So you have your student health survey data… Now what ???

Jeanette Voas Partnership for Youth Franklin Regional Council of Governments

When to use your data…

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 • 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 • Planning: • Select strategies relevant to local • situation Target strategies to appropriate audiences

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) Grades 9-12 • 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

MA Youth Health Survey (MDPH)

Grades 6-12 • 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

Communities That Care (e.g., Bach Harrison PNA, Pride CTC) Grades 6-12 • 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

Attitudes and Behaviors Survey (Search Institute) Grades 6-12 • 40 Developmental Assets • 8 thriving indicators • Recent use of alcohol, tobacco, marijuana, inhalants, heroin/narcotics • Violence, delinquency • Depression & suicidality • Sexual intercourse • DFC core measures

Comparing to the nation & the state

• Monitoring the Future 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

• MA survey sponsored by DESE, in coordination with MDPH YHS http://www.doe.mass.edu/cnp/hprograms/yrbs/ • Grades 9-12

Who’s at risk? You can cut the data by…

CTC

Grade and/or age Sex/gender Race/ethnicity Sexual orientation Length of time in US Home living situation Transgender Disabilities x x x

YRBS

x x x x x x x x

A&B

x x x x x x

Who is at risk of being overweight?

LGBTQ 38% female 23% male 30% white 26% nonwhite 31% hetero sexual 25% higher SES 23% lower SES 32% 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.

30%

% current cigarette smokers

25% 20% 15% 10% 5% 0%

all LGBTQ 8th M LGBTQ

• Scenario 3: Smoking among 8 boys surveyed who self-identify as LGBTQ. th grade • 1/19, or about 5% are current smokers.

But think about what you’re obscuring when you aggregate 12th grade; 63% Reported alcohol use among local youth in the 30 days preceding the survey: 40% 8th grade; 26% 10th grade; 35%

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 have adult to talk with at home do not have adult to talk with at home 49% 45% 41% 40% 15% 23% 22% 21% 15% 11% recent binge physical fight depressive feelings Data from 2013 FC/NQ YRBS, n=1767 self-injury considered suicide

Breakfast and grades in school

100% 80% 60%

64%

40% 20% 0% 0 1 Data from 2013 FC/NQ YRBS, n=1767 2 3 4

# days/week eat breakfast

5 6

85%

7

Are students who use prescription drugs more likely to use alcohol or marijuana?

% who report alcohol/marijuana use 81% 67% 52% drank alcohol binged used marijuana 32% 21% 12% used prescription drugs Data from 2014 FC/NQ Teen Health Survey, n=1788 did not use prescription drugs

Are students who use alcohol & marijuana more likely to use prescription drugs?

% who report prescription drug use alcohol binge marijuana 15% 23% 18% used alcohol/marijuana Data from 2014 FC/NQ Teen Health Survey, n=1788 2% 4% 3% did not use alcohol/marijuana

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.