The Plunging Number of Primary Care Physicians Reaches a Tipping Point.

Elisabeth Rosenthal

KFF Health News

Originally posted 8 September 23

Here are two excerpts:

The percentage of U.S. doctors in adult primary care has been declining for years and is now about 25% — a tipping point beyond which many Americans won’t be able to find a family doctor at all.

Already, more than 100 million Americans don’t have usual access to primary care, a number that has nearly doubled since 2014. One reason our coronavirus vaccination rates were low compared with those in countries such as China, France, and Japan could be because so many of us no longer regularly see a familiar doctor we trust.

Another telling statistic: In 1980, 62% of doctor’s visits for adults 65 and older were for primary care and 38% were for specialists, according to Michael L. Barnett, a health systems researcher and primary care doctor in the Harvard Medical School system. By 2013, that ratio had exactly flipped and has likely “only gotten worse,” he said, noting sadly: “We have a specialty-driven system. Primary care is seen as a thankless, undesirable backwater.” That’s “tragic,” in his words — studies show that a strong foundation of primary care yields better health outcomes overall, greater equity in health care access, and lower per capita health costs.

One explanation for the disappearing primary care doctor is financial. The payment structure in the U.S. health system has long rewarded surgeries and procedures while shortchanging the diagnostic, prescriptive, and preventive work that is the province of primary care. Furthermore, the traditionally independent doctors in this field have little power to negotiate sustainable payments with the mammoth insurers in the U.S. market.

Faced with this situation, many independent primary care doctors have sold their practices to health systems or commercial management chains (some private equity-owned) so that, today, three-quarters of doctors are now employees of those outfits.

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Some relatively simple solutions are available, if we care enough about supporting this foundational part of a good medical system. Hospitals and commercial groups could invest some of the money they earn by replacing hips and knees to support primary care staffing; giving these doctors more face time with their patients would be good for their customers’ health and loyalty if not (always) the bottom line.

Reimbursement for primary care visits could be increased to reflect their value — perhaps by enacting a national primary care fee schedule, so these doctors won’t have to butt heads with insurers. And policymakers could consider forgiving the medical school debt of doctors who choose primary care as a profession.

They deserve support that allows them to do what they were trained to do: diagnosing, treating, and getting to know their patients.

The info is here.

Here is my warning:

The number of primary care physicians in the US is declining, and this trend is reaching a tipping point. More than 100 million Americans don't have usual access to primary care, and this number has nearly doubled since 2014. This shortage of primary care physicians could have a negative impact on public health, as people without access to primary care are more likely to delay or forgo needed care.

A Metacognitive Blindspot in Intellectual Humility Measures

Costello, T. H., Newton, C., Lin, H., & Pennycook, G.

(2023, August 6).

https://doi.org/10.31234/osf.io/gux95

Abstract

Intellectual humility (IH) is commonly defined as recognizing the limits of one’s knowledge and abilities. However, most research has relied entirely on self-report measures of IH, without testing whether these instruments capture the metacognitive core of the construct. Across two studies (Ns = 898; 914), using generalized additive mixed models to detect complex non-linear interactions, we evaluated the correspondence between widely used IH self-reports and performance on calibration and resolution paradigms designed to model the awareness of one’s mental capabilities (and their fallibility). On an overconfidence paradigm (N observations per model = 2,692-2,742), none of five IH measures attenuated the Dunning-Kruger effect, whereby poor performers overestimate their abilities and high performers underestimate them. On a confidence-accuracy paradigm (Nobservation per model = 7,223 - 12,706), most IH measures were associated with inflated confidence regardless of accuracy, or were specifically related to confidence when participants were correct but not when they were incorrect. The sole exception was the “Lack of Intellectual Overconfidence” subscale of the Comprehensive Intellectual Humility Scale, which uniquely predicted lower confidence for incorrect responses. Meanwhile, measures of Actively Open-minded Thinking reliably predicted calibration and resolution. These findings reveal substantial discrepancies between IH self-reports and metacognitive abilities, suggesting most IH measures lack validity. It may not be feasible to assess IH via self-report–as indicating a great deal of humility may, itself, be a sign of a failure in humility.

GeneralDiscussion

IH represents the ability to identify the constraints of one’s psychological, epistemic, and cultural perspective— to conduct lay phenomenology, acknowledging that the default human perspective is (literally) self-centered (Wallace, 2009) — and thereby cultivate an awareness of the limits of a single person, theory, or ideology to describe the vast and searingly complex universe. It is a process that presumably involves effortful and vigilant noticing – tallying one’s epistemic track record, and especially one’s fallibility (Ballantyne, 2021).

