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- An epic Twitter thread that explains Trump and his insane press conference
- Daily Kos is prepared to resist Trump every single day for the next four years and beyond. Can you chip in $1 to support independent, progressive media?
- Seth Meyers opens with powerful statement about Charlottesville & Trump’s response
- Ted Lieu bats off Ivanka’s Twitter block & continues to castigate Trump/White House cronies
- President Obama defeats Trump at Twitter using love
- U.S. tourist breaks German law by giving Hitler salute in public—gets minor beating from passerby
- Watch this embedded reporter from HBO in Charlottesville
- GOP on the brink: Embrace Nazis or reject Trump
- Sign the petition: Tear Confederate statues down
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- 82nd Airborne—who jumped into Normandy on D-Day—has zero tolerance for Nazi wearing their hat
- White supremacist terrorists are protected from the laws that affect Islamic terrorists
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- White supremacist and ‘alt-right’ groups celebrate Trump speech
Republicans just don’t know how to stop. As if attacking healthcare, immigration, affirmative action, and transgender rights weren’t enough, the GOP is now going after poor people’s access to phone and Internet service.
This week, Republican Representative Austin Scott introduced the “End Taxpayer Funded Cell Phone Act,” which targets Lifeline—a crucial program that provides telephone, cell phone, and Internet subsidies to low-income Americans.
This bill would cut off funding for cell phone and Internet, and “restore” Lifeline’s services to only fund landline telephones. Sign now if you agree that Lifeline should continue to fund landline phones, cell phones, and Internet service.
Reducing Lifeline’s services is unacceptable. Lifeline makes landline phones, cell phones, and Internet accessible for poor, disabled, and elderly people. Taking those services away would be cruel.
Sarah Hogg, Daily Kos
By Tamara Sims, Department of Psychology, Stanford University, Building
420, Jordan Hall, Stanford, CA 94305
How people interpret and respond to negative feelings (e.g., Boiger, Mesquita, Uchida, & Barrett, 2013; Diener & Suh, 2000; Matsumoto, 1993; Mesquita & Leu, 2007). Such culture-specific understandings of the nature and source of emotion can have powerful implications for mental and physical well-being. Indeed, multiple studies have shown considerable divergence across cultures in the degree to which negative affect influences physiological and psychological functioning (e.g., Consedine, Magai, Cohen, & Gillespie, 2002; Diener & Suh, 2000; Mauss & Butler, 2010; Miyamoto et al., 2013;
Soto, Perez, Kim, Lee, & Minnick, 2011).
The theoretical case for expecting cultural variation in the health consequences of negative emotions is particularly strong for the comparison between European
American and East Asian cultural contexts.
The concept of negative feelings in the United States is grounded in Western philosophical assumptions as well as in a set of historically derived and selected ideas and practices, such as the Protestant ethic and the American dream.
In the United States, negative feelings are construed as internal entities that are the individual’s responsibility (Chentsova-Dutton & Tsai, 2010; Kitayama, Mesquita, &
Karasawa, 2006; Uchida, Townsend, Markus, & Bergsieker, 2009). It is believed that people should assume responsibility for their negative affective experiences, so when they feel bad, they may also fear or experience social sanctions (Bastian et al., 2012). As a result, negative feelings can signal a moral failing and are construed as harmful
(e.g., Wierzbicka, 1994).
In sharp contrast, in East Asian contexts, the concept of negative feelings is rooted in Buddhist, Taoist, and Confucian traditions. Negative feelings in these contexts are construed as situationally afforded and grounded in specific relationships (Chentsova-Dutton & Tsai, 2010; Kitayama et al., 2006; Uchida et al., 2009).
Consequently, individuals do not bear the weight of negative affective experiences alone; rather, experiencing negative affect may even foster social ties.
In this context, negative emotions are seen as arising from external sources and thus
as inevitable and transient elements of a natural cycle (e.g., Peng & Nisbett, 1999).
We would predict, then, that among people who experience frequent negative affect, Americans are more likely than Japanese to suffer adverse health consequences.
