Sharing names and information: Incidental similarities between CEOs and analysts can lead to favoritism in information disclosure.

When two people coincidentally have something in common (such as a name or birthday), they tend to like each other more and are thus more likely to offer help and comply with requests. This dynamic can have important legal and ethical consequences whenever these incidental similarities give rise to unfair favoritism. Using a large-scale, longitudinal natural experiment, covering nearly 200,000 annual earnings forecasts over more than 25 y, we show that when a CEO and a securities analyst share a first name, the analyst's financial forecast is more accurate. We offer evidence that name matching improves forecast accuracy due to CEOs privately sharing pertinent information with name-matched analysts. Additionally, we show that this effect is especially pronounced among CEO-analyst pairs who share an uncommon first name. Our research thus demonstrates how incidental similarities can give way to special treatment. Whereas most investigations of the effects of similarity consider only one-shot interactions, we use a longitudinal dataset to show that the effect of name matching diminishes over time with more interactions between CEOs and analysts. We also point to the findings of an experiment suggesting that favoritism born of sharing a name may evade straightforward regulation in part due to people's perception that name similarity would exert little influence on them. Taken together, our work offers insight into when private disclosures are likely to be made. Our results suggest that the effectiveness of regulatory policies can be significantly impacted by psychological factors shaping the context in which they are implemented.

A 680,000-person megastudy of nudges to encourage vaccination in pharmacies.

Encouraging vaccination is a pressing policy problem. To assess whether text-based reminders can encourage pharmacy vaccination and what kinds of messages work best, we conducted a megastudy. We randomly assigned 689,693 Walmart pharmacy patients to receive one of 22 different text reminders using a variety of different behavioral science principles to nudge flu vaccination or to a business-as-usual control condition that received no messages. We found that the reminder texts that we tested increased pharmacy vaccination rates by an average of 2.0 percentage points, or 6.8%, over a 3-mo follow-up period. The most-effective messages reminded patients that a flu shot was waiting for them and delivered reminders on multiple days. The top-performing intervention included two texts delivered 3 d apart and communicated to patients that a vaccine was "waiting for you." Neither experts nor lay people anticipated that this would be the best-performing treatment, underscoring the value of simultaneously testing many different nudges in a highly powered megastudy.

A megastudy of text-based nudges encouraging patients to get vaccinated at an upcoming doctor's appointment.

Many Americans fail to get life-saving vaccines each year, and the availability of a vaccine for COVID-19 makes the challenge of encouraging vaccination more urgent than ever. We present a large field experiment (N = 47,306) testing 19 nudges delivered to patients via text message and designed to boost adoption of the influenza vaccine. Our findings suggest that text messages sent prior to a primary care visit can boost vaccination rates by an average of 5%. Overall, interventions performed better when they were 1) framed as reminders to get flu shots that were already reserved for the patient and 2) congruent with the sort of communications patients expected to receive from their healthcare provider (i.e., not surprising, casual, or interactive). The best-performing intervention in our study reminded patients twice to get their flu shot at their upcoming doctor's appointment and indicated it was reserved for them. This successful script could be used as a template for campaigns to encourage the adoption of life-saving vaccines, including against COVID-19.

Evaluation of behavioral economic strategies to raise influenza vaccination rates across a health system: Results from a randomized clinical trial.

Influenza vaccination rates are low. Working with a large US health system, we evaluated three health system-wide interventions using the electronic health record's patient portal to improve influenza vaccination rates. We performed a two-arm RCT with a nested factorial design within the treatment arm, randomizing patients to usual-care control (no portal interventions) or to one or more portal interventions. We included all patients within this health system during the 2020-2021 influenza vaccination season, which overlapped with the COVID-19 pandemic. Through the patient portal, we simultaneously tested: pre-commitment messages (sent September 2020, asking patients to commit to a vaccination); monthly portal reminders (October - December 2020), direct appointment scheduling (patients could self-schedule influenza vaccination at multiple sites); and pre-appointment reminder messages (sent before scheduled primary care appointments, reminding patients about influenza vaccination). The main outcome measure was receipt of influenza vaccine (10/01/2020-03/31/2021). We randomized 213,773 patients (196,070 adults ≥18 years, 17,703 children). Influenza vaccination rates overall were low (39.0%). Vaccination rates for study arms did not differ: Control (38.9%), pre-commitment vs no pre-commitment (39.2%/38.9%), direct appointment scheduling yes/no (39.1%/39.1%), pre-appointment reminders yes/no (39.1%/39.1%); p > 0.017 for all comparisons (p value cut-off adjusted for multiple comparisons). After adjusting for age, gender, insurance, race, ethnicity, and prior influenza vaccination, none of the interventions increased vaccination rates. We conclude that patient portal interventions to remind patients to receive influenza vaccine during the COVID-19 pandemic did not raise influenza immunization rates. More intensive or tailored interventions are needed beyond portal innovations to increase influenza vaccination.