IH, therefore, manifests dynamically in individuals as a boundary between one’s informational environment and one’s model of reality. This portrait of IH-as-boundary appears repeatedly in philosophical and psychological treatments of IH, which frequently frame awareness of (epistemic) limitations as IH’s conceptual, metacognitive core (Leary et al., 2017; Porter, Elnakouri, et al., 2022). Yet as with a limit in mathematics, epistemic limits are appropriately defined as functions: their value is dependent on inputs (e.g., information environment, access to knowledge) that vary across contexts and individuals. Particularly, measuring IH requires identifying at least two quantities— one’s epistemic capabilities and one’s appraisal of said capabilities— from which a third, IH-qua-metacognition, can be derived as the distance between the two quantities.

Contemporary IH self-reports tend not to account for either parameter, seeming to rest instead on an auxiliary assumption: That people who are attuned to, and “own”, their epistemic limitations will generate characteristic, intellectually humble patterns of thinking and behavior. IH questionnaires then target these patterns, rather than the shared propensity for IH which the patterns ostensibly reflect.

We sought to both test and circumvent this assumption (and mono-method measurement limitation) in the present research. We did so by defining IH’s metacognitive core, functionally and statistically, in terms of calibration and resolution. We operationalized calibration as the convergence between participants’ performance on a series of epistemic tasks, on the one hand, and participants’ estimation of their own performance, on the other. Given that the relation between self-estimation and actual performance is non-linear (i.e., the Dunning-Kruger effect), there were several pathways by which IH might predict calibration: (1) decreased overestimation among low performers, (2) decreased underestimation among high performers, or (3) unilateral weakening of miscalibration among both low and high performers (for a visual representation, refer to Figure 1). Further, we operationalized epistemic resolution by assessing the relation between IH, on the one hand, individuals’ item-by-item confidence judgments for correct versus incorrect answers, on the other hand. Thus, resolution represents the capacity to distinguish between one’s correct and incorrect judgments and beliefs (a seemingly necessary prerequisite for building an accurate and calibrated model of one’s knowledge).

The research is here.

Older Americans are more vulnerable to prior exposure effects in news evaluation.

Lyons, B. A. (2023). 

Harvard Kennedy School Misinformation Review.

https://doi.org/10.37016/mr-2020-118

Outline

Older news users may be especially vulnerable to prior exposure effects, whereby news comes to be seen as more accurate over multiple viewings. I test this in re-analyses of three two-wave, nationally representative surveys in the United States (N = 8,730) in which respondents rated a series of mainstream, hyperpartisan, and false political headlines (139,082 observations). I find that prior exposure effects increase with age—being strongest for those in the oldest cohort (60+)—especially for false news. I discuss implications for the design of media literacy programs and policies regarding targeted political advertising aimed at this group.

Essay Summary

• I used three two-wave, nationally representative surveys in the United States (N = 8,730) in which respondents rated a series of actual mainstream, hyperpartisan, or false political headlines. Respondents saw a sample of headlines in the first wave and all headlines in the second wave, allowing me to determine if prior exposure increases perceived accuracy differentially across age.  

• I found that the effect of prior exposure to headlines on perceived accuracy increases with age. The effect increases linearly with age, with the strongest effect for those in the oldest age cohort (60+). These age differences were most pronounced for false news.

• These findings suggest that repeated exposure can help account for the positive relationship between age and sharing false information online. However, the size of this effect also underscores that other factors (e.g., greater motivation to derogate the out-party) may play a larger role. 

The beginning of the Implications Section

Web-tracking and social media trace data paint a concerning portrait of older news users. Older American adults were much more likely to visit dubious news sites in 2016 and 2020 (Guess, Nyhan, et al., 2020; Moore et al., 2023), and were also more likely to be classified as false news “supersharers” on Twitter, a group who shares the vast majority of dubious news on the platform (Grinberg et al., 2019). Likewise, this age group shares about seven times more links to these domains on Facebook than younger news consumers (Guess et al., 2019; Guess et al., 2021). 

Interestingly, however, older adults appear to be no worse, if not better, at identifying false news stories than younger cohorts when asked in surveys (Brashier & Schacter, 2020). Why might older adults identify false news in surveys but fall for it “in the wild?” There are likely multiple factors at play, ranging from social changes across the lifespan (Brashier & Schacter, 2020) to changing orientations to politics (Lyons et al., 2023) to cognitive declines (e.g., in memory) (Brashier & Schacter, 2020). In this paper, I focus on one potential contributor. Specifically, I tested the notion that differential effects of prior exposure to false news helps account for the disjuncture between older Americans’ performance in survey tasks and their behavior in the wild.

