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AP PSYCHOLOGY: INFORMATION & SUMMER PROJECT
Mrs. Lundgren, Instructor
Instructor email: [email protected]
REMIND MESSAGES: Text the message @lundgrenap to the number 81010
AP Psychology is a year long course comprised of thirteen intense units which will introduce students to the
systematic and scientific study of the behavior and mental processes of human beings and animals. The ultimate
goal is for students to perform well on the AP Psychology Exam administered by the College Board, therefore, it
is the expectation that all students will be taking the AP Exam in May. The AP Exam is $93.
Topics we will study include:
1. Introduction, History and Methodology
2. Research Methods
3. Biological Bases of Behavior
4. Sensation and Perception
5. States of Consciousness
6. Learning
7. Cognition (Memory, Thinking, Problem Solving, Creativity and Language)
8. Motivation and Emotion; Stress & Health
9. Developmental Psychology
10. Personality
11. Testing & Individual Differences
12. Abnormal Psychology
13. Treatment of Psychological Disorders
14. Social Psychology
Here is what you can expect in this course…
✔ Lots of independent reading from the text and selected primary sources
✔ A great deal of class discussion, lecture, and interactive demonstrations/labs
✔ Practice tests that will prepare you for the May exam
✔ Projects that will help you apply course material
✔ Quizzes, quizzes and quizzes. You will find these very helpful when it comes to how well you are taking
your notes. If you don’t read, you will not do well on the quizzes…all quizzes are open note
✔ I promise that I will do MY best to prepare you in the best way I know!
By the end of the year I hope you will be better critical thinkers and will have mastered the
content of Introductory Psychology at the college level!!!
***STUDY GUIDE: Purchase an AP Psychology Study Guide!!!
My top choice is the AP Psychology prep book Barron’s AP Psychology study guide by Robert McEntarffer but
ANY AP Psychology study guide will be useful!!! These are listed around $18.95 from major retailers but are
usually much less if ordered online. Bring it to class on the first day. “They ran out and I had to order it” will
not get you an approved excuse. Make sure your NAME is on it ☺
ALL ASSIGNMENTS ARE SUBMITTED IN GOOGLE CLASSROOM!!!
Part I: Log in to google with your SCHOOL EMAIL/PASSWORD and Join AP Psychology
1. Go to google.com
2. SIGN IN WITH SCHOOL EMAIL AND PASSWORD 3. Go to the waffle in the top right corner and click google classroom. 4. IF you are signed in, click continue and click I'm a student. 5. Click the + sign in the top right corner to Join Class 6. Enter the class code: a3dhbbb and click JOIN
Part II: Personal Statement — Due June 20 Directions: Psychology is defined as the science of human and animal behavior and mental processes (Myers,
2001). In order to get to know you better, I would like to learn what I could about how you view yourself and
the world we live in. Please answer each of the 8 topics fully, using FULL sentences and proper grammar. This
response is worth 30 points. Please type this assignment in google classroom!!! Please note that late assignments
will only count for HALF credit. Write in the boxes provided and use appropriate English and grammar. Due to
the personal nature of this paper, this will NOT be shared with anyone…feel free to include as much personal
info as you feel comfortable doing. However, I am a mandated reporter if you include any information putting
you in danger I have to report it.
You and your traits:
What kind of person are you? Describe characteristic personality traits and talents, positive & negative.
Your family and friends:
What kind of family and friends do you have and how have they affected your life?
Your social persona:
How has gender, race/ethnicity, religious beliefs, & socioeconomic status affected your attitudes & life?
Your achievements:
List as many of your accomplishments/recognition/awards that you can recall. Describe two that you consider to
be your greatest achievements.
Your present and past problems:
What have been or are your greatest problems? Describe any unusual circumstances or challenges you have
faced and the ways you have responded.
Your future plans:
What do you plan for yourself after high school? Why are you taking this course? (don’t worry, I will not take
offense to any answer like “my counselor put me in it!”)
Your interests:
What are your interests? List all areas or as many as come to mind. Include something academic such as your
favorite subject in school.
You and Psychology:
What subjects or issues in Psychology are you most interested in learning about?
[look at the outline on the 1st page to get an idea of what we study!]
Part III: Reaction Paper: Summer – Submitted by July 18
Directions: Below (and also in GOOGLE CLASSROOM) are 7 articles that relate to topics in
psychology. Pick THREE of the first SIX articles ALONG WITH the last article (Body Image and
Eating Patterns). You will be doing FOUR articles total. For each article you are going to write a
short analysis including a concise summary, the problem addressed, any procedures mentioned, and the
relevance of the article. Make sure you title each section with the article title!
For each article:
❖ Content: Write a concise summary of the article in your own words. Include information about the
problem/theory addressed, procedures (as you understand them—what was tested? How was it
tested?), results, and conclusions of the researchers.
❖ Relevance: Describe the relevance of the article for a particular topic you have previously learned
about in a different class, its real life implications, or what you would like to discuss in this course.
Part IV: Chapter 1 Coursework DON’T WAIT TO START THIS ONE!!!
Due on the first day of school
You must obtain your textbook and supplementary book (40 Studies) through the bookroom before
the end of the year or over the summer.
1. Read MODULES 1, 2, & 3 in the textbook.
2. TAKE NOTES! These notes CANNOT be electronic. MUST be handwritten ☺
3. Go To GOOGLE CLASSROOM and log in.
4. There will be a quiz for Unit 1.
5. You must take (and retake) the quiz until you get at LEAST a 75%.
Study links brain anatomy, academic achievement, and family income
Date: April 17, 2015 Source: Massachusetts Institute of Technology In middle-schoolers, neuroscientists find differences in brain structures where knowledge is stored. Credit: Illustration: Jose-Luis Olivares/MIT
Many years of research have shown that for students from lower-income families, standardized test scores and other measures of academic success tend to lag behind those of wealthier students. A new study led by researchers at MIT and Harvard University offers another dimension to this so-called "achievement gap": After imaging the brains of high- and low-income students, they found that the higher-income students had thicker brain cortex in areas associated with visual perception and knowledge accumulation. Furthermore, these differences also correlated with one measure of academic achievement -- performance on standardized tests.
