Encouraging Mammograms Using Behavioral Economics: A Randomized Controlled Trial in Chile

OBJECTIVES

This article illustrates the effect of a direct mail campaign that used insights from behavioral economics and psychology to increase the number of free mammograms in Chilean women aged 50 years or older.

METHODS

We hypothesized 4 barriers in obtaining a mammogram based on previous literature and focus group analysis. A behavioral economic approach providing incentives was used to help overcome these barriers. We accessed a unique data set, which comprised 12 000 women 50 years old or older, with private health insurance who have not had a mammogram for 24 or more months. We conducted a randomized controlled trial with 8 treatments, each involving a specific combination of messages.

RESULTS

The intervention overall led to a 167% increase in the use of free mammograms, a 1.13% to 3.03% average increase from the control to treatment groups, respectively. Regarding barriers, we found that all messages were effective, with a slightly larger and persistent effect for the less complex ones in terms of information. This finding illustrates the benefits of keeping the message simple.

CONCLUSIONS

Finally, these results suggest a successful public policy for increasing use of free mammography programs. Moreover, they are potentially transferable because the study considered decision-making heuristics that are not specific to one culture or social context.

Care Ethics versus the CARES Act

One of the biggest policy interventions during the last year of the COVID-19 pandemic was the Coronavirus Aid, Relief, and Economic Securities Act, instituting a novel form of economic relief similar to a universal basic income. The economic impact payments, colloquially known as "stimulus checks," were distributed based on the socioeconomic status of American citizens and legal residents and provided much-needed financial aid. However, the distribution of these payments paid little attention to other important factors that might determine the economic security of said individuals, such as race and gender. This article calls for policy-makers to pay particular attention to how structural inequity and discrimination based on identity could affect the efficacy of proposed policies and demonstrate an ethic of care informed by an understanding of intersectionality.

Initial development of a brief assessment of cocaine demand

Cocaine demand is a behavioral economic measure assessing drug reward value and motivation to use drug. The purpose of the current study was to develop a brief assessment of cocaine demand (BACD). Results from the BACD were compared with self-report measures of cocaine use. Participants consisted of treatment-seeking individuals with cocaine use disorder (N = 22). Results revealed that indices of brief demand were significantly associated with various self-report measures of cocaine use. Overall, these results support the utility of a BACD for assessing cocaine demand.

Using Insights from Behavioral Economics to Mitigate the Spread of COVID-19

The outbreak of 2019 coronavirus disease (COVID-19) has become a public health emergency of international concern. The number of COVID-infected individuals and related deaths continues to rise rapidly. Encouraging people to adopt and sustain preventive behaviors is a central focus of public health policies that seek to mitigate the spread of COVID-19. Public health policy needs improved methods to encourage people to adhere to COVID-19-preventive behaviors. In this paper, we introduce a number of insights from behavioral economics that help explain why people may behave irrationally during the COVID-19 pandemic. In particular, present bias, status quo bias, framing effect, optimism bias, affect heuristic, and herding behavior are discussed. We hope this paper will shed light on how insights from behavioral economics can enrich public health policies and interventions in the fight against COVID-19.

Threat appeals reduce impulsive decision making associated with texting while driving: A behavioral economic approach

The primary purpose of the present study was to examine the effectiveness of threat appeals in influencing impulsive decision making associated with texting while driving. The participants in the treatment group were exposed to a threatening message about the danger of texting while driving, whereas those in the control group were exposed to a non-threatening message. Following the exposure to either message, the participants completed a delay-discounting task that assessed the degree of impulsive decision making in a hypothetical texting-while-driving scenario. A comparison between the groups revealed that the threat appeals reduced the degree of impulsive decision making associated with texting while driving. In addition, the threat appeals led to greater anticipated regret from texting while driving, less favorable attitudes toward texting while driving, and decreased intentions to text while driving in the future in the treatment group. These results suggest that video-based threat appeals are promising intervention strategies for the public health challenge of texting while driving. Implications from the behavioral economic perspective are discussed.

