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

Friday, December 4, 2020

Blind loyalty? When group loyalty makes us see evil or engage in it

J. A. Hildreth, F. Gino, & M. Bazerman
Organizational Behavior and 
Human Decision Processes
Volume 132, January 2016, 16-36

Abstract

Loyalty often drives corruption. Corporate scandals, political machinations, and sports cheating highlight how loyalty’s pernicious nature manifests in collusion, conspiracy, cronyism, nepotism, and other forms of cheating. Yet loyalty is also touted as an ethical principle that guides behavior. Drawing on moral psychology and behavioral ethics research, we developed hypotheses about when group loyalty fosters ethical behavior and when it fosters corruption. Across nine studies, we found that individuals primed with loyalty cheated less than those not primed (Study 1A and 1B). Members more loyal to their fraternities (Study 2A) and students more loyal to their study groups (Study 2B) also cheated less than their less loyal counterparts due to greater ethical salience when they pledged their loyalty (Studies 3A and 3B). Importantly, competition moderated these effects: when competition was high, members more loyal to their fraternities (Study 4) or individuals primed with loyalty (Studies 5A and 5B) cheated more.

Highlights

• We define loyalty as the principle of partiality toward an object (e.g. group).

• Across nine studies we found that loyalty reduced rather than increased cheating when group goals were unclear.

• Pledging loyalty increased the salience of ethics which led to less cheating.

• Competition moderated these effects: when competition was high the loyal cheated more.

• The findings are consistent with loyalty’s role as an ethical principle.

Thursday, December 3, 2020

The psychologist rethinking human emotion

David Shariatmadari
The Guardian
Originally posted 25 Sept 20

Here is an excerpt:

Barrett’s point is that if you understand that “fear” is a cultural concept, a way of overlaying meaning on to high arousal and high unpleasantness, then it’s possible to experience it differently. “You know, when you have high arousal before a test, and your brain makes sense of it as test anxiety, that’s a really different feeling than when your brain makes sense of it as energised determination,” she says. “So my daughter, for example, was testing for her black belt in karate. Her sensei was a 10th degree black belt, so this guy is like a big, powerful, scary guy. She’s having really high arousal, but he doesn’t say to her, ‘Calm down’; he says, ‘Get your butterflies flying in formation.’” That changed her experience. Her brain could have made anxiety, but it didn’t, it made determination.”

In the lectures Barrett gives to explain this model, she talks of the brain as a prisoner in a dark, silent box: the skull. The only information it gets about the outside world comes via changes in light (sight), air pressure (sound) exposure to chemicals (taste and smell), and so on. It doesn’t know the causes of these changes, and so it has to guess at them in order to decide what to do next.

How does it do that? It compares those changes to similar changes in the past, and makes predictions about the current causes based on experience. Imagine you are walking through a forest. A dappled pattern of light forms a wavy black shape in front of you. You’ve seen many thousands of images of snakes in the past, you know that snakes live in the forest. Your brain has already set in train an array of predictions.

The point is that this prediction-making is consciousness, which you can think of as a constant rolling process of guesses about the world being either confirmed or proved wrong by fresh sensory inputs. In the case of the dappled light, as you step forward you get information that confirms a competing prediction that it’s just a stick: the prediction of a snake was ultimately disproved, but not before it grew so strong that neurons in your visual cortex fired as though one was actually there, meaning that for a split second you “saw” it. So we are all creating our world from moment to moment. If you didn’t, your brain wouldn’t be able make the changes necessary for your survival quickly enough. If the prediction “snake” wasn’t already in train, then the shot of adrenaline you might need in order to jump out of its way would come too late.

Wednesday, December 2, 2020

Do antidepressants work?

Jacob Stegenga
aeon.co
Originally published 5 Mar 19

Here is an excerpt:

To see this, consider an analogy. Imagine we are testing a drug for weight loss. For every 100 subjects in the drug group, three subjects lose one kilogramme and 97 subjects gain five kilos. For every 100 subjects in the placebo group, two lose four kilos and 98 subjects do not gain or lose any weight. How effective is the drug for weight loss? The odds ratio of weight loss is 1.5, and yet this number tells us nothing about how much weight people on average gain or lose – indeed, the number entirely conceals the real effects of the drug. Though this is an extreme analogy, it shows how cautious we must be when interpreting this celebrated meta-analysis. Unfortunately, however, in response to this work, many leading psychiatrists celebrated, and news headlines misleadingly claimed ‘The drugs do work.’ On the winding route from the hard work of these researchers to the news reports where you were most likely to hear about that study, a simple number became a lie.

