Politically partisan left-right online news echo chambers are real, but only a minority of approximately 5% of internet news users inhabit them; the continued popularity of mainstream outlets often preclude the formation of large partisan echo chambers

How Many People Live in Politically Partisan Online News Echo Chambers in Different Countries? Richard Fletcher, Craig T. Robertson, Rasmus Kleis Nielsen. Journal of Quantitative Description: Digital Media, Vol. 1 (2021). Aug 4 2021. https://doi.org/10.51685/jqd.2021.020

Abstract: Concern over online news echo chambers has been a consistent theme in recent debates on how people get news and information. Yet, we lack a basic descriptive understanding of how many people occupy bounded online news spaces in different countries. Using online survey data from seven countries we find that (i) politically partisan left-right online news echo chambers are real, but only a minority of approximately 5% of internet news users inhabit them, (ii) in every country covered, more people consume no online news at all than occupy partisan online echo chambers, and (iii) except for the US, decisions over the inclusion or exclusion of particular news outlets make little difference to echo chamber estimates. Differences within and between media systems mean we should be very cautious about direct comparisons between different echo chambers, but underlying patterns of audience overlap, and the continued popularity of mainstream outlets, often preclude the formation of large partisan echo chambers.

Keywords: echo chambers, selective exposure, algorithmic selection, news audiences, polarization

Check also  Users do not universally interpret high numbers of “likes” for messages congruent to their own attitudes as valid evidence for the public agreeing with them, especially if their interest in a topic is high:

Luzsa, R., & Mayr, S. (2021). False consensus in the echo chamber: Exposure to favorably biased social media news feeds leads to increased perception of public support for own opinions. Cyberpsychology: Journal of Psychosocial Research on Cyberspace, 15(1), Article 3. https://www.bipartisanalliance.com/2021/02/users-do-not-universally-interpret-high.html

And: Humans in specific instances are psychologically prepared to prioritize misinformation over truth to, inter alia, mobilize the ingroup against the outgroup & signal commitment to the group to fellow ingroup members

Petersen, Michael Bang, Mathias Osmundsen, and John Tooby. 2020. “The Evolutionary Psychology of Conflict and the Functions of Falsehood.” PsyArXiv. August 29. https://www.bipartisanalliance.com/2020/08/humans-in-specific-instances-are.html

And: Echo Chambers Exist! (But They're Full of Opposing Views). Jonathan Bright, Nahema Marchal, Bharath Ganesh, Stevan Rudinac. arXiv Jan 30 2020. arXiv:2001.11461. https://www.bipartisanalliance.com/2020/02/echo-chambers-exist-but-theyre-full-of.html

And: The rise in the political polarization in recent decades is not accounted for by the dramatic rise in internet use; claims that partisans inhabit wildly segregated echo chambers/filter bubbles are largely overstated:

Deri, Sebastian. 2019. “Internet Use and Political Polarization: A Review.” PsyArXiv. November 6. https://www.bipartisanalliance.com/2019/11/the-rise-in-political-polarization-in.html

And Testing popular news discourse on the “echo chamber” effect: Does political polarisation occur among those relying on social media as their primary politics news source? Nguyen, A. and Vu, H.T. First Monday, 24 (5), 6. Jun 4 2019. https://www.bipartisanalliance.com/2019/10/testing-popular-news-discourse-on-echo.html

Check also
Why Smart People Are Vulnerable to Putting Tribe Before Truth. Dan M Kahan. Scientific American, Dec 03 2018. https://www.bipartisanalliance.com/2018/12/why-smart-people-are-vulnerable-to.html

Baum, J., Rabovsky, M., Rose, S. B., & Abdel Rahman, R. (2018). Clear judgments based on unclear evidence: Person evaluation is strongly influenced by untrustworthy gossip. Emotion, https://www.bipartisanalliance.com/2018/12/clear-judgments-based-on-unclear.html

The key mechanism that generates scientific polarization involves treating evidence generated by other agents as uncertain when their beliefs are relatively different from one’s own:

Scientific polarization. Cailin O’Connor, James Owen Weatherall. European Journal for Philosophy of Science. October 2018, Volume 8, Issue 3, pp 855–875. https://www.bipartisanalliance.com/2018/12/the-key-mechanism-that-generates.html

Polarized Mass or Polarized Few? Assessing the Parallel Rise of Survey Nonresponse and Measures of Polarization. Amnon Cavari and Guy Freedman. The Journal of Politics, https://www.bipartisanalliance.com/2018/03/polarized-mass-or-polarized-few.html

Tappin, Ben M., and Ryan McKay. 2018. “Moral Polarization and Out-party Hate in the US Political Context.” PsyArXiv. November 2. https://www.bipartisanalliance.com/2018/11/moral-polarization-and-out-party-hate.html

Forecasting tournaments, epistemic humility and attitude depolarization. Barbara Mellers, PhilipTetlock, Hal R. Arkes. Cognition, https://www.bipartisanalliance.com/2018/10/forecasting-tournaments-epistemic.html

Does residential sorting explain geographic polarization? Gregory J. Martin & Steven W. Webster. Political Science Research and Methods, https://www.bipartisanalliance.com/2018/10/voters-appear-to-be-sorting-on-non.html

Liberals and conservatives have mainly moved further apart on a wide variety of policy issues; the divergence is substantial quantitatively and in its plausible political impact: intra party moderation has become increasingly unlikely:

Peltzman, Sam, Polarizing Currents within Purple America (August 20, 2018). SSRN: https://www.bipartisanalliance.com/2018/09/liberals-and-conservatives-have-mainly.html

Does Having a Political Discussion Help or Hurt Intergroup Perceptions? Drawing Guidance From Social Identity Theory and the Contact Hypothesis. Robert M. Bond, Hillary C. Shulman, Michael Gilbert. Bond Vol 12 (2018), https://www.bipartisanalliance.com/2018/10/having-political-discussion-with-out.html

All the interactions took the form of subjects rating stories offering ‘ammunition’ for their own side of the controversial issue as possessing greater intrinsic news importance:

Perceptions of newsworthiness are contaminated by a political usefulness bias. Harold Pashler, Gail Heriot. Royal Society Open Science, https://www.bipartisanalliance.com/2018/08/all-interactions-took-form-of-subjects.html

