Background Influenza vaccine uptake remains low worldwide, inflicting substantial costs to public health. Messages promoting social welfare have been shown to increase vaccination intentions, and it has been recommended that health professionals communicate the socially beneficial aspects of vaccination. We provide the first test whether this prosocial vaccination hypothesis applies to actual vaccination behaviour of high-risk patients. Methods In a field experiment at a tertiary care public hospital in Istanbul, Turkey, we compare the effects of two motivational messages for promoting vaccination. Using a between-subjects single-blind experimental design patients were randomly assigned to frames emphasizing the vaccine’s benefits to self (n = 125) or social benefits (n = 119). Free influenza vaccination was offered to each patient. Results Among 222 patients who were not vaccinated for the season prior to the study (72% medically assessed to be at high risk), 42% in the self-benefit frame chose to receive a vaccination compared with 34% in the social-benefits frame, but the difference was not statistically significant (aOR = 1.63, 95% CI 0.90 to 2.95, p = 0.108). Reasons for vaccination focused primarily on self-benefit (67%) rather than social-benefit (5%). Exploratory analysis showed that the effect of messages depended on patient perception of risk group membership (aORHigh / aORLow = 5.59, 95% CI 1.30 to 24.05, p = 0.021). In particular, emphasis on self-benefit was more influential among patients who perceived themselves to be in the risk group (aOR = 6.22, 95% CI 1.69 to 22.88, p = 0.006). Conclusions In contrast to the literature observing intentions of low-risk populations, we found no evidence that social-benefit motivates actual vaccination behaviour among a high-risk patient population. Instead, those who self-categorize as being in the high risk group are more motivated by the self-benefit message. Our results suggest that a stratified approach can improve coverage: even if an emphasis on social-benefit could be effective among low-risk groups, an emphasis on self-benefit holds more promise for increasing vaccination in medical organizational settings where high-risk groups are prevalent. Trial registration ClinicalTrials.gov NCT04230343 Retrospectively registered on the 13th January 2020.
According to the 'Description-Experience gap' (DE gap), when people are provided with the descriptions of risky prospects they make choices as if they overweight the probability of rare events; but when making decisions from experience after exploring the prospects' properties, they behave as if they underweight such probability. This study revisits this discrepancy while focusing on information-search in decisions from experience. We report findings from a lab-experiment with three treatments: a standard version of decisions from description and two versions of decisions from experience: with and without a 'history table' recording previously sampled events. We find that people sample more from lotteries with rarer events. The history table proved influential; in its absence search is more responsive to cues such as a lottery's variance while in its presence the cue that stands out is the table's maximum capacity. Our analysis of risky choices captures a significant DE gap which is mitigated by the presence of the history table. We elicit probability weighting functions at the individual level and report that subjects overweight rare events in experience but less so than in description. Finally, we report a measure that allows us to compare the type of DE gap found in studies using choice patterns with that inferred through valuation and find that the phenomenon is similar but not identical across the two methods.
The Description-Experience gap (DE gap) is widely thought of as a tendency for people to act as if overweighting rare events when information about those events is derived from descriptions but as if underweighting rare events when they experience them through a sampling process. While there is now clear evidence that some form of DE gap exists, its causes, exact nature, and implications for decision theory remain unclear. We present a new experiment which examines in a unified design four distinct causal mechanisms that might drive the DE gap, attributing it respectively to information differences (sampling bias), to a feature of preferences (ambiguity sensitivity), or to aspects of cognition (likelihood representation and memory). Using a model-free approach, we elicit a DE gap similar in direction and size to the literature’s average and find that when each factor is considered in isolation, sampling bias stemming from under-represented rare events is the only significant driver of the gap. Yet, model-mediated analysis reveals the possibility of a smaller DE gap, existing even without information differences. Moreover, this form of analysis of our data indicates that even when information about them is obtained by sampling, rare events are generally overweighted.
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