Welcome to the Nexus of Ethics, Psychology, Morality, Philosophy and Health Care

Welcome to the nexus of ethics, psychology, morality, technology, health care, and philosophy
Showing posts with label Contagion. Show all posts
Showing posts with label Contagion. Show all posts

Sunday, August 30, 2020

Prosocial modeling: A meta-analytic review and synthesis

Jung, H., Seo, E., et al. (2020).
Psychological Bulletin, 146(8), 635–663.
https://doi.org/10.1037/bul0000235

Abstract
Exposure to prosocial models is commonly used to foster prosocial behavior in various domains of society. The aim of the current article is to apply meta-analytic techniques to synthesize several decades of research on prosocial modeling, and to examine the extent to which prosocial modeling elicits helping behavior. We also identify the theoretical and methodological variables that moderate the prosocial modeling effect. Eighty-eight studies with 25,354 participants found a moderate effect (g = 0.45) of prosocial modeling in eliciting subsequent helping behavior. The prosocial modeling effect generalized across different types of helping behaviors, different targets in need of help, and was robust to experimenter bias. Nevertheless, there was cross-societal variation in the magnitude of the modeling effect, and the magnitude of the prosocial modeling effect was larger when participants were presented with an opportunity to help the model (vs. a third-party) after witnessing the model’s generosity. The prosocial modeling effect was also larger for studies with higher percentage of female in the sample, when other people (vs. participants) benefitted from the model’s prosocial behavior, and when the model was rewarded for helping (vs. was not). We discuss the publication bias in the prosocial modeling literature, limitations of our analyses and identify avenues for future research. We end with a discussion of the theoretical and practical implications of our findings.

Impact Statement

Public Significance Statement: This article synthesizes several decades of research on prosocial modeling and shows that witnessing others’ helpful acts encourages prosocial behavior through prosocial goal contagion. The magnitude of the prosocial modeling effect, however, varies across societies, gender and modeling contexts. The prosocial modeling effect is larger when the model is rewarded for helping. These results have important implications for our understanding of why, how, and when the prosocial modeling effect occurs. 

Saturday, December 14, 2019

The Dark Psychology of Social Networks

Jonathan Haidt and Tobias Rose-Stockwell
The Atlantic
Originally posted December 2019

Her are two excerpts:

Human beings evolved to gossip, preen, manipulate, and ostracize. We are easily lured into this new gladiatorial circus, even when we know that it can make us cruel and shallow. As the Yale psychologist Molly Crockett has argued, the normal forces that might stop us from joining an outrage mob—such as time to reflect and cool off, or feelings of empathy for a person being humiliated—are attenuated when we can’t see the person’s face, and when we are asked, many times a day, to take a side by publicly “liking” the condemnation.

In other words, social media turns many of our most politically engaged citizens into Madison’s nightmare: arsonists who compete to create the most inflammatory posts and images, which they can distribute across the country in an instant while their public sociometer displays how far their creations have traveled.

(cut)

Twitter also made a key change in 2009, adding the “Retweet” button. Until then, users had to copy and paste older tweets into their status updates, a small obstacle that required a few seconds of thought and attention. The Retweet button essentially enabled the frictionless spread of content. A single click could pass someone else’s tweet on to all of your followers—and let you share in the credit for contagious content. In 2012, Facebook offered its own version of the retweet, the “Share” button, to its fastest-growing audience: smartphone users.

Chris Wetherell was one of the engineers who created the Retweet button for Twitter. He admitted to BuzzFeed earlier this year that he now regrets it. As Wetherell watched the first Twitter mobs use his new tool, he thought to himself: “We might have just handed a 4-year-old a loaded weapon.”

The coup de grâce came in 2012 and 2013, when Upworthy and other sites began to capitalize on this new feature set, pioneering the art of testing headlines across dozens of variations to find the version that generated the highest click-through rate. This was the beginning of “You won’t believe …” articles and their ilk, paired with images tested and selected to make us click impulsively. These articles were not usually intended to cause outrage (the founders of Upworthy were more interested in uplift). But the strategy’s success ensured the spread of headline testing, and with it emotional story-packaging, through new and old media alike; outrageous, morally freighted headlines proliferated in the following years.

The info is here.

Thursday, December 5, 2019

How Misinformation Spreads--and Why We Trust It

Cailin O'Connor and James Owen Weatherall
Scientific American
Originally posted September 2019

Here is an excerpt:

Many communication theorists and social scientists have tried to understand how false beliefs persist by modeling the spread of ideas as a contagion. Employing mathematical models involves simulating a simplified representation of human social interactions using a computer algorithm and then studying these simulations to learn something about the real world. In a contagion model, ideas are like viruses that go from mind to mind.