When do we care about political neutrality? The hypocritical nature of reaction to political bias. Omer Yair, Raanan Sulitzeanu-Kenan. PLOS, https://www.bipartisanalliance.com/2018/05/when-do-we-care-about-political.html

Democrats & Republicans were both more likely to believe news about the value-upholding behavior of their in-group or the value-undermining behavior of their out-group; Republicans were more likely to believe & want to share apolitical fake news:

Pereira, Andrea, and Jay Van Bavel. 2018. “Identity Concerns Drive Belief in Fake News.” PsyArXiv. September 11. https://www.bipartisanalliance.com/2018/09/democrats-republicans-were-both-more.html

In self-judgment, the "best option illusion" leads to Dunning-Kruger (failure to recognize our own incompetence). In social judgment, it leads to the Cassandra quandary (failure to identify when another person’s competence exceeds our own): The best option illusion in self and social assessment. David Dunning. Self and Identity, https://www.bipartisanalliance.com/2018/04/in-self-judgment-best-option-illusion.html

People are more inaccurate when forecasting their own future prospects than when forecasting others, in part the result of biased visual experience. People orient visual attention and resolve visual ambiguity in ways that support self-interests: "Visual experience in self and social judgment: How a biased majority claim a superior minority." Emily Balcetis & Stephanie A. Cardenas. Self and Identity, https://www.bipartisanalliance.com/2018/04/people-are-more-inaccurate-when.html

Can we change our biased minds? Michael Gross. Current Biology, Volume 27, Issue 20, 23 October 2017, Pages R1089–R1091. https://www.bipartisanalliance.com/2017/10/can-we-change-our-biased-minds.html

Summary: A simple test taken by millions of people reveals that virtually everybody has implicit biases that they are unaware of and that may clash with their explicit beliefs. From policing to scientific publishing, all activities that deal with people are at risk of making wrong decisions due to bias. Raising awareness is the first step towards improving the outcomes.

People believe that future others' preferences and beliefs will change to align with their own:

The Belief in a Favorable Future. Todd Rogers, Don Moore and Michael Norton. Psychological Science, Volume 28, issue 9, page(s): 1290-1301, https://www.bipartisanalliance.com/2017/09/people-believe-that-future-others.html

Kahan, Dan M. and Landrum, Asheley and Carpenter, Katie and Helft, Laura and Jamieson, Kathleen Hall, Science Curiosity and Political Information Processing (August 1, 2016). Advances in Political Psychology, Forthcoming; Yale Law & Economics Research Paper No. 561. SSRN: https://ssrn.com/abstract=2816803

Abstract: This paper describes evidence suggesting that science curiosity counteracts politically biased information processing. This finding is in tension with two bodies of research. The first casts doubt on the existence of “curiosity” as a measurable disposition. The other suggests that individual differences in cognition related to science comprehension - of which science curiosity, if it exists, would presumably be one - do not mitigate politically biased information processing but instead aggravate it. The paper describes the scale-development strategy employed to overcome the problems associated with measuring science curiosity. It also reports data, observational and experimental, showing that science curiosity promotes open-minded engagement with information that is contrary to individuals’ political predispositions. We conclude by identifying a series of concrete research questions posed by these results.

Facebook news and (de)polarization: reinforcing spirals in the 2016 US election. Michael A. Beam, Myiah J. Hutchens & Jay D. Hmielowski. Information, Communication & Society, http://www.bipartisanalliance.com/2018/03/our-results-also-showed-that-facebook.html

The Partisan Brain: An Identity-Based Model of Political Belief. Jay J. Van Bavel, Andrea Pereira. Trends in Cognitive Sciences, http://www.bipartisanalliance.com/2018/02/the-tribal-nature-of-human-mind-leads.html

The Parties in our Heads: Misperceptions About Party Composition and Their Consequences. Douglas J. Ahler, Gaurav Sood. Aug 2017, http://www.bipartisanalliance.com/2018/01/we-tend-to-considerably-overestimate.html

The echo chamber is overstated: the moderating effect of political interest and diverse media. Elizabeth Dubois & Grant Blank. Information, Communication & Society, http://www.bipartisanalliance.com/2018/01/the-echo-chamber-is-overstated.html

Processing political misinformation: comprehending the Trump phenomenon. Briony Swire, Adam J. Berinsky, Stephan Lewandowsky, Ullrich K. H. Ecker. Royal Society Open Science, published on-line March 01 2017. DOI: 10.1098/rsos.160802, http://rsos.royalsocietypublishing.org/content/4/3/160802

Competing cues: Older adults rely on knowledge in the face of fluency. By Brashier, Nadia M.; Umanath, Sharda; Cabeza, Roberto; Marsh, Elizabeth J. Psychology and Aging, Vol 32(4), Jun 2017, 331-337. http://www.bipartisanalliance.com/2017/07/competing-cues-older-adults-rely-on.html

Stanley, M. L., Dougherty, A. M., Yang, B. W., Henne, P., & De Brigard, F. (2017). Reasons Probably Won’t Change Your Mind: The Role of Reasons in Revising Moral Decisions. Journal of Experimental Psychology: General. http://www.bipartisanalliance.com/2017/09/reasons-probably-wont-change-your-mind.html

Science Denial Across the Political Divide — Liberals and Conservatives Are Similarly Motivated to Deny Attitude-Inconsistent Science. Anthony N. Washburn, Linda J. Skitka. Social Psychological and Personality Science, 10.1177/1948550617731500. http://www.bipartisanalliance.com/2017/09/liberals-and-conservatives-are.html

Biased Policy Professionals. Sheheryar Banuri, Stefan Dercon, and Varun Gauri. World Bank Policy Research Working Paper 8113. http://www.bipartisanalliance.com/2017/08/biased-policy-professionals-world-bank.html

Dispelling the Myth: Training in Education or Neuroscience Decreases but Does Not Eliminate Beliefs in Neuromyths. Kelly Macdonald et al. Frontiers in Psychology, Aug 10 2017. http://www.bipartisanalliance.com/2017/08/training-in-education-or-neuroscience.html

