Underweighting of rare events in social interactions  and its implications to the design of voluntary health applications

Plonsky, Ori; Roth, Yefim; Erev, Ido

doi:10.31234/osf.io/9q3db

“…8 For example, the tendency to pollute and ignore the risks associated with global warming can be addressed by taxing polluting products. Similarly, the tendency to underweight the risk associated by COVID-19 can be addressed by using vaccination certificates that help vaccinated individuals skip time consuming tests (see Erev et al, 2020;Plonsky et al, 2021).…”

Section: Figurementioning

confidence: 99%

Decisions from valuations of unknown payoff distributions.

Erev¹,

Roth²,

Sonsino³

2022

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Four experiments are presented that clarify the impact of experience on the way people use valuations. In each of the 100 trials of Study 1, participants were asked to choose between the status quo and an unknown binary lottery based on valuations by two expert systems: a well-calibrated “expert” reporting the expected values, and an expert that ignores the low probability outcome and reports the medians (that equaled the modes). The results suggest that experience decreased the inclination to follow the recommendation of the well-calibrated expert. This deviation from maximization appears to reflect two biases: the tendency to follow the expert that has recommended the action that provided higher payoff in most cases, and the tendency to follow the more extreme valuation. Studies 2 and 3 suggest similar reliance on experts that recommend the best choice in most trials, in choices between two payoff distributions, and even when these experts do not provide the median or the mode of the distributions. Study 4 shows that the impact of experts that direct people toward the optimal choice can be increased by exaggeration (inflating the estimated advantage of the payoff maximizing option). However, the long-term impact of exaggeration depends on the proportion of cases in which the optimal choice leads to the best payoff; a lasting positive effect of exaggeration was observed only when this proportion was high. These results can be captured by assuming several “expert weighting rules” and the selection between the rules based on small samples of past experiences.

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“…Hence, the individual's choice to not act responsibly and the guilt that comes with it are attributed to others by the individual. To address this challenge, Plonsky et al ( 40 ) proposed a gentle rule enforcement and the implementation of utilitarian features that increase the personal benefits users derive from installing and using a CTA, which can help users meet the gentle rule easily. The gentle rule can help to save time and minimize efforts.…”

Section: Discussionmentioning

confidence: 99%

“…The gentle rule can help to save time and minimize efforts. One of such features is the ability to use one's CTA to book a vaccination appointment, download one's vaccination certificate, and use it to access public facilities without having to fill long forms, go through long checks, or be physically screened or tested for COVID-19 ( 40 ). The enforcement of gentle rules (such as the display of a green signal on one app's screen in order to enter stores and public facilities or to travel) helped break the chains of COVID-19 transmission in China ( 41 ).…”

Section: Discussionmentioning

confidence: 99%

Factors Influencing the Adoption of Contact Tracing Applications: Systematic Review and Recommendations

