Love Hurts

"That will be us someday!" It's the sweet wish of a young couples when they spy older couples on the street, in restaurants, on the dance floor who still seem to be in love. 

But the other side of that wish is this: love may have no expiration date, but all people do. Death of a partner is most likely to happen in old age, more likely to happen to older women, and is often considered to be one of the most traumatic events a person can experience.

This sort of loss, or bereavement, is often related to Major Depressive Disorder (clinical depression). The most recent version of the Diagnostic and Statistical Manual (DSM-V) removed the "bereavement exclusion": thus a grieving person who exhibits the symptoms of depression may receive that diagnosis even though these symptoms are a normative response to loss of a loved one.

Fried, Bockting, Arjadi, Borsboom, Amshoff, Cramer, Epskamp, Tuerlinckx, Carr, and Streoebe (2015) note that we often assume bereavement causes a person to have depression, and depression produces symptoms. This is called the "Common Cause Hypothesis" because all symptoms are thought to come from one situation: depression. However, the authors caution us that this hypothesis may not be appropriate because there are thousands of symptoms that depressed people may have, these may contradict each other (e.g.; some depressed people eat too much while other depressed people don't feel like eating at all), and risk factors, such as suicide, may vary depending on the constellation of symptoms that an individual exhibits.

Instead, Fried et al. (2015) encourage us to consider a Network model. From this view, bereavement would cause symptoms, and these symptoms would create situations, such as depression. These symptoms could also interact with (influence) each other to produce such situations.

To test these two viewpoints, the authors used data on depression symptoms from the Changing Lives of Older Couples (CLOC) study. First, they compared the scores on a depression test from 241 widowed seniors (from Follow-Up 1) to 274, age- and gender-matched, married seniors (from Follow-Ups 1-3). The majority of the participants were female and senior citizens. When these individuals joined the CLOC study there was no difference in their reported depression symptoms, but in the follow-up interviews, six months after the death of a spouse the bereaved seniors demonstrated slightly more of these symptoms compared to the seniors who were still married. In fact, 84 of the widowed seniors exceeded the criteria for Major Depressive Disorder by endorsing at least six symptoms. The most commons symptoms were: feeling lonely; feeling sad; feeling depressed; having trouble motivating themselves; problems sleeping; problems eating.

Then Fried et al. (2015) applied complicated statistical models to see if the Common Cause or the Network frameworks would best explain the relationship between bereavement, depression, and depression symptoms. For the Common Cause model to be supported these six symptoms should be better predicted by Depression; instead four of these symptoms were better predicted by loss itself (bereavement) lending support to the Network model. Further investigation revealed that bereavement was especially linked to one symptom, feeling lonely.

These results caution us to think more broadly about depression and spousal loss in older age, especially for older women. Instead of assuming that bereavement causes depression, it may be that bereavement causes a set of symptoms including loneliness. In turn, it could be that this loneliness is what eventually leads a person to experience Major Depressive Disorder. 

As this week's meme suggests, true love may last forever: into old age and even when the person we love is gone. With love still in our hearts but now suddenly on our own, it is easy to see how loneliness could set in. And that is a depressing thought.

FURTHER READING:

The Fried et al. (2015) Journal of Abnormal Psychology article can be accessed through your local college library.

Advice from the American Association of Retired Persons (AARP) on ways to survive bereavement.

WebMD's suggestions to "Help Yourself Out of Depression." If loneliness or depression are causing you to have suicidal thoughts, it is very important that you get help. In the U.S. you can call the National Suicide Prevention Lifeline is 1-800-273-8255.

BONUS!

A TEDx talk by Dr. John Cacioppo on "The Lethality of Loneliness."

Equality, Eggs, and Nest Eggs

You never thought this would happen. As a teenager it was drilled into your head that having sex without using birth control would surely result in a pregnancy. Now you are an adult, you want to have a baby, and it is not happening.

So what do you do? You probably talk with a doctor and maybe she suggests some infertility treatments. One of the cheaper interventions is Artificial Insemination: injecting sperm into the uterus during ovulation. This costs on average $865, although the price can vary considerably. Other interventions like In Vitro Fertilization (embryos are created from sperm and egg and then inserted into the uterus) cost an average of $8,158, with additional expenses up to $5,000 for the medication used to increase egg production prior to each treatment. Because there is no guarantee of pregnancy, these procedures may need to be repeated many times before it occurs, if it occurs at all. With yearly college tuition costing $9,000 - $30,000 it is possible to spend more trying to create your child than to educate your child.

Insurance lightens this burden for some but not everyone has health insurance or insurance policies that cover infertility treatments. As of 2016 only 15 states in the U.S. require that infertility treatments are covered by private insurance; and even in those states there are exceptions based on a woman's place of employment and the specific insurance plans offered through that workplace. In some states insurance companies' definitions of infertility (failure to conceive after a year of unprotected heterosexual sexual intercourse) also unfairly deny lesbian women coverage.

Blanchfield and Patterson (2015) raised further concerns about access to infertility help and insurance coverage. They evaluated data from thousands of women who participated in the 2002, then in the 2006-2013 waves of the National Survey of Family Growth (NSFG) to determine if racial minority women (non-White) and sexual minority women (lesbian women and women who report sexual attractions that are not exclusively heterosexual) have the same access to "fertility assistance" and insurance coverage as women in related majority groups.