Effect of Financial Bonus Size, Loss Aversion, and Increased Social Pressure on Physician Pay-for-Performance: A Randomized Clinical Trial and Cohort Study

Importance

Despite limited effectiveness of pay-for-performance (P4P), payers continue to expand P4P nationally.

Objective

To test whether increasing bonus size or adding the behavioral economic principles of increased social pressure (ISP) or loss aversion (LA) improves the effectiveness of P4P.

Design, Setting, and Participants

Parallel studies conducted from January 1 to December 31, 2016, consisted of a randomized clinical trial with patients cluster-randomized by practice site to an active control group (larger bonus size [LBS] only) or to groups with 1 of 2 behavioral economic interventions added and a cohort study comparing changes in outcomes among patients of physicians receiving an LBS with outcomes in propensity-matched physicians not receiving an LBS. A total of 8118 patients attributed to 66 physicians with 1 of 5 chronic conditions were treated at Advocate HealthCare, an integrated health system in Illinois. Data were analyzed using intention to treat and multiple imputation from February 1, 2017, through May 31, 2018.

Interventions

Physician participants received an LBS increased by a mean of $3355 per physician (LBS-only group); prefunded incentives to elicit LA and an LBS; or increasing proportion of a P4P bonus determined by group performance from 30% to 50% (ISP) and an LBS.

Main Outcomes and Measures

The proportion of 20 evidence-based quality measures achieved at the patient level.

Results

A total of 86 physicians were eligible for the randomized trial. Of these, 32 were excluded because they did not have unique attributed patients. Fifty-four physicians were randomly assigned to 1 of 3 groups, and 33 physicians (54.5% male; mean [SD] age, 57 [10] years) and 3747 patients (63.6% female; mean [SD] age, 64 [18] years) were included in the final analysis. Nine physicians and 864 patients were randomized to the LBS-only group, 13 physicians and 1496 patients to the LBS plus ISP group, and 11 physicians and 1387 patients to the LBS plus LA group. Physician characteristics did not differ significantly by arm, such as mean (SD) physician age ranging from 56 (9) to 59 (9) years, and sex (6 [46.2%] to 6 [66.7%] male). No differences were found between the LBS-only and the intervention groups (adjusted odds ratio [aOR] for LBS plus LA vs LBS-only, 0.86 [95% CI, 0.65-1.15; P = .31]; aOR for LBS plus ISP vs LBS-only, 0.95 [95% CI, 0.64-1.42; P = .81]; and aOR for LBS plus ISP vs LBS plus LA, 1.10 [95% CI, 0.75-1.61; P = .62]). Increased bonus size was associated with a greater increase in evidence-based care relative to the comparison group (risk-standardized absolute difference-in-differences, 3.2 percentage points; 95% CI, 1.9-4.5 percentage points; P < .001).

Conclusions and Relevance

Increased bonus size was associated with significantly improved quality of care relative to a comparison group. Adding ISP and opportunities for LA did not improve quality.

Trial Registration

ClinicalTrials.gov Identifier: NCT02634879.

Behavioral responses to surveys about nicotine dependence

Behavioral responses to surveys can significantly affect inferences about population prevalence unless correctly modeled statistically. An important case study is the prevalence of nicotine dependence, a formal psychiatric disorder satisfying clinical criteria. Data from the National Epidemiologic Survey on Alcohol and Related Conditions in the United States are used, along with a flexible semi-nonparametric sample selection model. Corrections for sample selection responses to "gateway" survey questions lead to significantly higher estimates of the prevalence of nicotine dependence among current daily smokers. These corrections also imply even higher levels of the decades-long and lifetime-long persistence of nicotine dependence after the onset of smoking.