When analysed properly, the best evidence indicates that antidepressants are not clinically beneficial. The meta-analyses worth considering, such as the one above, involve attempts to gather evidence from all trials on antidepressants, including those that remain unpublished. Of course it is impossible to know that a meta-analysis includes all unpublished evidence, because publication bias is characterised by deception, either inadvertent or wilful. Nevertheless, these meta-analyses are serious attempts to address publication bias by finding as much data as possible. What, then, do they show?

In meta-analyses that include as much of the evidence as possible, the severity of depression among subjects who receive antidepressants goes down by approximately two points compared with subjects who receive a placebo. Two points. Remember, a depression score can go down by double that amount simply if a subject stops fidgeting. This result, found by both champions and critics of antidepressants, has been replicated year after year for more than a decade (see, for example, the meta-analyses led by Irving Kirsch in 2008, by J C Fournier in 2010, and by Janus Christian Jakobsen in 2017). The phenomena of blind-breaking, the placebo effect and unresolved publication bias could easily account for this trivial two-point reduction in severity scores.

Tuesday, December 1, 2020

Using Machine Learning to Generate Novel Hypotheses: Increasing Optimism About COVID-19 Makes People Less Willing to Justify Unethical Behaviors

Sheetal A, Feng Z, Savani K. 
Psychological Science. 2020;31(10):
1222-1235. 
doi:10.1177/0956797620959594

Abstract

How can we nudge people to not engage in unethical behaviors, such as hoarding and violating social-distancing guidelines, during the COVID-19 pandemic? Because past research on antecedents of unethical behavior has not provided a clear answer, we turned to machine learning to generate novel hypotheses. We trained a deep-learning model to predict whether or not World Values Survey respondents perceived unethical behaviors as justifiable, on the basis of their responses to 708 other items. The model identified optimism about the future of humanity as one of the top predictors of unethicality. A preregistered correlational study (N = 218 U.S. residents) conceptually replicated this finding. A preregistered experiment (N = 294 U.S. residents) provided causal support: Participants who read a scenario conveying optimism about the COVID-19 pandemic were less willing to justify hoarding and violating social-distancing guidelines than participants who read a scenario conveying pessimism. The findings suggest that optimism can help reduce unethicality, and they document the utility of machine-learning methods for generating novel hypotheses.

Here is how the research article begins:

Unethical behaviors can have substantial consequences in times of crisis. For example, in the midst of the COVID-19 pandemic, many people hoarded face masks and hand sanitizers; this hoarding deprived those who needed protective supplies most (e.g., medical workers and the elderly) and, therefore, put them at risk. Despite escalating deaths, more than 50,000 people were caught violating quarantine orders in Italy, putting themselves and others at risk. Governments covered up the scale of the pandemic in that country, thereby allowing the infection to spread in an uncontrolled manner. Thus, understanding antecedents of unethical behavior and identifying nudges to reduce unethical behaviors are particularly important in times of crisis.

Here is part of the Discussion

We formulated a novel hypothesis—that optimism reduces unethicality—on the basis of the deep-learning model’s finding that whether people think that the future of humanity is bleak or bright is a strong predictor of unethicality. This variable was not flagged as a top predictor either by the correlational analysis or by the lasso regression. Consistent with this idea, the results of a correlational study showed that people higher on dispositional optimism were less willing to engage in unethical behaviors. A following experiment found that increasing participants’ optimism about the COVID-19 epidemic reduced the extent to which they justified unethical behaviors related to the epidemic. The behavioral studies were conducted with U.S. American participants; thus, the cultural generalizability of the present findings is unclear. Future research needs to test whether optimism reduces unethical behavior in other cultural contexts.

