1. 1 Angela Goldberg, Consultant Center for Community Action & Training (CCAT) D ATA : W HAT I S I T T ELLING M E ? Tennessee Advanced School on Addictions June 22-23, 2010 Center for Community Action & Training

2. A GENDA 3 WHOS + WHYS + 4 W HAT ' S =S UCCESS  Three Who’s to Consider  How to Use Data in Beginning, Middle and End  Four Types Of Data To Use In Prevention Planning and Evaluation  Data Strategies To Fill Gaps 2

3. S TRATEGIC P REVENTION F RAMEWORK (SPF)

4. T HINKING ABOUT THE W HO  Universal  Broad; e.g. all students at the school  Selective  Risk by virtue of membership in a subgroup; e.g. children of substance using parents  Indicated  Individuals who exhibit early signs or consequences of AOD use 4 IOM

5. T HE WHO  Data Is Different  Data Informs Choice of Different Strategies 5

6. T HREE S TAGES OF U SING D ATA G ETTING THE P ROBLEM INTO F OCUS Assessment  Nature of the Problem  Needs and Resources  Begin with the End in Mind 6

7.  Assess Community Readiness  Power Analysis – Who Can Make The Change  What’s The Community’s History Of Problem Solving?  Getting Beyond Archival (Student Surveys, Crime Data…)  Quantitative & Qualitative O THER D ATA IN P LANNING

8. W HAT A RE Y OU L OOKING F OR ?  Measuring individual behavior leads to efforts to change those individuals  Measuring environments leads to efforts to change environments  Not only ‘Who’ and ‘What’ but also ‘When’ ‘Where’ and ‘How ’

9. Individual  Individual Drinking Rates  Beliefs  Attitudes  Family History  Individual Problem Use Rates (CHKS)  Changes in Knowledge Environmental  Outlet Density  Rates Of Sales To Minors  Aggregate Law Enforcement Data  Community Indicators Such As DUI Rates  Belief/Attitudes Towards Policy Issues S ENSITIVE A SSESSMENT

10. I NTERPRETING D ATA  No Single Indicator Tells The Story  Need to triage with multiple sets  Understand The Data Limitations  Trends = Seven Points In One Direction  Who Examines? Bias, Skills & Values All Have A Role 10

11.  The “SPF” of Data:  S  P  F G OOD M EASURES

12. Use 3-5 minutes to consider your capacity in:  Quantitative data collection  Qualitative data collection Use the remaining time to answer:  What data sources do you currently use to know about AOD problems?  What data do you wish you had? 10 Minutes Total: Select a Recorder, Reporter, Timekeeper T ABLE S HARING ON DATA

13.  Four kinds of data collected will define the problems to address.  Both qualitative and quantitative data are essential.  Assessment should result in clear problem statements and priorities to address.  The assessment clearly sets the stage for evaluation. D ATA IN A SSESSMENT

14. H OW M UCH OF W HAT ?  The key is not simply to collect boxes and boxes of data, but rather to focus on the kinds of data that will help you understand the link between alcohol and other drugs and the problems.

15. 4 T YPES OF D ATA TypeExample Use Often archival from student and adult surveys Consequences of Use DUI collisions, AOD related arrests, student AOD violations Contributing Factors Youth Access, Density, Norms or Attitudes in Measurable Terms Local Conditions Local patterns on social/retail access, promotions, community events 15

16. U SE DATA  What Specific Indicator About Use?  30 day? Lifetime?  What Period Of Time?  Calendar? School Year? How Many Years?  Unit of Analysis  School, District, County, State, National 16

17. D ATA M INING B REAKING IT DOWN TO FIND MEANING 17 Manner <1 Year 1-19 Years 20-29 Years 30-39 Years 40-49 Years 50-59 Years 60-70 Years TOTAL Accidental (Drug Related) --7161535881 Accidental (Motor Vehicle) -12223-10 Accidental (Other) --113-27 Natural with methamphetamine present ---21115 Homicide -24612116 Suicide --2483-17 Other/Undetermined ------- 2 (age unknown for both) Fetal/Perinatal Death ------ TOTAL 0 31631304412138 Example Looking at Manner of Death by Age Reveals Patterns

18. U SE D ATA A RCHIVAL S OURCES  Youth Use  YRBS: www.cdc.gov/HealthyYouth/yrbs.htmwww.cdc.gov/HealthyYouth/yrbs.htm  SAMSHA’s Office of Applied Statistics: http://www.oas.samhsa.gov/alcohol.cfm  Adult Use  www.oas.samhsa.gov/nhsda.htm  www.monitoringthefuture.org 18