"Just as you would expect, there's a real cost to not living in a supportive environment. We can see it not only in test scores, in educational attainment, but within the brains of these children," says MIT's John Gabrieli, the Grover M. Hermann Professor in Health Sciences and Technology, professor of brain and cognitive sciences, and one of the study's authors. "To me, it's a call to action. You want to boost the opportunities for those for whom it doesn't come easily in their environment." This study did not explore possible reasons for these differences in brain anatomy. However, previous studies have shown that lower-income students are more likely to suffer from stress in early childhood, have more limited access to educational resources, and receive less exposure to spoken language early in life. These factors have all been linked to lower academic achievement. In recent years, the achievement gap in the United States between high- and low-income students has widened, even as gaps along lines of race and ethnicity have narrowed, says Martin West, an associate professor of education at the Harvard Graduate School of Education and an author of the new study.
"The gap in student achievement, as measured by test scores between low-income and high-income students, is a pervasive and longstanding phenomenon in American education, and indeed in education systems around the world," he says. "There's a lot of interest among educators and policymakers in trying to understand the sources of those achievement gaps, but even more interest in possible strategies to address them." Allyson Mackey, a postdoc at MIT's McGovern Institute for Brain Research, is the lead author of the paper, which appears the journal Psychological Science . Other authors are postdoc Amy Finn; graduate student Julia Leonard; Drew Jacoby-Senghor, a postdoc at Columbia Business School; and Christopher Gabrieli, chair of the nonprofit Transforming Education.
Explaining the gap
The study included 58 students -- 23 from lower-income families and 35 from higher-income families, all aged 12 or 13. Low-income students were defined as those who qualify for a free or reduced-price school lunch. The researchers compared students' scores on the Massachusetts Comprehensive Assessment System (MCAS) with brain scans of a region known as the cortex, which is key to functions such as thought, language, sensory perception, and motor command. Using magnetic resonance imaging (MRI), they discovered differences in the thickness of parts of the cortex in the temporal and occipital lobes, whose primary roles are in vision and storing knowledge. Those differences correlated to differences in both test scores and family income. In fact, differences in cortical thickness in these brain regions could explain as much as 44 percent of the income achievement gap found in this study. Previous studies have also shown brain anatomy differences associated with income, but did not link those differences to academic achievement.
In most other measures of brain anatomy, the researchers found no significant differences. The amount of white matter -- the bundles of axons that connect different parts of the brain -- did not differ, nor did the overall surface area of the brain cortex. The researchers point out that the structural differences they did find are not necessarily permanent. "There's so much strong evidence that brains are highly plastic," says Gabrieli, who is also a member of the McGovern Institute. "Our findings don't mean that further educational support, home support, all those things, couldn't make big differences."
In a follow-up study, the researchers hope to learn more about what types of educational programs might help to close the achievement gap, and if possible, investigate whether these interventions also influence brain anatomy. "Over the past decade we've been able to identify a growing number of educational interventions that have managed to have notable impacts on students' academic achievement as measured by standardized tests," West says. "What we don't know anything about is the extent to which those interventions -- whether it be attending a very high-performing charter school, or being assigned to a particularly effective teacher, or being exposed to a high-quality curricular program -- improves test scores by altering some of the differences in brain structure that we've documented, or whether they had those effects by other means."
Massachusetts Institute of Technology. (2015, April 17). Study links brain anatomy, academic achievement, and family income. ScienceDaily . Retrieved April 17, 2015 from www.sciencedaily.com/releases/2015/04/150417121908.htm
What is more rewarding: Soccer goal or prize money? Date: April 15, 2015 Source: Universität Bonn Prof. Dr. Bernd Weber (left) and Alexander Niklas Häusler from the Center for Economics and Neuroscience at Bonn University. Soccer fans hold their breath in situations like these: Two players on a team are in front of the opponent's goal with the attacking player having to make an important decision: Is it better to pass the ball to the teammate or to take the shot yourself? What happens in the brain during the course of such situations and upon scoring a goal is very similar to the processes and reward sequence with monetary incentives. This is what researchers at the Center for Economics and Neuroscience (CENs) of the University of Bonn discovered together with their colleagues at the University of Bonn Hospital and the Life&Brain Center. They are now presenting their results in the journal PLOS ONE. As a preliminary study, the researchers showed 200 different photos depicting such scenes in front of the opponent's goal to 377 German soccer players. The players were asked to estimate in each situation whether they would pass the ball or take aim at the goal themselves and about the chances of scoring a goal from each point of view. "Using this method, we obtained representative data from experienced soccer players regarding the situations in which, based on experience, the chances of scoring a goal are higher when passing or shooting," says Prof. Dr. Bernd Weber from the Center for Economics and Neuroscience of the University of Bonn. The next step of the study followed by using these results: The brain activity in a total of 33 male soccer players was measured using magnetic resonance imaging (MRI) while they were shown situations in front of the goal using video goggles. With the push of a button, they were able to report whether they would pass the ball to a teammate or would rather prefer to shoot the ball themselves. They subsequently learned whether or not a goal was made. "Two phases of the experiment are of particular interest to us. Firstly, which processes in the brain take place during the decision to either pass or shoot the ball. Secondly, which brain areas are active when a goal is scored or not," says lead author Alexander Niklas Häusler, a