At this point, the limited amount of empirical evidence is mixed; some evidence supports cross-cultural continuity (e.g., Pressman et al., 2013), whereas other evidence is consistent with cross-cultural variation in the association between negative affect and health (e.g., Miyamoto et al., 2013; Miyamoto & Ryff, 2011).
One reason for these conflicting findings may be the lack of consensus in how emotion and health are measured. Some studies have measured state affect (i.e., how people feel in a given moment or on a given day), and others have measured trait affect (i.e., how people typically feel).
Additionally, the measures of health outcomes used in these studies varied widely in terms of relative subjectivity/objectivity as well as in their clinical relevance. Finally, conclusions based on significance testing increase the possibility of inferring cross-cultural similarity when examining large samples.
Thus, we focus here on comparing effect sizes.
Addressing this issue, we compared the magnitude of the effect of negative affect on health in the United States and Japan using a stable index of negative affectivity and
six clinically relevant, well-known self-report health metrics.
The United States/Japan comparison is a relatively ideal one because both nations are modernized, democratized, industrialized societies with well-developed systems
of health care. Yet these two societies are markedly different in their historically derived ideas about negative affect and in the everyday social practices that lend form
and organization to affective experience (Markus & Kitayama, 1994; Mesquita & Leu, 2007).
To examine this possibility, we compared survey data from two large samples of Japanese (n = 988) and American adults (n = 1,741) participating in the Midlife in the United States (MIDUS) and Survey of Midlife Development in Japan (MIDJA) survey studies. To measure negative affect, participants reported how often (1 = none of the time, 5 = all of the time) they had experienced negative emotions (i.e., how often they had felt nervous, hopeless, lonely, afraid, jittery, irritable, ashamed, upset, angry, and frustrated) over the previous 30 days. We indexed physical health using two relatively objective measures—number of chronic conditions and degree of functional limitations— and we administered a single-item measure of subjective global health. We indexed mental health using two multi-item measures of psychological well-being and self esteem, and we administered a single-item measure of life satisfaction.
We included positive affect and demographic variables as covariates in our analyses (for details, see Methodological Details in the Supplemental Material available
online). Japanese participants reported higher mean
levels of and variance in negative affect (M = 1.80, SD =
0.62) than did Americans (M = 1.57, SD = 0.53), t(1806.31) =
9.52, p < .001, Levene’s F(1, 2727) = 65.53, p < .001.
Overall, we found that for each measure, negative affect significantly predicted poor health in both the United States and Japan. However, a comparison of the magnitude of the effect revealed that negative affect was indeed worse for one’s health in the United States than in Japan (see Fig. 1).
Differences in negative affect–health associations (calculated as critical ratios of the differences) indicated that in the United States, compared with Japan, negative affect more strongly predicted more chronic conditions, z = 6.47; worse physical function, z =
2.45; worse psychological well-being, z = 6.59; and lower self-esteem, z = 5.65.
Across cultures, negative affect similarly predicted poor global health, z = 0.62, and lower
life satisfaction, z = −0.62. Multigroup structural equation modeling confirmed these findings even when we controlled for cultural differences in variances (see Additional
Analyses in the Supplemental Material).
Our findings are consistent with the generalization made by Pressman et al. (2013) that negative emotions matter for health around the globe. However, the magnitudes
of the effects vary considerably between cultures, particularly for objective and multi-item assessments.
The link between negative affect and health may be stronger in U.S. contexts because negative affect is commonly conceptualized as harmful and as the individual’s responsibility, in contrast to East Asian contexts, in which negative affect is construed as natural and rooted in relationships.
Further research is needed to explicitly test cultural construals of negative affect as an explanatory mechanism.
Unfortunately, at this point, no large-scale representative surveys have assessed this type of information.
We found no cultural variation for single-item ratings of life satisfaction and global health, possibly because they are more holistic indices of well-being that reflect
more than individuals’ physical and mental health status.
For instance, people may base global-health ratings not only on existing health problems but also on their health behaviors (Krause & Jay, 1994), and people may judge
life satisfaction according to how well close others are
doing in addition to themselves (e.g., Diener & Suh,
2000). Further, the fact that we found no variation in the
single-item global measures suggests that negative feelings
are not more predictive of negative self-assessments
overall in the United States than in Japan.
