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Media ID	Source Name	Media Type	Language	Media Name	Media Description	Keywords	Keywords	Link to Article
5868	Centers for Disease Control and Prevention	Html	en	Diisobutyl ketone - NIOSH Pocket Guide to Chemical Hazards	null	MPEG 0.378858 search 0.263099 PDF 0.261307 PPT 0.446092	DOC 0.368812 information 0.262482 different file formats 0.938484 page 0.276773	CLICK HERE
7565	Centers for Disease Control and Prevention	Html	en	ADHD - PLAY Study Design (Project to Learn About ADHD in Youth)	ADHD is one of the most common neurobehavioral disorders of childhood. It is usually first diagnosed in childhood and often lasts into adulthood. Children with ADHD have trouble paying attention, controlling impulsive behaviors (may act without thinking about what the result will be), and in some cases, are overly active.	high school 0.581096 diverse populations 0.581488 school-based samples 0.580656 in-depth assessment 0.632878 children 0.716272 multiple waves 0.587026 semi-annual data collection 0.642536 school districts 0.659501 ADHD Prevalence 0.765312 brief quarterly contacts 0.637812 ADHD diagnosis 0.760637 ADHD Criteria 0.753996 high number 0.57914 school elementary students 0.650896 Robert E. McKeown 0.665058 ADHD Change Depending 0.815472 high risk 0.579002 ADHD symptoms 0.840908 similar assessment protocols 0.634809 public health impact 0.659507 geographical settings 0.58258 role ADHD 0.777014 research sites 0.588051 low risk 0.577366	ADHD 0.985559 community study 0.582031 Oklahoma Health Sciences 0.659832 baseline assessment 0.592337 South Carolina 0.659116 additional waves 0.576995 comprehensive picture 0.576304 certain ADHD symptoms 0.807307 additional studies 0.575668 investigator Mark L. 0.663381 Data analysis 0.57917 low number 0.577461 study population 0.591295 annual in-depth interviews 0.637352 data collection 0.646223 school-based sample 0.590547 follow-up project 0.576288 children’s development 0.605804 baseline study 0.607282 core set 0.574718 principal investigator 0.653524 comparison group 0.575956 site-specific measures 0.578368 PLAY study methods 0.674449	CLICK HERE
7799	Centers for Disease Control and Prevention	Html	en	Ovarian Cancer - Health Communication	Gateway to Health Communication and Social Marketing Practice - Ovarian Cancer	oral contraceptives 0.476965 Corinne’s family 0.451889 common type 0.439277 appropriate tests 0.433608 stage ovarian cancer 0.536231 close relatives 0.437362 tumor marker 0.434517 hysterectomy 0.415987 rough time 0.433748 tubal ligation 0.479928 Germ cell tumors 0.473814 non-gynecologic conditions 0.437911 blood levels 0.434447 transvaginal ultrasound 0.438566 Corinne 0.45838 Pap test 0.435075 tumor markers 0.43609 ovarian cancer 0.938794 younger women 0.441018 history 0.413965 women age 0.463933 Corinne’s problem 0.450261 female hormones 0.44307 symptoms 0.422295 certain risk factors 0.466735	menstrual cycle 0.443562 annual pelvic exam 0.464552 egg-producing cells 0.439084 new cases 0.439146 women 0.467667 potential screening methods 0.466102 woman 0.447747 ovaries 0.447775 sooner ovarian cancer 0.597286 Epithelial carcinoma 0.442524 aggressive therapy 0.434998 familial predisposition 0.438884 abdominal pain 0.436649 ovarian cancer increases 0.550335 stromal tumors 0.440698 types 0.414115 disease 0.477583 greater chance 0.440345 colon cancer 0.447536 common form-epithelial-is 0.438174 better chance 0.472992 Corinne’s friends 0.450356 prophylactic oophorectomy 0.439589 screening test 0.43422	CLICK HERE
