data: what is it telling me?

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Angela Goldberg, ConsultantCenter for Community Action & Training (CCAT)

D A T A : W H A T I S I T T E L L I N G M E ?

Tennessee Advanced School on AddictionsJune 22-23, 2010

Center for Community Action

& Training

AGENDA3 WHOS + WHYS+ 4 WHAT'S=SUCCESS

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

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STRATEGIC PREVENTION FRAMEWORK (SPF)

THINKING ABOUT THE WHO

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

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IOM

THE WHO

Data Is Different Data Informs Choice of Different

Strategies

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THREE STAGES OF USING DATAGETTING THE PROBLEM INTO FOCUS

Assessment Nature of the Problem

Needs and Resources

Begin with the End in Mind

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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

OTHER DATA IN PLANNING

WHAT ARE YOU LOOKING FOR?

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’

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

SENSITIVE ASSESSMENT

INTERPRETING DATA

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

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The “SPF” of Data:

S P F

GOOD MEASURES

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

TABLE SHARING ON DATA

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.

DATA IN ASSESSMENT

HOW MUCH OF WHAT?

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.

4 TYPES OF DATAType Example

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

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USE 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

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DATA MININGBREAKING IT DOWN TO FIND MEANING

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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) - - 7 16 15 35 8 81

Accidental (Motor Vehicle) - 1 2 2 2 3 - 10

Accidental (Other) - - 1 1 3 - 2 7

Natural with methamphetamine

present- - - 2 1 1 1 5

Homicide - 2 4 6 1 2 1 16Suicide - - 2 4 8 3 - 17

Other/Undetermined - - - - - - -2

(age unknown for both)

Fetal/Perinatal Death - - - - - -

TOTAL 0 3 16 31 30 44 12 138

Example

Looking at Manner of Death by Age Reveals Patterns

USE DATA ARCHIVAL SOURCES

Youth Use

YRBS: www.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

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CONSEQUENCES DATA

Health

School / Work / Family

Traffic Collision & Injury

Arrest & Criminal Justice Involvement

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CONSEQUENCES DATA SOURCES

Hospital, Medical Examiner, Treatment System

District Suspensions

Fatality Analysis Reporting System for NHTSA

www-fars.nhtsa.dot.gov/States/StatesAlcohol.aspx

Arrests, Probation

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CONTRIBUTING FACTORS

May Include:

Availability

Youth Access

Community Norms

Perception of Harm

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DATA ON CONTRIBUTING FACTORS

WHY?

Less Likely To Be Archival

Data Hunt

Look and Listen

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LOCAL CONDITIONS

Such As:

Local Retail Environments

Patterns of Social Access

Near Peer, Parents, Parties

Alcohol Presence in Community Events

Local Economies Built around AOD

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DATA EXERCISE

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.

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15 Minutes Total: Select a Recorder, Reporter, Timekeeper

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?

USING YOUR DATA

Problem

Contributing Factors/(Generic)

Local Conditions /

The CADCA Problem Analysis Process

Data Drives Planning

Problem /Goal

Contributing Factors/Objectives(Generic)

Local Conditions / Short Term Objectives

The CADCA Problem Analysis Process

Data-Based or No GoIdentify at least two sources of data for every point

MAKING THE RIGHT MATCH

The Essential Questions: Does your strategy address the

contributing factors? Does your strategy fit the

population or setting?

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DATA HELPS YOU MAKE YOUR CASE

What Is Happening? How Will Your Strategy Produce

The Desired Change? How Can You Show The

Difference?

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LOGIC MODEL: GUIDE

Does it add up?

Informs you about what data you need to look at change at short term, intermediate and long term levels

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PULLING IT ALL TOGETHER

No Single Bullet

Coalitions and Agencies Make Great Partners Data Help

Linkages re Services

Comprehensive

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FINDING MEANING OVER TIME

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?

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EXPERIMENTAL DESIGN?

Re-think Your Expectation

Consider “Contributes to rather than Attribution”

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INTERMEDIATE

Did One Thing Lead To The Other?

How Do You Know? Follow Your Logic

Model to the Right Indicators

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EVALUATION

Did Change Happen?

Your Original Data Can Be Revisited

Long Term Change Most Likely Archival

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DATA STRATEGIES

GIS

Surveys

Observations

Interviews

Focus Groups

Neighborhood Talks

Town Halls

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GIS MAPPING37

GIS Maps Paint The Picture

NEIGHBORHOOD TALKS

Who Did We Talk With? 35 households on Meadow, Milo and

Cotton Streets. 59% Female; 41% male 54% Latino; 23% Caucasian; 14%

African American 60% either had raised or were

raising teenagers

Two-thirds of Neighbors Have Concerns about Drinking at the ParkWhen asked about specific concerns, those who responded shared concerns such as violence and rowdiness, underage drinking, trash, and impact on young children. The biggest specific concern mentioned was violence and rowdiness at 27%.

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Two-Thirds Of Respondents Said That Alcohol Problems Keep Families Away From The Park.

FOCUS GROUPS

Youth In Programs Are Experts

Think Through Your Protocol

Compose Groups

Facilitate, Record

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PLACE OF LAST DRINK SURVEY RESULTSOCEANSIDE, 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

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SURVEYS1 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

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55.8% 58.0% 54.1%58.4%

44.3%

0%

25%

50%

75%

100%

Youth Total(N=412)

Female(N=200)

Male(N=209)

High SchoolStudents(N=317)

CollegeStudents

(N=61)

N=384

DATA IS YOUR FRIEND

Use Facts, Not Opinion

Find Your Gaps And Fill Them

Use Your Findings To Strengthen And Succeed

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CONTACTS Center for Community Action & Training

www.ccat-ca.org Angela Goldberg

760-749-8792

angelagoldberg@sbcglobal.net

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