From 2002 to the most recent wave in 2013, about twice as many White women compared to racial minority women reported getting medical assistance for pregnancy. Heterosexual women were also more likely to receive this help compared to sexual minority women. However, regardless of race or sexual orientation, women who received help reported getting the same forms of assistance, including advice, testing, fertility drugs, and Artificial Insemination.

Private health insurance coverage varied by race and sexual orientation with White heterosexual women being most likely to have this financial help. In 2002, this comparative lack of insurance and related lower income failed to explain racial and sexual minority women's lower rate of medical assistance for pregnancy: even when these women could pay for these services they were less likely to receive them. However, from 2006-2013, lack of insurance coverage was enough to completely explain the persistent lower level of medical assistance for sexual minority women's infertility. In other words, if sexual minority women can pay for the treatments they are now just as likely to receive them as heterosexual women. On the other hand, even from 2006-2013 lower income and lack of insurance could only account for part of the persistent lower level of medical assistance for racial minority women's infertility. This means that even when non-White women have the means to pay they do not always get these interventions.

This is particularly disturbing as White, Black, and Hispanic women have approximately the same rate of infertility (11%) and these groups represented more than 90% of the women surveyed in the NSFG. Thus with equal means to pay, these groups should have reported equal experience with medical assistance. Blanchfield and Patterson (2015) offer three possible explanations for this racial discrepancy. First, racial minority women may not have the "social support" that White women have when they are faced with infertility: if your friends and family don't suggest talking to a doctor then you are less likely to do so. Second, for Black women in particular, our nation's history of abusing Black citizens for medical testing (see for example: U.S. Military in WWII; the Tuskegee Study; Henrietta Lacks) may make them more cautious about involving the medical community in their personal lives. Finally, although it is unethical and illegal, stereotypes and prejudices about racial minority fertility may bias doctors away from discussing infertility with women from these groups.

This is something that we must try to change. Along with the emotional and financial devastation that often accompanies infertility, a woman should not have to fear or be denied the chance to talk with her doctor about this condition.


FURTHER READING:

You can access the Blanchfield and Patterson (2015) article online or through your local college library. 

Resolve: The National Infertility Association offers facts and information about support groups for individuals and couples coping with infertility.

The Broken Brown Egg is a blog about Black women and infertility; it also includes links to useful resources.

Losing our minds in middle age

When negative stress affects our well-being, we sometimes feel like we are losing our minds...

But when in the lifespan does this really happen? When do we lose our brains?

Until age two we experience rapid growth of brain cells, or neurons. Around that age, rarely used neurons and unneeded connections between neurons (synapses) are reduced. Past research by Hedman, van Haren, Schnack, Kahn, and Hulshoff (2012) suggests that childhood is a time of brain growth, with more neurons being produced. Starting around age thirteen and continuing through adolescence we see brain volume loss as pruning reoccurs so that our brains can be more efficient. Most of young adulthood sees little change in brain volume, but starting at age 35, MRI scans demonstrate a yearly loss of about 0.2% of brain volume. This loss accelerates in older age: in our sixties this increases to a loss of about 0.5% of brain volume every year; this acceleration is often given as one of many explanations for other normal declines associated with aging.

To examine in detail the brain volume loss during the transition to midlife, Guo, Isohanni, Miettunen, Jääskeläinen, Kiviniemi, Nikklinen, Remes, Huhtaniska, Veijola, Jones, and Murray (2016) examined MRI scans of 43 men and 23 women as they aged from their 30s (33-35 years) to their 40s (42-44 years). The participants in this longitudinal study were part of the Northern Finland 1966 Birth Cohort so they should have had similar experiences in their lives as they grew up at the same time. The researchers' goals were to measure overall brain volume at both ages, to identify the locations of any loss as observed in the second MRI performed when the participants were in their 40s, and to clarify any sex differences that emerged.

Total brain volume decline was higher than predicted by past research: on average men lost 3.21% and women lost 4.03%. This sex difference was very small but it reached statistical significance, meaning that the difference was unlikely to be due to chance.

The location of loss also showed a sex difference. After taking into account percentage of total brain loss, Guo et al. found that men lost most of their neurons in the midline areas (specifically: bilateral precentral gyri; bilateral paracingulate gyri; and bilateral supplementary motor cortices). Most of these areas relate to motor skills and one may be involved in decoding certain emotions.

Women's loss was more spread out with most of it occurring in the outer brain (specifically: bilateral frontal parietal; temporal lobe; occipital cortex; cerebellum). These areas relate to language, motor skills, sensory interpretation, vision and visual memories, and emotion association.

Guo et al. did not make guesses beyond a quick mention of hormones as to what caused the sex differences in overall brain loss or the sex differences in loss locations. They also speculated that these differences may translate into differences in midlife men's and women's health or behavior, yet they did not offer any examples.

