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61.
Nudge: This study looked at probability framings on preferences for cancer treatment alternatives in which tradeoffs between quantity and quality of life are made. 129 healthy volunteers and 154 cancer patients indicated their preferences for a toxic or non-toxic treatment at varying survival probabilities. They were randomly assigned into 3 treatments: (1) a positive frame in which the probability of survival was given; (2) a negative frame in which the probability of dying was given; and (3) a mixed frame in which the probability of surviving and dying were both given.
The cancer patients' preferences for the more effective toxic treatment was significantly stronger than the healthy volunteers. Both groups were significantly influenced by the level of probability that was presented. Preferences for the toxic treatment were weaker when the chance of survival dropped below 50%. This weakening preference below 50% survival was enhanced for subjects who responded in the negative frame. A negative frame or probability level below 0.5 seems to stimulate a "dying mode" type of value system in which quality, not quantity, of life becomes more salient in decision making.
Tags: framing / health
Source: O’Connor (1988), “Effects of Framing and Level of Probability on Patients’ Preferences for Cancer Chemotherapy”, Journal of Clinical Epidemiology.
62.
Nudge: This classic study used a series of framing experiments to demonstrate preference reversals. For example, “Imagine that the U.S. is preparing for the outbreak of a disease, which is expected to kill 600 people. Two programs to combat the disease have been proposed. Assume that the exact scientific consequences of the program are as follows: If Program A is adopted, 200 people will be saved. If Program B is adopted, there’s a 1/3 probability that 600 people will be saved and 2/3 probability that no people will be saved.” In expected utility terms the choice is (200*1 = 200 live or 600*0.33 = 200 live).
In this case 72% of people chose A.
The authors then presented the same issue with the following formulation: “If Program C is adopted 400 people will die. If Program D is adopted there is 1/3 probability that nobody will die and 2/3 probability that 600 people will die.” In expected utility terms the choice is (400*1 = 400 die or 600*0.33 = 400 die)
Despite the identical expected values as the previous programs, here 78% chose D.
Tags: framing / risk perception
Source: Kahneman & Tversky (1981), ‘The framing of decisions and the psychology of choice’, Science.
63.
Nudge: The authors study the UK Winter Fuel Payment (WFP), a cash transfer to households aged over 60. The WFP can range from £100-£300 and is usually given in November / December. Standard economic theory implies that the labelling of cash transfers or cash-equivalents (e.g. child benefits, food stamps) should have no effect on spending patterns but this is not the case here. Exploiting sharp eligibility criteria in a regression discontinuity design, the authors found evidence of a behavioural effect of the labelling. If households were given an unconditional, neutrally-named cash transfer of £100, they would be expected to spend £3 of it on fuel. If it is called Winter Fuel Payment, they spend an average of £41 on fuel.
Tags: framing
Source: Beatty et al. (2011), 'Cash by any other name? Evidence on labelling from the UK winter fuel payment', Institute for Fiscal Studies Working Paper.
64.
Nudge: When nudges go wrong. In an attempt to reduce the theft of wood from Arizona’s Petrified Forest National Park the authors put up a sign with the descriptive social normative message “Many past visitors have removed petrified wood from the Park, changing the natural state of the Petrified Forest”. This led to a near 8% increase in wood theft, as people interpreted the salient message to be “theft is common” rather than “theft is bad”.
Tags: negative social proof / normative messages
65.
Nudge: Using RCTs, the author looks at the efficacy of text message reminders and peer mentor outreach at increasing college entry among low-income students. The results show that an automated and personalized text messaging campaign to remind students of required college tasks increased college enrollment by 4-7%, with effects concentrated among students who resided in communities with low levels of educational attainment. A peer mentor intervention increased four-year college enrollment by 4.5%, with effects largest for males and students with less-defined college plans. Given the meagre costs - $7 per participant for the text message campaign and $80 per participant for the peer mentor campaign - both strategies are impressively cost-effective.
Tags: education / personalised text messaging / peer mentoring
Source: Castleman (2013), “Summer Nudging: Can Text Messages and Peer Mentor Outreach Increase College-Going Among Low-Income High School Graduates?”
66.
Nudge: The B.I.T. looked at the area of Legacy Giving (leaving money to charity through a will), working with the organizations Co-Operative Legal Services and Remember a Charity. Although 35% of those surveyed indicated they wanted to leave money to charity in their will, only 7% of wills contain such bequests. When customers rang to book a will-writing appointment, they were randomly assigned to a will-writer who would write them will with them over the phone.
There were two treatment groups with over 1,000 individuals in each. The treatments were as follows:
(1) The will-writers asked “Would you like to leave any money to charity in your will?” [Plain ask]
(2) The will-writers asked “Many of our customers like to leave money to charity in their will. Are there any causes you’re passionate about?” [Social Norm]
The results showed 10.8% of customers in the ‘plain ask’ group included a donation and 15.4% in the ‘social norm’ group. This compares to 4.9% in the baseline period which was a period before the trial began.
Tags: charitable giving / social norms
Source: Behavioural Insights Team (2013), 'Applying behavioural insights to charitable giving'
67.
Nudge: The B.I.T. worked with Deutsche Bank to encourage employees to donate a day’s salary to charity. The control group received an impersonal email from the CEO (“Dear colleague). Treatment groups were targeted with one (or more) of several interventions; some sweets as they entered the building, a personalized email from the CEO (“Dear Joe”) or a combination of sweets and personalized email.
The Deutsche Bank staff gave £500,000 overall on the day. The B.I.T. suggest that if the effects of the most effective treatment had been replicated across all donors, over £1 million would have been raised.
Tags: charitable giving / incentives / personalization
Source: Behavioural Insights Team (2013), 'Applying behavioural insights to charitable giving'
68.
Nudge: The B.I.T. worked with a HMRC office (n=1,500) to see whether using social proof could increase charitable giving among employees. In December 2012 employees of the office received e-cards from HMRC employees who currently donated to charity.
The control group received an e-card from an existing donor simply explaining why that person donates and asking the recipient to join them. The treatment group received the same card but with an attached picture of the existing donor. This addition of a picture increased the number of new donors from 2.9% to 6.4%.
Tags: charitable giving / social proof
Source: Behavioural Insights Team (2013), 'Applying behavioural insights to charitable giving'
69.
Nudge: The BIT worked with Home Retail Group (50,000 staff & 1,079 stores in the U.K.) and Charities Trust to raise charitable giving through a payroll giving scheme. They have an automatic escalation program called Xtra Factor which increases donations by 3% per year. However, only 10% of new donors were taking it up.
By changing the default for the Xtra Factor to opt-out for new donors,the proportion of new donors using it jumped from 6% to 49%.
Tags: charitable giving / defaults
Source: Behavioural Insights Team (2013), 'Applying behavioural insights to charitable giving'
70.
Nudge: Similar to the Save More Tomorrow program which encouraging increasing amounts of wage savings, the B.I.T. worked with Zurich Community Trust to encourage their 702 donors to sign up to annual increases in their charitable giving rather than just one-off increases.
They conducted three trials on this group of donors; (1) asking for a one-off payment each month from 2013 (2) asking for increasing amounts donated each month from 2013 with future annual increases of either £1/£2/£3/£5/£10 (3) the same as (2) but with future increases of either £2/£4/£6/£8/£10.
They found that those in group 3 (the high increases) donated more and if extrapolated over their lifetime would donate considerably more than the other 2 groups.
Tags: charitable giving / framing
Source: Behavioural Insights Team (2013), 'Applying behavioural insights to charitable giving'
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