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1- Only conducted in USA, culture plays a part
2- Gender
3- A child won't necessary know their sexuality
4- Unethical because they were not asking the participants 🤬 their relatives about their sexuality instead
5- the participants were already briefed about the study hence the results may vary (retrospective)

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Culture & Age being sample non genralizable.

Self Report, Social Desirability/ Demand Characteristics/Hawthorne Effect

Low Ecological validity.

Methodology:

Longitudnal Method: Drop out, lack of control, right of withdraw.

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BRAVE NEW WORLD | Aldous Huxley (SUMMARY) I Draw My Life

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What is epigenetics? - Carlos Guerrero-Bosagna

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IB Psychology_ Methodology of helping research

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Vicks - Generations of Care #TouchOfCare

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Diffusion of Responsibility | Ethics Defined

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Results suggest that people who are influenced by oxytocin are more prosocial and take fewer risks because they feel accountable for their group/community.

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The queen bee releases signals through pheromones to indicate her location. This message is passed on through worker bees.

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Washington DC [US], March 24 (ANI): In a recent study, researchers have found that the bees collectively located their queen via olfactory communication, in which they release pheromones and direct the pheromones toward other bees by fanning their wings.
According to the study, the pheromones travel the distance between individual bees, and thereby create an olfactory map over large distances that led to the queen.
This research was conducted by combining machine learning with observations of more than 6,600 apiary European honey bees (Apis mellifera L). The findings of the study were published in the journal Proceedings of the National Academy of Sciences of the United States of America (PNAS).
The study shows that bees locate their queen by performing a cascade of "scenting" events, where individual bees direct their pheromone signals by fanning their wings. The bees create a dynamic spatiotemporal network that recruits new broadcasting bees over time, as the pheromones travel a distance that is orders of magnitude the length of an individual.
The scientist developed high-throughput machine learning tools to identify the locations and timings of scenting events, and demonstrate that these events integrate into a global "map" that leads to the queen.
"We use these results to build an agent-based model that illustrates the advantage of the directional signaling in amplifying the pheromones, thus leading to an effective search and aggregation process," the researchers said.

"We find that bees collectively create a scenting-mediated communication network by arranging in a specific spatial distribution where there is a characteristic distance between individuals and directional signaling away from the queen," they added.
The study highlights an example of extended classical stigmergy: Rather than depositing static information in the environment, individual bees locally sense and globally manipulate the physical fields of chemical concentration and airflow.
Animals routinely navigate unpredictable and unknown environments in order to survive and reproduce. One of the prevalent communication strategies in nature is conducted via volatile signal communication, for example, pheromones.
As the range and noise tolerance of information exchange is limited by the spatiotemporal decay of these signals, animals find creative solutions to overcome this problem by leveraging the diffusivity, decay, and interference with information from other individuals.
For olfactory communication, honeybees use their antennae to recognise and respond to specific odors. Recent studies have revealed the bees' distinct electrophysiological responses to different chemicals with quantifiable preferences.
Olfactory communication with pheromones is crucial for many coordinated processes inside a honeybee colony, such as caste recognition, regulating foraging activities, and alarm broadcasting.
Studies have shown that the queen mandibular pheromone regulates gene expression in the brains of workers, inducing changes in downstream behaviors, such as nursing and foraging. Among worker bees, adult foragers produce ethyl oleate, a chemical inhibitory factor, plays a role in delaying foraging in younger workers. (ANI)

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Bees locate their queen by performing cascade of 'scenting' events: Study

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Washington DC [US], March 24 (ANI): In a recent study, researchers have found that the bees collectively located their queen via olfactory communication, in which they release pheromones and direct the pheromones toward other bees by fanning their wings.According to the study, the pheromones travel the distance between individual bees, and thereby create an olfactory map over large distances that led to the queen.

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https://www.google.com/url?sa=i&url=https%3A%2F%2Fme.me%2Fi%2Fninety-percent-of-a-womans-pheromones-come-out-the-top-16334847&psig=AOvVaw3g-MfdHDGRM99_sRblnrcn&ust=1618635228429000&source=images&cd=vfe&ved=0CAIQjRxqFwoTCMjmmKT8gfACFQAAAAAdAAAAABAJ

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News article on pheromones from the-scientist.com

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News article on pheromones from the-scientist.com

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https://www.the-scientist.com/features/a-pheromone-by-any-other-name-38639

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The smelly mystery of the human pheromone | Tristram Wyatt

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https://www.google.co.in/url?sa=i&url=https%3A%2F%2Fwww.theguardian.com%2Fscience%2Fneurophilosophy%2F2015%2Foct%2F16%2Fbrains-immune-cells-hyperactive-in-schizophrenia&psig=AOvVaw0KODhafsw2HpJEfdZOSETV&ust=1616130473557000&source=images&cd=vfe&ved=0CAIQjRxqFwoTCJjq2rKJue8CFQAAAAAdAAAAABAD

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Real-time fMRI using controls and patients with alcohol use disorder (alcoholics)

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Real-time fMRI using controls and patients with alcohol use disorder (alcoholics)

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Trepanation- Drilling holes in the skull

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Trepanation- Drilling holes in the skull

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Welcome to BBC Earth, a place to explore the natural world through awe-inspiring documentaries, podcasts, stories and more.

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How hard could learning a map of a city be? In London, earning the credentials to drive one of the city's iconic cabs is equivalent to earning a university degree. It's so advanced, in fact, that being able to navigate the streets isn't just considered knowledge, but is formally called " The Knowledge." The way London's taxi drivers talk about it, it seems a little like getting a black belt in karate while becoming an Eagle Scout while vying for admission to Mensa.

The reason why is London's curious urban design, a squirrely mix of streets that were designed over centuries rather than by a one-time urban design grid that you might find in New York or Washington DC. There's no pattern to learn in London, or a system of mnemonics to remember the order of roads. You simply have to learn every street in the city. And before you can legally drive a taxi, you have to prove to a group of city officials that you can, without fail, navigate between any two points. During the tests, aspiring drivers have to dictate the most efficient route and recall landmarks they'll pass on the way. The people who are very good at it-and let's be honest, more than 90 percent are men-can master the system in two years. Most people take four or longer.

It's a fun tourist novelty to know that the person driving you has a very detailed spatial map of the city in his head. But for about a decade, a group of researchers at the University College of London have looked into the effect that memorizing such a disorganized system has on your brain. The part of the brain that navigates spatial intelligence is called the hippocampus, a pair of two chestnut sized masses toward the back of your head. The researchers found that London cab drivers have uniquely bigger hippocampi than almost anyone else.