That leaves us all free to speculate. One bit of demographic information that caught my eye was that the researchers coded participants on "parental leave" as working full-time, because it meant that the participants usually worked full-time but were absent from that work to take care of a newborn child. This made me think about other research related to brain volume and parenting. For example, when women are pregnant their brain volumes can shrink an average 4% and not return to normal volume until about six months after birth. First, that makes the 4.03% decline found in Guo et al.'s female participants sound less ominous: this sort of decline is a normal experience for many women in young adulthood. Second, although most Finnish women in the 1980s usually started having babies at age 29, is it possible that some of the 23 women in this study gave birth just before the second MRI scan? Or is the location of brain loss during pregnancy similar to the location of women's brain loss in the transition to middle age?

Starting in the 80s, Finland offered parental leave to fathers as well as mothers. So it is possible that some of the male participants may have also identified themselves as being on parental leave. However, we know that fathers and mothers often take on different roles in parenting. For example, women are more likely to report that they get up to feed or care for babies in the middle of the night; mothers report more sleep loss than fathers even as children grow older. Poor sleep is associated with brain volume loss in the frontal, temporal, and parietal lobes. Different parental roles and related sleep loss may contribute to women's additional 1% of brain loss; brain volume loss related to poor sleep and brain volume loss related to women's transition to midlife are located in similar areas.

In the end we do not know what is causing these declines or sex differences, and even if we did, at this point we cannot know if these are related to any changes in men's and women's behavior or health as they age. The one thing you can know for sure is that if you are middle aged, pregnant, a new mother, or are sleep-deprived, you ARE losing your mind.

FURTHER READING:

The Guo et al. (2016) article can be accessed online or through your local college library.

Loss of brain cells does not always relate to loss of cognitive functioning. Read an APA Monitor on Psychology article by Melissa Phillips on the strengths of the middle-aged mind.

Childhood trauma can also reduce brain volume. Read a report on trauma's effects on brain development from the Child Welfare Information Gateway (U.S. Dept. of Health and Human Services).

BONUS:

Watch a video from Brown University on Synaptic Pruning:

Puberty: Getting more than you hoped

When I was growing up, all the girls read Are you There God? It's Me Margaret., by Judy Blume. Its main character, Margaret, looks forward to developing breasts and getting her first menstrual period. When these finally occur she feels triumphant! More recently, Hello Flo advertisements also portray puberty as something that girls desire: they are upset if menstruation doesn't start quickly enough. Of course, fiction writing and advertisements may not reflect the full story of girls' puberty as witnessed by these memes:



Keenan, Culbert, Grimm, Hipwell, and Stepp (2014) investigated the relationship between African-American and European-American girls' pubertal timing (what age things happen), pubertal tempo (how much time passes between stages of puberty; how long puberty lasts), and depression symptoms. Their sample was part of the longitudinal Pittsburgh Girls Study, so it was large (more than 2,000 girls of diverse backgrounds), data were collected at age 10 and then each year for up to a decade, and the participants were more likely to come from low-income homes.

Each year the girls completed a depression inventory; their caregivers (mostly mothers) completed the same depression inventory about their daughters. From this Keenan et al. could learn how many depression symptoms were common at each age and see how they related to the other variables of ethnicity and puberty. Overall, depression symptoms were highest at age 10 and declined at various rates after that. Even so, across the decade the girls reported that only one or two symptoms on average. The authors maintained that even "minor depression" like this can put individuals at risk for other problems.

The girls provided data on pubertal timing and tempo by matching themselves to standard pictures that portrayed different stages of breast and pubic hair development, and by indicating if they had gotten their first period. One of these scales was also completed by the caregivers in reference to their daughters' development.

The results replicated past research in that the earliest maturing girls (early pubertal timing for breast and pubic hair development) reported more depression symptoms at age 10 than later maturing girls (late pubertal timing). A new finding was that girls who were late to develop breasts (late pubertal timing) and also had a slow pubertal tempo (change progressed slowly) also reported more depression symptoms. There was no effect on depression related to the development of pubic hair and pubertal tempo.

Similar to past research, African-American girls reported slightly higher depression symptoms. For example, at age 10 African-American girls reported one extra depression symptom compared to European-American girls. Likewise, African-American girls demonstrated earlier pubertal timing: pubic hair development occurred almost nine months earlier and breast development began about eleven months earlier than what was reported by European-American girls. Keenan et al. added to the literature by suggesting a trend: African-American girls demonstrated a little slower pubertal tempo, meaning that they took just ever so slightly longer to pass through the stages of puberty compared to the European-American girls. This trend requires further investigation in future research.

New and most importantly, the relationship between depression, ethnicity, and pubertal timing was significant. The ethnic difference in depression symptoms at age 10 (their peak) was reduced up to 32% when pubertal timing was factored in. Pubertal tempo did not have a similar effect. Thus, a considerable portion of the ethnic difference in depression can be explained by African-American girls' earlier entry into puberty compared to European-American girls.

In explaining their findings Keenan et al. suggested that sex hormones might be to blame for at least some of the low level depression seen in preteen girls. Girls with an earlier pubertal timing have higher levels of sex hormones like estrogen compared to girls who have not yet begun pubertal development. This biological argument would, at least in part, explain African-American girls' slightly higher rates of depression.



