Optimising nudges and boosts for financial decisions under uncertainty

Franklin, Matija; Folke, Tomas; Ruggeri, Kai

doi:10.1057/s41599-019-0321-y

Cited by 28 publications

(33 citation statements)

References 58 publications

(60 reference statements)

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“…The objective must thus be transparent to the boosted individuals. They can then harness the new or 'boosted' competence to make choices for themselves (e.g., whether to undergo a medical test, consume a particular food or choose a certain type of investment; e.g., see Kaufmann et al, 2013;Dallacker et al, 2019aDallacker et al, , 2019bFranklin et al, 2019).…”

Section: Self-nudges Are Boostsmentioning

confidence: 99%

Self-nudging and the citizen choice architect

Reijula

Hertwig

2020

Behav. Public Policy

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This article argues that nudges can often be turned into self-nudges: empowering interventions that enable people to design and structure their own decision environments – that is, to act as citizen choice architects. Self-nudging applies insights from behavioral science in a way that is practicable and cost-effective, but that sidesteps concerns about paternalism or manipulation. It has the potential to expand the scope of application of behavioral insights from the public to the personal sphere (e.g., homes, offices, families). It is a tool for reducing failures of self-control and enhancing personal autonomy; specifically, self-nudging can mean designing one's proximate choice architecture to alleviate the effects of self-control problems, engaging in education to understand the nature and causes of self-control problems and employing simple educational nudges to improve goal attainment in various domains. It can even mean self-paternalistic interventions such as winnowing down one's choice set by, for instance, removing options. Policy-makers could promote self-nudging by sharing knowledge about nudges and how they work. The ultimate goal of the self-nudging approach is to enable citizen choice architects’ efficient self-governance, where reasonable, and the self-determined arbitration of conflicts between their mutually exclusive goals and preferences.

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Section: Self-nudges Are Boostsmentioning

confidence: 99%

Self-nudging and the citizen choice architect

Reijula

Hertwig

2020

Behav. Public Policy

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“…Given these barriers, there is a clear space for behavioral interventions to support attendance for those that might wish to attend. Specifically, this could include interventions that apply principles from nudging, which involve small changes in the choice architecture that encourage optimal choices while ensuring autonomy remains with individuals, utilizing theory from behavioral economics and social psychology [10].…”

Section: Introductionmentioning

confidence: 99%

Nudging New York: adaptive models and the limits of behavioral interventions to reduce no-shows and health inequalities

Ruggeri

Folke

Benzerga

et al. 2020

BMC Health Serv Res

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Background: Missed healthcare appointments (no-shows) are costly and operationally inefficient for health systems. No-show rates are particularly high for vulnerable populations, even though these populations often require additional care. Few studies on no-show behavior or potential interventions exist specifically for Federally Qualified Health Centers (FQHCs), which care for over 24 million disadvantaged individuals in the United States. The purpose of this study is to identify predictors of no-show behavior and to analyze the effects of a reminder intervention in urban FQHCs in order to design effective policy solutions to a protracted issue in healthcare. Methods: This is a retrospective observational study using electronic medical record data from 11 facilities belonging to a New York City-based FQHC network between June 2017 to April 2018. This data includes 53,149 visits for 41,495 unique patients. Seven hierarchical generalized linear models and generalized additive models were used to predict no-shows, and multiple regression models evaluated the effectiveness of a reminder. All analyses were conducted in R. Results: The strongest predictor of no-show rates in FQHCs is whether or not patients are assigned to empaneled providers (z = − 91.45, p < 10 − 10), followed by lead time for appointments (z = 23.87, p < 10 − 10). These effects were fairly stable across facilities. The reminder had minimal effects on no-show rates overall (No show rate before: 41.6%, after: 42.1%). For individuals with appointments before and after the reminder, there was a small decrease in no-shows of 2%. Conclusions: The limited effects of the reminder intervention suggest the need for more personalized behavioral interventions to reduce no-shows. We recommend that these begin with increasing the use of empaneled providers for preventive care appointments and reducing the lag time between setting the appointment and the actual date of the appointment, at least for individuals with a high rate of no-show. By complementing these with low-intensity, lowcost behavioral interventions, we would expect greater impacts for improved access to care, contributing to the wellbeing of vulnerable populations.

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“…The objective must thus be transparent to the boosted individuals. They can then harness the new or "boosted" competence to make choices for themselves (e.g., whether to undergo a medical test, consume a particular food, or choose a certain type of investment; see, e.g., Kaufmann, Weber, and Haisley 2013;Dallacker, Mata, and Hertwig 2019;Dallacker, Hertwig, and Mata 2019;Franklin, Folke, and Ruggeri 2019).…”

Section: Self-nudges Are Boostsmentioning

confidence: 99%

Self-nudging and the citizen choice architect

Reijula¹,

Hertwig²

2019

Preprint

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This article argues that nudges can often be turned into self-nudges: empowering interventions that enable people to design and structure their own decision environments—that is, to act as citizen choice architects. Self-nudging applies insights from behavioral science in a way that is practicable and cost-effective but that sidesteps concerns about paternalism or manipulation. It has the potential to expand the scope of application of behavioral insights from the public to the personal sphere (e.g., homes, offices, families). It is a tool for reducing failures of self-control and enhancing personal autonomy; specifically, self-nudging can mean designing one’s proximate choice architecture to alleviate the effects of self-control problems, engaging in education to understand the nature and causes of self-control problems, and employing simple educational nudges to improve goal attainment in various domains. It can even mean self-paternalistic interventions such as winnowing down one’s choice set by, for instance, removing options. Policy makers could promote self-nudging by sharing knowledge about nudges and how they work. The ultimate goal of the self-nudging approach is to enable citizen choice architects’ efficient self-governance, where reasonable, and the self-determined arbitration of conflicts between their mutually exclusive goals and preferences.

show abstract

Optimising nudges and boosts for financial decisions under uncertainty

Cited by 28 publications

References 58 publications

Self-nudging and the citizen choice architect

Self-nudging and the citizen choice architect

Nudging New York: adaptive models and the limits of behavioral interventions to reduce no-shows and health inequalities

Self-nudging and the citizen choice architect

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