We asked a few London cabbies about this in hopes they could help us understood how their brains worked.

"Oh yeah mate, it's called the hippocampus," one cabbie named Simon told us. "Most people don't use it because of the simplicity of navigating most other places and because of maps and GPS. But with London there's really no other way."

What's it like to map something very complex in your brain, we asked?

"Well, right when the person asks where to go, it's like an explosion in your brain. You see it instantly."

An explosion in the brain is a pretty vivid image to understand just how someone's mind works. Yet it rings true. Each time we got into a cab and stated an obscure street name or small neighborhood, the driver didn't even respond. He just started driving, seeming to know immediately which streets to take, and what the most direct route would be.

The downside to having a big hippocampus is that when cabbies retire and stop using their spatial mapping so regularly, the hippocampus actually starts to shrink back to normal. It's like a muscle that shrinks if you don't use it. What's more, memorizing such a detailed map of a sprawling city actually took up the place of other grey matter. Researchers found that cabbies were worse at remembering things based on visual information and had worse short term memories. There is, after all, only so much real estate in one's head.

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The Bigger Brains of London Taxi Drivers

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How hard could learning a map of a city be? In London, earning the credentials to drive one of the city's iconic cabs is equivalent to earning a university degree. It's so advanced, in fact, that being able to navigate the streets isn't just considered knowledge, but is formally called " The Knowledge."

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Tan Le: A headset that reads your brainwaves TEDTalks

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Daniel Kish: How I use sonar to navigate the world

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Split-brain patient 'Joe' being tested with stimuli presented in different visual fields

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Patients explain the disruption to their everyday lives caused by hemispatial neglect, and Dr Paresh Malhotra of Imperial College London describes his research into this baffling syndrome guardian.co.uk

Alan Burgess doesn't need a rhyme to remember the 5th of November. He'll never forget the day he had his stroke. It left him with a syndrome known as hemispatial neglect and a strange new perspective.

I asked him how he explains this to other people. "I say it's two different worlds," says Burgess. "My old world finished on 5 November 2007 and the new world started the same day."

His stroke damaged the parietal lobe on the right side of his brain, the part that deals with the higher processing of attention. The damage causes him to ignore people, sounds, and objects on his left.

"Hemispatial neglect typically occurs after a stroke," says Dr Paresh Malhotra, senior lecturer in neurology at Imperial College London. "It is not blindness in one eye, and it's not damage to the primary sensory cortex, it's a process of ignoring, for want of a better word, one side of space."

Burgess, 64, originally trained as a tool design draughtsman and, before his stroke, he was working as a driver. His visual neglect makes driving impossible, and he was forced into early retirement. He had never painted before his stroke, but it became an important outlet for him afterwards.

Look at his artwork, though, and it is not only the vivid colours that grab your attention. He hands me a sketch of a pig that has half its head missing, and then produces two robins copied from a Christmas card - the robin on the right is full of rich detail, but the one on the left remains unfinished.

"Vision is most strikingly affected because we are visual creatures, but hearing, touch, representation and sense of self are also affected," says Dr Malhotra.

People with hemispatial neglect are often unaware of their condition. Friends or relatives might suggest they look to their neglected side but that instruction misunderstands the problem they have with navigating the space around them. Burgess, and people like him, are not aware that something is missing, so why would they seek it out?

Patients might bump into things on their neglected side, shave or apply makeup only on one side of their face, or leave half of the food on their plate.

Alan often has to stop and think to make sense of the world around him. Walking down a street, he hugs the right side of the pavement, brushing up against walls and hedges. He won't notice any potential dangers coming from the left, so he cannot go out on his own.

"I can't describe how the world looks to neglect patients," says Dr Malhotra. "Part of the reason it's so difficult is because we don't really appreciate how the world looks to ourselves. We think it's just a nice screen and you can see everything, but that's something that your brain is computing and telling you you're seeing.

"In fact you're attending to specific things at specific times. Your eyes are darting all over the place, but you have a sensation of a static world."

After his stroke, Burgess was assessed by Dr Malhotra, who tested the severity of his condition by asking him to mark the centre of a 25cm line on a piece of paper. During his first meetings, Burgess marked approximately 2cm from the right edge - he simply did not attend to the left side of the line. Nowadays, after regular practice, his mark is more accurate, approximately 10cm from the right.

"It's in the middle of my line, not the middle of your line," Burgess told Dr Malhotra during one consultation.

Dr Malhotra says that people with visual neglect do realise something is wrong when it is pointed out to them over and over and over again. "So in a way I think for them it's slightly abstract that they know there's some problem on the left hand side, and they use strategies to try and overcome the problem, without really being able to appreciate it in its fullness."

His most recent work has looked at how patients might reduce this bias to the right. Previous research suggests that people with normal vision perform better at visual attention tasks when they are rewarded for good performance and Dr Malhotra and his team have found the same thing in neglect patients.

In the experiment, he asked patients to circle images of coins and buttons on a piece of paper covered with lots of other similar symbols. On their first visit, patients performed equally badly with coins or buttons. When they returned for a second test, they were told they would get a pound for each coin they circled.

Their performance subsequently improved on the coins test, but not on the buttons test - where they were told there was no reward - suggesting that motivation could be used in the rehabilitation of stroke patients.

Burgess is going from strength to strength in his rehabilitation. As I shook his hand to leave I remarked on his muscular grip. This somehow ended up with our having an arm wrestle. He is 37 years older than me, and yet he won hands down.

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The man whose brain ignores one half of his world | Thom Hoffman

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Alan Burgess doesn't need a rhyme to remember the 5th of November. He'll never forget the day he had his stroke. It left him with a syndrome known as hemispatial neglect and a strange new perspective. I asked him how he explains this to other people. "I say it's two different worlds," says Burgess.

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To the cerebellum, the controller of stability, balance and movement.
You can't blame me for falling for you, you quite literally made me trip.

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Letter to the Limbic system

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love letter- "Thanks for making me remember those lovely and beautiful memories forever, without them I would feel so empty"

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Letter to cerebellum

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love letter- " Without you, I'd be breathless...without any thoughts"

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love letter -  “you make my heart race”

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https://montreal.ctvnews.ca/eyewitness-says-he-told-police-camara-was-not-the-man-who-attacked-cop-1.5298907

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Double Jeopardy-a fantastical loophole in normative models of decisions

Did you know you cannot be tried for the same crime twice 🤐 😲 😱

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Best Advertisement ever-Winner of Best Ad 2014

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International Journal of Behavioral Nutrition and Physical Activity

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International Journal of Behavioral Nutrition and Physical Activity 3, Article number: 11 (2006) Cite this article

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Abstract

Background

To investigate the efficacy of the Theory of Planned Behavior (TPB) to predict healthy eating behavior in a group of urban Native American youth.