On the other hand, the authors predicted that a slow pubertal tempo would also predict higher levels of depression because it would mean exposure to high levels of hormones for an extended period of time. In this study, only for girls with later breast development (which implies lower hormone levels) did slow pubertal tempo predict slightly higher depression symptoms. As well, slow pubertal tempo did not explain any of the differences in depression between African- and European-American girls. So hormones cannot be the only explanation for girls' depression symptoms during puberty.

One possibility is that girls receive feedback based on their development that makes them self-conscious. Increases in estrogen cause weight gain so an early maturing girl may feel overweight compared to other girls. Breast development, a sign of puberty that is visible to others, may be desired to attract dating partners - so later maturing girls (especially those with a slow tempo) might be embarrassed by smaller breasts (but not care about lacking pubic hair, a trait that is not socially visible). Conversely, early breast development may bring with it unwanted sexual attention and comments that are uncomfortable for a young girl to navigate. It is also possible that early development of breasts and early menarche may lead parents to treat girls differently: for example, fathers may be less affectionate with their daughters once puberty begins. Parents, fearing sexual experimentation, sexually transmitted infections, teen pregnancy, or sexual assault may also impose new limits on what an early maturing girl can wear, where she can go, and whom she can be with. These sorts of social factors could also explain some of the low level depression seen in preteen girls.

FURTHER READING:

The Keenan et al. (2014) article is available online and through your local college library.

Parents are not the only ones who may regulate girls bodies once puberty begins. Read an article in The Atlantic magazine by Li Zhou: "The Sexism of School Dress Codes."

Starting at puberty, girls and women are twice as likely as boys and men to suffer from depression. This also means that depression symptoms might be missed in males because we are not expecting them to be depressed. Counselor and writer, Michael Gurian, explains some possible symptoms to look for in boys:

Sharing is caring

Sharing with those less fortunate is a value that many parents wish to pass on to their children, and one that is emphasized in many traditional religions. Apparently it is valued by guinea pigs as well:

Recently, a study about sharing has received a lot of mention in the media. Decety, Cowell, Lee, Mahasneh, Malcolm-Smith, Selcuk, and Zhou (2015) examined the influence of religion on the sharing behavior of more than 1,000 school children (ages five to twelve) in six different countries (USA, Canada, South Africa, Turkey, Jordan, and China).

Children were tested individually in their schools using a modified version of The Dictator Game. Each child was offered 30 stickers and asked to choose their ten favorites. They were then informed that there would not be enough time to test all of the children at the school, so they should donate some of their stickers to the children who would otherwise receive none. The number of stickers that children chose to donate served as the measurement of sharing.

The parents of these participants also completed a questionnaire about their religious identities and religious practices, including the number of times per week the family attended religious services and the family's level of spirituality. The most commonly reported identities were: Muslim (43%); Non-religious (28%); Christian (24%).

The results grabbed media attention because the children from Non-religious families shared more stickers than the children from Muslim or Christian families. This effect was the same regardless of the level of religious practice or belief of the Muslim or Christian children. The trend was strongest among the older children in the sample (ages 8-12 years) which implies that the religious children had a longer time to internalize the values of their faiths. The authors noted that children's ages, socioeconomic statuses, and countries of origin were also predictive of sharing, but they did not explore these results in depth.

In the United States, headlines like "Religion makes children more selfish, say scientists," and, "Nonreligious children are more generous," splashed across the Internet. Some people delighted in the irony of reported selfishness from people whose religions teach generosity. Others, especially some practitioners of Islam and Christianity, were offended. But do Decety et al.'s results deserve these strong reactions?

It is true that the study demonstrated a statistical difference between Non-religious children when compared to Muslim and Christian students. That means that the results are unlikely to be due to chance, luck, or accident. So this trend is worthy of further study in future investigations of how religion influences sharing and other prosocial behaviors.

On the other hand, the average number of stickers shared by these groups were very similar. Non-religious children shared on average 4.09 of their ten stickers; Muslim and Christian children shared 3.20-3.33 of their ten stickers. The difference was consistent enough to reach statistical significance, but small enough that we would be unlikely to see a practical difference in our daily lives. In other words, if an elementary school class was made up of children from these three groups, the teacher would be unlikely to notice more or less generosity from any one group: all of the children would donate about three or four of their stickers to students who had none.

At the same time, these data tell us that we cannot assume that religious children will share more than non-religious children. In the United States this is increasingly important to understand as the number of Americans reporting that they are atheist, agnostic, or of "no religion in particular" has increased to almost 23% of adults.

Further Reading:

An online version of the Decety et al. (2015) study is temporarily available; the Current Biology publication can be accessed through your local college library.

Read Phil Zuckerman's opinion piece on "How secular family values stack up," from the Los Angeles Times.

Regardless of their religion or lack of religion, parents can get excellent tips from the Ask Dr. Sears article on "11 ways to teach your child to share." This list also includes when you should not force your child to share.

BONUS:

From the children's television program, Sesame Street, a music video "Share It Maybe;" an educational parody of Carly Rae Jepsen's "Call Me Maybe."