Effect of Personalized Messages Sent by a Health System's Patient Portal on Influenza Vaccination Rates: a Randomized Clinical Trial.

BACKGROUND: Adult influenza vaccination rates are low. Tailored patient reminders might raise rates. OBJECTIVE: Evaluate impact of a health system's patient portal reminders: (1) tailored to patient characteristics and (2) incorporating behavioral science strategies, on influenza vaccination rates among adults. DESIGN: Pragmatic 6-arm randomized trial across a health system during the 2019-2020 influenza vaccination season. The setting was one large health system-53 adult primary care practices. PARTICIPANTS: All adult patients who used the patient portal within 12 months, stratified by the following: young adults (18-64 years, without diabetes), older adults (≥65 years, without diabetes), and those with diabetes (≥18 years). INTERVENTIONS: Patients were randomized within strata to either (1) pre-commitment reminder alone (1 message, mid-October), (2) pre-commitment + loss frame messages, (3) pre-commitment + gain frame messages, (4) loss frame messages alone, (5) gain frame messages alone, or (6) standard of care control. Patients in the pre-commitment group were sent a message in mid-October, asking if they planned on getting an influenza vaccination. Patients in loss or gain frame groups were sent up to 3 portal reminders (late October, November, and December, if no documented influenza vaccination in the EHR) about importance and safety of influenza vaccine. MAIN MEASURES: Receipt of 1 influenza vaccine from 10/01/2019 to 03/31/2020. KEY RESULTS: 196,486 patients (145,166 young adults, 29,795 older adults, 21,525 adults with diabetes) were randomized. Influenza vaccination rates were as follows: for young adults 36.8%, for older adults 55.6%, and for diabetics 60.6%. On unadjusted and adjusted (for age, gender, insurance, race, ethnicity, and prior influenza vaccine history) analyses, influenza vaccination rates were not statistically different for any study group versus control. CONCLUSIONS: Patient reminders sent by a health system's patient portal that were tailored to patient demographics (young adults, older adults, diabetes) and that incorporated two behavioral economic messaging strategies (pre-commitment and loss/gain framing) were not effective in raising influenza vaccination rates. TRIAL REGISTRATION: This trial was registered with ClinicalTrials.gov (NCT04110314).

Conspiracy Theory as Individual and Group Behavior: Observations from the Flat Earth International Conference.

Conspiratorial thinking has been with humanity for a long time but has recently grown as a source of societal concern and as a subject of research in the cognitive and social sciences. We propose a three-tiered framework for the study of conspiracy theories: (1) cognitive processes, (2) the individual, and (3) social processes and communities of knowledge. At the level of cognitive processes, we identify explanatory coherence and faulty belief updating as critical ideas. At the level of the community of knowledge, we explore how conspiracy communities facilitate false belief by promoting a contagious sense of understanding, and how community norms catalyze the biased assimilation of evidence. We review recent research on conspiracy theories and explain how conspiratorial thinking emerges from the interaction of individual and group processes. As a case study, we describe observations the first author made while attending the Flat Earth International Conference, a meeting of conspiracy theorists who believe the Earth is flat. Rather than treating conspiracy belief as pathological, we take the perspective that is an extreme outcome of common cognitive processes.

A Randomized Trial of Behavioral Nudges Delivered Through Text Messages to Increase Influenza Vaccination Among Patients With an Upcoming Primary Care Visit.