A large body of literature has been dedicated to exploring the magnitude and potential boundary conditions of the illusory truth effect (Hassan & Barber, 2021; Henderson et al., 2021; Pillai & Fazio, 2021)—a phenomenon in which false statements or news headlines (De keersmaecker et al., 2020; Pennycook et al., 2018) come to be believed over multiple exposures. Might this effect increase with age? As detailed by Brashier and Schacter (2020), cognitive deficits are often blamed for older news users’ behaviors. This may be because cognitive abilities are strongest in young adulthood and slowly decline beyond that point (Salthouse, 2009), resulting in increasingly effortful cognition (Hess et al., 2016). As this process unfolds, older adults may be more likely to fall back on heuristics when judging the veracity of news items (Brashier & Marsh, 2020). Repetition, the source of the illusory truth effect, is one heuristic that may be relied upon in such a scenario. This is because repeated messages feel easier to process and thus are seen as truer than unfamiliar ones (Unkelbach et al., 2019).

The essay is here.

Who supports redistribution? Replicating and refining effects of compassion, malicious envy, and self-interest

Lin, C.A., & Bates, T.C.

(2023). Evolution and Human Behavior

https://doi.org/10.1016/j.evolhumbehav.2020.08.010

Abstract

Debate over wealth redistribution plays a prominent role in society, but the causes of differences in support for redistribution remain contested. A recent three-person two-situation model suggests these differences are shaped by evolved motivational systems of self-interest, compassion, and dispositional envy. We conducted a close replication testing this prediction, all subjects were British, recruited from an online subject pool. Study 1 (N = 206) confirmed the roles of self-interest (β = 0.20) and compassion for others (β = 0.37), as well as a predicted null effect of procedural fairness. Dispositional envy was non-significant (β = 0.06). In study 2 (N = 304), we tested whether it was better to conceptualize envy as being two separate emotions, benign envy and malicious envy. A significant effect of malicious envy was found (β = 0.13) and no significant effect of benign envy (β = −0.06). Study 3 (N = 501) closely replicated this improved model, confirming significant effects of compassion (β = 0.40), self-interest (β = 0.21), and malicious envy (β = 0.15), accounting for one third of variance in support for redistribution. These results support the role of evolved motivational systems to explain and improve important aspects of contemporary economic redistribution.

A pdf is here.

The authors conducted three studies to test their hypotheses. In Study 1, they replicated the findings of a previous study that found that compassion, malicious envy, and self-interest all predict support for redistribution. In Study 2, they developed a new measure of envy and found that this measure also predicted support for redistribution. In Study 3, they found that left-political support was associated with higher support for redistribution.

The authors conclude that their findings support the hypothesis that compassion, malicious envy, and self-interest all play a role in shaping people's support for wealth redistribution. They suggest that future research should examine the relative importance of these three motivational systems in different contexts.

Here are some additional key points from the article:

• The authors propose a model of wealth redistribution that is based on three motivational systems: compassion, malicious envy, and self-interest.
• They conducted three studies to test their hypotheses.
• The findings of the studies support the hypothesis that compassion, malicious envy, and self-interest all play a role in shaping people's support for wealth redistribution.
• The authors suggest that future research should examine the relative importance of these three motivational systems in different contexts.

Rational simplification and rigidity in human planning

Ho, M. K., Cohen, J. D., & Griffiths, T.

(2023, March 30). PsyArXiv

https://doi.org/10.31234/osf.io/aqxws

Abstract

Planning underpins the impressive flexibility of goal-directed behavior. However, even when planning, people can display surprising rigidity in how they think about problems (e.g., “functional fixedness”) that lead them astray. How can our capacity for behavioral flexibility be reconciled with our susceptibility to conceptual inflexibility? We propose that these tendencies reflect avoidance of two cognitive costs: the cost of representing task details and the cost of switching between families of representations. To test this hypothesis, we developed a novel paradigm that affords participants opportunities to choose different families of simplified representations to plan. In two pre-registered online studies (N = 377; N = 294), we found that participants’ optimal behavior, suboptimal behavior, and reaction time are explained by a computational model that formalizes people’s avoidance of representational complexity and switching. These results demonstrate how the selection of simplified, rigid representations leads to the otherwise puzzling combination of flexibility and inflexibility observed in problem solving.

