When Institutions Harm Those Who Depend on Them: A Scoping Review of Institutional Betrayal

Christl, M. E., et al. (2024).

Trauma, violence & abuse

15248380241226627.

Advance online publication.

https://doi.org/10.1177/15248380241226627

Abstract

The term institutional betrayal (Smith and Freyd, 2014) builds on the conceptual framework of betrayal trauma theory (see Freyd, 1996) to describe the ways that institutions (e.g., universities, workplaces) fail to take appropriate steps to prevent and/or respond appropriately to interpersonal trauma. A nascent literature has begun to describe individual costs associated with institutional betrayal throughout the United States (U.S.), with implications for public policy and institutional practice. A scoping review was conducted to quantify existing study characteristics and key findings to guide research and practice going forward. Multiple academic databases were searched for keywords (i.e., "institutional betrayal" and "organizational betrayal"). Thirty-seven articles met inclusion criteria (i.e., peer-reviewed empirical studies of institutional betrayal) and were included in analyses. Results identified research approaches, populations and settings, and predictor and outcome variables frequently studied in relation to institutional betrayal. This scoping review describes a strong foundation of published studies and provides recommendations for future research, including longitudinal research with diverse individuals across diverse institutional settings. The growing evidence for action has broad implications for research-informed policy and institutional practice.

Here is my summary:

A growing body of research examines institutional betrayal, the harm institutions cause people who depend on them. This research suggests institutional betrayal is linked to mental and physical health problems, absenteeism from work, and a distrust of institutions. A common tool to measure institutional betrayal is the Institutional Betrayal Questionnaire (IBQ). Researchers are calling for more studies on institutional betrayal among young people and in settings like K-12 schools and workplaces. Additionally, more research is needed on how institutions respond to reports of betrayal and how to prevent it from happening in the first place. Finally, future research should focus on people from minority groups, as they may be more vulnerable to institutional betrayal.

LSD-Based Medication for GAD Receives FDA Breakthrough Status

Megan Brooks

Medscape.com

Originally posted March 08, 2024

The US Food and Drug Administration (FDA) has granted breakthrough designation to an LSD-based treatment for generalized anxiety disorder (GAD) based on promising topline data from a phase 2b clinical trial. Mind Medicine (MindMed) Inc is developing the treatment — MM120 (lysergide d-tartrate).

In a news release the company reports that a single oral dose of MM120 met its key secondary endpoint, maintaining "clinically and statistically significant" reductions in Hamilton Anxiety Scale (HAM-A) score, compared with placebo, at 12 weeks with a 65% clinical response rate and 48% clinical remission rate.

The company previously announced statistically significant improvements on the HAM-A compared with placebo at 4 weeks, which was the trial's primary endpoint.

"I've conducted clinical research studies in psychiatry for over two decades and have seen studies of many drugs under development for the treatment of anxiety. That MM120 exhibited rapid and robust efficacy, solidly sustained for 12 weeks after a single dose, is truly remarkable," study investigator David Feifel, MD, PhD, professor emeritus of psychiatry at the University of California, San Diego, and director of the Kadima Neuropsychiatry Institute in La Jolla, California, said in the news release.

The info is here.

Here is some information from the Press Release from Mind Medicine.

About MM120

Lysergide is a synthetic ergotamine belonging to the group of classic, or serotonergic, psychedelics, which acts as a partial agonist at human serotonin-2A (5-hydroxytryptamine-2A [5-HT2A]) receptors. MindMed is developing MM120 (lysergide D-tartrate), the tartrate salt form of lysergide, for GAD and is exploring its potential applications in other serious brain health disorders.

About MindMed

MindMed is a clinical stage biopharmaceutical company developing novel product candidates to treat brain health disorders. Our mission is to be the global leader in the development and delivery of treatments that unlock new opportunities to improve patient outcomes. We are developing a pipeline of innovative product candidates, with and without acute perceptual effects, targeting neurotransmitter pathways that play key roles in brain health disorders.

MindMed trades on NASDAQ under the symbol MNMD and on the Cboe Canada (formerly known as the NEO Exchange, Inc.) under the symbol MMED.

Ageism in health care is more common than you might think, and it can harm people

Ashley Milne-Tyte

npr.org

Originally posted 7 March 24

A recent study found that older people spend an average of 21 days a year on medical appointments. Kathleen Hayes can believe it.