Methods

Native American boys and girls (n = 139), ages 9-18 years old, were given a self-administered survey to assess eating behavior using the TBP constructs (intention, attitude, subjective norm, barriers, self-efficacy, and perceived behavioral control). Youth were also measured for height and weight and body mass index (BMI) was calculated. Bivariate correlations and stepwise regression analyses of TBP model were performed with SPSS software.

Results

No association was found between intention and healthy eating behavior. However, independently healthy eating behavior was correlated with barriers (0.46), attitude (0.44), perceived behavioral control (0.35), and subjective norm (0.34). The most predictive barriers to eating healthy included the availability and taste of foods. Boys' eating behavior was most predicted by subjective norm, while girls' eating behavior was most predicted by barriers.

Conclusion

Lack of association between intention and healthy eating behavior suggests that factors other than intentions may drive healthy eating behaviors in urban Native American youth. Results indicate that programs promoting healthy eating to youth might focus on collaborating with families to make healthy foods more appealing to youth.

Background

Several studies suggest that Native American youth have a higher prevalence of obesity than the general United States population [ 1- 7]. The problem is not restricted to just Native American youth, increases in pediatric obesity have been noted globally [ 8]. Additionally, research suggests that obesity may persist into adulthood and increase the risk of chronic diseases including heart disease, increased blood pressure, and type 2 diabetes, thus making it a major public health concern [ 9, 10]. Because of the known association between dietary intake and obesity [ 11, 12], promoting healthy eating behaviors in youth could help decrease the elevated prevalence of obesity. While little is know about the dietary habits of urban Native American youth, research by Ballew et al. [ 13] found that 12-19 year-old rural youth participating in the Navajo Health and Nutrition Survey consumed fruits, vegetables, and dairy products less than once per day and mean intakes of several vitamins and minerals were below the sex-and-age specific recommended dietary allowances. Because preliminary research indicates poor dietary intake and a high prevalence of obesity among Native American youth, it seems prudent to examine whether youth have an interest in or intend to eat healthfully and to identify the factors that influence those intentions so that appropriate nutrition intervention programs could be developed to assist youth in changing their dietary behavior. Therefore, the purpose of this project was to learn more about why urban Native American youth eat the way that they do. Specifically, we were interested in identifying attitudes that promote, or create barriers, to healthful eating; identifying who or what promotes healthful dietary behavior; and examining to what extent the youth perceive control over their dietary behavior. We utilized the Theory of Planned Behavior (TPB) as the theoretical framework to accomplish this.

The TPB is often used to study health related decision making behavior in youth [ 14- 19]. The TPB is an extension of the Theory of Reasoned Action (TRA) [ 20], but incorporates a third construct known as perceived behavioral control (PBC). The TPB model suggests that intention is directly driven by three major constructs attitude, subjective norm, and PBC and the stronger the intention, the more likely an individual will perform the behavior [ 21]. Attitude is known as the degree to which an individual has a favorable or unfavorable evaluation of the behavior, subjective norm measures the importance others hold about performing or not performing a behavior and one's willingness to comply to those referents, and PBC describes the perceived ease or difficulty an individual has for performing a behavior. In addition, PBC is thought to directly affect behavior by accounting for factors outside an individual's control and especially for behaviors not under volitional control [ 22]. Like many health behaviors, healthy eating is not under complete volitional control, as a result, perceived behavioral control becomes a more important determinant of behavior [ 23].

Self-efficacy is another term that has sometimes been used to define PBC. Self-efficacy is a component of Bandura's [ 24] Social Cognitive Theory and is defined as an individual's perceived ability to perform a behavior. Ajzen [ 23] considers the PBC construct of TPB identical to self-efficacy. However, researchers have not yet come to agreement about this. Self-efficacy has been shown to be an independent contributor to eating behavior [ 25] and several studies support a distinction between self-efficacy and PBC when applying the TPB to health behaviors [ 26- 28]. Armitage and Conner [ 27] applied the TPB to eating a low-fat diet in a group of undergraduate students. They differentiated self-efficacy, the individual's internal motivation to eat a low fat diet, from PBC, the extent to which an individual has control over external factors related to eating a low fat diet [ 27]. In another study, Armitage and Conner [ 27] found that when self-efficacy was added to the TPB model, it was not only an important contributor but it was often the most important predictor of both behavior and intention. Giles et al. [ 29] suggested that the predictive utility of the TPB may be enhanced by replacing PBC with self-efficacy. Alternatively, some research indicates that self-efficacy is not a useful addition to the theory. For example, Terry and O'Leary [ 28] suggest that self-efficacy may not be an important predictor of behavior. Based on previous research findings, this current study examined self-efficacy and PBC as separate constructs that could indirectly, through intention, or directly influence healthy eating behavior in urban Native American youth.

Previous research has also investigated adolescents' knowledge and perceptions of healthy eating and found that while adolescents are informed about healthy eating practices and recommendations, they find it difficult to follow recommendations and often ate unhealthy foods because they perceived too many barriers to eat healthfully [ 30, 31]. According to the Health Belief Model, perceived barriers are an individual's opinion of the tangible costs of an action or behavior [ 32]. In addition to the Health Belief Model, perceived barriers were also used as a construct to determine how well the TBP predicted fruit and vegetable consumption in adolescents [ 15]. Since perceived barriers appear to be a determinant of healthy eating behavior, and may also indirectly affect intention, this study also included barriers as a construct in the TBP model.

This current study used an expanded TBP model which incorporates the original constructs of attitude, subjective norm, and PBC, as well as two additional constructs, barriers and self-efficacy, to investigate healthy eating behaviors in urban Native American youth (Figure 1). Because of the high prevalence of obesity among Native American youth, and the association between diet and weight gain, results from this study are important for the development of intervention strategies that promote healthy eating behaviors in urban Native American youth who are overweight or at risk for becoming overweight.

Study model of healthy eating based on the TPB.