Individuals with greater science literacy and education have more polarized beliefs on controversial science topics. Caitlin Drummond and Baruch Fischhoff. Proceedings of the National Academy of Sciences, vol. 114 no. 36, pp 9587–9592, doi: 10.1073/pnas.1704882114, http://www.bipartisanalliance.com/2017/09/individuals-with-greater-science.html

Expert ability can actually impair the accuracy of expert perception when judging others' performance: Adaptation and fallibility in experts' judgments of novice performers. By Larson, J. S., & Billeter, D. M. (2017). Journal of Experimental Psychology: Learning, Memory, and Cognition, 43(2), 271–288. http://www.bipartisanalliance.com/2017/06/expert-ability-can-actually-impair.html

Public Perceptions of Partisan Selective Exposure. Perryman, Mallory R. The University of Wisconsin - Madison, ProQuest Dissertations Publishing, 2017. 10607943. http://www.bipartisanalliance.com/2017/10/citizens-believe-others-especially.html

The Myth of Partisan Selective Exposure: A Portrait of the Online Political News Audience. Jacob L. Nelson, and James G. Webster. Social Media + Society, http://www.bipartisanalliance.com/2017/09/the-myth-of-partisan-selective-exposure.html

Echo Chamber? What Echo Chamber? Reviewing the Evidence. Axel Bruns. Future of Journalism 2017 Conference. http://www.bipartisanalliance.com/2017/09/echo-chamber-what-echo-chamber.html

Fake news and post-truth pronouncements in general and in early human development. Victor Grech. Early Human Development, http://www.bipartisanalliance.com/2017/09/fake-news-and-post-truth-pronouncements.html

Consumption of fake news is a consequence, not a cause of their readers’ voting preferences. Kahan, Dan M., Misinformation and Identity-Protective Cognition (October 2, 2017). Social Science Research Network, http://www.bipartisanalliance.com/2017/10/consumption-of-fake-news-is-consequence.html

Fake News & Ideological (a)symmetries in Perceptions of Media Legitimacy: Partisans are motivated to believe fake news & dismiss true news that contradicts their position as fake news

Harper, Craig A., and Thom Baguley. 2019. ““You Are Fake News”: Ideological (a)symmetries in Perceptions of Media Legitimacy” PsyArXiv. January 23. doi:10.31234/osf.io/ym6t5. https://www.bipartisanalliance.com/2019/01/fake-news-ideological-asymmetries-in.html

Twitter: While partisan opinion leaders are certainly polarized, centrist/non-political voices are much more likely to produce the most visible information; & there is little evidence of echo-chambers in consumption

Mukerjee, Subhayan, Kokil Jaidka, and Yphtach Lelkes. 2020. “The Ideological Landscape of Twitter: Comparing the Production Versus Consumption of Information on the Platform.” OSF Preprints. June 23. https://www.bipartisanalliance.com/2020/06/twitter-while-partisan-opinion-leaders.html

Contrary to this prediction, we found that moderate and uncertain participants showed a nonreciprocal attraction towards extreme and confident individuals:

Zimmerman, Federico, Gerry Garbulsky, Dan Ariely, Mariano Sigman, and Joaquin Navajas. 2020. “The Nonreciprocal and Polarizing Nature of Interpersonal Attraction in Political Discussions.” PsyArXiv. August 21. https://www.bipartisanalliance.com/2020/08/contrary-to-this-prediction-we-found.html

Cross-Partisan Discussions on YouTube: Conservatives Talk to Liberals but Liberals Don't Talk to Conservatives. Siqi Wu, Paul Resnick. arXiv Apr 12 2021. https://www.bipartisanalliance.com/2021/04/cross-partisan-discussions-on-youtube.html

To quantify partisan audience bias, we developed a domain-level score by leveraging the sharing propensities of registered voters on a large Twitter panel; we found little evidence for the "filter bubble'' hypothesis 

Auditing Partisan Audience Bias within Google Search. Ronald E. Robertson et al. Proceedings of the ACM on Human-Computer Interaction - CSCW archive. Volume 2 Issue CSCW, November 2018, Article No. 148, doi: 10.1145/3274417. https://www.bipartisanalliance.com/2018/11/to-quantify-partisan-audience-bias-we.html

Few people are actually trapped in filter bubbles. Why do they like to say that they are? Plus: Are your Google results really that different from your neighbor’s? Laura Hazard Owen. NiemanLab, Dec 07 2018. https://www.bipartisanalliance.com/2018/12/few-people-are-actually-trapped-in.html

UPDATED with later information

Young, Dannagal G. 2021. “Young and Miller, Political Communication in Oxford Handbook of Poli Psych 3rd Ed.” OSF Preprints. August 27. doi:10.31219/osf.io/mwdtu, https://www.bipartisanalliance.com/2021/08/this-chapter-argues-that-conventional.html

Exposure to partisan and centrist news websites – no matter if it is congenial or cross-cutting – does not enhance polarization; null effects are found among strong & weak partisans, & for Democrats & Republicans alike:

Wojcieszak, Magdalena, Sjifra E. de Leeuw, Ericka Menchen-Trevino, Seungsu Lee, Ke M. Huang-Isherwood, and Brian Weeks. 2021. “Wojcieszak Et Al No Polarization from Partisan News IJPP Forthcoming.” OSF Preprints. September 1 2021. https://www.bipartisanalliance.com/2021/09/exposure-to-partisan-and-centrist-news.html

No support was found for the hypothesis that social media use contributed to the level of affective polarization; instead, it was the level of affective polarization that affected subsequent use of social media:

Affective polarization in the digital age: Testing the direction of the relationship between social media and users’ feelings for out-group parties. Maria Nordbrandt. New Media & Society, September 19, 2021. https://www.bipartisanalliance.com/2021/09/no-support-was-found-for-hypothesis.html

The population is widely exposed to online false news; however, echo chambers are minimal, and the most avid readers of false news content regularly expose themselves to mainstream news sources

Zhang, Jiding and Moon, Ken and Veeraraghavan, Senthil K., Does Fake News Create Echo Chambers? (June 23, 2022). SSRN. https://www.bipartisanalliance.com/2022/08/the-population-is-widely-exposed-to.html

The impact of social media on beliefs or actual outcomes has been either non-existent or inconclusive; people who believe in conspiracies gravitate toward groups that espouse these

Processes of Persuasion and Social Influence in Conspiracy Beliefs. Dolores Albarracin. Current Opinion in Psychology, September 5 2022, 101463. https://www.bipartisanalliance.com/2022/09/the-impact-of-social-media-on-beliefs.html

Abstract: If conspiracy beliefs were an individual process, no conspiracy theory would be alike. Instead, these beliefs are promoted by individuals or social groups through the media or informal channels of communication, leading to identical beliefs being espoused by different people and social groups. This paper reviews the role of the social influence as a basis for conspiracy beliefs and describes the role of legacy media, discussions with others, and social media, as well as the underlying informational and normative mechanisms. The role of trust is also considered, including how trust in science can increase vulnerability to conspiracy theories by opening audiences up to the influence of pseudo-scientists. Mitigating the impact of these influences will require research attention to processes that go beyond correction, elucidating the interpersonal consequences of corrections within contemporary information wars.