Monday, November 30, 2020

In Japan, more people died from suicide last month than from Covid in all of 2020

S. Wang, R. Wright, & Y. Wakatsuki
CNN.com
Originally posted 29 Nov 20

Here is an excerpt:

In Japan, government statistics show suicide claimed more lives in October than Covid-19 has over the entire year to date. The monthly number of Japanese suicides rose to 2,153 in October, according to Japan's National Police Agency. As of Friday, Japan's total Covid-19 toll was 2,087, the health ministry said.

Japan is one of the few major economies to disclose timely suicide data -- the most recent national data for the US, for example, is from 2018. The Japanese data could give other countries insights into the impact of pandemic measures on mental health, and which groups are the most vulnerable.

"We didn't even have a lockdown, and the impact of Covid is very minimal compared to other countries ... but still we see this big increase in the number of suicides," said Michiko Ueda, an associate professor at Waseda University in Tokyo, and an expert on suicides.

"That suggests other countries might see a similar or even bigger increase in the number of suicides in the future."

(cut)

Compounding those worries about income, women have been dealing with skyrocketing unpaid care burdens, according to the study. For those who keep their jobs, when children are sent home from school or childcare centers, it often falls to mothers to take on those responsibilities, as well as their normal work duties.

Increased anxiety about the health and well-being of children has also put an extra burden on mothers during the pandemic.

Sunday, November 29, 2020

Freerolls and binds: making policy when information is missing

Duke, A. & Sunstein, C.
(2020). Behavioural Public Policy, 1-22. 

Abstract

When policymakers focus on costs and benefits, they often find that hard questions become easy – as, for example, when the benefits clearly exceed the costs, or when the costs clearly exceed the benefits. In some cases, however, benefits or costs are difficult to quantify, perhaps because of limitations in scientific knowledge. In extreme cases, policymakers are proceeding in circumstances of uncertainty rather than risk, in the sense that they cannot assign probabilities to various outcomes. We suggest that in difficult cases in which important information is absent, it is useful for policymakers to consider a concept from poker: ‘freerolls.’ A freeroll exists when choosers can lose nothing from selecting an option but stand to gain something (whose magnitude may itself be unknown). In some cases, people display ‘freeroll neglect.’ In terms of social justice, John Rawls’ defense of the difference principle is grounded in the idea that, behind the veil of ignorance, choosers have a freeroll. In terms of regulatory policy, one of the most promising defenses of the Precautionary Principle sees it as a kind of freeroll. Some responses to climate change, pandemics and financial crises can be seen as near-freerolls. Freerolls and near-freerolls must be distinguished from cases involving cumulatively high costs and also from faux freerolls, which can be found when the costs of an option are real and significant, but not visible. ‘Binds’ are the mirror-image of freerolls; they involve options from which people are guaranteed to lose something (of uncertain magnitude). Some regulatory options are binds, and there are faux binds as well.

From the Conclusion

In ordinary life, people may be asked whether they want a freeroll, in the form of a good or opportunity from which they will lose nothing, but from which they gain something of value, when the magnitude of the gain cannot be specified. The gain might take the form of the elimination of a risk. More commonly, people are given near-freerolls, because they have to pay something for the option. Often what they have to pay is very low, which makes the deal a good one. The central point here is an asymmetry in what people know. They know the costs, while they have large epistemic gaps with respect to the potential gains. People often fall prey to ‘freeroll neglect.’ When this is so, they do not see pure or near-freerolls; they seek missing information before choosing among options, even though they have no need to do so.

Freerolls are mirrored by binds, in which people are given an option from which they can only lose, even though they do not know how much they might lose. To know that binds are undesirable, the chooser need not have full knowledge about the range of possible downside outcomes. Nor need the chooser know anything about the shape of the distribution of those outcomes.

Saturday, November 28, 2020

Toward a Hierarchical Model of Social Cognition: A Neuroimaging Meta-Analysis and Integrative Review of Empathy and Theory of Mind

Schurz, M. et al.
Psychological Bulletin. 
Advance online publication. 

