Linking Program Needs and Desired Outcomes in a Sound Research Project

1. A Sound Research Project – Linking Program Needs and Desired Outcomes Caile E. Spear, Dept. of Kinesiology, Boise State Universitycspear@boisestate.edu Gayle Bush, Kinesiology & Health Promotion, Troy University Ping Hu Johnson, Dept of Health, Physical Education and Sports Science, Kennesaw State University Michele Pettit, Dept. of Health Education & Health Promotion, UW-La Crosse AAHPERD -March 17, 2010

2. Program Objectives: By the end of this workshop, participants will be able to:   Iterate steps in developing a research proposal   Write succinct research hypotheses   Identify the appropriate research design   Select appropriate statistical methods and            analysis

3. Steps to Develop a Research Proposal

4. Decide what you want to do • Based on: • Interest • Knowledge and expertise • Available resources • personnel, equipment, materials, $$$, etc. • Identify project goal(s) • What do you want to accomplish? • What is the problem that needs to be solved? • Develop hypotheses

5. Conduct literature review Search literature Organize literature Select research design Depends on type of research Needs assessment, intervention, evaluation Study Population vs. Study Sample Sample selection Select statistical methods

6. Subject/Title Search      Author Search Identify possible articles review titles and abstracts Locate and obtain articles library, online, interlibrary loan Organize literature Literature Review

7. Provide background information • What has been done • What needs to be done - need for research • Why the need for research – justification/significance • Identify theory/theories to guide research • Assist with • Selection of research design and statistical methods • Selection or development of instrument for data collection • Development and implementation of intervention activities • Development and implementation of evaluation activities

8. Choosing a Theoretical Framework

9. Many health education projects are based on specific theories or models. A framework is critical in planning a health education or intervention project. Having a valid, reliable, and objective model gives a research study credibility and a basis for planning and evaluation.

10. Constructs: • Perceived susceptibility • Perceived severity • Perceived benefits of action • Perceived barriers to action • Cues to action • Self-efficacy • Example: For a person to adopt recommended physical activity behaviors, his/her perceived threat of disease (and its severity) and benefits of action must outweigh his/her perceived barriers to action. Health Belief Model

11. Theory of Reasoned Action/Planned Behavior Constructs- Attitude Perceived behavioral control Subjective norm Example: Obese people who have a positive attitude towards exercise, feel they can exercise, and have friends thinking exercise is important, have positive intent and are more likely to exercise

12. Social Cognitive Theory Modeling Skill Training (reasoning) – psychomotor social skills (refusal skills) - behavioral rehearsal Self-Monitoring - a contract with oneself Contracting- contracting with others Include a reward Specific behaviors Goals Signatures Example- Smoking cessation support groups

13. Stages of ChangeTranstheoretical Model People progress through 5 levels based on readiness to change: Precontemplation Contemplation Preparation Action Maintenance Example- In adopting healthy behaviors (regular physical activity) or eliminating unhealthy ones (smoking, excessive alcohol intake), people cycle through 5 stages

14. Socio-ecological Model: Steps to a Healthier US and other community based health initiatives

15. The Precede-Proceed Model

16. Health Behavior Models 1. Health Belief Model http://www.healthierus.gov/steps/2006Slides/A2/hefelfinger.html 2. Theory of Reasoned Action 3. Theory of Planned Behavior http://www.etr.org/recapp/index.cfm?fuseaction=pages.TheoriesDetail&PageID=522#condomUse 4. Social Cognitive Theory http://usaoll.org/mobile/theory_workbook/social_learning_theory.htm 5. Precede-Procede Model http://envirocancer.cornell.edu/obesity/intervention101.cfm 6. Socio-ecological Model http://www.ahrq.gov/clinic/uspstf07/methods/tfmethods.htm 7. Transtheoretical Model (Stages of Change) http://www.aafp.org/afp/20000301/1409.html

17. Hypothesis

18. Formulating the Hypothesis A Hypothesis is the expected result; It must be “testable” The study must be designed in such a way that the hypothesis can be either supported or refuted.