Exposure to Poverty and Productivity

We study whether exposure to poverty can induce affective states that decrease productivity. In a controlled laboratory setting, we find that subjects randomly assigned to a treatment, in which they view a video featuring individuals that live in extreme poverty, exhibit lower subsequent productivity compared to subjects assigned to a control treatment. Questionnaire responses, as well as facial recognition software, provide quantitative measures of the affective state evoked by the two treatments. Subjects exposed to images of poverty experience a more negative affective state than those in the control treatment. Further analysis shows that individuals in a more positive emotional state exhibit less of a treatment effect. Also, those who exhibit greater attentiveness upon viewing the poverty video are less productive. The results are consistent with the notion that exposure to poverty can induce a psychological state in individuals that adversely affects productivity.

Human Factors in Financial Trading: An Analysis of Trading Incidents

OBJECTIVE

This study tests the reliability of a system (FINANS) to collect and analyze incident reports in the financial trading domain and is guided by a human factors taxonomy used to describe error in the trading domain.

BACKGROUND

Research indicates the utility of applying human factors theory to understand error in finance, yet empirical research is lacking. We report on the development of the first system for capturing and analyzing human factors-related issues in operational trading incidents.

METHOD

In the first study, 20 incidents are analyzed by an expert user group against a referent standard to establish the reliability of FINANS. In the second study, 750 incidents are analyzed using distribution, mean, pathway, and associative analysis to describe the data.

RESULTS

Kappa scores indicate that categories within FINANS can be reliably used to identify and extract data on human factors-related problems underlying trading incidents. Approximately 1% of trades (n = 750) lead to an incident. Slip/lapse (61%), situation awareness (51%), and teamwork (40%) were found to be the most common problems underlying incidents. For the most serious incidents, problems in situation awareness and teamwork were most common.

CONCLUSION

We show that (a) experts in the trading domain can reliably and accurately code human factors in incidents, (b) 1% of trades incur error, and (c) poor teamwork skills and situation awareness underpin the most critical incidents.

APPLICATION

This research provides data crucial for ameliorating risk within financial trading organizations, with implications for regulation and policy.

Statistical issues in pragmatic trials of behavioral economic interventions

BACKGROUND

Randomized clinical trials provide gold-standard evidence for the efficacy of interventions, but have limitations, including highly selected populations that make inference on effectiveness difficult and a lack of ability to adapt and change midstream.

METHODS

We propose two innovations for pragmatic trial design.

RESULTS

Evidence-based evolutionary testing, a framework that allows adaptation of interventions and rapid-cycle innovation, preserves the power of randomization while acknowledging the need for adaptation and learning. An opt-out consent framework increases the fraction of the target population who participate in trials, but may lead to dampening of effect sizes.

CONCLUSION

Pragmatic trials offer numerous advantages in the evaluation of behavioral interventions in health. Statistical innovations, including evidence-based evolutionary testing and opt-out framing of consent and enrollment processes, can enhance the power of pragmatic trials and lead to more rapid progress.

Generalised Sandpile Dynamics on Artificial and Real-World Directed Networks

The main finding of this paper is a novel avalanche-size exponent τ ≈ 1.87 when the generalised sandpile dynamics evolves on the real-world Japanese inter-firm network. The topology of this network is non-layered and directed, displaying the typical bow tie structure found in real-world directed networks, with cycles and triangles. We show that one can move from a strictly layered regular lattice to a more fluid structure of the inter-firm network in a few simple steps. Relaxing the regular lattice structure by introducing an interlayer distribution for the interactions, forces the scaling exponent of the avalanche-size probability density function τ out of the two-dimensional directed sandpile universality class τ = 4/3, into the mean field universality class τ = 3/2. Numerical investigation shows that these two classes are the only that exist on the directed sandpile, regardless of the underlying topology, as long as it is strictly layered. Randomly adding a small proportion of links connecting non adjacent layers in an otherwise layered network takes the system out of the mean field regime to produce non-trivial avalanche-size probability density function. Although these do not display proper scaling, they closely reproduce the behaviour observed on the Japanese inter-firm network.