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Types of Research and Designs

Types of Research and Designs

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Types of Research and Designs

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  1. Types of Research and Designs • This week and next week… • Covering • Research classifications • Variables • Steps in Experimental Research • Validity • Research Designs • Common Sources of Error


  3. Research Classifications • System #1 (first tier): • Experimental • Nonexperimental • System #2 (second tier): • Quantitative research • Qualitative research • System #3 (third tier): • Basic • Applied

  4. Experimental Research Three fundamental characteristics: At least 1 active IV Extraneous variable controls Observations of the DV in response to the IV Classifications: Cross-sectional designs Longitudinal designs Nonexperimental Research Causal-comparative Descriptive Correlational Historical Research Classifications

  5. Quantitative Direct measurement of a score Numerical data Research questions Hypotheses Developed research procedures Controls Large samples Statistical procedures Qualitative Relies on… Extensive observations In-depth interviews Non-numerical data Example The general consensus among faculty in higher education is that the university administration and the faculty are nearly always in opposition. Research Classifications

  6. Basic Pure/fundamental research Discovery of new knowledge Development of theory Applied Central purpose Solution of an immediate problem Research Classifications

  7. Experimental Quantitative Basic Applied

  8. Nonexperimental Correlational Descriptive Basic Applied Basic Applied

  9. Experimental Research • Three fundamental characteristics: • At least 1 active IV • Extraneous variable controls • Observations of the DV in response to the IV • Classifications: • Cross-sectional designs • Longitudinal designs

  10. Experimental Research • Cross-sectional designs • Individuals with different characteristics are studied at the same point in time • Between-subjects comparisons • Advantages • Time efficient, quick results • Disadvantages • Error associated with inter- (between) and intra-(within) subject variability

  11. Experimental Research • Longitudinal designs • The same individuals are observed or measured repeatedly over a period of time • Within-subjects comparisons • Advantages • Error associated with intra- (within) subject variability • Disadvantages • Longer, time-consuming process • Attrition

  12. Wallace LS ; Buckworth J Title: Longitudinal shifts in exercise stages of change in college students. Source: J Sports Med Phys Fitness. 2003 Jun; 43(2): 209-12 Abstract: AIM: The protective health benefits of regular physical activity are well established. To date, few studies have assessed the prevalence of exercise behavior and factors influencing exercise adoption and maintenance among college students. The purpose of this study was to examine the relationship of exercise self-efficacy, social support, and sedentary behavior and longitudinal shifts in stage of exercise behavior change among a sample of college students without intervention. METHODS: A cross-sectional design was used to examine demographic characteristics, stage of exercise behavior change, exercise self-efficacy, social support (family and friend) and sedentary behavior. One hundred and sixty-one students at a large Midwestern university completed a valid and reliable written mailed questionnaire during baseline assessment and again 6 months later (follow-up). RESULTS: Changes in exercise self-efficacy, social support, and sedentary behavior were not observed among students who maintained their stage of exercise behavior change from baseline to follow-up. Exercise relapsers experienced significant decreases in exercise self-efficacy and peer social support from baseline to follow-up. CONCLUSION: These findings have important implications for further research on exercise adoption and maintenance among college students. From an applied perspective, it would be valuable for the practitioner to understand that different predictors are likely to influence exercise adoption and relapse.

  13. Marsh AP ; Rejeski WJ ; Lang W ; Miller ME ; Messier SP Title: Baseline balance and functional decline in older adults with knee pain: the Observational Arthritis Study in Seniors. Source: J Am Geriatr Soc. 2003 Mar; 51(3): 331-9 Abstract: OBJECTIVES: To examine the cross-sectional and longitudinal effect of baseline balance, independent of multiple covariates (sociodemographic variables, comorbidities), on self-reported disability and several measures of functional performance. DESIGN: Observational Arthritis Study in Seniors was a community-based longitudinal study. SETTING: Data collection was conducted at an exercise science research laboratory. PARTICIPANTS: A cohort of 245 women and 235 men, aged 65 and older, with self-reported knee pain. MEASUREMENTS: Measurements of balance, self-reported disability, functional performance, strength, sociodemographic characteristics, disease burden (including radiographic knee osteoarthritis (OA)), and functional limitations were obtained on participants at baseline and 30 months. The four outcome measures (self-reported disability, stair climb time, car time, preferred walking speed) were also collected at 15 months. RESULTS: In cross-sectional analyses, baseline balance was significantly associated with each of the four outcome measures before adjusting for baseline knee strength. After adjusting for knee strength, baseline balance remained significantly associated with all functional performance outcomes and self-reported disability. In longitudinal analyses, baseline balance had a significant effect on car-time performance, whereby individuals in the lowest quartile of baseline balance scores declined in a quadratic manner from baseline to Month 30. CONCLUSION: Baseline balance, independent of strength and various other covariates, is an important component of performance for transfer and ambulatory tasks and for self-reported disability. Balance was predictive of change in performance over time only in a task that presented a significant challenge to the lateral mobility/stability of participants. Balance was not predictive of decline in ambulatory performance-based tasks or in self-reported disability.