Found that anal sex had a much later age of initiation compared to oral and vaginal sex; anal sex is a less common and more sexually advanced behavior and may require greater preparation compared to oral and vaginal varieties

Roberts H, Clark A, Sherman C, Heitzeg MM, Hicks BM (2021) Age, sex, and other demographic trends in sexual behavior in the United States: Initial findings of the sexual behaviors, internet use, and psychological adjustment survey. PLoS ONE 16(8): e0255371. https://doi.org/10.1371/journal.pone.0255371

Abstract: It remains unclear how the seemingly ubiquitous use of the internet impacts user’s offline personal relationships, particularly those that are romantic or sexual. Therefore, we conducted a national online survey to better understand the associations among internet use, sexual behavior, and adjustment called the Sexual Behaviors, Internet Use, and Psychological Adjustment Survey (SIPS). Here, we report patterns of sexual behavior in a sample of adults (N = 1987; ages 18–70) in the United States to establish its representativeness and consistency with similar recent surveys. We found age- and sex-related trends in oral, vaginal, and anal sex in terms of prevalence, frequency, number of partners, and age of initiation consistent with prior studies. We also detected differences in sexual behaviors based on relationship status and sexual orientation, but small and relatively few significant differences across racial and ethnic groups. The results confirm and expand upon trends identified in prior national surveys of sexual behavior, establishing the representativeness of the SIPS sample for use in future research examining the links among sexual behaviors and romantic relationships, internet use, and adjustment.

Discussion

We sought to evaluate the representativeness of the SIPS sample—a national survey conducted to better understand relationships among sexual behavior, internet use, and psychological adjustment—by examining whether the rates and demographic trends in sexual behavior replicated prior estimates from similar national surveys. Sample estimates of the prevalence, frequency, number of partners, and age of initiation in oral, vaginal, and anal sex were broadly consistent with prior studies, as were subgroup analyses examining differences in sexual behavior associated with relationship status, sexual orientation, race, and ethnicity.

Trends associated with age and sex

Results for age and sex trends in the prevalence, frequency, number of partners, and age of initiation were consistent with and expand upon previous nationally representative online samples [12]. We replicated the finding of high rates of lifetime participation in oral and vaginal sex (>80%), and a much lower, but not trivial, rate of anal sex (<40%). As our subgroup analyses on sexual orientation revealed, this difference is largely attributable to the low proportion of homosexual men in an unselected national sample. This is to be expected in population samples, where rates of non-heterosexual orientation and male-male sexual behavior are relatively low, and heterosexual couples are more likely to choose to engage in oral and vaginal sex. For example, only 17.6% of respondents reported a non-heterosexual orientation in the current sample, and only 34.4% of respondents endorsing 100% heterosexual orientation reported ever having engaged in anal sex, whereas 61.7% of respondents endorsing 100% homosexual orientation reported engaging in anal sex. The lower levels of anal sex among heterosexual participants may be explained by the stigma associated with anal sex, for example, beliefs that anal sex is immoral or “dirty,” along with historical restrictions on activities such as sodomy and same-sex marriage [27, 28].

We also replicated prior findings that the frequency of these sexual behaviors was highest in middle adulthood [12, 29]. The associations between frequency of sex and age may be at least partially attributable to relationship status. That is, people in serious relationships tend to have more frequent sex than single people, and people tend to form more serious relationships in young and middle adulthood. For example, the average age of first marriage in the United States was 29 years old in 2020 [30]. The frequency of sex may also be influenced by fertility and intention to birth children, a process that must occur before menopause (typically, before ages 45–55 years old) [31, 32].

We also replicated prior findings that men reported a greater number of sexual partners than women throughout their lifetime [10, 12, 20]. Men’s report of the number of sexual partners also exhibited higher variance than women’s report of the number of sexual partners. This was primarily due to a small proportion of men that reported an especially high number of sexual partners, increasing both the mean and variance of the number of sexual partners relative to women [33]. We also identified a considerably lower median value for the number of sexual partners compared to the mean value across gender, further illustrating the influence of the small proportion of respondents reporting a very high number of partners, with the effect being stronger in men compared to women. Further, in a study addressing why estimates of sexual partners are often higher in men than women, Mitchell et al. [34] found that men tend to estimate their number of sexual partners (often rounding up to numbers that end in 0 or 5) whereas women tend to count them, a reporting error which may have affected the point estimates in our sample.

We also found that anal sex had a much later age of initiation compared to oral and vaginal sex [18]. This is consistent with the lower prevalence rate of anal sex relative vaginal and oral sex. That is, anal sex is a less common and more sexually advanced behavior and may require greater preparation compared to oral and vaginal sex [35]. This may pose a barrier to populations with limited access to certain sexual wellness resources (i.e., lubrication).

Trends associated with relationship status, sexual orientation, race, and ethnicity

We also found that numerous aspects of sexual behavior varied by subgroups of relationship status, sexual orientation, race, and ethnicity. As oral, vaginal, or anal sex are all partnered behaviors, it follows that participating in ongoing romantic and sexual relationships facilitates access to potential sex partners, access that is more limited or at least not as readily available to people not participating in such relationships. This finding is in line with prior research, confirming that while single people may have greater opportunities for casual sex with a greater number of partners, people in a relationship have more frequent sex [14–16]. Interestingly, people that reported being in a casual relationship(s) reported a higher frequency of sex and more sexual partners, though they constituted a small proportion of the sample.

