The document summarizes research from surveys on youth exposure to online pornography and violence. It finds that around one-third of youth report unwanted exposure to pornography, with older teens and boys more likely to report it. Around 10-13% report intentional exposure, with older boys more likely. Exposure to violent websites is low at 2-4%. Youth reporting any exposure tend to face other challenges like substance use, bullying, and poor family relationships. The document concludes that simply knowing about certain websites is not enough for youth to visit them.
Why They Run presented by the National Runaway Switchboardguest54554c
Why They Run: An in-depth look at America’s runaway youth, presented by the National Runaway Switchboard, sheds new light on the runaway problem in America and begins to fill in the gaps of what is already known and what can be done based on new research.
Why They Run is comprised of research from three main sources: 1) existing research and reports, 2) NRS Crisis Caller Trends report (April 2010), and 3) new research conducted with youth between ages 14-17 on the street and in shelters (in Chicago and Los Angeles), which was implemented by the National Opinion Research Center (NORC), a social science research organization affiliated with the University of Chicago. Below are key findings from the new research from the NORC study.
Lee Rainie, director of internet and technology research at Pew Research Center, discussed recent findings about the prevalence and impact of online harassment at the Cyber Health and Safety Virtual Summit: 41% of American adults have been harassed online and 66% have witnessed harassment. The findings come from the Center’s recent report on these issues.
Amanda Lenhart delivered this presentation to the Year of the Child summit at the National Association of Attorneys General Year of the Child Conference, Philadelphia, PA, this talk surveys the current research on cyberbullying and online harassment, pulling in Pew Internet data as well as the work of the Crimes Against Children Research Center at the University of New Hampshire, Internet Solutions for Kids and other academics and scholars researching this topic. 5/13/09
Why They Run presented by the National Runaway Switchboardguest54554c
Why They Run: An in-depth look at America’s runaway youth, presented by the National Runaway Switchboard, sheds new light on the runaway problem in America and begins to fill in the gaps of what is already known and what can be done based on new research.
Why They Run is comprised of research from three main sources: 1) existing research and reports, 2) NRS Crisis Caller Trends report (April 2010), and 3) new research conducted with youth between ages 14-17 on the street and in shelters (in Chicago and Los Angeles), which was implemented by the National Opinion Research Center (NORC), a social science research organization affiliated with the University of Chicago. Below are key findings from the new research from the NORC study.
Lee Rainie, director of internet and technology research at Pew Research Center, discussed recent findings about the prevalence and impact of online harassment at the Cyber Health and Safety Virtual Summit: 41% of American adults have been harassed online and 66% have witnessed harassment. The findings come from the Center’s recent report on these issues.
Amanda Lenhart delivered this presentation to the Year of the Child summit at the National Association of Attorneys General Year of the Child Conference, Philadelphia, PA, this talk surveys the current research on cyberbullying and online harassment, pulling in Pew Internet data as well as the work of the Crimes Against Children Research Center at the University of New Hampshire, Internet Solutions for Kids and other academics and scholars researching this topic. 5/13/09
An updated look at the research and definitions around bullying and cyberbullying. Presented to the Youth Online Safety Working Group assembled by NCMEC, this talk unpacks both what current research can tell us about cyberbullying as well as where the gaps our understanding of this issue lie.
Title: Sense of Smell
Presenter: Dr. Faiza, Assistant Professor of Physiology
Qualifications:
MBBS (Best Graduate, AIMC Lahore)
FCPS Physiology
ICMT, CHPE, DHPE (STMU)
MPH (GC University, Faisalabad)
MBA (Virtual University of Pakistan)
Learning Objectives:
Describe the primary categories of smells and the concept of odor blindness.
Explain the structure and location of the olfactory membrane and mucosa, including the types and roles of cells involved in olfaction.
Describe the pathway and mechanisms of olfactory signal transmission from the olfactory receptors to the brain.
Illustrate the biochemical cascade triggered by odorant binding to olfactory receptors, including the role of G-proteins and second messengers in generating an action potential.
Identify different types of olfactory disorders such as anosmia, hyposmia, hyperosmia, and dysosmia, including their potential causes.