  14. Experimental Research • Other classifications: • Human vs. animal research • Invasive vs. noninvasive research


  16. Variables • A variable is a characteristic, trait, or attribute of a person or thing that can be classified or measured. • “Variable” = “more than one value” • Age, gender, height, weight, ethnicity, etc. • 2 basic types of variables: • Quantitative • Qualitative

  17. Qualitative Variables • A.k.a. = Categorical Variables • “Unmeasurable” variables • Gender, eye color, political affiliation, etc. • 2 types of categorical variables: • Ordinal • Data values represent categories with some intrinsic order (for example, low, medium, high; strongly agree, agree, disagree, strongly disagree). • Nominal • Data values represent categories with no intrinsic order (1 = Male, 2 = Female).

  18. Quantitative Variables • Characteristics, attributes, or traits that can be measured. • “Measurable” variables • Age, height, weight, etc. • 2 types of quantitative variables: • Discrete or Scale Variables • Data values are numeric values on an interval or ratio scale. • Values that cannot be fractionated or divided (whole numbers). • Test scores, game scores, age, etc. • Continuous Variables • Precision-based measurements • Strength, endurance, track & field times, height, weight, girth, etc.

  19. Variables • Independent variables • Dependent variables • Extraneous variables

  20. Independent Variables (IV) • Experimental treatment; treatment variable • Will not change during the course of the study • Antecedent to other variables • 2 types of IVs: • Active • A variable that is actually manipulated by the researcher • Methods of training, form of reinforcement, type of nutritional supplement • Attribute • Preexisting attribute that cannot be manipulated • Gender, race, age, or grade level… • Comparison groups can be formed

  21. Dependent Variables (DV) • Expected to change as a result of the treatment • Not under the control of the researcher(s) • IV  affects  DV

  22. IVs Exercise Diet Medicine(s) Drugs Motivation Programs Procedures Methods Techniques DVs Performance Fitness Learning Health Knowledge Behavior Common IV and DV examples

  23. Extraneous Variables • Error-producing variables (other than the IVs) that may impact the DV response. • A.k.a.: • Intervening variables • Modifying variables • Confounding variables

  24. Qualitative Ordinal Nominal Quantitative Discrete (scale) Continuous Independent variable (IV) Dependent variable (DV) Extraneous variable (EV) Overview of Variable Classifications


  26. Steps to Experimental Research • Identifying the research question or problem area • Initial review of literature • Distilling the question to a specific research problem • Continued review of literature • Formulation of hypotheses • Determining the basic research approach • Identifying the population and sample

  27. Steps to Experimental Research • Designing data collection plan • Selecting or developing specific data collection instruments or procedures • Choosing the method of data analysis • Implementing the research plan • Preparing the research report

  28. Experimental Research • Traditional type of research • Virtually the only type of research in science • To increase the body of knowledge in the discipline • To suggest what procedures should be followed • Always involves manipulation of the experimental unit • Human or animal participants

  29. Experimental Research • In Chapter 7 of the textbook (Baumgartner, Strong, and Hensley), there are 14 Steps of Experimental Research • We’re going to summarize them in 8 steps.

  30. Step 1 • Stating the research problem • Identify the problem to be researched • More global in nature • Identify the purpose statement • More specific

  31. Step 2 • Specify the independent variables (IVs) • Specify the levels for each IV • Characterizes the “dimensions” of the study

  32. Step 3 • Specify all the dependent variables (DVs)

  33. Step 4 • Determine the availability of measures for the potential DVs • Are they valid? • Are they reliable?

  34. Step 5 • State all the hypotheses • Research hypothesis • Based on previous research • Based on theoretical outcomes • Unbiased • Null hypothesis • Alternative hypothesis

  35. Step 6 • Design the experiment • Very time consuming • Considerable planning • Day-to-day, hour-to-hour conduct of the study

  36. Step 7 • Conduct a pilot study • See what needs to be tweaked • Time for the investigator to get used to the timing of the protocol, etc.

  37. Step 8 • Conduct the study as planned • Analyze the data • Report the results