Hayes lives in Chicago and has spent a lot of time lately taking her parents, who are both in their 80s, to doctor's appointments. Her dad has Parkinson's, and her mom has had a difficult recovery from a bad bout of Covid-19. As she's sat in, Hayes has noticed some health care workers talk to her parents at top volume, to the point, she says, "that my father said to one, 'I'm not deaf, you don't have to yell.'"

In addition, while some doctors and nurses address her parents directly, others keep looking at Hayes herself.

"Their gaze is on me so long that it starts to feel like we're talking around my parents," says Hayes, who lives a few hours north of her parents. "I've had to emphasize, 'I don't want to speak for my mother. Please ask my mother that question.'"

Researchers and geriatricians say that instances like these constitute ageism – discrimination based on a person's age – and it is surprisingly common in health care settings. It can lead to both overtreatment and undertreatment of older adults, says Dr. Louise Aronson, a geriatrician and professor of geriatrics at the University of California, San Francisco.

"We all see older people differently. Ageism is a cross-cultural reality," Aronson says.

The info is here.

Here is my summary:

This article and other research point to a concerning prevalence of ageism in healthcare settings. This bias can take the form of either overtreatment or undertreatment of older adults.

Negative stereotypes: Doctors may hold assumptions about older adults being less willing or able to handle aggressive treatments, leading to missed opportunities for care.

Communication issues: Sometimes healthcare providers speak to adult children instead of the older person themselves, disregarding their autonomy.

These biases are linked to poorer health outcomes and can even shorten lifespans.  The article cites a study suggesting that ageism costs the healthcare system billions of dollars annually.  There are positive steps that can be taken, such as anti-bias training for healthcare workers.

Ready or not, AI chatbots are here to help with Gen Z’s mental health struggles

Matthew Perrone

AP.com

Originally posted 23 March 24

Here is an excerpt:

Earkick is one of hundreds of free apps that are being pitched to address a crisis in mental health among teens and young adults. Because they don’t explicitly claim to diagnose or treat medical conditions, the apps aren’t regulated by the Food and Drug Administration. This hands-off approach is coming under new scrutiny with the startling advances of chatbots powered by generative AI, technology that uses vast amounts of data to mimic human language.

The industry argument is simple: Chatbots are free, available 24/7 and don’t come with the stigma that keeps some people away from therapy.

But there’s limited data that they actually improve mental health. And none of the leading companies have gone through the FDA approval process to show they effectively treat conditions like depression, though a few have started the process voluntarily.

“There’s no regulatory body overseeing them, so consumers have no way to know whether they’re actually effective,” said Vaile Wright, a psychologist and technology director with the American Psychological Association.

Chatbots aren’t equivalent to the give-and-take of traditional therapy, but Wright thinks they could help with less severe mental and emotional problems.

Earkick’s website states that the app does not “provide any form of medical care, medical opinion, diagnosis or treatment.”

Some health lawyers say such disclaimers aren’t enough.

The info is here.

Here is my summary:

AI chatbots can provide personalized, 24/7 mental health support and guidance to users through convenient mobile apps. They use natural language processing and machine learning to simulate human conversation and tailor responses to individual needs.

 This can be especially beneficial for those who face barriers to accessing traditional in-person therapy, such as cost, location, or stigma.

Research has shown that AI chatbots can be effective in reducing the severity of mental health issues like anxiety, depression, and stress for diverse populations.  They can deliver evidence-based interventions like cognitive behavioral therapy and promote positive psychology.  Some well-known examples include Wysa, Woebot, Replika, Youper, and Tess.

However, there are also ethical concerns around the use of AI chatbots for mental health. There are risks of providing inadequate or even harmful support if the chatbot cannot fully understand the user's needs or respond empathetically. Algorithmic bias in the training data could also lead to discriminatory advice. It's crucial that users understand the limitations of the therapeutic relationship with an AI chatbot versus a human therapist.

Overall, AI chatbots have significant potential to expand access to mental health support, but must be developed and deployed responsibly with strong safeguards to protect user wellbeing. Continued research and oversight will be needed to ensure these tools are used effectively and ethically.

Perceptions of Falling Behind “Most White People”: Within-Group Status Comparisons Predict Fewer Positive Emotions and Worse Health Over Time Among White (but Not Black) Americans

Caluori, N., Cooley, E., et al. (2024).