8087	Centers for Disease Control and Prevention	Html	en	Preventing Chronic Disease | An Integrated Framework for Assessing the Value of Community-Based Prevention: A Report of the Institute of Medicine - CDC	Since the early 1900s, the major causes of illness and death in the United States have changed from infectious disease to chronic disease. Recognition is growing that nonclinical community- and population-based prevention has a large role in improving the public’s health and well-being.	intelligent decision making 0.606034 HIV transmission rates 0.605175 state policy implications 0.611171 nonclinical community 0.619096 senior program assistant 0.607237 IOM study committee 0.63172 population-based prevention 0.613818 Prev Chronic Dis 0.619046 California Endowment 0.616615 important step 0.611631 Wood Johnson Foundation 0.715076 W.K. Kellogg Foundation 0.714115 new framework 0.722082 Beaumont Foundation 0.614742 Integrated Framework 0.653411 health inequalities 0.60412 community process 0.825324 Lyla M. Hernandez 0.687797 health sector 0.606567 public’s health 0.64594 Hopkins Bloomberg School 0.677103 nonclinical prevention policies 0.65943 overall health 0.613302 decision makers 0.661718 community benefit 0.637129	quality-adjusted life 0.614429 community-based prevention interventions 0.72263 Angeles County Department 0.603404 health-adjusted life expectancy 0.710539 community health promotion 0.705255 Good-quality cost data 0.607758 Johns Hopkins Bloomberg 0.67225 IOM study staff 0.624196 community well-being 0.863956 Robert Wood Johnson 0.713966 community-based prevention intervention 0.703066 Public Health Practice 0.666281 community-based prevention 0.993555 value 0.760566 public health 0.856233 Robert S. Lawrence 0.675955 Nicolaas P. Pronk 0.707933 Health Promotion Department 0.65004 Health risks 0.620418 public health workers 0.686132 Public Health Service 0.663653 Health behaviors 0.621106 potential legitimacy problem 0.604097 Non-Clinical Prevention Programs 0.746654	CLICK HERE
8981	Centers for Disease Control and Prevention	Video	en	CDC: Tips from Former Smokers - Nathan: "I never smoked a day in my life!"	Nathan was Lakota, a member of the Oglala Sioux tribe, and never smoked. However, he worked in a facility where smoking was allowed, and experienced health problems as a result. In this video from CDC's Tips From Former Smokers campaign, Nathan describes his health problems—including asthma—triggered by exposure to secondhand smoke. He had to give up many activities he loved, including tribal dancing, because of damage to his lungs. That damage led to his early death at age 54. Comments on this video are allowed in accordance with our comment policy: http://www.cdc.gov/SocialMedia/Tools/CommentPolicy.html This video can also be viewed at http://streaming.cdc.gov/vod.php?id=cffaad4ff59ef8601e66780918669cef20130605130611015	Smokers 0.923068 CDC 0.901732 Nathan 0.85422	YouTube 0.846462 life 0.430486	CLICK HERE
10683	Centers for Disease Control and Prevention	Html	null	Business Improvements	Centers for Disease Control and Prevention's (CDC) Business Improvements			CLICK HERE
10815	Centers for Disease Control and Prevention	Html	en	QuickStats: Percentage of Adults Aged ?18 Years Who Looked Up Health Information on the Internet, by Age Group and Sex--- National Health Interview Survey, United States, January--September 2009	Persons using assistive technology might not be able to fully access information in this file. For assistance, please send e-mail to: mmwrq@cdc.gov.	mmwrq@cdc.gov. 0.484187 endorsement 0.368145 adult core component 0.611048 Alternate Text 0.45837 Human Services 0.577895 assistive technology 0.492977 health information 0.962191 National Health Interview 0.632915 final data files 0.604885 MMWR HTML versions 0.576873 U.S. Department 0.57138 electronic PDF version 0.57166 percentage 0.734187 e-mail 0.365978 estimates 0.402779 household interviews 0.464027 higher percentage 0.729355 Contact GPO 0.477677 commercial sources 0.458537 age groups 