regarding patients’ choices to receive the influenza vaccination.

Objective: To test the impact of framing effect and agency attribution on patients’ intention to vaccinate.

Study Design: A randomized 2x2 factorial design with four experimental groups, each with a unique combination of framing and agency variables. Messaging about vaccine efficacy was presented as a gain- or loss-frame, and agency was attributed to either the patient or the virus.

Setting: Two large outpatient family medicine clinics serving urban, suburban, and rural populations.

Population Studied: All adult patients who were eligible to receive a flu vaccine during the 2020 flu season. Clinic staff were instructed to exclude pediatric patients and patients unable to consent for themselves.

Intervention: Four handouts that were identical in every way except for framing and agency variables were randomized and given to the patient. Patients indicated their decision to vaccinate on the handout, and providers had a chance to counsel the patients, if necessary, after form collection. Post-intervention chart review was conducted after four months, and data including sex, age, race, insurance, prior vaccination, and vaccine uptake during the remainder of the season was recorded.

Outcome Measures: The primary outcome measured is intention to vaccinate across all four experimental groups. Secondary outcome measures included demographic effects on intention to vaccinate and any moderation of framing effect and agency attribution.

Anticipated Results: The combination of gain-framing and human agency attribution should result in the highest intent-to-vaccinate rates, and the combination of loss-framing and viral agency should result in the lowest intent-to-vaccinate rates.

Conclusion: Gain-framed messages with agency attributed to patients should nudge patients to receive vaccinations, with differing effect sizes for various demographic groups.
Leave a Comment
John Epling
jwepling@carilionclinic.org 11/20/2021

Great work on this project, Shyam!

Shyam Bhatt
11/20/2021

Thank you Dr. Epling!

Jack Westfall
jwestfall@aafp.org 11/21/2021

Very interesting research. Great work. Thanks for sharing at NAPCRG

Shyam Bhatt
11/23/2021

Thank you for having me!

Diane Harper
harperdi@med.umich.edu 11/22/2021

I am VERY interested in seeing this next year. Present your results in Phoenix next year! Thank you for sharing your work with NAPCRG!

Shyam Bhatt
11/23/2021

I would love to! Thank you for having me!

William R. Phillips
wphllps@uw.edu 11/23/2021

Thanks for this attractive and effective poster describing a great study on a critical current problem. Create use of theory driven design for a practical clinical intervention. Good luck with recruiting, meeting your necessary N. I wonder if you will run into a problem with "refusal to be randomized" - which would seem highly associated with "refusal to get immunized" - that might interfere with recruitment and bias the results. Great work. Good luck. Thanks for sharing your work here at NAPCRG. - Bill Phillips

Shyam Bhatt
11/23/2021

Thank you for your kind words Dr. Phillips! Luckily, we have already finished data collection, and have a final n=307, which was within our target range. As for "refusal to be randomized" this wasn't an issue we faced as consent was given by completion of the handout (there was a disclaimer at the top of the page). I appreciate the comments!

Andy Pasternak
avpiv711@sbcglobal.net 11/28/2021

As someone who has been doing a lot of vaccine education, I'm going to be interested to hear your findings. I like the approach you are taking

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