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Example Community: Healthy Kids Colorado Survey

Example Community: Healthy Kids Colorado Survey. Data Presentation. Presentation Outline. Overview of Healthy Kids Colorado Survey (HKCS) Interpreting Data HKCS Report Structure Presentation of Community Data EVB Programming and Resources, Prevention Resources Next Steps.

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Example Community: Healthy Kids Colorado Survey

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  1. Example Community:Healthy Kids Colorado Survey Data Presentation

  2. Presentation Outline • Overview of Healthy Kids Colorado Survey (HKCS) • Interpreting Data • HKCS Report Structure • Presentation of Community Data • EVB Programming and Resources, Prevention Resources • Next Steps

  3. Healthy Kids Colorado Survey Overview

  4. Overview: Benefits of HKCS • Provide Locally Relevant Data • Supporting planning and decision-making processes • Minimal disruption to instructional time • 45 minute administration time • Flexibility in Scheduling • Administration dates between September and May • User-Friendly Survey Reports • Easy to read school, district, and community level reports • Provision of Survey Materials • All administration materials will be provided (except pencils)

  5. Overview: Background • HKCS contains items from: • Youth Risk Behavior Survey (CDC) • Colorado Youth Survey (risk and protective factors) • Asset and resiliency scales • Supported and developed by the following Colorado State Agencies: • Departments of Education • Public Health and Environment • Human Services • Alcohol and Drug Abuse Division • Public Safety • Division of Criminal Justice • Office of Adult and Juvenile Justice Assistance

  6. Interpreting Data

  7. Interpreting Data • Association • Causation • Modeling • State Level Data Comparisons • Multi-Year Comparisons

  8. Interpreting Data: Association Association - When things happen together Association = Correlation Association DOES NOT = Causation Modeling Tools Association Line : X and Y Happen Together X Y

  9. Interpreting Data: Association Two Types of Associations: AccidentalMeaningful

  10. Interpreting Data: Causation • Causation - the exposure or presence of something is the cause of change in another • To make a claim of Causation we Need: • Theory that supports the claim • Data that supports the claim • Time order of cause(s) and effect(s) Modeling Tools Cause Arrow - X Causes Y Y X

  11. Interpreting Data: Causation

  12. Relaxed Values Not Enough To Do KEY Cause Assoc. B=Belief D=Data R=Research Interpreting Data: Modeling Teen Pregnancy Sexually Transmitted Diseases

  13. Interpreting Data: Modeling Line Arguments B = Is a BELIEF D = Is Implied by the DATA R = Has RESEARCH or Theory to Support

  14. Interpreting Data: Modeling Teen Pregnancy Relaxed Values D B Sexually Transmitted Diseases Not Enough To Do KEY Cause Assoc. B=Belief D=Data R=Research

  15. Teen Pregnancy R School Drop Out D Sexually Transmitted Diseases Interpreting Data: Modeling Relaxed Values B Not Enough To Do KEY Cause Assoc. B=Belief D=Data R=Research KEY B=Belief D=Data R=Research

  16. HKCS Report Structure

  17. HKCS Domains Substance Use Delinquency Personal Safety/Violence Physical Health Mental Health School and Family Risk and Protective Factors Integrity of Responses Students are removed from sample if: Grade/school don’t match > 3 Sections of dishonesty i.e. at least 3 instances of reporting “never use” but also reporting “30-day use” HKCS Report

  18. Increase Risk Increase Protection Risk and Protective Factors • Risk factors: increase likelihood of adolescent problem behaviors • Protective factors: help to buffer against those risk factors, reducing the likelihood of problem behaviors • For example, the model of heart disease • (Risks: family history, high cholesterol, etc.) • (Protective: exercise, healthy diet, etc.)

  19. Community Individual/ Peer Family School Risk and Protective Model

  20. Risk and Protective Factors • Scales • The data for risk and protective factor scales are computed as cut-points. • Cut Off Points • The cut-point for a riskscale is the point at which a score on the scale predicts negative outcomes. • The cut-point of a protective factor scale is the point at which a score on the scale predicts positive outcomes.

  21. Q94 Q95 Q93 Low Commitment To School Risk Scale Q98 Q99 Q97 Q96 Risk and Protective Example Domain: School

  22. HKCS Report: Bar Graph Format

  23. HKCS Report: Pie Chart Format

  24. HKCS Report: Table Format

  25. HKCS Report: Resources • Missing and Suppressed Data • Section Headers • Table and Graph Footers • Definitions • Appendices • Sample Survey • Risk and Protective Factor Information

  26. Presentation of Community Data

  27. Demographics

  28. Demographics & Generalizability • What are the schools included in this report? How is this community defined? • Are at least 70% of the student population (and subpopulations) represented in the results? • If not, what are potential reasons or limitations to the data?

  29. Alcohol and Drug Use Key Point: Alcohol is used most commonly in the last 30 days by students in all grades.

  30. Alcohol and Drug Use Key Point: Students have used alcohol, marijuana, and prescription drugs most often in their lifetimes.

  31. Community Strengths: ATOD • 83% of students have not used alcohol in the last 30 days • 88% of students have never used heroin in their lifetime

  32. What can we do? • School Engagement • Collect Trend Data • Administer HKCS Survey again to compare data • Youth Engagement • Use data to inform strategic plan

  33. Second Issue: Mental Health Key Point: Approximately 1/3rd of all students report feeling depressed in the last year.

  34. Second Issue: Mental Health Key Point: The majority of student feel finishing high school is a very important or important aspiration.

  35. Second Issue: Mental Health Key Point: Over 75% of females and males reported participating in extracurricular activities at school.

  36. What can we do? • Engage with schools, teachers, and administration • Talk to youth • Investigate association with ATOD use • Promotion of mental health services

  37. Community Strengths: Mental Health • 91% of students feel that it is very important or somewhat important to help people • 37% of students engaged in organized community service in the last 30 days

  38. Overall Community Findings • Alcohol and Drug Use • Alcohol is a prevalently used drug in the community • Students report significant alcohol use as early as 6th grade • Mental Health • Students reported depression more frequently than the state level data • Students generally feel supported

  39. Potential Influences on HKCS Data • Things to Consider….. • Community norms and local culture • Past and current prevention efforts • Factors influencing data quality

  40. Data to Action: Next Steps • Using data to Guide Needs Assessment • Targeting subpopulations at risk • Evidence Based Programs • School Engagement • Youth Engagement

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