Revenge of the preteen nerds

Many people get an education because they want good careers that earn good money. Being studious may not make you cool but it should set you up to meet that goal; students who party instead of studying may not be so successful:

This quotation is actually from Bill Gates, even if Actual Advice Mallard seems to be stating it here. Did Bill Gates get it right? Are today's nerdy kids likely to be well-employed and financially stable as adults?

Spengler, Brunner, Damian, Lüdtke, Martin, and Roberts (2015) examined data from a large-scale, longitudinal study done in Luxembourg, a small country in Europe. In 1968 the MAGRIP study collected data on Luxembourgish youngsters around age 12. This included measures of the children's IQs, their parents' levels of wealth and education (SES), ratings from teachers on how studious the children appeared to be, and self-reports about feelings of inferiority, being a responsible student, defying their parents' rules, and talking back to their parents.

In 2008, the second wave of MAGRIP followed up with 745 of these same individuals when they were in their 40s. At that time the participants were asked about their educational attainment (years of education after elementary school), their current or most recent jobs, and their yearly incomes. In their analysis, Spengler et al. wanted to know what traits at age 12 were associated with greater educational attainment, occupational success (as measured by prestige and social class), and higher incomes in middle age.

In line with past research, the participants who had higher IQs and higher SES families when they were 12 attained higher amounts of education by middle age. However, even when those two variables were accounted for, three other attributes predicted educational attainment: feeling that you are not as good as others; studiousness; talking back to parents and not always following the rules. Two of these are not surprising: self-reported feelings inferiority at age 12 were related to lower levels of education by one's 40s; while teachers' higher ratings of studiousness at age 12 predicted higher levels of education by middle age. Interestingly, reporting at age 12 that you talk back to and do not always obey your parents was also related to higher educational attainment in adulthood.

Likewise, more occupational success in middle age was predicted by having a higher IQ and coming from a higher SES family at age 12. Even when those two variables were held steady, seeing yourself as a responsible student at age 12 predicted occupational success in your 40s. Higher teacher ratings of studiousness during childhood also predicted occupational success, however this relationship played out through the amount of education that the participants experienced. Spengler et al. clarified that being seen as studious by your teachers in childhood suggests that you have traits that might lead you to choose more years of and more challenging levels of education. In fact, educational attainment was the best predictor of occupational success.

The analysis revealed an unexpected finding related to personal income. The participants who at age 12 admitted that they talked back to their parents and did not always follow their rules were more likely to have higher incomes during their 40s! This was true even when childhood IQ, family SES, and lifetime educational attainment were taken into account. Spengler et al. caution us that this finding needs to be replicated in future research - so this is not a green light for preteens around the globe to sass back at their parents. They also offer two explanations: these individuals may be more likely to argue to get higher wages; it is also possible that these individuals broke the rules as adults to get this higher income.

I would add that it is also possible that they were raised by good, Authoritative parents. These parents express love to their children and raise them with the correct amount of fair discipline; they are also willing to discuss household rules with their children, conversations which may start off with "talking back." Authoritative parents want their kids to be able to reason about their behavior choices instead of simply showing obedience to authority. So, it would stand to reason that their children may not always follow even their own rules to the letter. Authoritative parenting also prepares children for white collar jobs that require independent decision making and less emphasis on following orders; these jobs may also offer higher levels of pay.

Another possibility that I can imagine is that some of these individuals are Gifted. In general, higher IQs are related to higher incomes and Gifted children have IQs that are at least twice as different as we would expect from an average child. Parents of Gifted children often joke about them being "little lawyers," because they can be argumentative even with adults in authority. So Spengler et al.'s surprising finding may simply reflect a variable that is related to unusually high intelligence.

The authors admit that the predictive powers of pre-teen Luxembourgish children's behavior in 1968 may not generalize: it may be that educational attainment, occupational success, and income level are predicted by different traits today and these traits may vary from culture to culture. On the other hand, the Spengler et al. analysis demonstrated that personal factors like being a responsible student, coming across to teachers as being studious, and how you relate to people in positions of authority can predict achievement beyond their relationships with general intelligence and social class. In that case, being a studious (and perhaps argumentative) nerd may be enough: you don't have to be a genius like Bill Gates or have a wealthy parent like Bill Gates to become an adult with a good job and a good income.

Further Reading:

The Spengler et al. (2015) article can be accessed through your local college library.

Clinical Psychologist Kelly Flanagan blogged for The Huffington Post about why he thinks "...Every Kid Should Talk Back to Their Parents."

Serious students may have a good chance of landing a job found in U.S. News and World Report's list of "The 100 Best Jobs" of 2015.

BONUS: Watch an amusing promotional video titled "Is it true what they say about... Luxembourg?" made by the Luxembourg National Tourism Board. Spoiler Alert: no volcanoes; yes happy dogs.

When I'm 64

As a serious college student I remember feeling old before my time compared to some of my classmates who would blow off studying to socialize. Now as a middle-aged professor I don't "feel" as old as many of my peers (even though my daughter reminds me all of the time that I am "very old"). Apparently my experience is shared by Yoko Ono:

Chronological age, or how many years old you are, is just one way to think about aging. You can also consider: Biological age - how healthy you are; Social age - the habits you have and the roles that you take on; and Psychological age - how well you reason and think.