Key Topics:
Olfactory Genes:
3% of the human genome accounts for olfactory genes.
400 genes for odorant receptors.
Olfactory Membrane:
Located in the superior part of the nasal cavity.
Medially: Folds downward along the superior septum.
Laterally: Folds over the superior turbinate and upper surface of the middle turbinate.
Total surface area: 5-10 square centimeters.
Olfactory Mucosa:
Olfactory Cells: Bipolar nerve cells derived from the CNS (100 million), with 4-25 olfactory cilia per cell.
Sustentacular Cells: Produce mucus and maintain ionic and molecular environment.
Basal Cells: Replace worn-out olfactory cells with an average lifespan of 1-2 months.
Bowman’s Gland: Secretes mucus.
Stimulation of Olfactory Cells:
Odorant dissolves in mucus and attaches to receptors on olfactory cilia.
Involves a cascade effect through G-proteins and second messengers, leading to depolarization and action potential generation in the olfactory nerve.
Quality of a Good Odorant:
Small (3-20 Carbon atoms), volatile, water-soluble, and lipid-soluble.
Facilitated by odorant-binding proteins in mucus.
Membrane Potential and Action Potential:
Resting membrane potential: -55mV.
Action potential frequency in the olfactory nerve increases with odorant strength.
Adaptation Towards the Sense of Smell:
Rapid adaptation within the first second, with further slow adaptation.
Psychological adaptation greater than receptor adaptation, involving feedback inhibition from the central nervous system.
Primary Sensations of Smell:
Camphoraceous, Musky, Floral, Pepperminty, Ethereal, Pungent, Putrid.
Odor Detection Threshold:
Examples: Hydrogen sulfide (0.0005 ppm), Methyl-mercaptan (0.002 ppm).
Some toxic substances are odorless at lethal concentrations.
Characteristics of Smell:
Odor blindness for single substances due to lack of appropriate receptor protein.
Behavioral and emotional influences of smell.
Transmission of Olfactory Signals:
From olfactory cells to glomeruli in the olfactory bulb, involving lateral inhibition.
Primitive, less old, and new olfactory systems with different path
The prostate is an exocrine gland of the male mammalian reproductive system
It is a walnut-sized gland that forms part of the male reproductive system and is located in front of the rectum and just below the urinary bladder
Function is to store and secrete a clear, slightly alkaline fluid that constitutes 10-30% of the volume of the seminal fluid that along with the spermatozoa, constitutes semen
A healthy human prostate measures (4cm-vertical, by 3cm-horizontal, 2cm ant-post ).
It surrounds the urethra just below the urinary bladder. It has anterior, median, posterior and two lateral lobes
It’s work is regulated by androgens which are responsible for male sex characteristics
Generalised disease of the prostate due to hormonal derangement which leads to non malignant enlargement of the gland (increase in the number of epithelial cells and stromal tissue)to cause compression of the urethra leading to symptoms (LUTS
Title: Sense of Taste
Presenter: Dr. Faiza, Assistant Professor of Physiology
Qualifications:
MBBS (Best Graduate, AIMC Lahore)
FCPS Physiology
ICMT, CHPE, DHPE (STMU)
MPH (GC University, Faisalabad)
MBA (Virtual University of Pakistan)
Learning Objectives:
Describe the structure and function of taste buds.
Describe the relationship between the taste threshold and taste index of common substances.
Explain the chemical basis and signal transduction of taste perception for each type of primary taste sensation.
Recognize different abnormalities of taste perception and their causes.