Methods

Participants

Participants were 139 urban Native American youth, predominately from Ojibwe and Lakota tribes, attending an after school program in Minneapolis, Minnesota. The goal of the program was to promote cultural identity, academic success, physical well being, and chemical dependency awareness to Native American youth ages 5 to 18 years old. For this study, surveys were self-administered only to youth 9 to 18 years. This sample included 58 boys (mean age: 12.5 + 2.6 yrs) and 81 girls (mean age: 12.4 + 2.4). Parental consent was given for all activities at the time of program enrollment, and youth were asked to complete the survey voluntarily. Youth who completed the survey and anthropometric measurements received a modest monetary incentive for their participation. Of the approximately 150 youth (ages 9 to 18 yrs) attending the program at the time of this project, 93% volunteered to participate. The project was approved by the Institutional Review Board of Human Subjects at the University of Minnesota.

Measures

The survey was developed according to procedures defined by Ajzen and Fishbein [ 20]. Formative assessment included a review of literature and six focus group discussions with 39 youth, ages 9 to 18 years, to determine common beliefs about eating healthy, advantages and barriers to eating healthy, and important people who may influence behavior. Focus groups were audio taped and transcribed verbatim and analyzed for common themes. The themes were used to develop a survey using the constructs of the TPB to investigate healthy eating behavior. These include the original constructs of attitudes, subjective norm, PBC, as well as two additional constructs, self-efficacy and barriers (Figure 1). Self-efficacy was included to assess whether it was more predictive of intention and/or behavior than PBC. The construct 'barriers' was included in the model because the staff of the program were particularly interested in identifying factors that prevent youth from eating healthfully. The survey included 90 questions pertaining to eating behavior and measured all constructs. It was evaluated by an expert panel of nutritionists accomplished in the areas of survey development and behavioral theory for face validity and breadth of coverage and then pilot tested in a group of urban Native American youth (n = 32) attending an alternative high school for ease of comprehension and readability. The final version of the survey contained slight revisions in wording and question ordering based on recommendations from professionals and findings from the pilot study. Scales for the final survey were assessed using the Cronbach alpha coefficient, an index of inter-item homogeneity (internal consistency.) The reliability levels for the: attitude scale was 0.66, subjective norm scale was 0.66, PBC scale was 0.80, intention scale was 0.84, behavior scale was 0.72, barriers scale was 0.89, and self-efficacy scale was 0.85. These scores indicate a substantial (0.61 - 0.80) to almost perfect (0.81-1.0) range of reliability [ 32].

Survey questions were assessed using a five-point Likert response scale, youth had to choose one of the following responses "strongly agree", "agree", "unsure", "disagree", or "strongly disagree". For positively scaled questions responses were coded from 2 to -2 (strongly agree to strongly disagree) and for negatively scaled questions responses were coded from -2 to 2 (strongly agree to strongly disagree). Attitudes to eating healthy were measured by using the responses to eighteen questions about the importance of eating healthy foods, fruits, vegetables, regular pop, junk food, and fast food, and perceptions of eating healthy, being under or overweight, and diabetes (e.g. "It is important to me to eat healthy foods everyday"). Subjective norm was measured by using the responses to eight questions asking if parents, friends, elders, community programs, or television told youth to eat healthy everyday (e.g."My parents tell me it is important to eat healthy everyday"). PBC measured external factors that may directly or indirectly affect healthy eating behavior. Responses to eight questions concerning youth's perceived control over eating healthy, eating junk food, drinking regular pop, eating fast food, eating in front of the TV, and getting diabetes, as well as having fruits and vegetables available (e.g. " I have control over whether or not I eat healthy") were used to determine perceived behavior control. Intention to eat healthy was measured by using the responses to eight questions regarding youth's plans for the next week to eat healthy, eat vegetables, eat fruit, not eat junk food, not eat fast food, not drink regular pop, eat healthy foods in front of the TV, and eat healthy foods to keep a healthy weight everyday (e.g. " For the next week I plan to eat healthy everyday"). Eating behavior was measured by using the responses to questions assessing dietary intake of vegetables, fruits, soft drinks, and fast food consumption, along with eleven additional behavior questions using the Likert-scale. Eating behaviors questions included general questions such as, "I mostly eat healthy foods," "I eat healthy to keep me from getting diabetes," and "I eat junk food when I watch TV," but also used specific foods such as "fruits" and "vegetables" because youth defined foods, especially fruits and vegetables, as being healthy. Both healthy and junk foods were defined on the survey using terminology that the youth used during the focus group discussions. The assessment and behavioral question scales were were averaged, recoded, and the sum of the two were calculated to measure youth's behavior.

The two additional constructs, barriers and self-efficacy, were included in the expanded model. Barriers to eating healthy were measured by using the responses to fourteen questions concerning youth's perceptions about the taste of fruits, vegetables, regular pop, and junk food; the ease of eating healthy away from home, with friends, with family, in front of the TV and to keep a healthy weight; and availability of healthy foods (e.g. "It is hard for me to eat healthy foods at fast food restaurants"). Self-efficacy measured internal factors that may directly or indirectly affect healthy eating behavior. Responses to fifteen questions determining youth's ability to eat healthy foods and choose specific healthy foods (fruit, vegetables, chocolate milk, juice, white milk, low-fat milk, salads) over specific unhealthy foods (junk food, chips/cheetos, regular pop, chocolate milk, whole milk, hamburgers) (e.g. "I can eat healthy foods everyday") were used to assess self-efficacy to eat healthy.

Survey administration

Youth agreeing to participate in the study were seated in a quiet area and given a survey and writing instrument. Researchers explained to each youth that the purpose of the survey was to find out about how they feel about healthy eating and stressed that there were no right or wrong answers. Definitions for healthy eating, junk food, and fast food were provided on each survey and read aloud to each youth. These terms were identified and defined by youth attending the focus group discussions. Healthy eating was defined as eating different types of food from all food groups like bread, grains, cereals, fruit, vegetables, milk, and meat while limiting sugary and fatty foods; junk food was defined as foods such as pop, chips, candy, donuts, cakes, cookies, and sweets; and fast food was defined as burgers, fries, shakes and foods from McDonald's, Burger King, Taco Bell, KFC etc. Youth were asked to carefully read each question and mark only one response. For youth who had problems answering questions or understanding questions, several researchers were available to aid with completion. The time taken to complete each survey averaged 20 minutes with a range between 10 and 30 minutes. All surveys were rechecked to identify omitted or multiple response questions and youth were immediately instructed to finish or clarify unfinished or unclear responses. Four surveys were removed from analysis because of missing data.

