When (cont’d). Your data can help… Assessment: Identify problems Suggest underlying causes Identify assets Capacity Building: Build consensus Publicize your cause Add substance to grant applications Provide partners data they need Planning: Select strategies relevant to local situation Target strategies to appropriate audiences Implementation: Support social marketing/ social norms marketing Provide material for classroom use Educate parents, teachers, community members Evaluation: Determine what changed Gauge whether you have made a difference
Who can use it? Your organization Schools Community-based agencies Municipalities Hospitals doing community needs assessments Local news outlets
What…? What data might you have to work with? Communities That Care Youth Risk Behavior Survey Youth Health Survey Attitudes and Behaviors Survey What can the data tell you?
MA Youth Risk Behavior Survey (DESE) 30-day and lifetime use of tobacco, alcohol, marijuana + lifetime use of 5 other drugs Violence, bullying, sexual abuse Unintentional injury Nutrition & physical activity BMI, body image, weight control Sexual behaviors Depression, self-injury & suicidality Grades 9-12
MA Youth Health Survey (MDPH) 30-day and lifetime use of alcohol, marijuana + 7 other drugs Extensive section on tobacco use Violence, bullying, sexual abuse Unintentional injury, including concussion Nutrition & physical activity Screen time, gambling BMI, body image, weight control Sexual behaviors Depression, self-injury & suicidality Diabetes, asthma, dental care Grades 6-12
Communities That Care (e.g., Bach Harrison PNA, Pride CTC) 30-day and lifetime use of alcohol, tobacco, marijuana and 10 other substances Perception of others’ use Violence, delinquency, gambling Depression 22 risk factors & 11 protective factors in community, school, family, and peer/individual domains DFC core measures Grades 6-12
Attitudes and Behaviors Survey (Search Institute) 40 Developmental Assets 8 thriving indicators Recent use of alcohol, tobacco, marijuana, inhalants, heroin/narcotics Violence, delinquency Depression & suicidality Sexual intercourse DFC core measures Grades 6-12
Comparing to the nation & the state Monitoring the Future http://www.monitoringthefuture.org/http://www.monitoringthefuture.org/ Conducted by U Michigan Inst for Social Research Funded by NIDA National random sample 8 th, 10 th and 12 th grades + young adult Youth Risk Behavior Survey National survey conducted by CDC http://www.cdc.gov/HealthyYouth/yrbs/index.htm http://www.cdc.gov/HealthyYouth/yrbs/index.htm MA survey sponsored by DESE, in coordination with MDPH YHS http://www.doe.mass.edu/cnp/hprograms/yrbs/ http://www.doe.mass.edu/cnp/hprograms/yrbs/ Grades 9-12
Who’s at risk? You can cut the data by… CTCYRBSA&B Grade and/or agexxx Sex/genderxxx Race/ethnicityxxx Sexual orientationxx Length of time in USx Home living situationxx Transgenderxx Disabilitiesx
Who is at risk of being overweight? Data from 2013 FC/NQ YRBS, n=1767
A word about small numbers Scenario 1: Smoking among all students surveyed in Franklin County in 2014 186 students said they’d smoked in the past 30 days 1728 students answered the question about smoking So 186/1728, or about 11% are current smokers. Scenario 2: Smoking among self-identified LGBTQ youth surveyed 39/182, or 21% are current smokers. Scenario 3: Smoking among 8 th grade boys surveyed who self-identify as LGBTQ. 1/19, or about 5% are current smokers.
But think about what you’re obscuring when you aggregate Reported alcohol use among local youth in the 30 days preceding the survey: 40%
Who’s at risk? How else might you cut the data? If students have a parent they can talk to about important things, are they less likely to engage in risky behaviors? If students eat breakfast, are they more likely to get good grades? If students drink alcohol, are they more likely to use prescription drugs?
Comparing youth who have an adult at home to talk with about important things to those who do not Data from 2013 FC/NQ YRBS, n=1767
Breakfast and grades in school Data from 2013 FC/NQ YRBS, n=1767
Are students who use prescription drugs more likely to use alcohol or marijuana? Data from 2014 FC/NQ Teen Health Survey, n=1788
Are students who use alcohol & marijuana more likely to use prescription drugs? Data from 2014 FC/NQ Teen Health Survey, n=1788
Some limitations to ponder Survey data like ours (“cross-sectional data”) allow us to show associations among respondent characteristics, behaviors & attitudes. We cannot prove a cause-effect relationship. Different methods of data gathering will give different results. No single survey result is The Truth. The best use of these data may be to stick with a method and measure trends over time. You will not be able to survey everyone. Do you know who you’re missing? If so, can you adjust your analysis appropriately?
Why bother? Can we trust the data? We use well-established surveys that have been validated by extensive research and implemented across the nation. We check each respondent’s survey for internal consistency and include measures of honesty. The survey is anonymous, minimizing incentives to under- or over-report for social desirability. Survey data are fairly consistent over time, and local data are in line with national surveys.
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