Consistent with prior findings regarding sexual orientation, heterosexual and bisexual men reported higher rates of vaginal sex than homosexual men. This finding is easily understood via anatomical constraints, that is, vaginal sex is not possible in cisgender male-male partnerships. Further, homosexual males reported higher rates of anal sex than heterosexual and bisexual males. As discussed previously, the stigma surrounding anal sex may account for lower rates of anal sex in non-homosexual subgroups. We also found that bisexual respondents participated in a wide variety of sexual behavior and reported a particularly high frequency of sex and earlier age of sexual initiation compared to other sexual orientation groups. Similar trends were also observed for respondents that endorsed a mostly heterosexual or mostly homosexual orientation. Some prior work suggests that sexual minority groups have more liberal attitudes about sex compared to heterosexual people, that is, a greater acceptance of recreational sex, potentially contributing to an earlier age of sexual initiation and a higher frequency of sex [36, 37].

Results for racial differences in sexual behaviors were less consistent with prior findings. We did detect a significant difference for earlier ages of initiation for oral and vaginal sex for White and Black participants relative to Asian participants, and that Black participants reported more lifetime vaginal sex partners than White participants. Although the effects were small (Cohen’s d < .30), we did observe a trend for Black participants to report a higher frequency, more partners, and an earlier age of initiation for oral and vaginal sex than White and Asian participants as reported in prior studies [14, 15, 21–23]. The lack of significant differences could be due to a different design than most prior studies of general sexual behavior (i.e., our use of internet-based recruitment and survey methods assessing oral, vaginal, and anal sex separately). While Herbenick and colleagues [12] examined oral, vaginal, and anal sex trends in an online-based survey, they did not report on racial differences, which would have provided a useful comparison for the current study and allowed us to explore if racial differences in sexual behavior are smaller or less robust relative to factors such as relationship status and sexual orientation, or if racial differences in sexual behavior in the US are narrowing over time. Additionally, research is limited as to why these racial differences in normative sexual behavior may be present. It will be useful for future studies to expand analyses beyond simple group differences, and to test if additional covariates (e.g., cultural attitudes about sex and relationships) can account for any racial differences in these sexual behaviors.

For ethnicity, we also found that Hispanic respondents reported a higher frequency of oral, vaginal, and anal sex than non-Hispanic respondents, as well as slightly fewer lifetime vaginal sex partners and an earlier age of initiation of anal sex. To our knowledge, all prior studies explicitly examining ethnic differences in sexual behavior did so using the umbrella term “sexual intercourse” [14, 15]. We assessed sexual behavior in greater detail, specifying between oral, vaginal, and anal sex, expanding upon prior examinations of ethnic differences in sexual behavior. It will be important to replicate and dismantle such differences in future research.

Limitations

While the online survey design provided for a highly efficient mode of data of collection for a national sample, several limitations should be noted. Although the Qualtrics XM platform ensures a sample that mirrors the US general population for the quota variables, all participating respondents had either internet or cell phone access. Though the large majority of the U.S. population does have internet access, there remains a small percentage who do not. Also, while Qualtrics guarantees specific quotas, it does not guarantee representation on other non-quota variables. Furthermore, due to time constraints, we focused on assessing oral, vaginal, and anal sex. Other surveys have asked about a wide range of sexual behaviors including solo behaviors, participation in group sex, use of sex toys, and various kink behaviors. While we did not include that breadth, we were able to delve into greater detail of oral, vaginal, and anal sex than some prior reports.

Additionally, multivariate logistic and linear regression models were used to explore the effects of Age, Age2, Sex, and their interactions on oral, vaginal, and anal sex. We did not, however, perform these analyses within demographic subgroups. While one-way ANOVAs were useful in testing for mean differences across subgroups, we did not test for interactions among age, sex, and the other demographic variables. Given we identified numerous group differences in sexual behavior, this will be an important goal for future research, though some subgroup analyses may require larger sample sizes than the SIPS to provide adequate power to detect differences (e.g., non-heterosexual orientation subgroups). There are also other demographic variables that we did not examine (e.g., income, education), as well as other behaviors (e.g., internet use, substance use) and psychological characteristics (e.g., personality) that are associated with sexual behavior, some of which we intend to examine in future reports. Subgroups could also be further dissected in large samples, e.g., sexual attraction as a distinct facet of sexual orientation [38]. There are other demographic variables that we did not examine (e.g., income, education), as well as other behaviors (e.g., internet use, pornography consumption, substance use) and psychological characteristics (e.g., personality) that may be associated with sexual behavior, some of which we intend to examine in future reports [39, 40].

Overall, the results are consistent with most prior findings regarding patterns of oral, vaginal, and anal sex in the United States, and help establish the representativeness of the SIPS sample. The evidence for its representativeness provides a basis on which future investigations can examine and make valid inferences regarding associations among sexual behavior, technology, and adjustment. Future reports will analyze additional correlates of sexual behavior, including social media and dating app use, substance use, mental health, personality, and interpersonal relationship traits to explore how modern technology usage impacts the expression of sexual and romantic behavior.

The agony of partner choice: Excessive partner availability increased fear of being single, and perceived overload, and decreased self-esteem

The agony of partner choice: The effect of excessive partner availability on fear of being single, self-esteem, and partner choice overload. Marina F. Thomas, Alice Binder, Jörg Matthes. Computers in Human Behavior, August 6 2021, 106977. https://doi.org/10.1016/j.chb.2021.106977

Highlights

• Survey (Study 1) and experiment (Study 2) both showed adverse effects of excessive partner availability.

• In Study 1, dating app use related to increased partner availability, which in turn related to higher fear of being single.

• In Study 2, we manipulated low, moderate, or high partner availability by assigning 11, 31, or 91 dating app profiles.

• Higher partner availability increased fear of being single, and perceived overload, and decreased self-esteem.