Key Topics:
Significance of Taste Sensation:
Differentiation between pleasant and harmful food
Influence on behavior
Selection of food based on metabolic needs
Receptors of Taste:
Taste buds on the tongue
Influence of sense of smell, texture of food, and pain stimulation (e.g., by pepper)
Primary and Secondary Taste Sensations:
Primary taste sensations: Sweet, Sour, Salty, Bitter, Umami
Chemical basis and signal transduction mechanisms for each taste
Taste Threshold and Index:
Taste threshold values for Sweet (sucrose), Salty (NaCl), Sour (HCl), and Bitter (Quinine)
Taste index relationship: Inversely proportional to taste threshold
Taste Blindness:
Inability to taste certain substances, particularly thiourea compounds
Example: Phenylthiocarbamide
Structure and Function of Taste Buds:
Composition: Epithelial cells, Sustentacular/Supporting cells, Taste cells, Basal cells
Features: Taste pores, Taste hairs/microvilli, and Taste nerve fibers
Location of Taste Buds:
Found in papillae of the tongue (Fungiform, Circumvallate, Foliate)
Also present on the palate, tonsillar pillars, epiglottis, and proximal esophagus
Mechanism of Taste Stimulation:
Interaction of taste substances with receptors on microvilli
Signal transduction pathways for Umami, Sweet, Bitter, Sour, and Salty tastes
Taste Sensitivity and Adaptation:
Decrease in sensitivity with age
Rapid adaptation of taste sensation
Role of Saliva in Taste:
Dissolution of tastants to reach receptors
Washing away the stimulus
Taste Preferences and Aversions:
Mechanisms behind taste preference and aversion
Influence of receptors and neural pathways
Impact of Sensory Nerve Damage:
Degeneration of taste buds if the sensory nerve fiber is cut
Abnormalities of Taste Detection:
Conditions: Ageusia, Hypogeusia, Dysgeusia (parageusia)
Causes: Nerve damage, neurological disorders, infections, poor oral hygiene, adverse drug effects, deficiencies, aging, tobacco use, altered neurotransmitter levels
Neurotransmitters and Taste Threshold:
Effects of serotonin (5-HT) and norepinephrine (NE) on taste sensitivity
Supertasters:
25% of the population with heightened sensitivity to taste, especially bitterness
Increased number of fungiform papillae
Report Back from SGO 2024: What’s the Latest in Cervical Cancer?bkling
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TEST BANK for Operations Management, 14th Edition by William J. Stevenson, Verified Chapters 1 - 19, Complete Newest Version.pdf
TEST BANK for Operations Management, 14th Edition by William J. Stevenson, Verified Chapters 1 - 19, Complete Newest Version.pdf
Flu Vaccine Alert in Bangalore Karnatakaaddon Scans
As flu season approaches, health officials in Bangalore, Karnataka, are urging residents to get their flu vaccinations. The seasonal flu, while common, can lead to severe health complications, particularly for vulnerable populations such as young children, the elderly, and those with underlying health conditions.
Dr. Vidisha Kumari, a leading epidemiologist in Bangalore, emphasizes the importance of getting vaccinated. "The flu vaccine is our best defense against the influenza virus. It not only protects individuals but also helps prevent the spread of the virus in our communities," he says.
This year, the flu season is expected to coincide with a potential increase in other respiratory illnesses. The Karnataka Health Department has launched an awareness campaign highlighting the significance of flu vaccinations. They have set up multiple vaccination centers across Bangalore, making it convenient for residents to receive their shots.
To encourage widespread vaccination, the government is also collaborating with local schools, workplaces, and community centers to facilitate vaccination drives. Special attention is being given to ensuring that the vaccine is accessible to all, including marginalized communities who may have limited access to healthcare.
Residents are reminded that the flu vaccine is safe and effective. Common side effects are mild and may include soreness at the injection site, mild fever, or muscle aches. These side effects are generally short-lived and far less severe than the flu itself.
Healthcare providers are also stressing the importance of continuing COVID-19 precautions. Wearing masks, practicing good hand hygiene, and maintaining social distancing are still crucial, especially in crowded places.
Protect yourself and your loved ones by getting vaccinated. Together, we can help keep Bangalore healthy and safe this flu season. For more information on vaccination centers and schedules, residents can visit the Karnataka Health Department’s official website or follow their social media pages.
Stay informed, stay safe, and get your flu shot today!
ARTIFICIAL INTELLIGENCE IN HEALTHCARE.pdfAnujkumaranit
Artificial intelligence (AI) refers to the simulation of human intelligence processes by machines, especially computer systems. It encompasses tasks such as learning, reasoning, problem-solving, perception, and language understanding. AI technologies are revolutionizing various fields, from healthcare to finance, by enabling machines to perform tasks that typically require human intelligence.