General Discussion

Here, we evaluated the hypothesis that functional fixedness reflects the avoidance of complexity and switching costs during planning. To do so, we developed a novel paradigm in which participants navigated mazes that could be represented simply as blocks or more complexly as blocks and notches. Experiments revealed that people simplify problems(for instance, by adopting a blocks-only construal strategy if navigating through notches was unnecessary) and that they persist in these strategies (for instance, continuing to ignore notches even when attending to a notch would lead to a better solution).  Additionally, our computational analyses using the value-guided construal framework (Ho et al., 2022)confirmed that the avoidance of complexity and  switching costs explains observed patterns of optimal behavior, suboptimal behavior, and reaction times under different experimental manipulations. Overall, these results support our proposal and  help  clarify  the  computational  principles  that  underlie functional fixedness.

A pdf is here.

Summary:

The authors argue that people often simplify problems in order to make them more manageable, but this can lead to rigidity and suboptimal solutions.

The authors conclude that rational simplification is a common cognitive mechanism that can lead to both flexibility and rigidity in planning. They argue that the model provides a useful framework for understanding how people simplify problems and make decisions.

Here are some of the key takeaways from the article:

• People often simplify problems in order to make them more manageable.
• This can lead to rigidity and suboptimal solutions.
• The tendency to simplify problems is a cognitive mechanism that can be explained by the limited capacity for representing task details.
• The model provides a useful framework for understanding how people simplify problems and make decisions.

Market Cognition: How Exchange Norms Alter Social Experience

Zaki, J., Neumann, E., & Baltiansky, D. (2021).

Current Directions in Psychological Science, 

30(3), 236–241.

https://doi.org/10.1177/0963721421995492

Abstract

Market exchange and the ideologies that accompany it pervade human social interaction. How does this affect people’s beliefs about themselves, each other, and human nature? Here we describe market cognition as social inferences and behaviors that are intensified by market contexts. We focus on prosociality and two countervailing ways in which market cognition can affect it. On the one hand, marketplaces incentivize individuals to behave prosocially in order to be chosen as exchange partners—thereby generalizing cooperation and trust beyond group boundaries. On the other hand, markets encourage a view of people as self-interested and can thus taint people’s interpretation of prosocial actions and erode more communal forms of cooperation. We close by considering how market cognition can become self-fulfilling, altering relationships, communities, and cultural norms.

 A pdf is here.

Background: Market exchange is a ubiquitous feature of modern life, and it has been argued that this can have a profound impact on our social cognition.

Research question: The authors of this article investigated how market norms and beliefs can alter our social inferences and behaviors.

Conclusions: The authors concluded that market cognition can have a self-fulfilling prophecy effect. When we believe that others are self-interested, we are more likely to act selfishly ourselves. This can then lead others to believe that we are self-interested, and so on.

Kaiser agrees to $49-million settlement for illegal disposal of hazardous waste, protected patient information

Gabriel San Roman

Los Angeles Times

Originally posted 9 September 23

Here are two excepts:

“The illegal disposal of hazardous and medical waste puts the environment, workers and the public at risk,” Bonta said. “It also violates numerous federal and state laws. As a healthcare provider, Kaiser should know that it has specific legal obligations to properly dispose of medical waste and safeguard patients’ medical information.”

The state attorney general partnered with six district attorney offices — including Alameda, San Bernardino, San Francisco, San Joaquin, San Mateo and Yolo counties — in the undercover probe of 16 Kaiser facilities statewide that first began in 2015.

Investigators found hundreds of hazardous and medical waste items such as syringes, tubing with body fluid and aerosol cans destined for public landfills. The inspections also uncovered more than 10,000 pages of confidential patient files.

During a news conference on Friday, Bonta said that investigators also found body parts in the public waste stream but did not elaborate.

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As part of the settlement agreement, the healthcare provider must retain an independent third-party auditor approved by the state and local law enforcement involved in the investigation.

Kaiser faces a $1.75-million penalty if adequate steps are not taken within a five-year period.

“As a major corporation in Alameda County, Kaiser Permanente has a special obligation to treat its communities with the same bedside manner as its patients,” said Alameda County Dist. Atty. Pamela Price. “Dumping medical waste and private information are wrong, which they have acknowledged. This action will hold them accountable in such a way that we hope means it doesn’t happen again.”

The info is here.

Seeing and sanctioning structural unfairness

Flores-Robles, G., & Gantman, A. P. (2023, June 28).