doctoral student of Prof. Weber at the CENs and an active amateur soccer player himself. Using the recording of brain activity, it could be decoded which regions induce the decisions, how they work together, and how this relates to frustration or euphoria after the shot. Reward areas of egotistical players were not more active. A personality test was used to investigate the egoism of the soccer players participating in the study. In contrast to expectations, the players with a more egotistical personality did not demonstrate increased activity in the reward areas when they scored a goal themselves. On the contrary: Brain regions associated with learning and reflection were significantly more active in these players when a goal was made after the ball was passed to a teammate. "Our results indicate that more egotistical players perceive goals after their own shots as rather normal and are less positively surprised by their goal," says Häusler. Are athletes wired differently during soccer games or does the brain work similarly in everyday situations? To answer this question, the scientists conducted a standard monetary incentive test with the same soccer players: Again in the MRI, the participants had to guess which of up to four boxes displayed a hidden filled-in circle. If they guessed the correct box, they won money. "With this classical experiment, various aspects of reward processing can be investigated very well," says Häusler. The brain works very similarly upon soccer goals and financial wins. It came to a surprise that during soccer decisions and also during decisions involving monetary incentives, very similar regions of the reward network in the brain were activated: From studies involving monetary incentives, it is known that the so-called ventral striatum and the ventromedial prefrontal cortex play crucial roles here. The former is responsible for calculating the chances of success, for example, for scoring goals or winning money. The latter appraises the expected reward if the action is met with success. From many studies, the researchers at the University of Bonn know that the regions are always particularly active if the event unexpectedly surpasses the previously held expectations. "Although athletic successes and monetary incentives are very different things, the results demonstrate that the reward processing of goals in comparison to money takes place in an amazingly similar way in the brain," reports Prof. Weber. Universität Bonn. "What is more rewarding: Soccer goal or prize money?." ScienceDaily. ScienceDaily, 15 April 2015. <www.sciencedaily.com/releases/2015/04/150415140538.htm>.
Synesthesia: Why some people hear color, taste sounds Date: April 13, 2015 Source: The Australian National University
ANU researchers have shed new light on synesthesia. Credit: © Ragnarocks / Fotolia Researchers at The Australian National University (ANU) have shed new light on synesthesia -- the effect of hearing colors, seeing sounds and other cross-sensory phenomena.Lead Researcher, ANU Research School of Psychology's Dr Stephanie Goodhew, said the research found synesthetes had much stronger mental associations between related concepts. "For them words like 'doctor' and 'nurse' are very closely associated, where 'doctor' and 'table' are very unrelated. Much more so than for people without the condition," she said. The findings could help researchers better understand the mysteries of synesthesia, which Dr Goodhew said affects an estimated one in every 100 people. Dr Goodhew said synesthetes have stronger connections between different brain areas, particularly between what we think of as the language part of the brain and the color part of the brain. Those connections lead to a triggering effect, where a stimulus in one part of the brain would cause activity in another. "Things like hearing shapes, so a triangle will trigger an experience of a sound or a color, or they might have a specific taste sensation when they hear a particular sound," she said. "One person reported that smells have certain shapes. For example the smell of fresh air is rectangular, coffee is a bubbly cloud shape and people could smell round or square." The research centered on measuring the extent that people with Synesthesia draw meaning between words. "Going in we were actually predicting that synesthetes might have a more concrete style of thinking that does not emphasize conceptual-level relations between stimuli, given that they have very rigid parings between sensory experiences. "We found exactly the opposite," Dr Goodhew said.
The Australian National University. "Synesthesia: Why some people hear color, taste sounds." ScienceDaily. ScienceDaily, 13 April 2015. <www.sciencedaily.com/releases/2015/04/150413214343.htm>
Discovery of communication link between brain areas implicated in schizophrenia Date: April 7, 2015 Source: Cold Spring Harbor Laboratory The CSHL team induced PV interneurons of the medial prefrontal cortex (mPFC) to produce a red fluorescent marker that illuminates any neurons providing input to them. A direct connection is implied, therefore, with red-labeled neurons seen in this image, located in the mediodorsal thalamus (MD). Li's team has discovered an inhibitory circuit between the two brain areas that when disrupted may underlie cognitive disorders such as schizophrenia. The prefrontal cortex (PFC) plays an important role in cognitive functions such as attention, memory and decision-making. Faulty wiring between PFC and other brain areas is thought to give rise to a variety of cognitive disorders. Disruptions to one particular brain circuit--between the PFC and another part of the brain called the thalamus--have been associated with schizophrenia, but the mechanistic details are unknown. Now, Cold Spring Harbor Laboratory scientists have discovered an inhibitory connection between these brain areas in mice that can control the timing of information flow into PFC. This insight may help explain what goes wrong in schizophrenia and indicate a path to new treatments. A coronal section of a mouse brain. Bo Li and colleagues induced PV interneurons of the medial prefrontal cortex (mPFC) to produce a red fluorescent marker that illuminates any neurons providing input to them. A direct connection is implied, therefore, with red-labeled neurons seen in this image, located in the mediodorsal thalamus (MD). Li's team has discovered an inhibitory circuit between the two brain areas that when disrupted may underlie cognitive disorders such as schizophrenia. "The PFC and thalamus have been implicated in schizophrenia in studies of humans as well as animal models," says CSHL Associate Professor Bo Li, "yet the mechanism underlying the communication between these two areas has been unclear." The thalamus acts as a gateway through which information from other parts of the brain is collected and processed before being sent on to the cortex. This thalamocortical circuit is often