Explore natural remedies for syphilis treatment in Singapore. Discover alternative therapies, herbal remedies, and lifestyle changes that may complement conventional treatments. Learn about holistic approaches to managing syphilis symptoms and supporting overall health.
Lung Cancer: Artificial Intelligence, Synergetics, Complex System Analysis, S...Oleg Kshivets
RESULTS: Overall life span (LS) was 2252.1±1742.5 days and cumulative 5-year survival (5YS) reached 73.2%, 10 years – 64.8%, 20 years – 42.5%. 513 LCP lived more than 5 years (LS=3124.6±1525.6 days), 148 LCP – more than 10 years (LS=5054.4±1504.1 days).199 LCP died because of LC (LS=562.7±374.5 days). 5YS of LCP after bi/lobectomies was significantly superior in comparison with LCP after pneumonectomies (78.1% vs.63.7%, P=0.00001 by log-rank test). AT significantly improved 5YS (66.3% vs. 34.8%) (P=0.00000 by log-rank test) only for LCP with N1-2. Cox modeling displayed that 5YS of LCP significantly depended on: phase transition (PT) early-invasive LC in terms of synergetics, PT N0—N12, cell ratio factors (ratio between cancer cells- CC and blood cells subpopulations), G1-3, histology, glucose, AT, blood cell circuit, prothrombin index, heparin tolerance, recalcification time (P=0.000-0.038). Neural networks, genetic algorithm selection and bootstrap simulation revealed relationships between 5YS and PT early-invasive LC (rank=1), PT N0—N12 (rank=2), thrombocytes/CC (3), erythrocytes/CC (4), eosinophils/CC (5), healthy cells/CC (6), lymphocytes/CC (7), segmented neutrophils/CC (8), stick neutrophils/CC (9), monocytes/CC (10); leucocytes/CC (11). Correct prediction of 5YS was 100% by neural networks computing (area under ROC curve=1.0; error=0.0).
CONCLUSIONS: 5YS of LCP after radical procedures significantly depended on: 1) PT early-invasive cancer; 2) PT N0--N12; 3) cell ratio factors; 4) blood cell circuit; 5) biochemical factors; 6) hemostasis system; 7) AT; 8) LC characteristics; 9) LC cell dynamics; 10) surgery type: lobectomy/pneumonectomy; 11) anthropometric data. Optimal diagnosis and treatment strategies for LC are: 1) screening and early detection of LC; 2) availability of experienced thoracic surgeons because of complexity of radical procedures; 3) aggressive en block surgery and adequate lymph node dissection for completeness; 4) precise prediction; 5) adjuvant chemoimmunoradiotherapy for LCP with unfavorable prognosis.
Knee anatomy and clinical tests 2024.pdfvimalpl1234
This includes all relevant anatomy and clinical tests compiled from standard textbooks, Campbell,netter etc..It is comprehensive and best suited for orthopaedicians and orthopaedic residents.
micro teaching on communication m.sc nursing.pdfAnurag Sharma
Microteaching is a unique model of practice teaching. It is a viable instrument for the. desired change in the teaching behavior or the behavior potential which, in specified types of real. classroom situations, tends to facilitate the achievement of specified types of objectives.
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Youth exposure to pornography and violent web sites
1. Internet Safety Technical Taskforce
2nd Meeting, June 20 2008,
Washington, DC
Youth exposure to pornography and
violent web sites
Michele L. Ybarra MPH PhD
Internet Solutions for Kids, Inc.
* Thank you for your interest in this presentation. Please
note that analyses included herein are preliminary. More
recent, finalized analyses may be available by contacting
CiPHR for further information.
2. Roadmap for today’s discussion
Exposure to x-rated material
Examination of unwanted and wanted exposure
Comparisons of online and offline exposure
Exposure to violence online
Hate sites
Death sites
Sites depicting scenes of war, death,
terrorism
Cartoon sites
If it’s built, will they come??