Abstract: Dating apps advertise with high availability of potential partners because users seem to prefer extensive choice. However, on the basis of consumer decision making research, we theorized that such excessive choice could have adverse effects, specifically on fear of being single, self-esteem, and partner choice overload. In Study 1, a survey with 667 adults between 18 and 67, dating app use was associated with an increased perception that the number of potential partners is numerous which, in turn, predicted higher fear of being single. In Study 2, we replicated the positive effect of partner availability on fear of being single in an experimental design with 248 adults between 18 and 38. We experimentally induced low, moderate, or high partner availability by assigning 11, 31, or 91 dating app profiles of allegedly available potential partners to participants. High (compared to low) partner availability increased fear of being single, decreased participants’ state self-esteem, and increased partner choice overload. Findings demonstrate pitfalls of excessive swiping on dating apps and extend choice overload literature by revealing effects on novel outcomes.

Keywords: Dating app usePartner availabilityFear of being singleSelf-esteemPartner choice overload

Political Taste: Exploring how perception of bitter substances may reveal risk tolerance and political preferences

Friesen, A., Ksiazkiewicz, A., & Gothreau, C. (2021). Political Taste: Exploring how perception of bitter substances may reveal risk tolerance and political preferences. Politics and the Life Sciences, 1-47. doi:10.1017/pls.2021.20

Those who have a higher degree of preference for bitter tastes also tend to be more risk tolerant and to participate in politics.

Abstract not available as text. Preregistration: OSF | Political Taste: Exploring how perception of bitter substances may reveal risk tolerance and political preferences

Folklore in 1000 societies: Communities with low tolerance towards antisocial behavior, captured by the prevalence of tricksters getting punished, are more trusting and prosperous today

Folklore. Stelios Michalopoulos and Melanie Meng Xue. NBER Working Paper No. 25430. January 2019, Revised January 2021. https://www.nber.org/system/files/working_papers/w25430/w25430.pdf

Abstract: Folklore is the collection of traditional beliefs, customs, and stories of a community passed  through the generations by word of mouth. We introduce to economics a unique catalogue of oral traditions spanning approximately 1,000 societies. After validating the catalogue’s content by showing that the groups’ motifs reflect known geographic and social attributes, we present two sets of applications. First, we illustrate how to fill in the gaps and expand upon a group’s ethnographic record, focusing on political complexity, high gods, and trade. Second, we discuss how machine learning and human-classification methods can help shed light on cultural traits, using gender roles, attitudes towards risk, and trust as examples. Societies with tales portraying men as dominant and women as submissive tend to relegate their women to subordinate positions in their communities, both historically and today. More risk-averse and less entrepreneurial people grew up listening to stories where competitions and challenges are more likely to be harmful than beneficial. Communities with low tolerance towards antisocial behavior, captured by the prevalence of tricksters getting punished, are more trusting and prosperous today. These patterns hold across groups, countries, and second- generation immigrants. Overall, the results highlight the significance of folklore in cultural economics, calling for additional applications.

JEL No. N00,Z1,Z13

6 Concluding Remarks

Narratives are essential building blocks of our society. We introduce to economics a unique catalogue of oral traditions across approximately 1; 000 groups. After validating folkloreís content showing that episodes in a groupís oral tradition reáect its geographic and social attributes as articulated in the ethnographic record, we undertake a series of applications illustrating how to extract information from folklore. In the Örst set, we illustrate how to Öll in the gaps and expand upon a groupís ethnographic record. In the second set, we discuss how machine learning and human-classiÖcation methods can help shed light on ancestral norms. Our initial examination indicates a striking consistency between values derived from folklore and contemporary attitudes related to trust, risk-taking, and gender norms. Images and episodes in folklore appear to endure and, possibly, still shape how individuals perceive the world today. 

Next Steps

We view this study as a springboard for further research. The Önding that folklore-based measures of the economy and the polity correspond to what we know from ethnographers suggests that we can obtain more precise estimates of a groupís heritage by combining the two sources. Lowering the measurement error in the historical record will allow us to revisit and better understand our societiesílegacies and their consequences. One related idea is to use folklore to Öll in the EA and SCCS gaps for the universe of recorded traits along the lines described in Section 4. Moreover, one can utilize folklore to derive bilateral measures of cultural proximity, see Spolaore and Wacziarg (2009), or explore how di§erent geographical traits and historical events ináuence the content of oral traditions. For example, what do groups located in malaria-prone regions, fertile territories, or rugged terrains "talk" about? Similarly, what are the distinctive themes in the folklore of groups that have experienced disruptions from slavery, epidemics, forced migrations, and colonization? This approach would allow testing famous conjectures in anthropology including the "culture of honor" proposed by Goldschmidt and Edgerton in 1971 and "the original a­ uent society hypothesis" by Sahlins (1972).

 There is a long list of contemporary values and attitudes in regional and global surveys that we have not covered, including patience, aspirations, reciprocity, attitudes towards violence, strangers, the elderly, the community, the importance of imagination, obedience, independence, hard work, honesty, etc. We hope that the roadmap provided here can help trace these values in the respective oral traditions. Obtaining folklore-based measures of these attitudes may help us better understand the cultural traits that are stable over time.

Another avenue of future research relates to how motifs and concepts have traveled across oral traditions. Some motifs appear to be universal, whereas others are found in a handful of folklore traditions. Is there a pattern in the content of localized versus universal narratives? Moreover, the multiplicity of charactersíattributes in a given motif and oral tradition (at least as classiÖed by humans) may convey important information about the richness and the ambiguity of the charactersí personality. This within-oral tradition diversity in attitudes may provide a way to gauge the degree of áexibility in the norms transmitted intergenerationally. It would also be interesting to explore how the individual characteristics of those reading and classifying the motifs may systematically predict how a given motif is perceived. Finally, we posit that the degree of continuity in the narratives between contemporary childrenís books and the folktales and myths of the respective societies is a direct measure of the rate at which ancestral norms are intergenerationally transmitted.

 Given the versatility of folklore as a vehicle for obtaining a unique (and perhaps our only) view of our ancestral cultural heritage, we expect it to be useful to scholars interested in the historical origins of comparative development, social psychology, culture, and beyond.

Some people may frequently forget about their age and be horrified at those moments when they realise their age

What does feeling younger or older than one’s chronological age mean to men and women? Qualitative and quantitative findings from the PROTECT study. Serena Sabatini et al. Psychology & Health, Aug 5 2021. https://doi.org/10.1080/08870446.2021.1960989

Abstract

Objective: We explored which factors are associated with subjective age (SA), i.e. feeling younger, the same as, or older than one’s chronological age, and whether these factors differ between men and women and between two age sub-groups.

