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Research Methods
391
| Term | Definition |
|---|---|
| describe an academic discipline? | Learned societies, with bodies of knowledge printed in academic journals. |
| explain how kinesiology is interdisciplinary? | Kinesiology is interdisciplinary because it includes many other areas of study such as psychology, biology, anatomy, nutrition, etc. |
| describe the components of the field of kinesiology? | The Discipline (researchers) inform the professionals (practioners). |
| explain what it means to be an evidence-based professional? | They use the knowledge from their discipline to inform their practice. |
| describe what an operational definition is and provide an example. | A priori definition given to a word, concept or measure. |
| Descriptive stats | used when there is no intention to generalize beyond group. Look at something within that group and only within that group. |
| Inferential stats | used when you want to generalize the results to a larger population. Using a group to establish stats representing a larger group. |
| Quantitative research | uses the scientific method, presented in numbers & THE truth (only one) is out there. |
| Qualitative research | Does not use the scientific method, data presented in themes, stories, etc. Multiple truths. |
| Applied research | answers an immediate practical problem (immediate answer), and often applies the findings of basic research. |
| Basic research | motivated by intellectual curiosity. Essential for the development of theory. |
| Independent Variable (IV) | Manipulated or controlled. |
| Dependant Variable (DV) | Outcome measure. |
| Extraneous Variable (EX) | a variable that could affect the IV or DV & is not controlled by the researcher. |
| Explain what a literature review is using research language? | A summary of research that has been done in a specific field, and what research should be done next. |
| Nominal Data | numbers assigned to names. |
| Ordinal Data | Rank ordering. |
| Absolute Data | when number is made to whole unit. Ex cannot have 10.2 people. |
| Interval Data | no absolute zero point. Numbers have value and differences although the ratios are different. Ex 10 degrees is not 2 times as hot as 5 degrees. |
| Ratio Data | Has an absolute zero point, differences can be quantified |
| What is necessary in order to make valid statistical inferences from research with participants? | Random sampling. |
| Explain why random sampling considered the “gold standard” for generating a representative sample? | Because each person of the population of interest is equally likely to be selected. |
| Explain what a random sample is? | Is a impartial process that results in an unbiased sample of a population. |
| Explain why a representative sample allows for statistical inference | Because it is a mirror of the population of interest for external validity. |
| Describe external validity | is the ability to use the results of a study in other conditions or settings, the generalization of the study. |
| Explain why a representative sample contributes to external validity? | A representative sample mirrors the population of interest which then allows for the findings of a study to have external validity because it is a good representation of the generalized population. |
| Explain how volunteers and convenience samples introduce bias? | People who volunteer are different than the general population. |
| Explain non-respondent bias | People who do not respond are different from those who respond. |
| Explain ‘validity’ as it relates to a measure | Measures what it purports to measure. |
| Explain ‘reliability’ as it relates to a measure | The consistency of a measure. Required before establishing validity. |
| Explain what is meant by the ‘sensitivity of a measure’ | the degree of small differences that can be detected. Ex using a mm skinfold caliper vs using a .2 mm skinfold caliper. Or using a ruler in cm would be less sensitive than using a ruler in mm. |
| Explain why valid measures are critical in scientific research | Valid measures are critical because if the measurement is not valid than the information it is providing for the research is also going to be wrong. |
| Can a measure be reliable and not valid? | Yes a measure can be reliable without being valid because the results can be repeatable but they may not be correct. |
| Can a measure be valid if it is not reliable? | No because if it’s not reliable it cannot be measuring what it’s supposed to measure. |
| Scientific Methods Step 1. | Define and delimit the problem |
| Scientific Methods Step 2. | Form a hypothesis |
| Scientific Methods Step 3. | Develop a research plan |
| Scientific Methods Step 4. | Collect and analyze data |
| Scientific Methods Step 5. | Interpret the results |
| Scientific Methods Step 6. | Repeat the findings |