This study had the advantage of assessing six physical
and mental health outcomes.
While all measures were self reports, two were relatively objective reports of diagnosed
or observable chronic health conditions (e.g., diabetes) and functional limitations (e.g., ability to carry groceries).
Further, self-reports of physical and mental health have been reliably established as useful predictors of long-term health and mortality outcomes (e.g., Lee, 2000). Consistent
with our findings, results from prior research have shown that negative emotions also predict physiological outcomes
Studies in which negative affect has been induced in participants in the laboratory have revealed that East Asians show less intense reactivity than European Americans
across self-reported experience, expressive behavior, and physiological function (e.g., Mauss & Butler, 2010).
Nevertheless, it is possible that these effects are bidirectional, such that poorer health may lead people to feel worse in cultures that have come to expect good health.
Our study was also limited in that we were unable to compare our findings with those from so-called less developed societies.
Future studies may also reveal, as Pressman et al. (2013) originally speculated, that the link between negative emotions and compromised health may be of particular salience in first-world countries. We suggest this is because emotions tend to be construed as
relatively internal, individualized entities in these contexts (e.g., Uchida et al., 2009). Further, the use of more specific, multi-item measures of physical and mental
health as opposed to single-item measures may be more likely to reveal this difference.
Findings that reveal the significance of how negative affect is construed have important implications for health care among diverse populations. Interventions—chemical
or behavioral—aimed at reducing or relieving negative affect, although essential in some contexts, may not be universally desired or helpful.
The words of a Japanese psychiatrist underscore the cultural distinction observed
here: “Melancholia, sensitivity, fragility—these are not negative things in a Japanese context. It never occurred to us that we should try to remove them, because it never
occurred to us that they were bad” (Tooru Takahashi, as quoted in Schulz, 2004, p. 39).
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Those considered to be of prime working age are between the ages of 25 and 54.
In 2015, an estimated 128 million Americans fell into this age bracket. Over the past five years, Census estimates suggest many areas have experienced notable declines in the prime working age population even though overall numbers have increased slightly. In some places, aging of baby boomers accounts for the decline, while other regions are experiencing outmigration of their young and middle-aged adults.
Middle income and families
Middle income and couples contributed more in taxes compared to other income groups. Free education, housing support, child care support, health care access and other family-centered and middle-income centered benefits should be given more to this income group.
From these income groups, more than half of the monthly income goes to housing expense.
Strong economy measured by jobs and socioeconomic environment
“We assigned a heavier weight to the former as these factors most heavily influence a job seeker’s decision in terms of relocation for employment,” the finance website said of its methodology.
The results were not so friendly for California. Of the top ten best cities to find a job in 2016– only one of them was located in California. Irvine ranked number seven on the WalletHub list.
Top ten worst cities to find a job in 2016
Half of them were in California. San Bernardino, Ontario, Modesto, Fresno and Stockton were ranked in the bottom ten.
Here’s a link to the full, national list. But if you’re interested in keeping it in California, here’s how some of the golden state’s cities stack up:
#15: San Francisco
#46: San Jose
#80: Rancho Cucamonga
#81 Huntington Beach
#82: Santa Clarita
#92: Sana Ana
#98: San Diego
#99: Santa Rosa
#111: Garden Grove
#125: Chula Vista
#131: Los Angeles
#136: Moreno Valley
#138: Long Beach
#141: San Bernardino
Here are some more of the key findings from the study, courtesy of WalletHub:
Houston has the highest cost of living-adjusted monthly median starting salary, which is three times greater than in Honolulu, the city with the lowest.
Detroit, Mich., has the highest unemployment rate, which is six times greater than in Lincoln, Neb., the city with the lowest.
Providence, R.I., has the highest number of part-time employees for every 100 full-time employees, which is two times greater than in Plano, Texas, the city with the lowest.
Tallahassee, Fla., has the highest percentage of the workforce living under the poverty line, which is eight times greater than in Fremont, Calif., the city with the lowest.
Gilbert, Ariz., has the highest cost of living-adjusted median annual income, which is three times greater than in Cleveland, the city with the lowest.