Anthropometric measurements

After completing the survey each respondent was measured in light clothing with their shoes removed. Height was measured to the nearest one-tenth centimeter with a GPM anthropometer (Switzerland). Weight was measured to the nearest one-tenth kilogram with a high-quality electronic scale (Seca, France). Body mass index (BMI) was calculated by dividing weight in kilograms by height in meters squared and the BMI for each youth was plotted on age-sex-specific growth charts developed by the Centers for Disease Control and Prevention [ 33]. Youth were classified according to their BMI percentile as either underweight (<5 th percentile), normal weight (≥ 5 th to <85 th percentile), at risk for overweight (≥ 85 th to <95 th percentile), or overweight (≥ 95 th percentile) [ 34].

Data analysis

Data were analyzed using the Statistical Package for Social Sciences for Windows (SSPS, v. 11, Chicago, IL, 1999). Descriptive statistics were used to determine means and standard deviations of all constructs as well as age, gender, and BMI. Mean values for the constructs for boys and girls were compared using independent t-tests to identify any gender or age differences. No differences were found based on age.

Because gender differences were observed all analyses were conducted by gender. Pearson correlations were conducted to examine associations between the psychosocial variables (constructs) for both the original TPB model, then for the expanded TPB model. Because the PBC construct was only weakly associated to girl's behavior and not associated to girl's intention or boy's behavior or intention, the expanded version of TPB model was used for further analyses. In order to examine constructs (attitude, subjective norm, PBC, self-efficacy, and barriers) most predictive of intention and behavior, stepwise regression analyses were performed respectively. Additionally, further stepwise regression analyses were conducted with the construct that was most predictive of behavioral change for boys (subjective norms) and girls (barriers). Both of these issues will need to be addressed in future interventions if behavioral change is to be achieved. The level of significance was set at p < 0.05 for all statistical tests.

Results

The mean age and grade of boys and girls was not significantly different, 12.4 years old and 7 th grade respectively. According to CDC BMI percentiles 38% of girls and 38% of boys were classified as normal weight, 20% of girls and 26% of boys as at risk for overweight, and 42% girls and 36% of boys as overweight.

Boys

No association was found between intention and healthy eating behavior. Furthermore, the grade, age, and BMI were not associated with intention or behavior. However, the constructs of attitude, subjective norm, PBC, and barriers were all associated with behavior, and the constructs of attitude, subjective norm, and self-efficacy were all associated with intention (see Table 1). The mean value of barriers for boys (-0.006) was significantly higher than the mean value of barriers for girls (-0.032) (Table 1).

Table 1 Correlations between TBP model constructs. Means and standard deviations (SD) for each construct for the total sample and by gender.

Stepwise regression of behavior as the dependent variable and constructs (attitudes, subjective norms, PBC, barriers, and self-efficacy) as independent variables, showed that subjective norm (R ² = 0.21) and perceived behavioral control (R ² = 0.30) predicted 30% of the model (Table 2). Whereas when intention was regressed with the constructs as independent variables, self-efficacy accounted for 46% of the variance and attitude added another 4%. Furthermore, because subjective norm was most predictive of healthy eating behaviors we ran it as a dependent variable with all survey questions measuring subjective norm as independent variables to see which of the social norms were most predictive of that construct. Three questions explained 86% of the variance in behavior (Table 2). The three questions included "My family tells me I should eat healthy everyday to help keep me at a healthy weight" (R ² = 0.57), "I get hungry for foods I see on TV" (R ² = 0.74), and "The after school program I attend says it is important to eat healthy everyday" (R ² = 0.86).

Table 2 Stepwise regression analyses of healthy eating behavior.

Girls

No association was found between intention and behavior, therefore factors directly affecting behavior and intention were investigated. Healthy eating behavior was positively correlated with attitude, subjective norm, perceived behavior control, and barriers, while self-efficacy had a negative correlation (Table 1). While the constructs of attitude, subjective norm, and self-efficacy were all positively associated with intention, and barriers was negatively associated with it (see Table 1). The mean value of healthy eating intention (0.084) and self-efficacy (0.046) for girls was significantly higher than the mean value of intention (0.032) and self-efficacy (0.030) for boys (Table 1).

Stepwise regression of behavior as the dependent variable and constructs (attitudes, subjective norms, PBC, barriers, and self-efficacy) as independent variables, showed that barriers (R ² = 0.27), attitude (R ² = 0.35), self-efficacy (R ² = 0.39), and subjective norm (R ² = 0.45) predicted 45% of the model (Table 2). Whereas when intention was regressed with the constructs as independent variables, subjective norm (R ² = 0.18), attitude (R ² = 0.30), and barriers (R ² = 0.35) predicted 35% of the variance (Table 2). Furthermore, because barriers was most predictive of healthy eating behaviors, we ran it as a dependent variable with all survey questions measuring subjective norm as independent variables to see which of the barriers were most predictive of that construct. Four questions were identified as explaining 82% of the variance in barriers to eat healthy (Table 2). The four questions included "I don't eat healthy because healthy foods are not around" (R ² = 0.57), "My parent's don't buy healthy food" (R ² = 0.74), "It is hard for me to eat healthy foods because junk foods taste better" (R ² = 0.82), and "Healthy foods don't fill you up" (R ² = 0.87).

Discussion

In this investigation of the healthy eating behaviors in urban Native American youth, TPB was found to be predictive of factors affecting healthy eating intention and behavior independently, but found no direct association between intention to eat healthfully and eating behavior. Furthermore, gender, but not age, grade, or BMI, was found to be a significant factor in youths' responses. Among boys, intention and behavior were predicted by different constructs, with self-efficacy accounting for 46% of the variance for intention. Among the girls, three of the constructs (subjective norms, attitude, and barriers) entered the predictive equation in different ranking order for both intention and behavior and account for much of the variance.

The lack of association between intention and behavior might be explained by the concept of intention instability. Conner et al. found that intentions were stronger predictors of behavior when intentions were stable in adults eating a low-fat diet [ 35]. In the present study, youths' intention to eat healthy may be driven more by external cues and therefore constantly changing. As a result, behavior is affected to a greater extent by other factors and not intention. The TPB is based on the concept that the stronger the intention to perform a given behavior, the greater the likelihood that the person will perform that behavior [ 36]. In the current study, intention could not be considered strong because mean intention for boys was found to be 0.062 and girls was found to be 0.32 on a scale from -2 (low intention) to 2 (high intention). Forming strong intentions to eat healthy may not be a priority in youth and therefore do not affect eating behavior.

