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A Sound Research Project – Linking Program Needs and Desired Outcomes. Caile E. Spear, Dept. of Kinesiology, Boise State University [email protected] Gayle Bush, Kinesiology & Health Promotion, Troy University

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A sound research project linking program needs and desired outcomes

A Sound Research Project – Linking Program Needs and Desired Outcomes

Caile E. Spear, Dept. of Kinesiology, Boise State [email protected]

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


Program objectives

Program Objectives: Desired Outcomes

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


Steps to develop a research proposal

Steps to Develop a Desired OutcomesResearch Proposal


  • Decide what you want to do Desired Outcomes

    • 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


Conduct literature review Desired Outcomes

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


Literature review

Subject/Title Search      Author Search Desired Outcomes

Identify possible articles

review titles and abstracts

Locate and obtain articles

library, online, interlibrary loan

Organize literature

Literature Review


  • Provide background information Desired Outcomes

    • 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



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.


Health belief model

  • Constructs theories or models.:

    • 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


Theory of reasoned action planned behavior

Theory of Reasoned Action/Planned Behavior theories or models.

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


Social cognitive theory

Social Cognitive Theory theories or models.

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


Stages of change transtheoretical model

Stages of Change theories or models.Transtheoretical 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



The precede proceed model

The Precede-Proceed Model community based health initiatives


Health behavior models

Health Behavior Models community based health initiatives

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


Hypothesis
Hypothesis community based health initiatives


Formulating the hypothesis

Formulating the Hypothesis community based health initiatives

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.


Research hypothesis

  • The anticipated outcome of a study or experiment community based health initiatives

  • 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


Hypothesis testing

  • 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


Sampling
Sampling alternative hypothesis using appropriate statistical reasoning.


Study population vs study sample
Study Population vs. Study Sample alternative hypothesis using appropriate statistical reasoning.

  • 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


Non-Probability Sample alternative hypothesis using appropriate statistical reasoning.- limited generalizability

Convenience

Volunteers

Grab samples

Homogeneous samples

Judgmental samples

Snowball samples

Quota samples


Research design
Research Design alternative hypothesis using appropriate statistical reasoning.


Research designs

  • Non-experimental alternative hypothesis using appropriate statistical reasoning.

    • No randomization

    • No comparison/control group

  • Quasi-experimental

    • No randomization

    • Comparison/control group

  • Experimental

    • Randomization

    • Control group

  • Source: Windsor et al., 1994

  • Research Designs


    I nductive vs deductive reasoning

    • Deductive alternative hypothesis using appropriate statistical reasoning.

      • 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


    Qualitative vs quantitative research

    • Qualitative alternative hypothesis using appropriate statistical reasoning.

      • 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


    Statistics
    Statistics alternative hypothesis using appropriate statistical reasoning.


    Descriptive vs inferential statistics

    • Descriptive alternative hypothesis using appropriate statistical reasoning.

      • 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


    Examples of inferential statistics

    • Correlation alternative hypothesis using appropriate statistical reasoning.

    • Regression

    • T-tests

    • ANOVA

    Examples of Inferential Statistics


    Correlation

    Correlation alternative hypothesis using appropriate statistical reasoning.

    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?


    Regression

    Regression alternative hypothesis using appropriate statistical reasoning.

    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.


    T tests comparison of means

    “T” Tests (comparison of means) alternative hypothesis using appropriate statistical reasoning.

    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


    Pre post test examples

    Pre-Post Test Examples alternative hypothesis using appropriate statistical reasoning.

    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)


    Tying pieces together t test examples
    Tying Pieces Together alternative hypothesis using appropriate statistical reasoning.T test Examples


    Example 1

    • Example alternative hypothesis using appropriate statistical reasoning.: 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


    Example 2

    • Example: alternative hypothesis using appropriate statistical reasoning. 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


    Anova

    ANOVA alternative hypothesis using appropriate statistical reasoning.

    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


    Anova cont
    ANOVA (Cont.) alternative hypothesis using appropriate statistical reasoning.

    • 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


    Summary
    Summary alternative hypothesis using appropriate statistical reasoning.


    • HEDIR discussion on efficacy of abstinence program alternative hypothesis using appropriate statistical reasoning.

    • Issue-can results be replicated

    • Why?-many programs, what works in our community

    • Background of problem

      • Teen pregnancy

      • Variety of programs

      • Efficacy


    • Literature review alternative hypothesis using appropriate statistical reasoning.-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


    Project ideas
    Project Ideas alternative hypothesis using appropriate statistical reasoning.

    • 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


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