fine-tuned by inhibitory neurons, which tamp down signaling between message-propagating excitatory neurons. Li and colleagues focused on connections between sections of the PFC and the thalamus called the medial prefrontal cortex (mPFC) and the mediodorsal thalamus (MD). They observed a process called feedforward inhibition, a mechanism in which one neuron excites a neighboring or "downstream" neuron, but also recruits a third neuron to inhibit the downstream target after some delay. This process opens a narrow window in time during which the target neuron can be activated. When the thalamus propagates information gathered from the senses, feedforward inhibition acts to filter out extraneous inputs, resulting in highly precise sensory representations. Prior to the current research it was not known whether a similar inhibitory mechanism exists for the neural connection between mPFC and MD. The latter is an area associated with cognitive functioning rather than sensory processing. As described in work published in The Journal of Neuroscience, Li and his colleagues used optogenetic stimulation, a technique in which neurons expressing a light-sensitive protein are controlled with pulses of light, to activate neurons in the thalamus. These neurons in turn activated two classes of cells in the prefrontal cortex -- inhibitory PV interneurons as well as excitatory pyramidal neurons. The relative timing of their activation suggested to Li's team that the inhibitory cells might be shaping the activity of the excitatory ones.. The team now proposes that PV interneurons can dictate the time period during which the pyramidal neurons integrate excitatory input from neurons in the thalamus. "The current problem for treating schizophrenia is the lack of drugs that work, so the discovery of this mechanism for the disease is exciting," says Li. "This work is just the beginning of efforts to specify a neural pathway implicated in schizophrenia and what changes occur in this pathway." In future experiments, Li and his team will assess in a genetic mouse model of schizophrenia whether there are any noticeable changes in the observed feedforward inhibition in the MD-mPFC pathway. "This research can guide us to develop methods to reverse any changes we see in the MD-mPFC pathway in the animal model and could lead to improved therapeutics for this disease," says Li. Cold Spring Harbor Laboratory. "Discovery of communication link between brain areas implicated in schizophrenia." ScienceDaily. ScienceDaily, 7 April 2015. <www.sciencedaily.com/releases/2015/04/150407210901.htm>.
Don't blame kids if they do not enjoy school, study of twins suggests Date: April 8, 2015 Source: Ohio State University Why are some young people more motivated to learn than others? Genetics may play a key role. When children are unmotivated at school, new research suggests their genes may be part of the equation. A study of more than 13,000 twins from six countries found that 40 to 50 percent of the differences in children's motivation to learn could be explained by their genetic inheritance from their parents. The results surprised study co-author Stephen Petrill, who thought before the study that the twins' shared environment -- such as the family and teachers that they had in common -- would be a larger factor than genetics. Instead, genetics and nonshared environment factors had the largest effect on learning motivation, whereas the shared environment had negligible impact. "We had pretty consistent findings across these different countries with their different educational systems and different cultures. It was surprising," said Petrill, who is a professor of psychology at The Ohio State University. The results strongly suggest that we should think twice before automatically blaming parents, teachers and the children themselves for students who aren't motivated in class. "The knee-jerk reaction is to say someone is not properly motivating the student, or the child himself is responsible," Petrill said. "We found that there are personality differences that people inherit that have a major impact on motivation. That doesn't mean we don't try to encourage and inspire students, but we have to deal with the reality of why they're different." The findings appear in the July 2015 issue of the journal Personality and Individual Differences. The study involved separate studies of twins aged 9 to 16 in the United Kingdom, Canada, Japan, Germany, Russia and the United States. The study methodology and questions in each country were slightly different, but all measured similar concepts. In all the countries, students completed a measure of how much they enjoyed various academic activities. For example, in Germany, students rated how much they liked reading, writing and spelling. All students were also asked to rate their own ability in different subjects in school. For example, in the United States, students were asked to rate how much they agreed with statements like "I know that I will do well in reading next year." The researchers compared how close the answers were for fraternal twins -- who share half their inherited genes, on average -- with identical twins, who share all of their inherited genes. To the extent that identical twins' answers were more closely matched than those of fraternal twins, that suggests a stronger genetic effect. The results were strikingly similar across all six countries with children of all ages, Petrill said. On average, 40 to 50 percent of the difference between twins in motivation could be explained by genetics. About the same percentage could be explained by what is called the twins' nonshared environment -- for example, differential parenting or a teacher that one twin has but not the other. Only about 3 percent could be explained by their shared environment, such as their common family experience. "Most personality variables have a genetic component, but to have nearly no shared environment component is unexpected," Petrill said. "But it was consistent across all six countries." The results don't mean there is a gene for how much children enjoy learning, he said. But the findings suggest a complex process, involving many genes and gene-environment interactions, that help influence children's motivation to learn. "We should absolutely encourage students and motivate them in the classroom. But these findings suggest the mechanisms for how we do that may be more complicated than we had previously thought," he said. Petrill had 25 co-authors from institutions in all six countries. The lead author was Yulia Kovas, a professor of psychology at Goldsmiths, University of London. The study was partially supported by a grant from the Eunice Kennedy Shriver National Institute of Child Health and Development. Ohio State University. "Don't blame kids if they do not enjoy school, study of twins suggests." ScienceDaily. ScienceDaily, 8 April 2015. <www.sciencedaily.com/releases/2015/04/150408113309.htm>.