Psychological Science, 35(2), 175-190.

https://doi.org/10.1177/09567976231221546

Abstract

Despite the persistence of anti-Black racism, White Americans report feeling worse off than Black Americans. We suggest that some White Americans may report low well-being despite high group-level status because of perceptions that they are falling behind their in-group. Using census-based quota sampling, we measured status comparisons and health among Black (N = 452, Wave 1) and White (N = 439, Wave 1) American adults over a period of 6 to 7 weeks. We found that Black and White Americans tended to make status comparisons within their own racial groups and that most Black participants felt better off than their racial group, whereas most White participants felt worse off than their racial group. Moreover, we found that White Americans’ perceptions of falling behind “most White people” predicted fewer positive emotions at a subsequent time, which predicted worse sleep quality and depressive symptoms in the future. Subjective within-group status did not have the same consequences among Black participants.

The research is here.

Here is my succinct summary:

Despite their high group status, many White Americans experience poor well-being due to the perception that they are lagging behind their in-group. In contrast, Black Americans feel relatively better off within their racial group, while White Americans feel comparatively worse off within theirs.

The Puzzle of Evaluating Moral Cognition in Artificial Agents

Reinecke, M. G., Mao, Y., et al. (2023).

Cognitive Science, 47(8).

https://doi.org/10.1111/cogs.13315

Abstract

In developing artificial intelligence (AI), researchers often benchmark against human performance as a measure of progress. Is this kind of comparison possible for moral cognition? Given that human moral judgment often hinges on intangible properties like “intention” which may have no natural analog in artificial agents, it may prove difficult to design a “like-for-like” comparison between the moral behavior of artificial and human agents. What would a measure of moral behavior for both humans and AI look like? We unravel the complexity of this question by discussing examples within reinforcement learning and generative AI, and we examine how the puzzle of evaluating artificial agents' moral cognition remains open for further investigation within cognitive science.

The link to the article is the hyperlink above.

Here is my summary:

This article delves into the challenges associated with assessing the moral decision-making capabilities of artificial intelligence systems. It explores the complexities of imbuing AI with ethical reasoning and the difficulties in evaluating their moral cognition. The article discusses the need for robust frameworks and methodologies to effectively gauge the ethical behavior of AI, highlighting the intricate nature of integrating morality into machine learning algorithms. Overall, it emphasizes the critical importance of developing reliable methods to evaluate the moral reasoning of artificial agents in order to ensure their responsible and ethical deployment in various domains.

Daniel Kahneman, pioneering behavioral psychologist, Nobel laureate and ‘giant in the field,’ dies at 90

Jaime Saxon

Office of Communications - Princeton

Originally released 28 March 24

Daniel Kahneman, the Eugene Higgins Professor of Psychology, Emeritus, professor of psychology and public affairs, emeritus, and a Nobel laureate in economics whose groundbreaking behavioral science research changed our understanding of how people think and make decisions, died on March 27. He was 90.

Kahneman joined the Princeton University faculty in 1993, following appointments at Hebrew University, the University of British Columbia and the University of California–Berkeley, and transferred to emeritus status in 2007.

“Danny Kahneman changed how we understand rationality and its limits,” said Princeton President Christopher L. Eisgruber. “His scholarship pushed the frontiers of knowledge, inspired generations of students, and influenced leaders and thinkers throughout the world. We are fortunate that he made Princeton his home for so much of his career, and we will miss him greatly.”

In collaboration with his colleague and friend of nearly 30 years, the late Amos Tversky of Stanford University, Kahneman applied cognitive psychology to economic analysis, laying the foundation for a new field of research — behavioral economics — and earning Kahneman the Nobel Prize in Economics in 2002. Kahneman and Tversky’s insights on human judgment have influenced a wide range of disciplines, including economics, finance, medicine, law, politics and policy.

The Nobel citation commended Kahneman “for having integrated insights from psychological research into economic science, especially concerning human judgment and decision-making under uncertainty.”

“His work has inspired a new generation of researchers in economics and finance to enrich economic theory using insights from cognitive psychology into intrinsic human motivation,” the citation said. Kahneman shared the Nobel, formally the Sveriges Riksbank Prize in Economic Sciences in Memory of Alfred Nobel, with American economist Vernon L. Smith.