Abstract

Along with the increased interest in and volume of social cognition research, there has been higher awareness of a lack of agreement on the concepts and taxonomy used to study social processes. Two central concepts in the field, empathy and Theory of Mind (ToM), have been identified as overlapping umbrella terms for different processes of limited convergence. Here, we review and integrate evidence of brain activation, brain organization, and behavior into a coherent model of social-cognitive processes. We start with a meta-analytic clustering of neuroimaging data across different social-cognitive tasks. Results show that understanding others’ mental states can be described by a multilevel model of hierarchical structure, similar to models in intelligence and personality research. A higher level describes more broad and abstract classes of functioning, whereas a lower one explains how functions are applied to concrete contexts given by particular stimulus and task formats. Specifically, the higher level of our model suggests 3 groups of neurocognitive processes: (a) predominantly cognitive processes, which are engaged when mentalizing requires self-generated cognition decoupled from the physical world; (b) more affective processes, which are engaged when we witness emotions in others based on shared emotional, motor, and somatosensory representations; (c) combined processes, which engage cognitive and affective functions in parallel. We discuss how these processes are explained by an underlying principal gradient of structural brain organization. Finally, we validate the model by a review of empathy and ToM task interrelations found in behavioral studies.

Public Significance Statement

Empathy and Theory of Mind are important human capacities for understanding others. Here, we present a meta-analysis of neuroimaging data from 4,207 participants, which shows that these abilities can be deconstructed into specific and partially shared neurocognitive subprocesses. Our findings provide systematic, large-scale support for the hypothesis that understanding others’ mental states can be described by a multilevel model of hierarchical structure, similar to models in intelligence and personality research.

Friday, November 27, 2020

Where Are The Self-Correcting Mechanisms In Science?

Vazire, S., & Holcombe, A. O. 
(2020, August 13).

Abstract

It is often said that science is self-correcting, but the replication crisis suggests that, at least in some fields, self-correction mechanisms have fallen short of what we might hope for. How can we know whether a particular scientific field has effective self-correction mechanisms, that is, whether its findings are credible? The usual processes that supposedly provide mechanisms for scientific self-correction – mainly peer review and disciplinary committees – have been inadequate. We argue for more verifiable indicators of a field’s commitment to self-correction. These include transparency, which is already a target of many reform efforts, and critical appraisal, which has received less attention. Only by obtaining Measurements of Observable Self-Correction (MOSCs) can we begin to evaluate the claim that “science is self-correcting.” We expect the validity of this claim to vary across fields and subfields, and suggest that some fields, such as psychology and biomedicine, fall far short of an appropriate level of transparency and, especially, critical appraisal. Fields without robust, verifiable mechanisms for transparency and critical appraisal cannot reasonably be said to be self-correcting, and thus do not warrant the credibility often imputed to science as a whole.

Thursday, November 26, 2020

Oncologist Pays for Patient's Meds: A 'Boundary' Crossed?

Nic Mulcahy
medscape.com
Originally posted 4 Nov 20

It was an act of kindness: while overseeing a patient through a round of chemotherapy, an oncology fellow at Johns Hopkins University's Kimmel Comprehensive Cancer Center in Baltimore, Maryland, paid a modest amount of money (about $10) for that patient's antiemetic medication and retrieved it from the center's pharmacy.

Co-fellow Arjun Gupta, MD, witnessed the act and shared it with the world September 23 on Twitter.

"Just observed a co-fellow pay the co-pay for a patient's post-chemo nausea meds at the pharmacy, arrange them in a pill box, and deliver them to the patient in the infusion center. So that the patient could just leave after chemo."

Healthcare professionals applauded the generosity. "Phenomenal care," tweeted Carolyn Alexander, MD, a fertility physician in Los Angeles.

It's a common occurrence, said others. "Go ask a nurse how many times they've done it. I see it happen weekly," tweeted Chelsea Mitchell, PharmD, an intensive care unit pharmacist in Memphis, Tennessee.

Lack of universal healthcare brings about these moments, claimed multiple professionals who read Gupta's anecdote. "#ThisIsDoctoring. This is also a shameful indictment of our medical system," said Mary Landrigan-Ossar, MD, an anesthesiologist at Children's Hospital, Boston, Massachusetts.

However, one observer called out something no one else had ― that paying for a patient's medication is not allowed in some facilities.