A recent study highlights how people's perceptions of their Biological and Social ages can influence their Subjective ages - or how old they feel. Stephan, Demulier, and Terracciano (2012) asked more than 1,000 French adults ages 18-91 to rate their physical health, to complete a version of the Big Five personality inventory, and to report their subjective ages.

The results support the idea that how old we feel is based on more than how old we are. These effects varied depending on the ages of the participants. The authors did not state the ranges of the age groups, but we would usually assume that their young adults were ages 18-39, middle-aged adults were 40-59, and older adults were 60-91.

A strong relationship between chronological age, health, and subjective age emerged. Middle aged and older adult participants who rated themselves as being in good health were more likely to say that they felt younger than they actually were. Stephan et al. clarify that on average, these middle aged adults felt 2 years younger and these older adults felt four years younger. These results support the importance of considering a person's Biological age.

When the authors controlled for health and demographic factors a relationship between chronological age, certain Big Five traits, and subjective age appeared. Because our personality traits often relate to our behaviors and activities, these results support the importance of assessing a person's Social age. For example, young adults who were high in Conscientiousness felt older than they really were. Conscientiousness implies being responsible and organized. Motivated and reliable young adults might feel like they are older than their peers because these are not characteristics that Western culture often associates with that age.

Middle aged and older adults who were high in Openness to Experience, and older adults who were high in Extraversion felt younger than they were. Openness to Experience has to do with engaging in diverse interests and being open to new ideas; Extraversion is associated with being out-going and dynamic. Both are traits that Western culture does not associate with middle and older age, so people with these traits are likely to feel younger than they really are as they age.

These results explain the experience that Yoko Ono and I share. When I was a young adult, my conscientious behavior did not match with my stereotype about my age: so I felt older. Now as a middle aged person who has broad interests and loves creativity, my self-perception again runs contrary to the stereotype about my age: so I feel younger. In some decades, I can predict that I will continue to feel younger because I am relatively high in Extraversion.

This research also raises a question about Western stereotypes about age. What does it mean that we view young adults as irresponsible, middle-agers and seniors as stuck in their ways, and senior citizens as being unsociable? If we can imagine a time that these negative assumptions are no longer part of our culture, it would have implications for subjective age. Instead of feeling older or younger than our chronological age we would simply be that old and recognize that at all ages individuals can differ on Big Five traits.

Further Reading:

A pre-publication version of the Stephan et al. (2012) article can be read here thanks to the National Institute of Health. The Psychology and Aging article can be accessed through your local college library.

A blog post from the AARP about research done by Rippon and Steptoe (2015): "Feeling Old vs Being Old." More support for Biological age!

Know an Extraverted senior? The social networking site Meet Up has groups around the world for outgoing older people who want to socialize!

I can't be trusted around marshmallows

A pet peeve of mine is when news articles make it sound like parents can completely control their children's behaviors by simply saying the right thing. One gift from our children is the lesson that we cannot control everything -  even if we do everything "right." This confounding behavior comes in part from children's low self-control. Even if we tell them not to do something it is very hard for them to stop themselves from doing it anyway.

However children differ in the their abilities to delay gratification, their abilities to fight temptation. Classic research by Mischel and colleagues in the 1960s and 70s outlined a protocol that is often referred to as "The Marshmallow Test." In these studies preschool children were tested individually by a familiar adult experimenter. The child chose a preferred treat (along with marshmallows, animal cookies, pretzels, and other treats were choices) and then the experimenter said that he or she could eat that one piece of treat now, OR wait until the experimenter returned in 15 minutes to get two pieces. The children differed in how long they were able to wait: some only lasted a few moments and gobbled down the single treat; while others distracted themselves or literally sat on their hands until the 15 minutes was up to claim the double treat. Follow-up studies demonstrated that the children who waited the longest grew up to have better grades in school and show other markers of success. This work is still cited today to show the importance of self-control and is sometimes compared to the modern concept of grit.

Through the years some have raised questions about The Marshmallow Test. For example, Duckworth, Tsukayama, and Kirby (2013) asked if it really tests for self-control or if there is a third variable, another quality, that drives both the longer waiting time and higher grades. Based on past research, it could be that children who are higher in intelligence prefer to wait for a larger reward and tend to get higher grades than children who are lower in intelligence. Likewise, children's behavior in The Marshmallow Test and their achievement in school may be reflect how much they are tempted by reward: some children are more tempted by treats while others have little temptation. It may be that children who have low temptation do not have to work very hard to control their impulses - which allows them to wait and to do better in school.

To clarify this issue Duckworth et al. conducted two studies. Study 1 included 56 local 5th graders (average age 10) who participated in a modified version of The Marshmallow Test: the waiting time was extended to 30 minutes and the students completed a survey about what they like eating before the delay of gratification test began. On a separate occasion the children participated in two tests of intelligence, and answered questions related to temptation. The questions addressed: how excited they get when a reward is offered; how actively they seek out the reward; and the extent that getting in trouble impacts them. Teachers rated each child on self-control (as it relates to schoolwork) and reported end of year grades.