A sniff of happiness: Chemicals in sweat may convey positive emotion Date: April 16, 2015Source: Association for Psychological Science Chemicals in our sweat show others when we are truly happy, and the feeling is infectious. Humans may be able to communicate positive emotions like happiness through the smell of our sweat, according to new research published in Psychological Science, a journal of the Association for Psychological Science. The research indicates that we produce chemical compounds, or chemosignals, when we experience happiness that are detectable by others who smell our sweat. While previous research has shown that negative emotions related to fear and disgust are communicated via detectable regularities in the chemical composition of sweat, few studies have examined whether the same communicative function holds for positive emotions. "Our study shows that being exposed to sweat produced under happiness induces a simulacrum of happiness in receivers, and induces a contagion of the emotional state," explains psychological scientist Gün Semin of Utrecht University in the Netherlands, senior researcher on the study. "This suggests that somebody who is happy will infuse others in their vicinity with happiness. In a way, happiness sweat is somewhat like smiling -- it is infectious." To determine whether this emotional chemosignaling extends to positive emotions, Semin and colleagues examined whether sweat taken from people in a happy state would influence the behavior, perception, and emotional state of people exposed to the sweat. The researchers recruited 12 Caucasian males to provide the sweat samples for the study. The participants did not smoke or take any medications, and had no diagnosed psychological disorders. They were prohibited from engaging in alcohol use, sexual activity, consumption of smelly food, or excessive exercise during the study. The sweat donors came to the lab, rinsed and dried their armpits, and had absorbent pads attached to each armpit. They donned a prewashed T-shirt and sat down to complete the study tasks. They watched a video clip intended to induce a particular emotional state (fear, happiness, neutral) and they also completed a measure of implicit emotion, in which they were asked to view Chinese symbols and rate how pleasant or unpleasant each one was. The sweat pads were then removed and stored in vials. For the second part of the study, the researchers recruited 36 Caucasian females, with no psychological disorder, respiratory disease, or other illness. The researchers note that only females were included in this part of the study as women generally have both a better sense of smell and a greater sensitivity to emotional signals than men do. The study was double-blind, such that neither the researcher nor the participant knew which sweat sample the participant would be exposed to at the time of the experiment. The women were seated in a chair and placed their chins on a chin rest. The vial containing the sweat sample was placed in a holder attached to the chin rest and was opened immediately prior to the target task. The women were exposed to a sweat sample of each type (fear, happiness, neutral), with a 5-minute break in between samples. Initial data analyses confirmed that the videos did influence the emotional states of the male participants -- men who watched the fear video showed predominantly negative emotion afterward and men who watched the happiness video showed predominantly positive emotion. But were these emotions conveyed to the female participants? Some behavioral results suggest the answer is "yes." Facial expression data revealed that women who were exposed to "fear sweat" showed greater activity in the medial frontalis muscle, a common feature of fear expressions. And women who were exposed to "happy sweat" showed more facial muscle activity indicative of a Duchenne smile, a common component of happiness expressions. There was no observable association, however, between the women's facial responses and their explicit ratings of how pleasant and intense the sweat was. These findings, the researchers say, suggest a "behavioral synchronization" between the sender (the sweat donor) and receiver (the sweat smeller). Additional data indicated that women exposed to happy sweat showed a more global focus in perceptual processing tasks, in line with previous research showing that participants induced to experience positive mood tended to show more global processing styles. But the sweat samples did not seem to impact the women's ratings on the Chinese symbols task, suggesting that the sweat-based chemosignals did not bias their implicit emotional states. These findings, while preliminary, suggest that we communicate our positive and negative emotional states via distinct chemosignals, such that the receiver produces a simulacrum of the sender's emotional state. The researchers note that the fact that some measures indicated emotional contagion, while others did not, may highlight the difference between measures of emotion that draw on language versus those that don't. The findings have broad relevance -- emotion and sweat are two core features of the human experience, after all. But the fact that happiness may be communicated chemically could be of particular interest to the "odor industry," says Semin, due to its potential commercial applications. "This is another step in our general model on the communicative function of human sweat, and we are continuing to refine it to understand the neurological effects that human sweat has on recipients of these chemical compounds," Semin concludes. Study co-authors include Jasper H.B. de Groot of Utrecht University; Monique A.M. Smeets of Utrecht University and Unilever Research and Development; and Matt J. Rowson, Patricia Bulsin, Cor G. Blonk, and Joy E. Wilkinson of Unilever Research and Development. Association for Psychological Science. "A sniff of happiness: Chemicals in sweat may convey positive emotion." ScienceDaily. ScienceDaily, 16 April 2015. <www.sciencedaily.com/releases/2015/04/150416084348.htm>.
Body image and eating patterns among adolescents BMC Public Health. Published online 2013 Dec 1.
Background Adolescence is a transitional stage and many changes take place at physiological and behavioural levels. Among adolescents, the prevalence of overweight and obesity has risen greatly worldwide [1,2], and among the Balearic Islands’ adolescents the prevalence of overweight (19.9% boys and 15.5% girls) and obesity (12.7% boys and 8.5% girls) should take into consideration [3]. Adolescent obesity is associated with significant immediate and long term health risks, and also predicts obesity in adulthood and increase risk of adult morbidity and mortality [1,2]. A pattern of healthy eating habits and adequate physical activity during adolescence reduces the risk of major chronic diseases [4-6]. However, a high intake of total fat, saturated fat and sodium, a low intake of vitamins and minerals, and a low consumption of fruits and vegetables are usual dietary patterns among adolescents [7-9], and only a small proportion of the Balearic Islands’ adolescents met the requirements of dietary fibre, folate, iodine, total fat, saturated fat, polyunsaturated fatty acid, total carbohydrate, and fruit and vegetables [10]. It has been pointed out that people with higher relative weight usually underreported their food intake [11]. However, controversial results have been reported on the association between food consumption and overweight and obesity, which can be attributed to overestimation of healthy foods and underestimation of unhealthy foods. Moreover, to avoid high-calorie foods has been associated with attempts to lose weight in adolescents [12,13]. Body image is a multidimensional construct central to emotional well-being in which the attitudinal component is satisfaction with body size, a factor associated with self-esteem [14]. During this period, the self-evaluation of body image and social patterns of beauty are factors that have a strong influence on eating habits [15-17]. Currently, there is a lack of data referring to the association between body self-perception and eating patterns among overweight and obesity in adolescents. Therefore these data are needed in order to design interventions to improve an effective nutrition and weight counselling among adolescents.The aim of this study was to assess the association between body image and eating patterns among normal-weight, overweight and obese adolescents.