0.620898 current prices 0.453321 final weighting 0.473327 persons 0.443063 original paper copy 0.576347	Internet 0.523924 women 0.429288 earlier public access 0.602151 original MMWR paper 0.572679 age group 0.461969 adults 0.383199 assistance 0.332287 percentage points 0.586822 MMWR readers 0.45836 character translation 0.452376 format errors 0.449026 final data editing 0.607433 survey data 0.477908 civilian noninstitutionalized population 0.600635 question 0.359383 subject line 0.489966 typeset documents 0.455553 trade names 0.458629 official text 0.448153 sample 0.35278 non-CDC sites 0.454384 confidence interval 0.48167 Accommodation 0.3321 electronic conversions 0.446729	CLICK HERE
10851	Centers for Disease Control and Prevention	Html	en	Preventing Chronic Disease | Comparing Farmers™ Market Revenue Trends Before and After the Implementation of a Monetary Incentive for Recipients of Food Assistance - CDC	We examined the influence of an intervention to increase fruit and vegetable purchases at farmers’ markets for recipients of food assistance, Shop N Save (SNS), on revenue trends at a farmers’ market located at a federally qualified health center (FQHC) in rural South Carolina. We compared revenue trends for 20 weeks before the intervention (2011) and 20 weeks after (2012).	sales receipts 0.440234 SNS participants 0.471808 Fresh Start Farmers 0.434934 Supplemental Nutrition Program 0.388698 rural South Carolina 0.430713 market food assistance 0.411678 SNS unique identification 0.434407 revenue trends 0.481239 WIC FMNP vouchers 0.430663 healthy food retailers 0.391936 produce-only farmers 0.433078 food assistance dollars 0.417285 incentive programs 0.412394 FQHC-based farmers 0.437493 SNS enrollment 0.412091 Market Nutrition Program 0.421963 assistance incentive programs 0.3894 FMNP vouchers 0.491434 Total food assistance 0.389458 market 0.615487 food assistance incentive 0.407508 food assistance benefits 0.38815 federal food assistance 0.541446 Senior FMNP vouchers 0.439128 Senior FMNP 0.486233	food assistance programs 0.433845 WIC FMNP 0.465725 rural farmers 0.424958 SNS intervention 0.4472 future farmers 0.415949 farmers 0.761089 WIC Farmers 0.504542 farmers markets 0.462669 South Carolina 0.645889 Prevention Research Center 0.391047 SNS program 0.411385 SNS 0.658585 monetary incentive 0.549748 SNS coupon 0.415282 SNS customer 0.418486 nutrition assistance program 0.411444 federally qualified health 0.388886 food assistance revenue 0.518808 food assistance 0.919698 SNAP 0.454864 food assistance recipients 0.448357 monetary incentive programs 0.393378 Senior FMNP voucher 0.389265 small-scale farmers 0.448888	CLICK HERE
11923	Centers for Disease Control and Prevention	Html	en	Epidemiologic Risk Factors to Consider when Evaluating a Person for Exposure to Ebola Virus	null	country 0.209281 Laboratory processing 0.306309 uncertain control measures 0.413823 appropriate PPE 0.908847 Ebola cases 0.310604 Ebola survivors 0.305018 public health authorities 0.206456 urban settings 0.274645 widespread transmission 0.565445 Ebola virus 0.504839 n’t showing symptoms 0.2196 following epidemiologic risk 0.238557 Brief direct contact 0.226557 direct contact 0.515096	close contact 0.215942 potential exposure 0.210455 disease.  Unprotected contact 0.222236 high risk exposures 0.219511 public health 0.237921 personal protective equipment 0.229067 public health actions 0.233676 body fluids 0.553286 symptoms 0.31816 mucous membrane exposure 0.249157 person 0.632177 Ebola 0.800545 standard biosafety precautions 0.35679	CLICK HERE
14017	Centers for Disease Control and Prevention	Html	null	International Cancer Research	Selected articles that are authored or coauthored by scientists in CDC's Division of Cancer Prevention and Control are cited.			CLICK HERE