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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:

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    


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
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

literature review
Subject/Title Search      Author Search

Identify possible articles

review titles and abstracts

Locate and obtain articles

library, online, interlibrary loan

Organize literature

Literature Review

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
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
    • 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



Perceived behavioral control

Subjective norm


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


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



Example- Smoking cessation support groups

stages of change transtheoretical model

Stages of ChangeTranstheoretical Model

People progress through 5 levels based on readiness to change:






Example- In adopting healthy behaviors (regular physical activity) or eliminating unhealthy ones (smoking, excessive alcohol intake), people cycle through 5 stages

health behavior models

Health Behavior Models

1. Health Belief Model


2. Theory of Reasoned Action

3. Theory of Planned Behavior


4. Social Cognitive Theory


5. Precede-Procede Model


6. Socio-ecological Model


7. Transtheoretical Model (Stages of Change)


formulating the hypothesis

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.

research hypothesis
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

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

study population vs study sample
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
Non-Probability Sample - limited generalizability



Grab samples

Homogeneous samples

Judgmental samples

Snowball samples

Quota samples

research designs
      • 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
    • 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
    • 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

descriptive vs inferential statistics
    • 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



Represents the strength of the relationship or association between two or more variables from the same sample (values range -1 to 1)


RQ: What is the relationship between height and weight?



Used to predict a variable (dependent/ outcome) from one or more predictor (independent) variables


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)

Used to draw conclusions/infer differences in means (averages) between two populations or sets of scores


Repeated measures

Matched pairs

Post-test only between two groups with differing interventions

pre post test examples

Pre-Post Test Examples

Pre – post test for knowledge, fitness levels, attitudes, and specific behaviors.


Asthma 101 and Open Airways

Physical fitness: fall vs. spring

Attitudes and behaviors (the CATCH program related to diet and exercise)

example 1
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

example 2
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



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.)
  • 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
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
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
project ideas
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