| Two ways we have searched for answers | Traditions - wives tales we believe because it has always been that way Authority - Mom/Dad ideals |
| The Mean | the average of a distribution of scores. 5-15 Would make it 10(5) |
| The Median | The most frequent score. 4,5,6,6,6,7,8 = 6 |
| The Mode | The distance between endpoints. 3,4,5,7,8,9 9-3 = 6. 6 |
| Standard Deviation | Large SD = more variability Small SD = less variability |
| Characteristics of Scientific Research 1 | Systematic - steps are followed in a specific sequence. Logical - procedures used should lead to conclusions drawn. |
| Characteristics of Scientific Research 2 | Empirical - Evidence (data) collected in experiments. Reductive - Data used to establish general relationships, reducing info down to make research accurate. |
| Characteristics of Scientific Research 3 | Replicable - Process is recorded and reported so that findings and procedures can be tested again. |
| Purposes of conducting a Lit Review 1 | Find out what has and hasn't been done in an area of reasearch. Narrow/focus your research. |
| Purposes of conducting a Lit Review 2 | Develop Hypothesis. Develop methods - participants, measures, procedures etc. |
| Steps of a Lit Review 1 | Identify a topic. Consult/read secondary sources. |
| Steps of a Lit Review 2 | Refine topic/question. Determine keywords and locate primary sources. |
| Steps of a Lit Review 3 | Read & record literature (annotate). Write the lit review. |
| Internal Validity | Overall quality of the research. Confidence that the IV is responsible for the change in the outcome or DV |
| Why is it important to know the scale of measurement? | because it in part determines the selecting the correct statistic. |
| There is a difference between fat and healthy people and veggies consumed | Hypothesis |
| There is no different between veggie consumption among fat and healthy people | Null Hypothesis |
| define significance | the possibility that an effect happened by chance and not be the IV. IF P value is greater than .05 we accept the null |
| Effect Size | Mean1 - Mean2 / the bigger SD |
| Level 5 Evidence | Lowest level - opinions of experienced individuals in a field. |
| Level 4 Evidence | Descriptive Studies - cross sectional designs, case studies. |
| Level 3 Evidence | Experimental Studies - uncontrolled longitudinal, quasi, or epidemological studies |
| Level 2 Evidence | Controlled longitudinal studies. |
| Level 1 Evidence | Gold Standard - Large randomized controlled trials. |
| Explain of the levels of evidence make us better consumers? | They allow us to judge information given to us by the media and friends by rating the evidence of the information. Gives us an idea of the validity of the information. |
| What is an randomized controlled trial? | A way of grouping participants by allowing each member of a population an equal chance of being randomized into each group of the study. Controls for threats to both internal and external validity. |
| What is the purpose of Experimental Research? | To establish cause and effect, show that the intervention (IV) is responsible for the outcome. |
| The three criteria for cause and effect | 1. Cause precedes effect 2. Cause & effect are correlated 3. Correlation above cannot be explained by another variable |
| Explain the difference between True experimental research and Quasi | True randomly assigns participants to treatment and control, while quasi does not |
| What is inter-rater reliability? | the measure for different researchers to agree upon a result of a measure. Ex both researchers receive similar results from a measure giving it a high degree of inter-rater |
| Explain the trade off of external and internal validity? | If a study has high internal it controls for things outside of the research and is reductive, which in turn decreases external validity because the research is less like real life limiting generalization. |
| Threats to internal validity | Maturation, History, Repeated Testing, Experimental Mortality and Selection Maturation. |
| Maturation | Does growth, learning or maturation influence the DV? Children, older pop and long term studies. Control - Randomization and control groups. |
| History | Are things happening outside the study effecting the study that may influence the DV? Control - Randomization and control groups. |
| Repeated Testing | Does repeated testing influence the testing performance (learning effect)? Control - Randomization, control groups, multiple baseline assessments & including participants experienced with the test. |
| Experimental Mortality | Have participants differentially dropped out of the treatment or control group, and is there something different about these ppl? Control - Large sample sizes and pilot studies |
| Selection Maturation | Are participants improving because of the passage of time? Control - Randomization & control groups |
