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Health Care Opinion Research 1
Initial registration date
July 18, 2020
August 27, 2020 1:53 PM EDT
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Other Primary Investigator(s)
Additional Trial Information
The objective of this experiment is to investigate whether vignettes/stories about people suffering because of the Covid-19 pandemic can evoke (1) emotional reactions and (2) increase support for health polices to increase insurance coverage.
The objective of this experiment is to investigate whether vignettes/stories about people suffering because of the Covid-19 pandemic can evoke (1) emotional reactions and (2) increase support for health polices to increase insurance coverage. Four stories will be investigated. Two emphasize the suffering of other people who do not have adequate health coverage. Two emphasize the risk to self if others people are not covered.
Intervention Start Date
Intervention End Date
Primary Outcomes (end points)
All participants will fill out the Emotional Response Scale (e.g., Batson, et al., 1988, 1989, 1991, 1997, 2007). This scale includes a six-item measure of Empathic State.
The Emotional Response Scale also includes a 12-item measure of Distress and Negative State.
Health policy outcome
Ten items mostly drawn from Kaiser Family Foundation Health Tracking Polls [5, 6] that measure participant’s opinions about increasing health care coverage.
Primary Outcomes (explanation)
The Emotional Response Scale has been used in numerous experiments by Batson and colleagues to measure Empathic State and Distress-Negative State after providing participants with an emotionally evocative story. The scale is made up of 18 emotions (examples: sympathetic, compassionate, alarmed, sad). A participant self-rates (on a scale from 1 to 7) how much they experienced each emotion after reading the story.
The health policy outcome are eight items drawn directly from , one KFF item modified by us, and one item created by us. Examples:
a. “Do you favor or oppose having a national health plan, sometimes called Medicare-for-all, in which all Americans would get their insurance from a single government plan?”
b. “Please tell me if you have a positive or negative reaction to each term: National Health plan.”
c. “Generally speaking, do you favor or oppose the federal government doing more to help provide health insurance for more Americans?”
Response options are: strongly (favor/positive), somewhat (favor/positive), somewhat (oppose/negative), strongly (oppose/negative). The “don’t know” response forms the middle category.
Secondary Outcomes (end points)
Principle of Care State
These is an eight-item scale intended to measure a state of thinking about moral principles to help other people. It parallels Bekkers and Ottoni-Wilhelm’s (2016) dispositional measure, and was created by Verkaik, Bekkers, and Ottoni-Wilhelm (2015).
Secondary Outcomes (explanation)
Principle of Care State
The conditions are not intended to increase thinking about moral principles to help other people, but the conditions may unintentionally do this. The PoC State scale is included to check this.
The experimental design is between-subjects, 5 x 1.
The participants will be Amazon Mechanical Turk workers invited to complete a “Human Intelligence Task” (HIT) called “Evaluating Messages”. The inclusion criteria are: (1) U.S. citizen, (2) 18 years or older, (3) done at least one previous HIT, and (4) have completed 95% or more of their previous HITs.
Approximately one-fifth of the participants will be randomly assigned to each of the five conditions: Control, Suffering of Others 1, 2 and Risk to Self 1, 2. After reading the stories participants fill out the Emotional Response Scale, the Principle of Care state measurement, the health policy questions (the Attention-Check question is in the middle of the health policy questions), demographics, the Manipulation-Check question, and the political identity question.
Experimental Design Details
The randomization is by computer.
Individual (at the level of the individual MTurk worker).
Was the treatment clustered?
Sample size: planned number of clusters
Sample size: planned number of observations
N = 525 MTurk workers (approximately).
N = 105 per condition (approximately) is sufficient to detect a change of one-third of a standard deviation in the health policy scale and the Empathic State and Distress-Negative State scales. See “Power calculation” below.
Sample size (or number of clusters) by treatment arms
N = 105 (approximately) in each of the five conditions.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Based on previous measurements from an MTurk sample of the standard deviation of our (sES = 1.65), we are powered at 80% to detect a difference between conditions of 1/3 sES. We are also 80% powered to detect a 1/3 sDNS difference in Distress-Negative State.
Based on a previous KFF Health Tracking Poll [5} we are powered at 80% to detect a difference between conditions of 1/3 of a standard deviation in the health policy outcome variable.
Supporting Documents and Materials
We designed two additional conditions and a second "control" group. Details are in "chp01-Pre-reg-001B-v01a-AEA RCT Registry-PreTest01-MTurk-Modification01.pdf"
August 27, 2020
INSTITUTIONAL REVIEW BOARDS (IRBs)
Indiana University Institutional Review Board
IRB Approval Date
IRB Approval Number