PsyArXiv

https://doi.org/10.31234/osf.io/u9tfh

Abstract

People tend to explain wrongdoing as the result of a bad actor or bad system. In five studies (four U.S. online convenience, one U.S. representative sample), we tested whether the way people understand unfairness affects how they sanction it. In Pilot 1A (N = 40), people interpreted unfair offers in an economic game as the result of a bad actor (vs. unfair rules), unless incentivized (Pilot 1B, N = 40), which, in Study 1 (N = 370), predicted costly punishment of individuals (vs. changing unfair rules). In Studies 2 (N = 500) and 3, (N = 470, representative of age, gender, and ethnicity in the U.S), we found that people paid to change the rules for the final round of the game (vs. punished individuals), when they were randomly assigned a bad system (vs. bad actor) explanation for prior identical unfair offers. Explanations for unfairness affect how people sanction it.

Statement of Relevance

Humans are facing massive problems including economic and social inequality. These problems are often framed in the media, and by friends and experts, as a problem either of individual action (e.g., racist beliefs) or of structures (e.g., discriminatory housing laws). The current research uses a context-free economic game to ask whether these explanations have any effect on what people think should happen next. We find that people tend to explain unfair offers in the game in terms of bad actors (unless incentivized) which is related to punishing individuals over changing the game itself.  When people are told that the unfairness they witnessed was the result of a bad actor, they prefer to punish that actor; when they are told that the same unfair behavior is the result of unfair rules, they prefer to change the rules. Our understanding of the mechanisms of inequality affect how we want to sanction it.

My summary:

The article discusses how people tend to explain wrongdoing as the result of a bad actor or bad system.  In essence, this is a human, decision-making process. The authors conducted five studies to test whether the way people understand unfairness affects how they sanction it. They found that people are more likely to punish individuals for unfair behavior when they believe that the behavior is the result of a bad actor. However, they are more likely to try to change the system (or the rules) when they believe that the behavior is the result of a bad system.

The authors argue that these findings have important implications for ethics, morality, and values. They suggest that we need to be more aware of the way we explain unfairness, because our explanations can influence how we respond to it. How an individual frames the issue is a key to correct possible solutions, as well as biases.  They also suggest that we need to be more critical of the systems that we live in, because these systems can create unfairness.

The article raises a number of ethical, moral, and value-related questions. For example, what is the responsibility of individuals to challenge unfair systems? What is the role of government in addressing structural unfairness? And what are the limits of individual and collective action in addressing unfairness?

The article does not provide easy answers to these questions. However, it does provide a valuable framework for thinking about unfairness and how we can respond to it.

Academics Raise More Than $315,000 for Data Bloggers Sued by Harvard Business School Professor Gino

Neil H. Shah & Claire Yuan

The Crimson

Originally published 1 Sept 23

A group of academics has raised more than $315,000 through a crowdfunding campaign to support the legal expenses of the professors behind data investigation blog Data Colada — who are being sued for defamation by Harvard Business School professor Francesca Gino.

Supporters of the three professors — Uri Simonsohn, Leif D. Nelson, and Joseph P. Simmons — launched the GoFundMe campaign to raise funds for their legal fees after they were named in a $25 million defamation lawsuit filed by Gino last month.

In a series of four blog posts in June, Data Colada gave a detailed account of alleged research misconduct by Gino across four academic papers. Two of the papers were retracted following the allegations by Data Colada, while another had previously been retracted in September 2021 and a fourth is set to be retracted in September 2023.

Organizers wrote on GoFundMe that the fundraiser “hit 2,000 donors and $250K in less than 2 days” and that Simonsohn, Nelson, and Simmons “are deeply moved and grateful for this incredible show of support.”

Simine Vazire, one of the fundraiser’s organizers, said she was “pleasantly surprised” by the reaction throughout academia in support of Data Colada.

“It’s been really nice to see the consensus among the academic community, which is strikingly different than what I see on LinkedIn and the non-academic community,” she said.

Elisabeth M. Bik — a data manipulation expert who also helped organize the fundraiser — credited the outpouring of financial support to solidarity and concern among scientists.

“People are very concerned about this lawsuit and about the potential silencing effect this could have on people who criticize other people’s papers,” Bik said. “I think a lot of people want to support Data Colada for their legal defenses.”

Andrew T. Miltenberg — one of Gino’s attorneys — wrote in an emailed statement that the lawsuit is “not an indictment on Data Colada’s mission.”

The info is here.