19. C ONSEQUENCES D ATA  Health  School / Work / Family  Traffic Collision & Injury  Arrest & Criminal Justice Involvement 19

20. C ONSEQUENCES D ATA S OURCES  Hospital, Medical Examiner, Treatment System  District Suspensions  Fatality Analysis Reporting System for NHTSA  www-fars.nhtsa.dot.gov/States/StatesAlcohol.aspx  Arrests, Probation 20

21. C ONTRIBUTING F ACTORS May Include:  Availability  Youth Access  Community Norms  Perception of Harm 21

22. D ATA ON C ONTRIBUTING F ACTORS WHY?  Less Likely To Be Archival  Data Hunt  Look and Listen 22

23. L OCAL C ONDITIONS Such As:  Local Retail Environments  Patterns of Social Access  Near Peer, Parents, Parties  Alcohol Presence in Community Events  Local Economies Built around AOD 23

24. D ATA E XERCISE  At your tables, pick one problem together, and one place or population. Identify data sources for the problem, contributing factors and local conditions.  Identify any data gaps you want to fill. 24 15 Minutes Total: Select a Recorder, Reporter, Timekeeper

25.  What are the key assessment findings?  Based on the key data findings, what prevention priorities have been identified?  How do these priority areas translate into specific problem statements?  Which key findings be used to help determine outcome measurement indicators for evaluation? U SING Y OUR D ATA

26. Problem Contributing Factors/ (Generic) Local Conditions / The CADCA Problem Analysis Process Data Drives Planning

27. Problem /Goal Contributing Factors/ Objectives (Generic) Local Conditions / Short Term Objectives The CADCA Problem Analysis Process Data-Based or No Go Identify at least two sources of data for every point

28. M AKING THE R IGHT M ATCH The Essential Questions:  Does your strategy address the contributing factors?  Does your strategy fit the population or setting? 28

29. D ATA H ELPS Y OU M AKE Y OUR C ASE  What Is Happening?  How Will Your Strategy Produce The Desired Change?  How Can You Show The Difference? 29

30. L OGIC M ODEL : G UIDE  Does it add up?  Informs you about what data you need to look at change at short term, intermediate and long term levels 30

31. P ULLING IT ALL TOGETHER  No Single Bullet  Coalitions and Agencies Make Great Partners  Data Help  Linkages re Services  Comprehensive 31

32. F INDING M EANING OVER T IME  Track Data at short, intermediate and long range periods, per logic model  Look for Change  Is today different than at baseline?  What Happened (Process), and What Difference (Impact) Occurred? 32

33. E XPERIMENTAL D ESIGN ?  Re-think Your Expectation  Consider “Contributes to rather than Attribution” 33

34. I NTERMEDIATE  Did One Thing Lead To The Other?  How Do You Know?  Follow Your Logic Model to the Right Indicators 34

35. E VALUATION  Did Change Happen?  Your Original Data Can Be Revisited  Long Term Change Most Likely Archival 35

36. D ATA S TRATEGIES  GIS  Surveys  Observations  Interviews  Focus Groups  Neighborhood Talks  Town Halls 36

37. GIS M APPING 37 GIS Maps Paint The Picture

38. N EIGHBORHOOD T ALKS 38

39. F OCUS G ROUPS  Youth In Programs Are Experts  Think Through Your Protocol  Compose Groups  Facilitate, Record 39

40. P LACE OF L AST D RINK S URVEY R ESULTS O CEANSIDE, CA  Total in the last year = 233 (Carlsbad=105, Oceanside=85, and Vista=43)  One primary cluster of problem outlets in Carlsbad; two secondary clusters in Oceanside 40

41. S URVEYS 1 in 4 adult community survey respondents felt it was “somewhat” or “very” acceptable to allow youth to drink alcohol in their home % Youth Survey Respondents Who Reported Drinking in Their Homes 41

42. D ATA IS Y OUR F RIEND  Use Facts, Not Opinion  Find Your Gaps And Fill Them  Use Your Findings To Strengthen And Succeed 42

43. C ONTACTS  Center for Community Action & Training www.ccat-ca.org  Angela Goldberg 760-749-8792 angelagoldberg@sbcglobal.net 43