You start with a network, which consists of nodes, representing individuals, and edges, which represent social connections.  You seed an idea in one “mind” and see how it spreads under various assumptions about when transmission will occur.

Contagion models are extremely simple but have been used to explain surprising patterns of behavior, such as the epidemic of suicide that reportedly swept through Europe after publication of Goethe's The Sorrows of Young Werther in 1774 or when dozens of U.S. textile workers in 1962 reported suffering from nausea and numbness after being bitten by an imaginary insect. They can also explain how some false beliefs propagate on the Internet.

Before the last U.S. presidential election, an image of a young Donald Trump appeared on Facebook. It included a quote, attributed to a 1998 interview in People magazine, saying that if Trump ever ran for president, it would be as a Republican because the party is made up of “the dumbest group of voters.” Although it is unclear who “patient zero” was, we know that this meme passed rapidly from profile to profile.

The meme's veracity was quickly evaluated and debunked. The fact-checking Web site Snopes reported that the quote was fabricated as early as October 2015. But as with the tomato hornworm, these efforts to disseminate truth did not change how the rumors spread. One copy of the meme alone was shared more than half a million times. As new individuals shared it over the next several years, their false beliefs infected friends who observed the meme, and they, in turn, passed the false belief on to new areas of the network.

This is why many widely shared memes seem to be immune to fact-checking and debunking. Each person who shared the Trump meme simply trusted the friend who had shared it rather than checking for themselves.

Putting the facts out there does not help if no one bothers to look them up. It might seem like the problem here is laziness or gullibility—and thus that the solution is merely more education or better critical thinking skills. But that is not entirely right.

Sometimes false beliefs persist and spread even in communities where everyone works very hard to learn the truth by gathering and sharing evidence. In these cases, the problem is not unthinking trust. It goes far deeper than that.

The info is here.

Wednesday, November 27, 2019

Corruption Is Contagious: Dishonesty begets dishonesty, rapidly spreading unethical behavior through a society

Dan Ariely & Ximena Garcia-Rada
Scientific American
September 2019

Here is an excerpt:

This is because social norms—the patterns of behavior that are accepted as normal—impact how people will behave in many situations, including those involving ethical dilemmas. In 1991 psychologists Robert B. Cialdini, Carl A. Kallgren and Raymond R. Reno drew the important distinction between descriptive norms—the perception of what most people do—and injunctive norms—the perception of what most people approve or disapprove of. We argue that both types of norms influence bribery.

Simply put, knowing that others are paying bribes to obtain preferential treatment (a descriptive norm) makes people feel that it is more acceptable to pay a bribe themselves.

Similarly, thinking that others believe that paying a bribe is acceptable (an injunctive norm) will make people feel more comfortable when accepting a bribe request. Bribery becomes normative, affecting people's moral character.

In 2009 Ariely, with behavioral researchers Francesca Gino and Shahar Ayal, published a study showing how powerful social norms can be in shaping dishonest behavior. In two lab studies, they assessed the circumstances in which exposure to others' unethical behavior would change someone's ethical decision-making. Group membership turned out to have a significant effect: When individuals observed an in-group member behaving dishonestly (a student with a T-shirt suggesting he or she was from the same school cheating in a test), they, too, behaved dishonestly. In contrast, when the person behaving dishonestly was an out-group member (a student with a T-shirt from the rival school), observers acted more honestly.

But social norms also vary from culture to culture: What is acceptable in one culture might not be acceptable in another. For example, in some societies giving gifts to clients or public officials demonstrates respect for a business relationship, whereas in other cultures it is considered bribery. Similarly, gifts for individuals in business relationships can be regarded either as lubricants of business negotiations, in the words of behavioral economists Michel André Maréchal and Christian Thöni, or as questionable business practices. And these expectations and rules about what is accepted are learned and reinforced by observation of others in the same group. Thus, in countries where individuals regularly learn that others are paying bribes to obtain preferential treatment, they determine that paying bribes is socially acceptable. Over time the line between ethical and unethical behavior becomes blurry, and dishonesty becomes the “way of doing business.”

The info is here.