| Threats to external validity 1: Reactive or interactive effect of testing | Pre testing may make participants more sensitive to the treatment, they make be more inclined to getting a good result. Control - use a control group and representative sample. |
| Threats to external validity 2: Multiple-treatment interferences | One treatment may influence the next treatment. Control - randomization of treatments, design, and have a representative sample. |
| What do control variables control for? | They control for threats to internal validity, and if they aren't controlled the variable that may impact results is called an extraneous variable. |
| What is the difference between pure descriptive research and survey research? | Pure descriptive uses objective measures to measure characteristics of a group, while survey relies on self-reported subjective measures. |
| Strengths of Pure and Survey Research | Easier to obtain large samples, and data can be gathered relatively quickly |
| Weaknesses of Pure and Survey Research | Relies on self reports (subjective data), which introduces bias. |
| Subjective Measures and Bias | Recall bias - not able to remember, or recall something correctly. Response Bias - respondents provide desired answers. Both impact validity. |
| Recall bias example | Asking someone what their diet was like when they were a kid, they may not be able to remember. |
| Response bias example | Asking someone what their diet was like when they were a kid, and them giving you positive answers because they don't want you to view them poorly. |
| Descriptive Research | Has no IV, many DVs and describes why things are. |
| National College Health Assessment (NCHA) | A notable survey in PA |
| Questionaires: The Delphi Method | procedures for reaching consensus, using experts and several rounds. |
| Questionaires: The Personal Interview | More adaptable and versatile, observing responsibles = insight, and better return rates. |
| Questionaires: Other forms | telephone interview - less expensive, easy to reach ppl, work from central location. Normative sruveys - growth charts, fitness norms. |
| Guidelines for a Questionaire | Do no start with threatening questions, create short qs, avoid negative words, consider length of questionaire, and consider categorical variables. |
| Case Study | Describes one case in depth, represents other cases, utilizes objective, subjective and qualitative data. |
| Correlation Research | Collects DVs that may relate, examine the relationship, one criterion is that the cause and effect is related to the variables. |
| Job Analysis Research | Describes working conditions, skills needed, physical attributes. |
| Developmental Research | Changing behaviour across lifespan. Ex Longitudinal or cross sectional design. |
| Observational Research | Observe and record behaviours, can be done in authentic setting, mostly objective data, eliminates recall and response bias. |
| Longitudinal Design | Strength is same participants over time. Weaknesses expensive, time consuming, participant losses, and repeated exposure to test items. |
| Cross-sectional Design | Strength are multiple age groups at same time, and quick/less expensive. Weaknesses cohort problem - are we sure the different ages are similar pop and did they have different exposures. |
| Case-control Studies | Retrospective looking back. Strengths are efficient in terms of time and money, and can test multiple exposures for a disease outcome. Weaknesses are recall bias, looking back for cause is flawed, and difficult to have an representative population. |
| Cohort Studies | Prospective looks to the future. Strengths are good for examining rare exposures, can examine multiple effects of a single exposure. Weaknesses are Expensive, and bad for examining rare outcomes. |
| Explain why case-control studies have a low level of evidence | Things like recall bias, not having randomization, unable to control for all extraneous variables, and looking for cause after effect threaten the internal validity. Randomized controlled trials can control for these so it has a higher lvl of evidence. |
| Explain why cohort studies have a low level of evidence | Can't control for many threats to internal validity due to the fact you are observing/waiting for something to occur, no intervention, findings are strong inferences but not exact, also experimental mortality. |
| Experimental Mortality causes | threats to both internal and external validity |
| How could doing a survey with your parents about teen pregnancy influence the data? | The person might only tell their parents information they want to hear which is response bias. |
| How could doing a survey in person with ppl about veggie consumption influence the data? | They may overestimate their consumption of veggies because they don't want the interviewer to think badly about them. Response Bias. |
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