In comparing boys and girls, healthy eating behavior among boy was predicted by subjective norm and PBC, while among girls barriers, attitude, self-efficacy, and subjective norms predicted behavior. In addition, behavior in girls was positively associated with age and negatively associated with self-efficacy. It appears that as girls become older they are more likely to engage in healthy eating behavior, however a low self-efficacy also seems to be associated with healthy eating behavior. Results are puzzling and may be explained by girls' body dissatisfaction and distortions of a healthy body size. A study examining body perceptions among urban Native American youth found 61% of girls expressed a desire to be thinner compared to 41% of boys and 26% of girls selected the thinnest silhouette as the healthiest from range of eight varying sized silhouettes [ 7]. Compared to boys, girls had significantly higher mean values for intention and self-efficacy, and lower mean values for barriers to eat healthy. In another study examining food choice in youth, girls also reported greater intentions to eat fruit than boys [ 19]. Healthy eating promotion programs may benefit by offering gender separate activities that aim to enhance intention and self-efficacy in boys and reduce perceived barriers in girls.

Subjective norm and PBC explained 30% of the variance to eat healthy in boys while barriers, attitude, subjective norm, and self-efficacy explained 45% of the variance to eat healthy in girls. It appears that girls' behaviors are influenced by more factors and to a greater extent than boys. Subjective norm was the best predictor of healthy eating behavior in boys with family, television, after school programs, and friends being most instrumental in influencing eating behaviors. According to a review of the TPB's application to health related behaviors, the subjective norm construct often did not reach significance and had less influence on behavior than attitude and PBC constructs [ 37]. This was not found to be true in the sample of urban Native American boys in the present study. The primary social unit of Native Americans is the extended family and their culture is based on respect for elders and strong community ties [ 38]. A strong sense of family and community support may explain why youths' eating behaviors were directly affected by the subjective norm construct. For girls, similar to data from the total sample, barriers were most predictive of eating behavior with unavailability of healthy foods and taste cited as the greatest barriers. Including the entire Native American community in promotion strategies appears to be an appropriate method to enhance healthy eating behaviors in urban Native American youth, especially in boys and could also be effective in reducing perceived barriers regarding food availability in girls.

This study assessed self-reported eating behavior as part of the survey and as a result could have introduced inaccuracies. However, the authors feel that the this group of Native American youth, who are accustom to completing surveys during the after school program, were attentive when answering survey questions, thus minimizing potential problems. Additionally, youth were shown food models to increase the accuracy of their intake estimates. Measuring actual food intake is very labor intensive and dietary self-report is the method primarily used in studies assessing the TPB and eating practices in youth [ 15, 16, 18, 19, 39]. In addition, self-reported low-fat eating behaviors were better predicted by TPB than behavior measured by dietary observation in adults [ 27] and prediction was also found superior than observed behavior in a meta-analysis of the TPB [ 26]. Future studies may benefit from using multiple measurements of eating behavior to avoid potential inaccuracies from self-report.

This study only examined a sample of urban Native American youth and findings may not be true for all urban Native American youth. Tribe identity and regional location could alter the factors influencing healthy eating behavior in Native American youth. However, authors believe that findings are appropriate for basing future research and practice in populations of urban Native American youth.

Conclusion

Findings indicate that TPB is useful for predicting factors directly related to healthy eating behavior but not for predicting the indirect effect of intention in a sample of urban Native American youth. This suggests that other factors besides intention are driving healthy eating behavior and can be used to develop intervention strategies to promote healthy eating practices in youth who overweight or at risk for overweight. Since barriers, attitude, subjective norm, and self-efficacy appear to be factors affecting healthy eating behaviors they should be incorporated in program design. Nutrition professionals should work with Native American community leaders and elders to provide sound nutritional knowledge to the entire community. This data also suggests that working through the family is important. Encouraging parents and caretakers to purchase and make healthy foods regularly available to their children could reduce youths' perceived barriers to healthy eating. Because the extended family and community are a valuable component of Native American culture, youth appear more willing to accept and follow dietary advice from members of their community. Gender differences may require the need for separate programs or at least special considerations for boys and girls. Boys who have lower self-efficacy but seem receptive to subjective norms, would benefit more from activities involving family and peers to increase healthy eating behaviors. Girls who are most affected by barriers to healthy eating, would benefit more from programs designed to increase the availability of healthy foods and promote the awareness that healthy foods are also tasty. Because of the alarming prevalence of obesity in urban Native American youth, future studies should continue to investigate the factors influencing obesity, such as eating and activity behavior, to identify the most effective way to solve this problem.

Acknowledgements

We thank the urban Native American youth for volunteering to participate in dietary measurements. We thank Julie Green, Program Director of the after school program and her staff for their help and collaboration. We also thank Laura Gillispie for her assistance with this project. This project was funded by the Agriculture Experiment Station of the University of Minnesota and by the United Way.

Author information

Affiliations

1. Albuquerque School System, 1304 Sierra Larga NE, Albuquerque, NM, 87112, USA

Stefanie A Fila

2. University of Minnesota, Department of Food Science and Nutrition, 225 FScN, 1334 Eckles Ave, St. Paul, MN, 55108-6099, USA

Chery Smith

Corresponding author

Correspondence to Chery Smith.

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The author(s) declare that they have no competing interests.

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Fila, S.A., Smith, C. Applying the Theory of Planned Behavior to healthy eating behaviors in urban Native American youth. Int J Behav Nutr Phys Act 3, 11 (2006). https://doi.org/10.1186/1479-5868-3-11
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Keywords

Eating Behavior

Subjective Norm

Healthy Food

Perceive Behavioral Control

Junk Food

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Applying the Theory of Planned Behavior to healthy eating behaviors in urban Native American youth

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Background To investigate the efficacy of the Theory of Planned Behavior (TPB) to predict healthy eating behavior in a group of urban Native American youth. Methods Native American boys and girls (n = 139), ages 9-18 years old, were given a self-administered survey to assess eating behavior using the TBP constructs (intention, attitude, subjective norm, barriers, self-efficacy, and perceived behavioral control).

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There was the Cinnamon challenge, the Ice Bucket challenge and, now, the Kylie Jenner Lip Challenge.

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For starters, bruising, blistering and even infection that would require antibiotics to clear up could occur from suctioning the lips so aggressively.

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READ MORE: British woman dies while undergoing cosmetic surgery in Thailand
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In the meantime, teens have taken to social media to post their results:

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https://twitter.com/Mfeems24/status/590197307800334336
Kylie Jenner responded to the lip challenge:

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There was the Cinnamon challenge, the Ice Bucket challenge and, now, the Kylie Jenner Lip Challenge. Teenagers insert their lips into a shot glass, small jar or bottle, then suck out the air, creating a vacuum. The hope is they'll end up with pouty lips like the reality TV star.