3. Growing up with Media Survey
1,588 households
Online Survey
Baseline data: August and September, 2006
Follow-up: October – December, 2007 (76% rr)
Eligibility criteria:
Youth:
Between the ages of 10-15 years
Use the Internet at least once a month for the last 6 months
English speaking
Adults
Member of the Harris Poll OnLine
Equally or most knowledgeable about youth’s media use
Funded by the CDC (U49/CE000206)
4. Youth Internet Safety Surveys
1,500 households were surveyed
Random digit dial telephone survey
Eligibility criteria:
Youth:
Between the ages of 10-17 years
Use the Internet at least once a month for the last 6 months
English speaking
Adults
Equally or most knowledgeable about youth’s Internet use
YISS-1 conducted 1999-2000; YISS-2 conducted
in 2005 by Dr. David Finkelhor and colleagues at
UNH
6. YISS Definition
In the last 12 months:
Have you been on a website that showed
pictures of naked people or of people having
sex when you did not want to be on such a
site?
Have you opened an email or instant message
with advertisements or links to x-rated web
sites when you did not want to receive them.
7. Demographic profile of youth
reporting unwanted exposure to porn
Among 1,501 10-17 year olds surveyed in 2005 YISS-2:
34% reported an unwanted exposure (40% reported ANY
exposure)
54% were boys
Most (76%) were older youth (14-17)
Where did the unwanted exposures happen?
83% happened while surfing the web
40% occurred when doing online searches
17% clicked on links within sites
12% were from misspelled web addresses
18% came in the form of an email or IM
Wolak, Finkelhor and Mitchell, 2006
8. Demographic profile of youth
reporting unwanted exposure to porn
Similarly, in the UK…
57% of 9-19 year olds who use the Internet weekly
have been exposed to pornography.
As age increases, the likelihood of exposure also
increases: 21% of 9-11 year olds, 58% 12-15 year
olds, and 76% of 16-17 year olds
Most is unintentional exposure:
38% from a pop-up
36% accidentally founds themselves on a website
25% received pornographic junk mail
Livingstone & Bober, 2005
9. What does it mean to be “unwanted”
21% in YISS2 said they could tell it was x-rated
before entering (Wolak, Finkelhor, Mitchell, 2006)
Perhaps they didn’t understand the term “x-rated” until
they *saw* it
Perhaps they saw a different type (e.g., more
extreme) of pornography then they were expecting
10. Other important event characteristics
There is significant overlap of youth reporting
unwanted and wanted exposure
Those reporting unwanted exposure are 2.8
times more likely to report wanted exposure than
those not reporting unwanted exposure to sexual
material online.
2% report going back to the web site
Wolak, Finkelhor and Mitchell, 2006
11. Synopsis
Unwanted exposure is reported more commonly
reported than wanted exposure
Older youth are more likely to report unwanted
exposure to sexual material
Exposure occurs during a web search versus an
email/IM link about 4:1
Those who report unwanted exposure are more
likely to report wanted exposure to x-rated material
13. Definition
In the last 12 months, have you:
Gone to or seen an X-rated or “adult”
website where the main topic is sex
Watched an X-rated movie at a friend’s
house, your house, or in the theater where
the main topic was sex?
Looked at an X-rated magazine on purpose,
like Playboy, where the main topic was sex?
Definitions based upon those fielded in YISS-1
14. Frequency of intentional exposure:
GuwM
10%
11%
13% 13%
10%
0%
2%
4%
6%
8%
10%
12%
14%
16%
18%
20%
2006 (n=1588 10-15 yo) 2007 (n=1206 11-16 yo)
Internet
Magazines
Movies
15. Wacky Internet data?
Youth Internet Safety Survey 1:
8% reported looking at x-rated material online
12% reported looking at x-rated material offline
7% reported looking at x-rated material in magazines
8% reported looking at it in movies or videos
Youth Internet Safety Survey 2:
13% reported looking at x-rated material online (no data for
offline exposure)
YISS-1 data: Ybarra & Mitchell (2005) Exposure to Internet pornography among children and
adolescents: A National Survey. CyberPsychology and Behavior 8(5), 473-486.