Methods
Study design The study is a population-based cross-sectional nutritional survey carried out (2007–2008) in the Balearic Islands (Spain), a Mediterranean region.
Selection of participants, recruitment and approval A multicenter study was performed on Balearic Islands’ adolescents aged 12–17 years.The population was selected by means of a multiple-step, simple random sampling, first taking into account the location (Palma de Mallorca, Calvià, Inca, Manacor, Maó, Eivissa, Llucmajor, Santa Margalida, S’Arenal, Sant Jordi de Ses Salines) and then by random assignment of the schools within each city. Sample size was stratified by age and sex. The socio-economic variable was considered to be associated to geographical location and type of school. As the selection of schools was done by random selection and fulfilling quota, this variable was also considered to be randomly assigned. To calculate a representative number of adolescents, the variable BMI with the greatest variance for this age group from the data published in the literature at the time the study was selected [18]. Sampling was determined for the distribution of this variable; and a confidence interval (CI) was established at 95% with an error ± 0.25. The total number of subjects (1500) was uniformly distributed in the cities and proportionally distributed by sex and age. Exclusion criteria used were: type 2 diabetes, pregnancy, alcohol or drug abuse, and non-directly related nutritional medical conditions. The sample was oversized to prevent information loss and done when necessary to do the fieldwork in complete classrooms. In each school, classrooms were randomly selected among those of the same grade or level, and all the adolescents of one classroom were proposed to participate in the survey. A letter about the nature and purpose of the study informed parents or legal tutors and after receiving their written consent, the adolescents were considered for inclusion in the study. All responses to the questionnaires were filled in by adolescents. After finishing the field study, the adolescents who did not fulfil the inclusion criteria were excluded. Finally, the sample was adjusted by a weight factor in order to balance the sample in accordance to the distribution of the Balearic Islands’ population and to guarantee the representativeness of each of the groups, already defined by the previously mentioned factors (age and sex). The final number of subjects included in the study was 1231 adolescents (82% participation). Reasons for not participate were (a) the subject declined to be interviewed, and (b) the parents did not authorize the interview.
Anthropometry measurements Height was determined using a mobile anthropometer (Kawe 44444, Asperg, Germany) measured to the nearest millimetre, with the subject’s head in the Frankfurt plane. Body weight was determined to the nearest 100 g using a digital scale (Tefal, sc9210, Rumilly, France), and subjects were weighed in bare feet and light underwear. Waist circumference (WC) and hip circumference (HC) were measured using a non-stretchable measuring tape (Kawe, 43972, France). The subjects were asked to stand erect in a relaxed position with both feet together on a flat surface. WC was measured as the smallest horizontal girth between the costal
margins and the iliac crests at minimal respiration with measurements taken to the nearest 0.1 cm. HC was taken as the greatest circumference at the level of greater trochanters (the widest portion of the hip) on both sides with measurements taken to the nearest 0.1 cm. Triceps and subscapular skinfold thickness (ST) were measured on the right side of the using a Holtain skinfold caliper (Tanner/Whitehouse, Crosswell, Crymych, UK), and a mean of three measurements was used. Body fat percentage (%BF) was calculated from triceps and subscapular ST according to Slaughter et al. [19]. This equation has been proposed as the most accurate for estimation of %BF from ST in this particular population of adolescents [20]. Height and weight measures were used to calculate body mass index (BMI, kg/m2) and WC and height were used to calculate waist-to-height ratio (WHtR). %BF and height were used to calculate fat mass index (FMI; kg/m2).
Defining overweight and obesity Adolescents were age- and sex-specific classified using the BMI cut-offs developed and proposed by the International Obesity Task Force (IOTF) [21] and Cole et al. [22] definitions, and then subjects were classified as normal-fat and overfat according to their FMI using sex-specific cut-offs proposed for adolescents: 4.58 kg/m2 in boys and 7.76 kg/m2 in girls [23]. Thus, adolescents were classified into five weight and fat groups as following: 1) Underweight and normal-weight normal-fat (BMI for age and sex < P85; FMI < 4.58 kg/m2 in boys, FMI < 7.76 kg/m2 in girls). 2) Normal-weight overfat (BMI for age and sex < P85; FMI ≥ 4.58 kg/m2 in boys, FMI ≥ 7.76 kg/m2 in girls). 3) Overweight normal-fat (BMI for age and sex > P85 and < P97; FMI < 4.58 kg/m2 in boys, FMI < 7.76 kg/m2 in girls). 4) Overweight overfat (BMI for age and sex equivalent to > P85 and < P97; FMI ≥ 4.58 kg/m2 in boys, FMI ≥ 7.76 kg/m2 in girls). 5) Obesity (BMI for age and sex ≥ P97).
Body image Perceived body image was measured using the Stunkard scale [24], which consists of silhouette drawings ranging from 1 to 9 with monotonic increments in overweight percentage where 1 is the leanest and 9 is the heaviest. Separate figures for boys and girls were used. Participants were asked to identify of the 9 body figures: (a) ‘Which silhouette looks most like yourself?’ and (b) ‘Which silhouette would you like to look like?’ The difference between perceived body image and wished body image was used to determine the level of dissatisfaction with current body image. Values other than zero represent dissatisfaction with perceived body image. A positive value was indicative of the participant’s wish to be thinner than his/her perceived current size, while a negative value reflected the participant’s wish to be thicker than his/her current perceived size [25,26].