Tuesday, February 28, 2017

Creativity in unethical behavior attenuates condemnation and breeds social contagion when transgressions seem to create little harm

Scott S. Wiltermuth, Lynne C. Vincent, Francesca Gino
Organizational Behavior and Human Decision Processes
Volume 139, March 2017, Pages 106–126

Abstract

Across six studies, people judged creative forms of unethical behavior to be less unethical than less creative forms of unethical behavior, particularly when the unethical behaviors imposed relatively little direct harm on victims. As a result of perceiving behaviors to be less unethical, people punished highly creative forms of unethical behavior less severely than they punished less-creative forms of unethical behavior. They were also more likely to emulate the behavior themselves. The findings contribute to theory by showing that perceptions of competence can positively color morality judgments, even when the competence displayed stems from committing an unethical act. The findings are the first to show that people are judged as morally better for performing bad deeds well as compared to performing bad deeds poorly. Moreover, the results illuminate how the characteristics of an unethical behavior can interact to influence the emulation and diffusion of that behavior.

The article is here.

Thursday, October 2, 2014

In a Study, Text Messages Add Up to a Balance Sheet of Everyday Morality

By Benedict Carey
The New York Times
Originally posted September 11, 2014

Committing a small act of kindness, like holding the door for a harried stranger, often prompts the recipient to extend a hand to others, but it comes at a cost, psychologists have long argued. People who have done the good deed are primed to commit a rude one later on, as if drawing on moral credit from their previous act.

Now, in a novel survey of everyday moral behavior, researchers have tested whether that theory holds up in real life. It does, though the effects appear small.

The findings come from a survey of everyday morality in which researchers tracked people’s moral judgments and attitudes at regular intervals throughout a typical day, using text messages.

The entire article is here.

Sunday, June 2, 2013

Schoolmates of suicide victims at higher risk

By Kathryn Doyle
Reuters
Originally published May 21, 2013

Teens who have a classmate die of suicide are more likely to consider taking, or attempt to take, their own lives, according to a new study.

The idea that suicide might be "contagious" has been around for centuries, senior author Dr. Ian Colman, who studies mental health at the University of Ottawa, told Reuters Health.

Past studies supported the idea, but none had looked at such a large body of students, he said.
"There were a lot of surprising things about this study, we were surprised that the effect lasted so long and just how strong it was," Colman said.

Colman and his colleagues used data from a long-running national survey of more than 8,000 Canadian kids aged 12 to 17 years old. Students were asked about suicides of schoolmates, friends and their own thoughts of suicide, and researchers checked in with the kids two years later.

By the age of 17, one in four kids had a schoolmate who had committed suicide, and one in five knew the deceased personally, according to results published in the Canadian Medical Association Journal.

The entire article is here.

Source Article: Association between exposure to suicide and suicidality outcomes in youth

CMAJ 2013. DOI:10.1503/cmaj.121377

Abstract

Background: Ecological studies support the hypothesis that suicide may be "contagious" (i.e., exposure to suicide may increase the risk of suicide and related outcomes). However, this association has not been adequately assessed in prospective studies. We sought to determine the association between exposure to suicide and suicidality outcomes in Canadian youth.

Methods: We used baseline information from the Canadian National Longitudinal Survey of Children and Youth between 1998/99 and 2006/07 with follow-up assessments 2 years later. We included all respondents aged 12–17 years in cycles 3–7 with reported measures of exposure to suicide.

Results: We included 8766 youth aged 12–13 years, 7802 aged 14–15 years and 5496 aged 16–17 years. Exposure to a schoolmate's suicide was associated with ideation at baseline among respondents aged 12–13 years (odds ratio [OR] 5.06, 95% confidence interval [CI] 3.04–8.40), 14–15 years (OR 2.93, 95% CI 2.02–4.24) and 16–17 years (OR 2.23, 95% CI 1.43–3.48). Such exposure was associated with attempts among respondents aged 12–13 years (OR 4.57, 95% CI 2.39–8.71), 14–15 years (OR 3.99, 95% CI 2.46–6.45) and 16–17 years (OR 3.22, 95% CI 1.62–6.41). Personally knowing someone who died by suicide was associated with suicidality outcomes for all age groups. We also assessed 2-year outcomes among respondents aged 12–15 years: a schoolmate's suicide predicted suicide attempts among participants aged 12–13 years (OR 3.07, 95% CI 1.05–8.96) and 14–15 years (OR 2.72, 95% CI 1.47–5.04). Among those who reported a schoolmate's suicide, personally knowing the decedent did not alter the risk of suicidality.

Interpretation: We found that exposure to suicide predicts suicide ideation and attempts. Our results support school-wide interventions over current targeted interventions, particularly over strategies that target interventions toward children closest to the decedent.


The source article is here.