YISS-2 data: Wolak, Mitchell, and Finkelhor (2006) Online Victimization of Youth: Five Years
Later. Available online at: http://www.unh.edu/ccrc/internet-crimes/papers.html
17. Demographic profile of youth looking
at internet porn
Among 1,206 11-16 year old youth in GuwM 2 (Oct-Dec,
2007):
80% male (OR = 4.2, p<.001)
14.4 years old (OR = 1.3, p<.001)
How did they hear about the site? (top 5):
From a friend: 53%
Search engine: 30%
Another web site: 29%
Typed in an address to see what would come up: 22%
Pop-up ad: 22%
18. Psychosocial profile of Internet porn
seekers (GuwM2)
Physical bullying (OR = 4.6, p<0.001)
Getting into fights (OR = 3.1, p<.001)
Poor academic performance (OR = 2.7, p<.002)
Carrying a weapon to school in the past 30 days (OR = 6.6,
p=0.01)
Poor relationship with caregiver (poor monitoring: 1.3, p=0.006:
poor emotional bond: 1.2, p=0.006)
Substance use (alcohol: 7.9, p<0.001; cigarettes: 6.6, p<.001;
Marijuana: 5.5, p<.001)
Seriously violent behavior: OR = 7.1 p <.001
These youth are significantly more likely to
have a lot of things going on
Measures refer to ‘ever in the last year’. Caregiver-child relationship variables are a summation of related
indicators (e.g., “how often do your caregiver know where you are when you’re not at home”)
19. Synopsis
Older youth and boys are more likely to report looking at
x-rated material. Children are not likely to look at porn
(<1%)
The Internet is not the most common access point for x-
rated material.
Youth reporting exposure to x-rated material are more
likely to also report a myriad of other concurrent
psychosocial problems. It is possible that x-rated
material is a marker for concern for some youth whereas
in other cases it is a marker for developmentally
normative sexual curiosity.
21. Definitions
A “hate” site is one that tells you to hate a
group of people because of who they are,
how they look, or what they believe.
A “death” website that shows pictures of
dead people or people dying. Some people
call these “snuff” sites.
Definitions based upon YISS-1
22. Definitions
A website, including news-related sites, that
shows pictures of war, death, “terrorism”
A website (that’s not an online game) that
shows cartoons, like stick people or animals,
being beat up, hurt, or killed
Definitions specific to GuwM
23. Frequency of exposure GuwM Wave 2
2% 4%
51%
42%
47%
54%
0%
10%
20%
30%
40%
50%
60%
Hate sites Death sites
Yes
No
I don't know what you're talking about
24. Frequency of exposure GuwM Wave 2
22%
18%
49%
46%
29%
36%
0%
10%
20%
30%
40%
50%
60%
News sites Violent cartoon sites
Yes
No
I don't know what you're talking about
26. Demographic profile of youth looking
at hate and death sites
Among 1,206 11-16 year old youth in GuwM 2 (Oct-
Dec, 2007):
50% male (OR = 0.9, p=0.83)
13.4 years old (OR = 1.3, p=0.009)
74% are White (OR = 1.1, p=0.91)
15% are Hispanic (OR = 1.0, p=0.96)
Of those who went to a site, how did they hear about it?
(top 3)
Hate sites: Friend (50%), Link from another site (22%),
Typed it in (17%)
Death sites: Friend (71%), search engine (31%), email
(30%)
27. Psychosocial profile of seekers of hate
and death web sites in 2007
Physical bullying (OR = 4.4, p<0.001)
Getting into fights (OR = 4.3, p<.001)
Carrying a weapon to school in the past 30 days (OR =
7.0, p=0.007)
Poor relationship with caregiver (poor monitoring: 1.4,
p=<.001: poor emotional bond: 1.3, p<.001)
Substance use (alcohol: 6.0, p<0.001; cigarettes: 6.4,
p<.001; Marijuana: 5.4, p<.001)
Seriously violent behavior: OR = 10.1, p <.001
These youth are significantly more likely to
have a lot of things going on
Measures refer to ‘ever in the last year’. Caregiver-child relationship variables are a summation of related
indicators (e.g., “how often do your caregiver know where you are when you’re not at home”)
28. Synopsis
Older youth are more likely to seek out
violent web sites, but there are no apparent
differences between boys and girls
The 1-year prevalence rates of exposure to
death sites and hate sites are low: 2-4%
In addition to exposure to violent web sites,
these youth are significantly more likely to
have other challenges going on in their lives
31. What happened to kids who didn’t
*know* about these sites?