Design: Cross-sectional study using qualitative and quantitative data for 1457 individuals (mean age= 67.2 years).

Main outcome measures: Participants reported how old they feel they are and provided comments in relation to their SA judgments.

Results: By using content analysis participants’ comments were assigned to 13 categories, grouped into three higher-order categories (antecedents of age-related thoughts, mental processes, and issues when measuring subjective age). SA may result from the interaction between factors that increase or decrease age-related thoughts and mental processes that individuals use to interpret age-related changes. Chi-squared tests show that individuals reporting an older SA are more likely to experience significant negative changes and to engage in negative age-related thoughts than individuals reporting an age-congruent SA or a younger SA. Women experience a more negative SA and more age-salient events than men.

Conclusion: Individuals reporting an older SA may benefit from interventions promoting adaptation to negative age-related changes. There is the need to eradicate negative societal views of older women.

Keywords: Ageingsubjective agefelt ageawareness of age-related changehealth promotion

Discussion

This study identified thirteen factors related to SA judgments and tested whether the frequency with which individuals comment on these factors differs among individuals reporting a younger SA, an age-congruent SA, or an older SA; between age sub-groups; and between men and women. In line with our first hypothesis, when evaluating their SA participants considered, not only their health status, but also a variety of life events and psychosocial factors. Participants’ comments suggest that SA judgments emerge from the interaction between factors that facilitate or decrease age-related thoughts and several mental processes that people use to make sense of age-related changes or to decrease the emotional impact of negative changes. Use of these mental processes frequently results in positive evaluations of SA. In line with our second and third hypotheses, the factors that participants considered when reporting their SA differed among sub-samples. Participants reporting an older SA were more likely to be aware of changes and less likely to engage in activities, compared to participants reporting a younger SA or an age-congruent SA. In line with existing literature on SA, participants in the older age sub-group reported a younger SA compared to those in the younger age sub-group (Bordone et al., 2020). Women experienced more age-symbolic events, especially in the younger age sub-group, and reported a more negative SA than men.

Among the categories that we identified, awareness of changes (Bowling et al., 2005; Sabatini, Silarova, et al., 2020), poor physical health (Desrosiers et al., 2006), the experience of age-symbolic events, and some life circumstances were associated with participants reporting an older SA (Bordone & Arpino, 2016). Events such as retirement, menopause, birthdays, and bereavement, and life circumstances such as being a caregiver may have reminded participants of their position in their lifespan (Barrett, 2003; Bordone & Arpino, 2016; Brothers et al., 2016; Bytheway, 2009; Montepare, 1996a, 2009). The combination of levels of gains and losses experienced by older individuals may play a role in whether these changes are attributed to age. Indeed a recent study showed that individuals are more likely to attribute negative changes to ageing compared to positive changes (Rothermund et al., 2021). The interpretation of negative changes as being a consequence of older age may in turn result in an older SA. Indeed, evidence shows that those individuals that report higher levels of awareness of age-related losses (AARC losses) tend to report an older SA compared to those who experience fewer AARC losses (Brothers et al., 2019; Kaspar et al., 2019; Sabatini, Ukoumunne, Ballard, Brothers, et al., 2020).

As participants reporting an older SA were more likely to be aware of age-related changes, less likely to engage in adaptive behaviours or activities, and rated their health as being poor, an older SA may represent a legitimate reaction to significant and permanent losses (e.g. decrease functional and cognitive ability) (Sabatini, Ukoumunne, Ballard, et al., 2021). As the experience of AARC losses and of an older SA are related to poorer emotional and physical well-being (Mock & Eibach, 2011; Sabatini, Silarova, et al., 2020; Westerhof et al., 2014) and lower engagement in health-related and adaptive behaviours (Brothers & Diehl, 2017; Dutt et al., 2018; Montepare, 2020; Wilton-Harding & Windsor, 2021), the emotional well-being of individuals reporting an older SA could be enhanced through disengagement from unachievable goals (Wrosch et al., 2003) and acceptance of negative changes (Collins & Kishita, 2019). However, when individuals with an older SA experience potentially modifiable changes, more active coping strategies should be promoted in order to enable these individuals to continue engaging in enjoyable activities (Brandtstädter & Rothermund, 2002).

Some participants reported an age-congruent SA or even a younger SA despite experiencing negative age-related changes and negative life circumstances. This finding may be due to several reasons. First, these individuals may have experienced positive changes alongside negative ones (Sabatini, Ukoumunne, Ballard, Diehl, et al., 2020; Wilton-Harding & Windsor, 2021). Second, as those participants who reported a younger SA or an age-congruent SA perceived their health as good and were able to continue performing a variety of meaningful activities, the health changes they experienced may have been mild (Spuling et al., 2013) and not severe enough to prevent them from leading an active and independent life (Franke et al., 2017). Third, some participants may report a positive SA despite the experience of age-related losses due to the use of a variety of mental processes that enable them to perceive their situation in a more optimistic light (Heckhausen & Krueger, 1993). However, subjective evaluations of health can differ greatly from scores obtained with objective measures of health (Carstensen, 1992, 1993, 2006; Chan et al., 2007; Idler & Benyamini, 1997; Jylha et al., 2001). Due to the subjective nature of the concepts, SA may be more strongly associated with self-rated health compared to objective measures of health and future studies should test this. We were unable to test this in the current study as in 2019 the PROTECT study annual assessment did not include an objective measure of health. However, the assessment of comorbidity was included as part of the 2020 annual assessment of the PROTECT study; this will enable the authors to explore in future studies the associations of SA with self-rated health and comorbidity.