The results demonstrated that the children who waited longer were also rated as having more self-control. Although grades were marginally related to waiting time, intelligence and temptation by reward were not related to waiting time in The Marshmallow Test. However, Duckworth et al. note that the children did not differ very much from each other - especially on the variable of intelligence.

Because the first study involved a small sample lacking in diversity, Study 2 analyzed a data set from the NICHD Study of Early Child Care and Youth Development that covered a broader sample of 966 children. These participants had completed The Marshmallow Test at age four (in this version, the experimenter would return after a maximum of seven minutes) and were tested using two age-appropriate measures of intelligence. At that time, their parents and preschool teachers rated them on two measures of self-control: their abilities to concentrate and their abilities to control their behaviors. As well their mothers rated them on their temptation by reward: how excited they became when offered a reward.

When these children were in eighth and ninth grade, the students' grades were included in the data set. In ninth grade the participants also indicated how often they engaged in "risky behaviors" as a measure of impulsiveness.

The results demonstrated that the children who waited longer were higher in intelligence and higher in self control at age four: they received higher ratings on their abilities to concentrate and to control their behaviors. To a lesser extent, children who waited longer were also less tempted by rewards. The authors then used sophisticated statistical methods to separate out the influences of self-control, intelligence, and temptation by reward.

In line with past research, the children who waited longer at age four were more likely to become adolescents with higher grades and fewer reported risky behaviors. Analyses revealed that level of self-control beat intelligence as a better predictor of the associated high grades. However, unlike high self-control, being less tempted by reward did not predict grades or behaviors in adolescence.

Taken together, these studies support the long-assumed notion that The Marshmallow Test is a good test of self-control. Self-control was the most reliable predictor of the higher grades associated with longer waiting times in The Marshmallow Test; intelligence and temptation by reward were less effective or failed as predictors.

We can only assume that Mischel would be pleased with this confirmation that his famous protocol is a valid test of self-control. Considering that he had to wait more than four decades for this news, I would say that he has passed the "ultimate" marshmallow test (too bad he doesn't like the taste of marshmallows)!

Further Reading:

A pdf of the Duckworth et al. (2013) article can be read online courtesy of the University of Pennsylvania.

For an update on Duckworth's work, read "Measuring Students' Self-Control: A 'Marshmallow Test' for the Digital Age", an article by Ingfei Chen for Mind/Shift. Move over marshmallows! Can today's students delay gratification when it comes to video games?

Watch Walter Mischel explain delay of gratification to Stephen Colbert on the comedy news show, The Colbert Report. Very entertaining!

BONUS: If kids totally lose their cool waiting for an extra marshmallow, imagine their reactions to enormous portions of their favorite foods! Watch what happens in this BuzzFeed video:

Getting the gist of sex ed.

In the United States we have higher rates of teen pregnancy than in many other Western countries. We also know that our teenagers are at high risk for STIs, sexually transmitted infections. To combat these problems, we often require teens to participate in sexual education programs. However, the type of program that is most effective is still debated. This week's meme offers a humorous suggestion:

Because even the most mature adult parents can be worn down by incessant crying and endless repetition, the joke implies that if teenagers experienced these things it would be unforgettable and they would abstain from sex. The joke also implies that teaching statistics like, "six week old babies spend 30% of their awake time crying," is not necessary; instead teenagers will remember a take home message like, "babies cry a lot."

This emphasis on gist, or take home message, over specific quantitative facts is applied more formally to sexual education by Reyna and Mills (2014). These authors investigated if concepts from Fuzzy Trace Theory could make a pre-existing sex ed. curriculum more effective. Past research on Fuzzy Trace Theory suggests that better memory of ideas and better decision-making comes from understanding the the gist, the take home message, as opposed to weighing the pros and cons based on detailed facts or figures that are more forgettable. Because these gist-based thoughts are related to one's emotions and values, they allow for very rapid decision-making.

Their experiment followed more than 700 adolescents, ages 14-19, during a 16 session intervention period and for one year after its completion. The participants were randomly assigned to three types of interventions: an existing sexual education program called Reducing the Risk (RTR); a version of Reducing the Risk that had been modified to add ideas from Fuzzy Trace Theory (RTR+); a Control group focusing on communication skills unrelated to sexuality.

Reducing the Risk (RTR) teaches teens how to recognize situations of sexual risk, how to resist pressure to have sex, and how to reduce risk of pregnancy with contraception and infection by using condoms. Teens enrolled in this program should come to realize that they are personally at risk and that they possess the ability to avoid or reduce sexually related risk. The sessions usually include a factual presentation by an adult leader followed by activities such as guided role playing. For example, the leader might present detailed factual data like, "60% of teenagers report that they used condoms during their most recent sexual experience," followed by guided role play of how to reason with a partner who does not want to use a condom. This program is considered to be effective at delaying first sexual experiences and increasing the use of birth control and infection protection. However, Reyna and Mills note that there is little evidence to show if these effects are lasting.

Because Fuzzy Trace Theory predicts that gist thinking should have a lasting effect on decision making, the authors modified RTR with ideas from this theory to create RTR+. This version is identical to RTR with two additions that emphasize gist. First, at the end of every lesson students are presented with one line summaries of the take home ideas of risk from the lesson. For example, "You should use a condom every time you have sex." Second, the participants in RTR+ receive a checklist of possible values, such as, "I will use condoms every time I have sex," that they are asked to rate themselves on after every lesson. Because gist related decision making is closely influenced by our values, asking students to repeatedly clarify their values should also provoke attention to generalized risks related to sex.