Dietary assessment Dietary assessment was assessed by using a validated [27] semi-quantitative food-frequency questionnaire (FFQ) covering 145 items (118 of the original validated FFQ plus the most characteristic Balearic Islands foods in order to make easy the interviewee answer). The FFQ evaluated average consumption over the past year. To prevent seasonal variations, the questionnaire was administered in the warm season (May-September) and in the cold season (November-March). Food consumption frequency was based on times that food items were consumed (per day, week or month). Consumption <1/month was considered no consumption. Daily food consumption (g/d) was determined by dividing the reported amount (g) of food consumed by the frequency of intake (d). Volumes and portion sizes were reported in natural units, household measures or with the aid of a manual of sets of photographs [28]. The 145 foods items from the FFQ were reduced to twenty-eight food groups, which may have practical importance in daily diet and clinical practice with Mediterranean youths [29,30]. Well-trained dieticians administered, verified and quantified all dietary questionnaires. To estimate volumes and portion sizes, the household measures found in the subjects’ own homes were used. Conversion of food into nutrients was done using a computer program (ALIMENTA®, NUCOX, Palma, Spain) based on Spanish [31,32] and European [33] food composition tables and complemented with food composition data available for Majorcan food items [34]. As an identification of misreporters: an energy intake (EI)/basal metabolic rate (BMR) ratio of <0.92 (boys) and <0.85 (girls) was considered to represent underreporters [35], and an EI:BMR ≥2.4 as overreporters [36].
Assessment of meal patterns The number of daily meals and snacks was calculated from the total eating occasions that participants declared among the following: breakfast, mid-morning snack, lunch, mid-afternoon snack, dinner, before going to sleep, others. Three groups of eating frequency were considered: ≤3, 4 and ≥5 times/d. Information about breakfast habit (yes; occasionally; no) was also collected.
Assessment of socioeconomic factors Socio-demographic factors were recorded using a questionnaire that included age group, parental education level (according to years and education type: low, <6 years; medium, 6–12 years; high, >12 years), and parental profession level (based on the occupation of parents and classified as low, medium and high, according to the Spanish Society of Epidemiology [37].
Statistics Analyses were performed with Statistical Package for the Social Sciences version 21.0 (SPSS, Inc., Chicago, IL, USA). Significant differences in energy intake were calculated by means of ANOVA, and significant differences in prevalence by means of χ2. We further applied multiple logistic regression analysis evaluating the association between body composition taking into account body image (normal-fat vs. overfat desiring to be thinner vs. overfat satisfied) with consumption frequencies of several food groups adjusted for potential confounders (age, parental educational level, parental socio-economic status, breakfast habit, number of daily meals and snacks). Level of significance for acceptance was P < 0.05.
Results
Body image according to body composition (BMI and FMI) Prevalance of normal-weight, overweight and obesity (BMI) according to overall adiposity (FMI) and desire to change weight. The three body weight groups obtained by the IOTF cut-offs (underweight and normal-weight, overweight, and obesity) were subgrouped according to presence or absence of overfat. Adolescents were classified into five groups as following: 73.2% underweight and normal-weight normal-fat, 2.1% normal-weight overfat, 6.7% overweight normal-fat, 11.9% overweight overfat and 6.1% obesity. The wish to change weight was assessed for each subgroup. Among boys, 39.1% of underweight and normal-weight normal-fat and 10.5% of overweight normal-fat adolescents reported to wish a thicker body shape; whereas 61.9% of normal-weight overfat, 82.4% of overweight overfat and 97.0% of obese boys reported to wish a thinner body shape. Among girls, around half of underweight and normal-weight normal-fat adolescents (47.8%) reported to wish a thinner body shape which increased according to the presence of excessive weight and/or excessive BF.
Meal patterns according to body composition and body image Associations between meal patterns and body composition taking into account satisfaction with their body shape (normal-fat vs. overfat wishing to be thinner vs. overfat satisfied). It is important to note that most of overfat girls (96.6%) wished to be thinner, and an inverse association with number of daily meals and snacks and breakfast habit was found among them. Overfat boys that wished a thinner body shape (82.8%) also were more likely to have ≤3 eating occasions per day (50.8%) than their overfat satisfied and normal-fat counterparts.
Food consumption according to body composition and body image Associations between the food consumption and individual items and satisfaction with own body shapes were also evaluated. Overfat boys that wished to be thinner were less likely to consume breakfast cereals, pasta and rice dishes, other oils and fats, high fat foods, soft drinks and chocolates than their satisfied and normal-fat counterparts. Compared with normal-fat girls, those who were overfat also reported to consume dairy desserts and chocolates with less frequency. When energy intake (EI) was calculated, overfat adolescents (37%) misreported their EI more often than normal-fat peers (10%). Overfat adolescents who wished to be thinner showed a significant (P < 0.001) lower EI than overfat adolescents satisfied with their body shape and normal-fat adolescents, and overfat adolescents wishing to be thinner also showed significant (P < 0.001) lower energy intake from saturated fat acids than normal-fat peers. Multiple logistic regression analysis (after adjustment by age, parental educational level, parental socio-economic status, breakfast habit, number of daily meals and snacks) showed that overfat that wished to be thinner were less likely to frequently eat red meat, pasta and rice dishes and other oils and fats than their satisfied and normal-fat counterparts.
Discussion The main findings of this study were: (1) many overfat boys were satisfied with their body image while practically all overfat girls reported to wish a thinner body; and (2) meal patterns and food consumption were associated with body dissatisfaction among overfat adolescents. In both genders, overfat adolescents that wished a thinner body were more likely to declare ≤3 eating occasions per day than normal-fat adolescents, and also than overfat boys satisfied with their own body image. Overfat girls that wish to be thinner skipped breakfast more frequently than normal-fat girls. Overfat boys and girls that wished a thinner body reported lower consumption of several food groups than normal-fat adolescents and overfat boys satisfied with their own body image (i.e. breakfast cereals, pasta and rice dishes, other oils and fats, high fat foods, soft drinks and chocolates in boys; and dairy products and chocolates in girls). Consequently, the overfat adolescents studied misreported their energy intake more often than normal-fat peers, and overfat adolescents dissatisfied with their body shape showed lower energy intake than normal-fat and satisfied peers. Restrictive eating practices related to a preoccupation with a slim image have been also reported among adolescents [38-40].