Oyibo¹,

Sahu²,

Oetomo³

et al. 2022

Front. Digit. Health

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BackgroundThe emergence of new variants of COVID-19 causing breakthrough infections and the endemic potential of the coronavirus are an indication that digital contact tracing apps (CTAs) may continue to be useful for the long haul. However, the uptake of these apps in many countries around the world has been low due to several factors militating against their adoption and usage.ObjectiveIn this systematic review, we set out to uncover the key factors that facilitate or militate against the adoption of CTAs, which researchers, designers and other stakeholders should focus on in future iterations to increase their adoption and effectiveness in curbing the spread of COVID-19.Data SourcesSeven databases, including PubMed, CINAHL, Scopus, Web of Service, IEEE Xplore, ACM Digital Library, and Google Scholar, were searched between October 30 and January 31, 2020. A total of 777 articles were retrieved from the databases, with 13 of them included in the systematic review after screening.Study Eligibility Criteria, Participants, and InterventionThe criteria for including articles in the systematic review were that they could be user studies from any country around the world, must be peer-reviewed, written in English, and focused on the perception and adoption of COVID-19 contact tracing and/or exposure notification apps. Other criteria included user study design could be quantitative, qualitative, or mixed, and must have been conducted during the COVID-19 pandemic, which began in the early part of 2020.Study Appraisal and Synthesis MethodsThree researchers searched seven databases (three by the first author, and two each by the second and third authors) and stored the retrieved articles in a collaborative Mendeley reference management system online. After the removal of duplicates, each researcher independently screened one third of the articles based on title/abstract. Thereafter, all three researchers collectively screened articles that were in the borderline prior to undergoing a full-text review. Then, each of the three researchers conducted a full-text review of one-third of the eligible articles to decide the final articles to be included in the systematic review. Next, all three researchers went through the full text of each borderline article to determine their appropriateness and relevance. Finally, each researcher extracted the required data from one-third of the included articles into a collaborative Google spreadsheet and the first author utilized the data to write the review.ResultsThis review identified 13 relevant articles, which found 56 factors that may positively or negatively impact the adoption of CTAs. The identified factors were thematically grouped into ten categories: privacy and trust, app utility, facilitating conditions, social-cognitive factors, ethical concerns, perceived technology threats, perceived health threats, technology familiarity, persuasive design, and socio-demographic factors. Of the 56 factors, privacy concern turned out to be the most frequent factor of CTA adoption (12/13), followed by perceived benefit (7/13), perceived trust (6/13), and perceived data security risk (6/13). In the structural equation models presented by the authors of the included articles, a subset of the 56 elicited factors (e.g., perceived benefit and privacy concern) explains 16 to 77% of the variance of users' intention to download, install, or use CTAs to curb the spread of COVID-19. Potential adoption rates of CTA range from 19% (in Australia) to 75% (in France, Italy, Germany, United Kingdom, and United States). Moreover, actual adoption rates range from 37% (in Australia) to 50% (in Germany). Finally, most of the studies were carried out in Europe (66.7%), followed by North America (13.3%), and Australia, Asia, and South America (6.7% each).ConclusionThe results suggest that future CTA iterations should give priority to privacy protection through minimal data collection and transparency, improving contact tracing benefits (personal and social), and fostering trust through laudable gestures such as delegating contact tracing to public health authorities, making source code publicly available and stating who will access user data, when, how, and what it will be used for. Moreover, the results suggest that data security and tailored persuasive design, involving reward, self-monitoring, and social-location monitoring features, have the potential of improving CTA adoption. Hence, in addition to addressing issues relating to utility, privacy, trust, and data security, we recommend the integration of persuasive features into future designs of CTAs to improve their motivational appeal, adoption, and the user experience.Systematic Review Registrationhttps://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42021259080 PROSPERO, identifier CRD42021259080.

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“…8 For example, the tendency to pollute and ignore the risks associated with global warming can be addressed by taxing polluting products. Similarly, the tendency to underweight the risk associated by Covid-19 can be addressed by using vaccination certificates that help vaccinated individuals skip time consuming tests (see Plonsky, Roth & Erev, 2021).…”

Section: Discussionmentioning

confidence: 99%

Decisions From Valuations of Unknown Payoff Distributions

Erev¹,

Roth²,

Sonsino³

2022

Preprint

Self Cite

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Four experiments are presented that clarify the impact of experience on the way people use valuations. In each of the 100 trials of Study 1, participants were asked to choose between the status quo and an unknown binary lottery based on valuations by two expert systems: a well-calibrated “expert” reporting the expected values, and an expert that ignores the low probability outcome and reports the medians (that equaled the modes). The results suggest that experience decreased the inclination to follow the recommendation of the well-calibrated expert. This deviation from maximization appears to reflect two biases: the tendency to follow the expert that has recommended the action that provided higher payoff in most cases, and the tendency to follow the more extreme valuation. Studies 2 and 3 suggest similar reliance on experts that recommend the best choice in most trials, in choices between two payoff distributions, and even when these experts do not provide the median or the mode of the distributions. Study 4 shows that the impact of experts that direct people toward the optimal choice can be increased by exaggeration (inflating the estimated advantage of the payoff maximizing option). However, the long-term impact of exaggeration depends on the proportion of cases in which the optimal choice leads to the best payoff; a lasting positive effect of exaggeration was observed only when this proportion was high. These results can be captured by assuming several “expert weighting rules” and the selection between the rules based on small samples of past experiences.

show abstract

Underweighting of rare events in social interactions and its implications to the design of voluntary health applications

Cited by 8 publications

References 43 publications

Decisions from valuations of unknown payoff distributions.

Decisions from valuations of unknown payoff distributions.

Factors Influencing the Adoption of Contact Tracing Applications: Systematic Review and Recommendations

Decisions From Valuations of Unknown Payoff Distributions

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