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Social cognitive theory is a learning theory developed by the renowned Stanford psychology professor Albert Bandura. The theory provides a framework for understanding how people actively shape and are shaped by their environment. In particular, the theory details the processes of observational learning and modeling, and the influence of self-efficacy on the production of behavior.

Key Takeaways: Social Cognitive Theory

Origins: The Bobo Doll Experiments

In the 1960s, Bandura, along with his colleagues, initiated a series of well-known studies on observational learning called the Bobo Doll experiments. In the first of these experiments, pre-school children were exposed to an aggressive or nonaggressive adult model to see if they would imitate the model's behavior. The gender of the model was also varied, with some children observing same-sex models and some observing opposite-sex models.

In the aggressive condition, the model was verbally and physically aggressive towards an inflated Bobo doll in the presence of the child. After exposure to the model, the child was taken to another room to play with a selection of highly attractive toys. To frustrate participants, the child's play was stopped after about two minutes. At that point, the child was taken to a third room filled with different toys, including a Bobo doll, where they were allowed to play for the next 20 minutes.

The researchers found that the children in the aggressive condition were much more likely to display verbal and physical aggression, including aggression towards the Bobo doll and other forms of aggression. In addition, boys were more likely to be aggressive than girls, especially if they had been exposed to an aggressive male model.

A subsequent experiment utilized a similar protocol, but in this case, the aggressive models weren't just seen in real-life. There was also a second group that observed a film of the aggressive model as well as a third group that observed a film of an aggressive cartoon character. Again, the gender of the model was varied, and the children were subjected to mild frustration before they were brought to the experimental room to play. As in the previous experiment, the children in the three aggressive conditions exhibited more aggressive behavior than those in the control group and boys in the aggressive condition exhibiting more aggression than girls.

These studies served as the basis for ideas about observational learning and modeling both in real-life and through the media. In particular, it spurred a debate over the ways media models can negatively influence children that continues today.

In 1977, Bandura introduced Social Learning Theory, which further refined his ideas on observational learning and modeling. Then in 1986, Bandura renamed his theory Social Cognitive Theory in order to put greater emphasis on the cognitive components of observational learning and the way behavior, cognition, and the environment interact to shape people.

Observational Learning

A major component of social cognitive theory is observational learning. Bandura's ideas about learning stood in contrast to those of behaviorists like B.F. Skinner. According to Skinner, learning could only be achieved by taking individual action. However, Bandura claimed that observational learning, through which people observe and imitate models they encounter in their environment, enables people to acquire information much more quickly.

Observational learning occurs through a sequence of four processes:

1. Attentional processes account for the information that is selected for observation in the environment. People might select to observe real-life models or models they encounter via media.

2. Retention processes involve remembering the observed information so it can be successfully recalled and reconstructed later.

3. Production processes reconstruct the memories of the observations so what was learned can be applied in appropriate situations. In many cases, this doesn't mean the observer will replicate the observed action exactly, but that they will modify the behavior to produce a variation that fits the context.

4. Motivational processes determine whether or not an observed behavior is performed based on whether that behavior was observed to result in desired or adverse outcomes for the model. If an observed behavior was rewarded, the observer will be more motivated to reproduce it later. However, if a behavior was punished in some way, the observer would be less motivated to reproduce it. Thus, social cognitive theory cautions that people don't perform every behavior they learn through modeling.

Self-Efficacy

In addition to the information models can convey during observational learning, models can also increase or decrease the observer's belief in their self-efficacy to enact observed behaviors and bring about desired outcomes from those behaviors. When people see others like them succeed, they also believe they can be capable of succeeding. Thus, models are a source of motivation and inspiration.

Perceptions of self-efficacy influence people's choices and beliefs in themselves, including the goals they choose to pursue and the effort they put into them, how long they're willing to persevere in the face of obstacles and setbacks, and the outcomes they expect. Thus, self-efficacy influences one's motivations to perform various actions and one's belief in their ability to do so.

Such beliefs can impact personal growth and change. For example, research has shown that enhancing self-efficacy beliefs is more likely to result in the improvement of health habits than the use of fear-based communication. Belief in one's self-efficacy can be the difference between whether or not an individual even considers making positive changes in their life.

Modeling Media

The prosocial potential of media models has been demonstrated through serial dramas that were produced for developing communities on issues such as literacy, family planning, and the status of women. These dramas have been successful in bringing about positive social change, while demonstrating the relevance and applicability of social cognitive theory to media.

For example, a television show in India was produced to raise women's status and promote smaller families by embedding these ideas in the show. The show championed gender equality by including characters that positively modeled women's equality. In addition, there were other characters that modeled subservient women's roles and some that transitioned between subservience and equality. The show was popular, and despite its melodramatic narrative, viewers understood the messages it modeled. These viewers learned that women should have equal rights, should have the freedom to choose how they live their lives, and be able to limit the size of their families. In this example and others, the tenets of social cognitive theory have been utilized to make a positive impact through fictional media models.

Bandura, Albert. "Social cognitive theory for personal and social change by enabling media." Entertainment-education and social change: History, research, and practice, edited by Arvind Singhal, Michael J. Cody, Everett M. Rogers, and Miguel Sabido, Lawrence Erlbaum Associates, 2004, pp. 75-96.

Bandura, Albert. "Social Cognitive Theory of Mass Communication. Media Psychology, vol. 3, no. 3, 2001, pp. 265-299, https://doi.org/10.1207/S1532785XMEP0303_03

Bandura, Albert. Social Foundations of Thought and Action: A Social Cognitive Theory. Prentice Hall, 1986.

Bandura, Albert, Dorothea Ross, and Sheila A. Ross. "Transmission of Aggression Through Imitation of Aggressive Models." Journal of Abnormal and Social Psychology, vol. 63, no. 3, 1961, pp. 575-582, http://dx.doi.org/10.1037/h0045925

Bandura, Albert, Dorothea Ross, and Sheila A. Ross. "Imitation of Film-Mediated Aggressive Models." Journal of Abnormal and Social Psychology, vol. 66, no. 1, 1961, pp. 3-11, http://dx.doi.org/10.1037/h0048687

Crain, William. Theories of Development: Concepts and Applications. 5th ed., Pearson Prentice Hall, 2005.

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Social Cognitive Theory: How We Learn From the Behavior of Others

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Social cognitive theory, developed by Albert Bandura, is a learning theory that focuses on observational learning, modeling, and self-efficacy.

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To do-Charlton 2002 & Sabido Methods-Research 

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To do-Charlton 2002 & Sabido Methods-Research 

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Beat it!