Among the mental processes identified in the current study, consistent with social comparison theory (Rickabaugh & Tomlinson-Keasey, 1997) and with temporal comparison theory (Ferring & Hoffmann, 2007), participants reported a younger SA when they compared themselves to people in worse health than themselves (Beaumont & Kenealy, 2004) or when they concluded that despite their increasing age they had not changed significantly. In line with resilience theory some participants reported a younger SA when they concluded that they did not match negative stereotypes of older individuals (Kotter-Grühn & Hess, 2012). Finally, some participants reported a younger SA when others attributed a younger age to them or when they spent time with younger people (Bordone & Arpino, 2016). In contrast, participants reported an older SA when they compared themselves with more healthy others, they felt they matched negative stereotypes of older individuals and/or they thought they had changed significantly compared to previous versions of themselves. This pattern of results emphasises the positive impact that eradicating negative age-related stereotypes at societal level and promoting more realistic age-related expectations and intergenerational contact, may have on individuals’ experiences of ageing (Levy, 2017). Intervention programs promoting positive and realistic age-related beliefs, in addition to healthy behaviours, are effective in promoting more positive experiences of ageing, healthier lifestyle (e.g. more engagement in physical activity), and better mental (e.g. reduction in depressive symptoms) and physical (e.g. better physical performance in terms of balance, gait speed, and chair rise) health (Beyer et al., 2019; Brothers & Diehl, 2017; Menkin et al., 2020).

When estimating their SA, both men and women reflected most frequently on the changes they had experienced in multiple domains (e.g. physical, cognitive, social) of their lives and on how such changes led to modifications in their lifestyle. However, as expected, we found some differences in the way in which men and women evaluate their own ageing (Antonucci et al., 2010; Barrett, 2005). Compared to men, women, especially in the older sub-group, were more likely to experience variability in their SA evaluations. As women also commented more frequently than men on the co-occurrence of positive and negative changes in multiple domains of their lives, the more frequent variability in SA reported by women may be due to them being more likely to experience a mix of positive (e.g. enjoyable social relationships) and negative (e.g. decreased health) age-related changes (Miche et al., 2014). Whereas women were more likely to reflect on age-symbolic events, men commented more frequently on whether their preserved strength enabled them to continue those activities they had initiated earlier in life. This pattern of results suggests that when evaluating their SA men are more likely to reflect on their daily performance whereas women are more influenced by age-salient events and social expectations rather than by their actual daily abilities.

Discrepancies in the way in which men and women experience ageing may be due to our society having different expectations for older men and women. In support of this Kornadt et al. (2013) showed that individuals aged 20 to 92 years attach different stereotypes to older men and women; older women are believed to be more religious, friendly, and engaged in leisure activities whereas men are believed to be more capable in financial and work-related tasks. The different expectations that our society has for older men and women may result in older men and women being treated differently, and this may explain why in our study women reported a more negative SA than men. Indeed, older women often become invisible in the public domain. For instance, among TV presenters, older men are distinguished whereas older women are frequently dismissed (Jermyn, 2013). In sum, our results highlight one more time how much our society -and men, in particular - need to learn to think differently about ageing women and how strategies aiming to eradicate negative age-related stereotypes (Levy, 2017) should give particular attention to negative stereotypes of older women.

Finally, although it was not a primary aim of the current study, participants’ comments outlined several sources of lack of validity and reliability when measuring SA with an unidimensional measure asking participants to specify how old they feel in general (Barrett, 2003). First, as different participants interpreted the SA question in distinct ways, answers to unidimensional measure of SA may not be comparable. Indeed, for instance, some participants reported their SA after reflecting on physical changes, whereas others on their mental abilities.

Second, as some participants reported that their SA fluctuates, assessing SA at one time point may oversimplify individuals’ experiences of ageing. Future studies could therefore adopt methodological designs that take into account the fluctuating nature of self-perceptions in older age (Armenta et al., 2018), for instance, by controlling for situational factors, such as levels of pain, that impact on SA (Sabatini, Ukoumunne, Ballard, Collins, et al., 2020), or by averaging individuals’ SA across several time points (Neupert & Bellingtier, 2017). Third, some participants experienced difficulty in reporting SA which arose from not being able to assign a specific number to SA. Asking individuals to report their SA on a scale ranging from ‘a lot younger than my age’ to ‘a lot older than my age’ may reduce difficulty in answering (Montepare, 1996b). Moreover, difficulty in reporting SA may underlie the difficulty of capturing the complexity of perceptions of ageing when using unidimensional measures. By collecting information about the coexistence of positive and negative experiences in individuals’ lives, multidimensional measures of SA may facilitate SA judgments (Kastenbaum et al., 1972; Turner et al., 2021).

The nature of our dataset places some limitations on our findings. First, all data were collected through self-report measures and descriptive analysis have not been conducted on objective indicators of health. Second, the sample included a majority of women and was predominantly white, with above average education and self-rated health. Among the 14757 participants that took part in the PROTECT study in 2019, only a small sub-group of participants answered the open-ended item (N = 1457); hence the opinions of the remaining participants are unknown. Third, some of the characteristics of study participants are slightly different from the remaining PROTECT participants. For instance, compared to participants included in the current study sample, those excluded from the study sample reported on average a younger SA. Fourth, SA was assessed with a single-item question rather than in a domain-specific format (Kastenbaum et al., 1972; Turner et al., 2021). This is a limitation of the current study as individuals can experience ageing differently in relation to different domains of their lives (e.g. physical and cognitive) which may lead to individuals reporting different subjective ages in relation to different domains of one’s life (Kaspar et al., 2019). Finally, views on ageing and age stereotypes were not taken into account when explaining SA and SA-related thoughts. However, views on ageing and age stereotypes may influence SA (Brothers et al., 2017; 2020; Mock & Eibach, 2011; Sabatini, Ukoumunne, Ballard, et al., 2021).

It should be noted that ours was a large sample for content analysis. The large sample also made it possible to include quantitative data for all the identified categories and to compare frequencies among individuals reporting a younger SA, an age-congruent SA, or older SA; between age sub-groups; and between men and women. The examination of sex difference in SA enriched the scarce literature on factors underpinning sex differences in SA. To analyze data, we generated categories directly from the data; this is a strength of our study as it made it possible to explore the additional role that mental processes play in shaping individuals’ SA, going beyond what has been reported by previous studies (e.g. Giles et al., 2010) and providing targets for future health promoting interventions. For instance, as we found that individuals’ mental processes impact on the age their feel, targeting negative mental processes such as self-attribution of negative age stereotypes may help to enhance mental health in older age. It also made it possible to identify limitations related to the SA questionnaire that had not been considered before and that may find application in the development of a multidomain tool assessing SA.