All participants' sexual experience, and beliefs about sex and disease prevention were measured during the intervention, and at three months, six months, and 12 months after the intervention ended. The results demonstrated that the teenagers who had been randomly assigned to RTR and RTR+ showed overall lower risk in their behavior and beliefs than the teenagers who had been assigned to the Control condition.

When the results from RTR and RTR+ were compared, overall RTR+ was considered to be more successful. RTR+, that included Fuzzy Trace Theory's emphasis on gist, was related to:
*a lower rate of students who started having sex during that 12 month period.
*the lowest increase in the number of sexual partners during that 12 month period.
*the smallest increase in positive attitude toward sex (thinking that having sex at this age is a good idea).
*the smallest increase in beliefs that parents and peers think sex was okay for them to experience at this age.
*the highest belief that they were at risk for generalized (take home message) risks associated with sex. This is a measure of gist thinking - so it is not surprising that the teens in RTR+ demonstrated more of this.
*the highest knowledge of sex related risks lasting up to six months after the intervention.
*the highest recognition of warning signals of sexual risk.

On the other hand, RTR, the original sexual education program, was related to:
*more favorable attitudes toward condom use during that 12 month period.
*more agreement with gist-based summaries of sexual risk as measured three months after the intervention. This is another measure of gist thinking - so it IS surprising that the teens in RTR demonstrated more of this

The results were further influenced when the participants' races were taken into account. Reyna and Mills compared results from the three most prominent groups represented in their sample: African American; Hispanic; and White. Curiously, the authors decided to add data from Asian participants into the category White because the responses from those groups were similar. So data reported in relation to White participants should be understood as White and Asian. However, an improvement to this study would have been to further diversify the sample so that Asian adolescents were properly represented.

How did race influence the results? For example, RTR+:
*initially improved African American participants' attitudes toward condoms, but that effect disappeared after the intervention was over.
*increased White participants' beliefs that they could successfully use condoms.
*was related to higher sexual risk knowledge for Hispanic and White teens.
*increased African American and White participants' belief that they were at risk for generalized (take home message) risks associated with sex. This is a measure of gist thinking - so it is not surprising that some teens in RTR+ demonstrated more of this. However, it is surprising that Hispanic participants did not demonstrate more of this in RTR+.

Race also influenced the results of the other intervention. For example, RTR:
*increased Hispanic and White participants' belief that parents and peers think condoms should be used when having sex.
*increased Hispanic and White participants' belief that they were at risk for generalized (take home message) risks associated with sex. This is a measure of gist thinking - so it IS surprising that some of the teens in RTR demonstrated more of this.

Taken together, the results suggest that including an emphasis on the gist of sex related risks could be a positive addition to sexuality education if we want to encourage teenagers to delay sexual experience and to use condoms to prevent infection. This statement is based on results that reached statistical significance, meaning that the differences between teens assigned to RTR and RTR+ were not simply due to chance.

Some of these differences seem substantial. For example, Reyna and Mills note that being enrolled in RTR+ was 84% more effective at delaying the start of sexual activity when compared to the Control condition. At the same time some the differences were often very small even though they reached statistical significance. For example, teens assigned to RTR+ had fewer sexual partners than teens assigned to the regular RTR program. This result seems less impressive when you read that the teens in RTR+ reported an average of  2.15 partners while the teens in RTR reported an average of 2.21. In terms of a practical difference that would be of interest to parents and educators, this is almost nothing: both groups had about two sexual partners during that year.

Another issue is that interventions need to be tailored to the characteristics of the audience to be effective. The influence of race in the present study is especially important to note because teenagers from different racial groups differ in: how old they are when they start having sex; their risk of pregnancy (or getting somebody pregnant); and their risk of contracting a sexually transmitted infection (STI). Reyna and Mills also acknowledge that further research needs to focus on how and why concepts from Fuzzy Trace Theory may impact the sexual behaviors and beliefs of adolescents from diverse backgrounds.

Further Reading:

The Reyna and Mills (2014) article can be accessed through your local college library.

Watch a lecture by Dr. Valerie Reyna (one of the authors of this week's article) on "Risky Decision Making in Adolescence." This talk, given at Cornell University, covers, "...developmental differences in the way adolescents make decisions and reviews her research regarding why adolescents perceive risks and benefits and yet take more risks."

If you are interested in decreasing adolescent pregnancy and STIs, The National Campaign to Prevent Teen and Unplanned Pregnancy website includes statistics (state and national) and an excellent comparison of effective programs aimed at decreasing these problems. 

BONUS: The Reyna and Mills (2014) article includes a particularly cringe-worthy example used in RTR (and RTR+) as a warning sign that, "...unsafe sex may be imminent...": "being alone with a significant other, lights low and soft music playing..." (p. 1631). As goofy as that might sound to a modern teenager, I suppose that we do have evidence of its truth from the classic 1955 Disney film, "Lady and the Tramp."