Just *knowing* about a web site is not enough
for kids to go to them – even if it’s a “new” type
of site that some youth might find intriguing
It seems that there are other factors that
influence one’s decision to visit these sites
This is *good* news for us (bad news for
researchers, who are struggling to figure out
how to get kids to go to their health sites, and
keep them coming back!)
32. Final thoughts
Given that knowledge about unsavory web sites is
insufficient to predict whether a youth has visited the
site
Figuring out *why* some youth seek out / visit violent web
sites whereas others don’t seems likely to be a key to
prevention efforts.
Based upon youth-report, the Internet does not appear
to be a ‘risk environment’ for x-rated exposures
differently than the offline environment (movies and
magazines).
Only when we are clear about the influence the Internet is
and is not having on youth behavior will we be able to affect
appropriate intervention strategies.
33. *After* slides
What is an “OR”?
An odds ratio (OR) is the ratio of the odds that someone exposed (e.g., to
a violent web site) will report the behavior (e.g., bullying) versus the
odds that someone not exposed will report the behavior
For example, let’s say:
Behavior
reported (e.g.,
bullying)
No behavior
reported (not
bullying)
Exposure (e.g., visiting a
type of violent web site)
8 teens 2 teens
No exposure (e.g., not
visiting the web site in
question)
12 teens 78 teens
34. *After* slides
Thus, (from the grid on the previous slide):
8 out of 10 youth exposed also report the
behavior (so the odds are 8:2 or 4)
12 out of 90 youth not exposed also report the
behavior (so the odds are 12:78 or 0.15)
The ratio of these odds is 26 (4/0.15)
35. *After* slides
The ratio of the odds = odds ratio = OR = 26
Those with the exposure are 26 times more
likely to report the behavior than those
without the exposure.
Note: as you can see in the grid, this does not
mean that all youth with the exposure will
report the behavior, or that those who report
the behavior always report the exposure.
But, the odds are higher that the two will co-
occur than not…
36. *After* slides
So, what’s the relevance to the current slides?
Well, for example the odds that youth who report going to
hate and death sites engage in externalizing behaviors are
significantly higher than youth who do not (e.g., the OR =
10 related to seriously violent behavior with respect to
youth visiting hate/death sites versus not).
Again: not all youth who have visited hate and death sites in
the past year report these externalizing behaviors. And,
not all youth who report these externalizing behaviors also
visited these web sites. But, the odds that they co-occur
are higher than that they don’t….
Editor's Notes
The majority of the data I’ll be talking about today are recent and were just collected this past December…
Copies of the reports for the YISS-1 and YISS-2 can be found free of charge at: http://www.unh.edu/ccrc/internet-crimes/papers.html
Unfortunately, the question about movies for 2007 was not asked in a parallel fashion, and as such is not included here. For Internet and magazines however, you can see that there is not much change over the 12-months.
We now have data from four samples that allow us to map the frequency of intentional exposure to x-rated material over time. When we do so (above), we very clearly see a pattern for increased exposure rates as age increases. Note that this age group is also normatively and developmentally appropriately becoming curious about sex. Note also that GuwM W1 and W2 are the same youth, whereas YISS and GuwM are completely different samples
Friends are by far the most common source of information about x-rated web sites.
Data
Exposure to hate and death sites across time and age, based upon three data sets (note that GuwM W1 and W2 are the same youth, whereas YISS and GuwM are completely different samples)
Again, note the influence that friends have on learning about these types of web sites.
We looked at frequencies of visiting violent web sites at Wave 2 versus Wave 1, and we looked specifically at those who said they had never heard of these web sites at Wave 1: were they more likely to visit the web site at Wave 2? Did we inadvertently create exposures? The answer is no. These youth are no more likely at Wave 2 than youth who were aware of violent web sites at Wave 1 to visit violent web sites by Wave 2…