Gender differences in body satisfaction Boys and girls perceive their bodies in a different way [41]. It has been extensively previously reported that the current ideal male body is lean but highly muscular, characterised by a “well-developed chest and arms, with wide shoulders tapering down to a narrow waist” [42]. Thus, whereas boys with lower BMI and BF preferred a stronger muscular body, girls showed a preference for a slim body shape [41,43]. However, boys with elevated adiposity also showed a preference for a slim body shape; in fact, they
have been most likely to have negative feelings about their bodies [44]. It has been suggested that adolescents who are heavy and perceive themselves as overfat may have actively tried to lose weight [45], whereas adolescents who do not perceive themselves as heavy raise concerns may be less motivated to take steps to lose weight [46]. Moreover, despite that adolescents denigrate overweight and obesity, a decrease in body dissatisfaction has been suggested in studies among young people [47]. It has been also recognized that to be worried about body image is especially acute in puberty [48], but also that body image is an important target of intervention to improve subjective health in adolescence [49]. It has been pointed out that some level of body dissatisfaction may be beneficial for individuals with average or above-average weight, as it may lead to healthy weight management behaviours such as increased intake of fruits and vegetables and regular physical activity [50,51]. To understand how body shape satisfaction affects meal patterns, food preferences and the overall adolescent diet is a key issue for the development of strategies aimed at influencing dietary behaviour. Accordingly, findings from the present study will be useful to understand relationships between body image and eating patterns.
Meal patterns and food consumption are associated with body image A previous study reported that normal-fat adolescents were more likely to follow a Western dietary pattern than a Mediterranean dietary pattern, and the wish to have a thinner body shape was associated with a low consumption of the Western dietary pattern [52]. Moreover, it has been also reported that parallel to the omission of meals, it may be possible that overfat adolescents that wished to be thinner avoided the consumption of several foods to counteract being overfat; boys and girls have been reported to avoid sweets and salty snack consumption to counteract being overweight [3]. Accordingly, a study conducted among 3055 Massachusetts high school students (aged 16 ± 1.2 years) found that adolescents attempted to lose weight consumed fewer servings of fatty foods, but they did not increase fruit and vegetable consumption; to lose weight, they also ate few servings of desserts, whereas to gain weight they ate more servings of these foods [16]. Previous findings showed that girls tried to lose weight eating few servings of meat, fries, chips, and dessert foods, whereas to gain weight they consumed few servings of fruit and green salad and increased the consumption of fries and chips [16]. A study conducted among 1220 Costa Rican adolescents (aged 12–18 years) showed that body image was associated with a high consumption of high-calcium and saturated fat foods, iron rich foods, and fruits and vegetables [53]. Our results suggest that adolescents that wish a thinner body decreased consumption of typical-Western-diet foods, but they did not increase consumption of fruits and vegetables, which may reflect a diet restriction rather than eating healthier food as a method to lose weight. Overall, the current results highlight the importance of body image on adolescent nutritional habits and food choices. Particularly, a restriction of typical-Western-diet foods is associated with a wish to be thinner among overfat adolescents. A task for future research could be to include assessments of body image to better understand the prospective and concurrent contributions of body image to food consumption patterns among normal-weight, overweight and obesity adolescents. Our data could be useful to practitioners in targeting educational messages for individuals’ specific eating patterns and to community planners in encouraging the availability of a healthy dietary pattern.
Conclusions Many overfat boys were satisfied with their body image while practically all overfat girls reported wishing a thinner body. Meal patterns and food consumption were associated with body dissatisfaction and overfat status among adolescents.
Strengths and limitations This study has some limitations. The difficulties for assessing food intake among young people are well known but it should not serve as a deterrent to pursue this line of research. Moreover, BF was calculated using Slaughter et al. equations [19], which have been previously reported [20]. This study did not take into account pubertal development; however, a previous study [51] classified adolescents according to their pubertal stage and divided boys in two groups: pubertal (12–14 y.o.) and post-pubertal (15–17 y.o.). Moreover, it should be noted that we cannot ignore that adolescents that wish to be thinner could overestimate healthy foods consumption and underestimate unhealthy foods consumption; it has been well documented that people with high relative weight usually underreported their food intake [11]. Finally, we cannot infer causality because of the cross-sectional design of the study. This study also has several strengths. New data is provided about the association between body image and food consumption patterns among adolescents according to their body composition. Specifically, it provides data evaluating the association between food consumption and dissatisfaction with overfat status among adolescents, which is scarce in this age group. Moreover, most of the previous studies in adolescents analyzed differences in perception of body image and weight concerns according to gender [49], ethnic and social differences [41], and overweight and obesity status, showing that BMI is positively related to body dissatisfaction [43-45]. However, in the present study, the association between body image and food consumption patterns according to body composition has been demonstrated. Thirdly, the use of BMI for age to define being overweight and obesity in children and adolescents is well established for both clinical and public health applications [54,55]. However, it has been recognized that elevation of BMI does not always equate to increased adiposity because it does not distinguish between BF mass and lean body mass [56], whereas the FMI has a high accuracy level for overweight screening [23]. Accordingly, after several statistically known potential confounding factors were controlled in this study, the adolescent population was classified according to both BMI and FMI, as it has been published elsewhere [57].