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The Bobo Beatdown: Crash Course Psychology #12

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During the 1960s, Albert Bandura conducted a series of experiments on observational learning, collectively known as the Bobo doll experiments. Two of the experiments are described below:

Aim

Bandura (1961) conducted a controlled experiment study to investigate if social behaviors (i.e., aggression) can be acquired by observation and imitation.

Sample

Bandura, Ross, and Ross (1961) tested 36 boys and 36 girls from the Stanford University Nursery School aged between 3 to 6 years old.

The researchers pre-tested the children for how aggressive they were by observing the children in the nursery and judged their aggressive behavior on four 5-point rating scales.

It was then possible to match the children in each group so that they had similar levels of aggression in their everyday behavior. The experiment is, therefore, an example of a matched pairs design.

To test the inter-rater reliability of the observers, 51 of the children were rated by two observers independently, and their ratings were compared. These ratings showed a very high-reliability correlation (r = 0.89), which suggested that the observers had a good agreement about the behavior of the children.

Method

A lab experiment was used, in which the independent variable (the type of model) was manipulated in three conditions:

Aggressive model is shown to 24 children

Non-aggressive model is shown to 24 children

No model is shown (control condition) - 24 children

Stage 1: Modeling

In the experimental conditions, children were individually shown into a room containing toys and played with some potato prints and pictures in a corner for 10 minutes while either:

24 children (12 boys and 12 girls) watched a male or female model behaving aggressively towards a toy called a "Bobo doll". The adults attacked the Bobo doll in a distinctive manner - they used a hammer in some cases, and in others threw the doll in the air and shouted "Pow, Boom."

Another 24 children (12 boys and 12 girls) were exposed to a non-aggressive model who played in a quiet and subdued manner for 10 minutes (playing with a tinker toy set and ignoring the bobo-doll).

The final 24 children (12 boys and 12 girls) were used as a control group and not exposed to any model at all.

Stage 2: Aggression Arousal

All the children (including the control group) were subjected to "mild aggression arousal." Each child was (separately) taken to a room with relatively attractive toys.

As soon as the child started to play with the toys, the experimenter told the child that these were the experimenter's very best toys and she had decided to reserve them for the other children.

Stage 3: Test for Delayed Imitation

The next room contained some aggressive toys and some non-aggressive toys. The non-aggressive toys included a tea set, crayons, three bears and plastic farm animals. The aggressive toys included a mallet and peg board, dart guns, and a 3 foot Bobo doll.

The child was in the room for 20 minutes, and their behavior was observed and rated though a one-way mirror. Observations were made at 5-second intervals, therefore, giving 240 response units for each child.

Other behaviors that didn't imitate that of the model were also recorded e.g., punching the Bobo doll on the nose.

Results

Children who observed the aggressive model made far more imitative aggressive responses than those who were in the non-aggressive or control groups.

There was more partial and non-imitative aggression among those children who had observed aggressive behavior, although the difference for non-imitative aggression was small.

The girls in the aggressive model condition also showed more physically aggressive responses if the model was male, but more verbally aggressive responses if the model was female. However, the exception to this general pattern was the observation of how often they punched Bobo, and in this case the effects of gender were reversed.

Boys were more likely to imitate same-sex models than girls. The evidence for girls imitating same-sex models is not strong.

Boys imitated more physically aggressive acts than girls. There was little difference in verbal aggression between boys and girls.

Conclusion

Bobo doll experiment demonstrated that children are able to learn social behavior such as aggression through the process of observation learning, through watching the behavior of another person. The findings support Bandura's (1977) Social Learning Theory.

This study has important implications for the effects of media violence on children.

Evaluation

There are three main advantages of the experimental method.

1. Experiments are the only means by which cause and effect can be established. Thus, it could be demonstrated that the model did have an effect on the child's subsequent behavior because all variables other than the independent variable are controlled.

2. It allows for precise control of variables. Many variables were controlled, such as the gender of the model, the time the children observed the model, the behavior of the model, and so on.

3. Experiments can be replicated. Standardized procedures and instructions were used, allowing for replicability. In fact, the study has been replicated with slight changes, such as using video, and similar results were found (Bandura, 1963).

Limitations of the procedure include:

Many psychologists are very critical of laboratory studies of imitation - in particular, because they tend to have low ecological validity. The situation involves the child and an adult model, which is a very limited social situation and there is no interaction between the child and the model at any point; certainly the child has no chance to influence the model in any way.

Also, the model and the child are strangers. This, of course, is quite unlike "normal" modeling, which often takes place within the family.

Cumberbatch (1990) found that children who had not played with a Bobo Doll before were five times as likely to imitate the aggressive behavior than those who were familiar with it; he claims that the novelty value of the doll makes it more likely that children will imitate the behavior.

A further criticism of the study is that the demonstrations are measured almost immediately. With such snapshot studies, we cannot discover if such a single exposure can have long-term effects.

It is possible to argue that the bobo doll experiment was unethical. For example, there is the problem of whether or not the children suffered any long-term consequences as a result of the study. Although it is unlikely, we can never be certain.

Vicarious Reinforcement Bobo Doll Study

An observer's behavior can also be affected by the positive or negative consequences of a model's behavior.

So we not only watch what people do, but we watch what happens when they do things. This is known as vicarious reinforcement. We are more likely to imitate behavior that is rewarded and refrain from behavior that is punished.

Bandura (1965) used a similar experimental set up to the one outlined above to test vicarious reinforcement. The experiment had different consequences for the model's aggression to the three groups of children.

One group saw the model's aggression being rewarded (being given sweets and a drink for a "championship performance," another group saw the model being punished for the aggression (scolded), and the third group saw no specific consequences (control condition).

When allowed to enter the playroom, children in the reward and control conditions imitated more aggressive actions of the model than did the children in the punishment condition.

The children in the model punished group had learned the aggression by observational learning, but did not imitate it because they expected negative consequences.

Reinforcement gained by watching another person is known as vicarious reinforcement.

Bandura, A. (1965). Influence of models" reinforcement contingencies on the acquisition of imitative responses. Journal of personality and social psychology, 1(6), 589.

Bandura, A., Ross, D. & Ross, S.A. (1961). Transmission of aggression through imitation of aggressive models. Journal of Abnormal and Social Psychology, 63, 575-82.

Bandura, A., Ross, D., & Ross, S. A. (1963). Imitation of film-mediated aggressive models. The Journal of Abnormal and Social Psychology, 66(1), 3.

Bandura, A. (1977). Social Learning Theory. Englewood Cliffs, NJ: Prentice Hall.

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