PURPOSE: To evaluate if nudges delivered by text message prior to an upcoming primary care visit can increase influenza vaccination rates. DESIGN: Randomized, controlled trial. SETTING: Two health systems in the Northeastern US between September 2020 and March 2021. SUBJECTS: 74,811 adults. INTERVENTIONS: Patients in the 19 intervention arms received 1-2 text messages in the 3 days preceding their appointment that varied in their format, interactivity, and content. MEASURES: Influenza vaccination. ANALYSIS: Intention-to-treat. RESULTS: Participants had a mean (SD) age of 50.7 (16.2) years; 55.8% (41,771) were female, 70.6% (52,826) were White, and 19.0% (14,222) were Black. Among the interventions, 5 of 19 (26.3%) had a significantly greater vaccination rate than control. On average, the 19 interventions increased vaccination relative to control by 1.8 percentage points or 6.1% (P = .005). The top performing text message described the vaccine to the patient as "reserved for you" and led to a 3.1 percentage point increase (95% CI, 1.3 to 4.9; P < .001) in vaccination relative to control. Three of the top five performing messages described the vaccine as "reserved for you." None of the interventions performed worse than control. CONCLUSIONS: Text messages encouraging vaccination and delivered prior to an upcoming appointment significantly increased influenza vaccination rates and could be a scalable approach to increase vaccination more broadly.

Lay theories of financial well-being predict political and policy message preferences.

People differ in their lay theories about how and why the financial well-being of individuals changes over time or varies between individuals. We introduce a measure of Causal Attributions of Financial Uncertainty-the CAFU scale-and find that such attributions can be described reliably along three distinct dimensions, respectively capturing the extent to which changes in financial well-being are perceived to be: (a) knowable and within individuals' control due to individual factors such as effort ("Rewarding"); (b) knowable and outside of individuals' control due to factors such as favoritism and discrimination ("Rigged"); and (c) inherently unpredictable and determined by chance events ("Random"). In a sample representative of the U.S. population on various demographic characteristics (N = 1,102), we find that differences in these beliefs are associated with political ideology, revealing a predicted pattern: conservatives scored higher on the Rewarding subscale and liberals scored higher on the Rigged and Random subscales, even when controlling for key demographics. Moreover, we find that these three dimensions predict responses to different policy messages, even when controlling for political ideology. In three preregistered experiments (combined N = 2,560), we observe increased support for various social welfare policies when we highlighted aspects of these policies that are compatible with people's beliefs about financial well-being. Likewise, we observe increased support for political candidates when they expressed their positions in a way that is compatible with people's beliefs. Thus, this work can help better understand drivers of political attitudes and guide in crafting more persuasive policy messages. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Patient Portal Reminders for Pediatric Influenza Vaccinations: A Randomized Clinical Trial.

OBJECTIVES: In a large health system, we evaluated the effectiveness of electronic health record patient portal reminders in increasing pediatric influenza vaccination rates. METHODS: We conducted an intention-to-treat randomized clinical trial of 22 046 children from 6 months to <18 years of age in 53 primary care practices. Patients (or parent and/or proxies) who were active portal users were randomly assigned to receive reminder messages framed as gains or losses or no messages. They were separately randomly assigned to receive a precommitment message before the influenza season. The primary outcome was receipt of ≥1 seasonal influenza vaccinations. Additionally, children 6 months to <3 years of age due for a second influenza vaccine were randomly assigned to receive a reminder or no reminder for the second vaccination. RESULTS: First-dose influenza vaccination rates were 56.9% in the control group, 58.0% in the loss-frame reminders group (P = .07), and 58.0% in the gain-frame group (P = .47). Rates were 58.3% in the precommitment group versus 57.0% in the control group (P = .11). Adjusted risk ratios for first vaccination were 1.02 (95% confidence interval [CI]: 1.00-1.04) for loss-frame reminders, 1.01 (95% CI: 0.98-1.05) for gain-frame reminders, and 1.02 (95% CI: 1.00-1.04) for precommitment messages versus controls. Second-dose vaccination rates were 44.1% in the control group and 55.0% in the reminder group, with an adjusted risk ratio of 1.25 (95% CI: 1.07-1.45). CONCLUSIONS: Patient portal reminders for influenza vaccines in children, whether framed as gains or losses, did not increase first-dose influenza vaccination rates but were highly effective for the second dose of the vaccine.