19. The anticipated outcome of a study or experiment • Must be based on some theoretical construct, or on results from previous studies, or perhaps on the researcher’s past experience and observations • For example: • “Children who participated in a 6-wk pedometer-based intervention have higher daily step counts than children in the control group.” Research Hypothesis

20. A scientific process that examines a hypothesis against an alternative hypothesis using appropriate statistical reasoning. • Through the hypothesis testing, we infer the findings from a sample to the population (i.e., inferential statistics). • Using our sample statistic, we want to make a conclusion about what is happening in the population. Hypothesis Testing

21. Sampling

22. Study Population vs. Study Sample • Study Population: • share a common characteristic (age, sex, health condition) • Study Sample - a subset of the study population • Sampling - methods of selecting a study sample  • Probability sample - allows for valid generalization • simple - sampling unit (individual, natural group, etc.) • systemic - nth • stratified -proportional vs. nonproportional

23. Non-Probability Sample - limited generalizability Convenience Volunteers Grab samples Homogeneous samples Judgmental samples Snowball samples Quota samples

24. Research Design

25. Non-experimental • No randomization • No comparison/control group • Quasi-experimental • No randomization • Comparison/control group • Experimental • Randomization • Control group • Source: Windsor et al., 1994 Research Designs

26. Deductive • A theory exists and hypotheses are tested using quantitative methods • Quantitative research • Inductive • Hypotheses are generated from specific observations and theories emerge • Qualitative research • Source: Babbie, 2001 Inductive vs. Deductive Reasoning

27. Qualitative • Example: • RQ: What factorscontribute to binge drinking among college students? • Quantitative • Example: • RQ: Are gender and Greek involvement predictive of binge drinking among college students? Qualitative vs. Quantitative Research

28. Statistics

29. Descriptive • Describe a data set: Demographics, Mean, Range, Standard Deviation, etc. • Inferential • Attempt to accurately draw conclusions about a larger population based on information collected in a sample. Descriptive vs. Inferential Statistics

30. Correlation • Regression • T-tests • ANOVA Examples of Inferential Statistics

31. Correlation Represents the strength of the relationship or association between two or more variables from the same sample (values range -1 to 1) Example: RQ: What is the relationship between height and weight?

32. Regression Used to predict a variable (dependent/ outcome) from one or more predictor (independent) variables Example: RQ: Are attitude, subjective norm, and perceived behavioral control predictive of college students’ intentions to quit smoking? This example utilizes the Theory of Planned Behavior which has been used to examine individual behaviors and develop programs.

33. “T” Tests (comparison of means) Used to draw conclusions/infer differences in means (averages) between two populations or sets of scores Examples Repeated measures Matched pairs Post-test only between two groups with differing interventions

34. Pre-Post Test Examples Pre – post test for knowledge, fitness levels, attitudes, and specific behaviors. Examples: Asthma 101 and Open Airways Physical fitness: fall vs. spring Attitudes and behaviors (the CATCH program related to diet and exercise)

35. Tying Pieces TogetherT test Examples

36. Example: Evaluation of a 1-day advocacy training workshop for health educators • Design: Non-experimental • Research Question: Does a significant difference exist between participants’ knowledge of advocacy before and after the workshop? • Methods: Pre/post-tests • Statistical Analysis: Dependent t-test Example #1

37. Example: Evaluation of a comprehensive sex education curriculum for 9th graders • Design: Experimental • Research Question: Does the prevalence of unintended pregnancy differ between students who complete a comprehensive sex education curriculum and students who complete an abstinence-based sex education curriculum? • Methods: Post-tests • Statistical Analysis: Independent t-test Example #2

38. ANOVA Used for more than two groups with repeated measures such as a pre-mid-post test, or numerous post tests after an intervention Example: 1. Pre-test****Intervention-9th grade sex education curriculum2. Post-test3. Nine month follow-up test

39. ANOVA (Cont.) • Example: compare four physical education classes with differing curricula or exercise programs • Within-Group Variation–the amount of variation among observations within each group (class, school, gender, etc.) • Between-Group Variation–the amount of variation between all the group means

40. Summary

41. HEDIR discussion on efficacy of abstinence program • Issue-can results be replicated • Why?-many programs, what works in our community • Background of problem • Teen pregnancy • Variety of programs • Efficacy

42. Literature review -research-based, theoretically based, factual, developmentally appropriate, populations, short-term and long-term outcomes • Research question -Students in program greater intent to remain abstinent vs regular program • Operational definitions - type of sex, abstinence-only, abstinence-based • Data analysis • Results

43. Project Ideas • Think-Pair-Share • Premise lit review & theory selection done • Identify research question • Generate hypothesis • Sample • Methods • Data collection • Data analysis • Who needs to be on board