The info is here.

Here is my personal reflection:

Daniel Kahneman, a giant in psychology and economics, passed away recently. He revolutionized our understanding of human decision-making, revealing the biases and shortcuts that shape our choices. Through his work, he not only improved economic models but also empowered individuals to make more informed and rational decisions. His legacy will continue to influence fields far beyond his own.  May his memory be a blessing.

Lifetime Suicide Attempts in Otherwise Psychiatrically Healthy Individuals

Oquendo, M. A., et al. (2024).

JAMA psychiatry, e235672.

Advance online publication.

https://doi.org/10.1001/jamapsychiatry.2023.5672

Abstract

Importance: Not all people who die by suicide have a psychiatric diagnosis; yet, little is known about the percentage and demographics of individuals with lifetime suicide attempts who are apparently psychiatrically healthy. If such suicide attempts are common, there are implications for suicide risk screening, research, policy, and nosology.

Objective: To estimate the percentage of people with lifetime suicide attempts whose first attempt occurred prior to onset of any psychiatric disorder.

Design, setting, and participants: This cross-sectional study used data from the US National Epidemiologic Study of Addictions and Related Conditions III (NESARC-III), a cross-sectional face-to-face survey conducted with a nationally representative sample of the US civilian noninstitutionalized population, and included persons with lifetime suicide attempts who were aged 20 to 65 years at survey administration (April 2012 to June 2013). Data from the NESARC, Wave 2 survey from August 2004 to September 2005 were used for replication. Analyses were performed from April to August 2023.

Exposure: Lifetime suicide attempts.

Main outcomes and measures: The main outcome was presence or absence of a psychiatric disorder before the first lifetime suicide attempt. Among persons with lifetime suicide attempts, the percentage and 95% CI of those whose first suicide attempt occurred before the onset of any apparent psychiatric disorders was calculated, weighted by NESARC sampling and nonresponse weights. Separate analyses were performed for males, females, and 3 age groups (20 to <35, 35-50, and >50 to 65 years).

Conclusions and relevance: In this study, an estimated 19.6% of individuals who attempted suicide did so despite not meeting criteria for an antecedent psychiatric disorder. This finding challenges clinical notions of who is at risk for suicidal behavior and raises questions about the safety of limiting suicide risk screening to psychiatric populations.

How digital media drive affective polarization through partisan sorting

Törnberg, P. (2022).

PNAS of the United States of America,

119(42).

https://doi.org/10.1073/pnas.2207159119

Abstract

Politics has in recent decades entered an era of intense polarization. Explanations have implicated digital media, with the so-called echo chamber remaining a dominant causal hypothesis despite growing challenge by empirical evidence. This paper suggests that this mounting evidence provides not only reason to reject the echo chamber hypothesis but also the foundation for an alternative causal mechanism. To propose such a mechanism, the paper draws on the literatures on affective polarization, digital media, and opinion dynamics. From the affective polarization literature, we follow the move from seeing polarization as diverging issue positions to rooted in sorting: an alignment of differences which is effectively dividing the electorate into two increasingly homogeneous megaparties. To explain the rise in sorting, the paper draws on opinion dynamics and digital media research to present a model which essentially turns the echo chamber on its head: it is not isolation from opposing views that drives polarization but precisely the fact that digital media bring us to interact outside our local bubble. When individuals interact locally, the outcome is a stable plural patchwork of cross-cutting conflicts. By encouraging nonlocal interaction, digital media drive an alignment of conflicts along partisan lines, thus effacing the counterbalancing effects of local heterogeneity. The result is polarization, even if individual interaction leads to convergence. The model thus suggests that digital media polarize through partisan sorting, creating a maelstrom in which more and more identities, beliefs, and cultural preferences become drawn into an all-encompassing societal division.

Significance

Recent years have seen a rapid rise of affective polarization, characterized by intense negative feelings between partisan groups. This represents a severe societal risk, threatening democratic institutions and constituting a metacrisis, reducing our capacity to respond to pressing societal challenges such as climate change, pandemics, or rising inequality. This paper provides a causal mechanism to explain this rise in polarization, by identifying how digital media may drive a sorting of differences, which has been linked to a breakdown of social cohesion and rising affective polarization. By outlining a potential causal link between digital media and affective polarization, the paper suggests ways of designing digital media so as to reduce their negative consequences.