Category: Kinesiology

For this assignment, you will learn as much as you can about your desired profession (this should be something related to kinesiology such as personal trainer, strength coach, physical therapist, occupational therapist, sports coach, sports nutritionist, etc). If you aren’t sure exactly what profession you would like to pursue, choose one of your interests, perhaps the one that you think about the most. You will produce a written market analysis of your desired profession. Your work should be substantive and should use factual resources to back your statements. This is not an assignment that is opinion based. This is a project that should be based upon your actual findings through your research, with evidence to support as necessary. Think of it as not only your personal inquiry into the field, but also as your factual, unbiased presentation to prospects of the field.

Here the instructions from my teacher for that assignment
Assignment Content
Question Article EvaluationRequirementsFind the article listed below to use for your evaluation
Evaluations must be in proper APA format and uploaded as a PDF
Use good grammar and writing mechanics
Include the following information in your analysis:
Background Information – history of the problem, gap in the research, purpose of the study, and hypothesis
The study design
Number of subjects
Demographics of the subjects
Inclusion and exclusion criteria
Duration of the data collection
IV
DV
The outcome measures for the DV
How could the information be used to a potential client
How this information applies to an SES profession
ArticleMaenhourt, A.G., Mahieu, N.N., De Muynck, M., De Wilde, L.F., & Cools, A.M. (2013). Does adding heavy load eccentric training to rehabilitation of patients with unilateral subacromial impingement result in better outcome? A randomized controlled trial. Knee Surgery, Sports Traumatology, Arthroscopy, 21(5), 1158-1167 below the materials from my clas that can be helpful with that article VariablesIn the Sports and Exercise Science discipline, the study design of choice is typically randomized controlled trials or some experimental design variation. There will be more explanation of the experimental study designs in Chapter 5. Variable as and adjective is defined as “able or apt to vary” or “subject to variation or changes” (Merriam-Webster, 2024). Therefore, in research you are looking for the things that change. Simple Research Design PrinciplesIn a VERY simplified way research is like this equation X + Y = changes in Z. X = young, healthy college students
Y = strength training program
Z = increased strength measured by a 1 rep max
So in our VERY simplified design, we take young, healthy college students and have them work out with an experimental strength training program. Half of them go to a group that does their usual daily activities. The other group will get your strength program. At the end, you compare the two groups to see if the changes in strength were better with those in your training program. So, there are a couple of things that will change or are variable in this example. The first one is the treatment. The treatment will potentially cause variation to occur in the participants. The second variable are changes that occur in the participants – so their strength. In experimental research, we see the variables as they relate to a cause and effect relationship. The variables that cause (strength training) the effect (increased strength, measured by a 1 RM). Independent VariablesIndependent variable (IV) is the variable that the researcher changes or manipulates. The researcher controls this variable. It is independent of other variables in the study (it is not influenced by anything but the researcher), so it is called the independent variable. Dependent VariablesDependent variables are effected by the independent variable. They are dependent upon the IV to change. These variables are measured by the researcher. You may see the DV referred to as outcomes. A quality research study will have chosen appropriate DV to establish the cause and effect relationship of the IV and DV. If we take the example above with our strength training program, we wouldn’t use range of motion (ROM) testing to determine the effectiveness of our strength training program because ROM assessments are not a good measure of strength in this example. Disablement ModelDisablement Models allow practitioners to look beyond a person’s disease or health condition and determine how that disease affected their daily lives. This guides treatment decision-making for practioners. WHO Disablement ModelThe most used Disablement Model used currently is the World Health Organization (WHO) Model. The WHO’s International Classification of Function, Disability, and Health (ICF) starts with the disease or health condition and then looks at how different domains (body function and structure, activity, and participation) are affected by that health condition. Body function and structure domain refers to the normal physiological processes in our body – that include organ function or musculoskeletal function. Activity and Participation are the next 2 domains. They may seem similar but are slightly different in the context of the ICF Model. Activity is the performance of a task such as eating, and participation is “involvement in life situations” (Jette, 2016). An example would be activity is eating and going out to a restaurant is the participation. If a person’s body functions, activity, or participation is restricted due to the health condition, this is referred to as an impairment. The contextual factors, environmental and personal, refer to how these two factors can effect their limitations or disabilities from the Health Condition. What type of environment do they live – alone, with other people; athletics participation – these are just a few examples. Personal factors could be anything about the person from age, race, ethnicity, employment, or coping skills. Any of these may hinder or help their function.What Does This Have to do With Outcomes? A disablement model helps guide research and practice by looking the person not the disease process. Yes, it is important to see changes in body functions such as strength when a patient is weak, however, the patient doesn’t see it that way. Patients/clients look through a lens of what they cannot do at home or in society which is more important that what we want as practitioners. As you are looking at research, the outcomes that are used to measure changes because of an experimental treatment will be looked at for the changes in body function, of course, but did they also look at the changes of the whole person?Outcome MeasuresReminder from IV and DVs. DVs are also known as the outcomes. DVs, or outcomes, are effected by the IV. If our IV is a strength training program and our DV is improved strength, how do we know that the strength changed? We have to have a measurement tool, outcome measure, to test the strength change. Types of Outcome MeasuresSports and Exercise Science encompasses a complex subject around health. “Health” is has different aspects that can be measured in very different ways. The meanings of the measurements may be very important to the clinician, but that same measurement tool may not mean much to the patient/client. Some may be important to both. It is important to look at the outcome measure to make sure the measure is an adequate indicator of is important to you, but more importantly, your patient/client. Some measurement tools may fit into more than one category.Disease-OrientedAs indicated by the name, disease-oriented outcome measures focus on the disease, or the Health Condition, activity, participation, or body structure/function of the ICF Model. It provides information on the progression of the disease process. These types of measures may not be of much importance to the patient/client. These outcome measures are more important for the clinician. Examples:blood pressure
bone density
range of motion (ROM)
strength
imaging studies
Patient-Oriented Evidence that Matters (POEM)POEM puts the focus on the patient’s health status and how that health condition effects their health status. Examples of outcome measures: quality of life
morbidity
mortality
Clinician-Based OutcomesClinician-based outcomes are performed by the clinician. These outcomes are evaluating the client’s response to the treatment that is being provided. These outcome measures typically evaluate functional limitations and impairments. These outcome measures are often measurements that can be classified as disease-oriented outcomes. Examples: ROM
strength
Patient-Based OutcomesPatient-based outcomes are usually surveys or questionnaires that the patient completes themselves. Since the patient/client are completing these the following items need to be considered: Readability: measures should be written at an average of an 8th grade level of reading
Time to complete: The time to fill out and score the survey should not take an excessive amount of time. Both your time and the time of your patient/client is important.
Disease-Specific OutcomesDisease specific outcomes are outcome measurements that are based on the perceived affect of the disease on the patient’s life. These outcome measures may be specific to a region in the body or a disease process. Examples include: Arthritis Impact Measurement Scale (AIMS): not body segment specific. Global rating of the effect of arthritis on function
Western Ontario Shoulder Instability Questionnaire (WOSI): shoulder and pathology specific
Region-Specific OutcomesThese outcomes assess the patient/clients perception of the disease process on function at a specific region of the body. Examples: WOSI
Oswestry Low Back Pain Disability Questionnaire
Disabilities of the Arm, Shoulder, and Hand Scoring System (DASH)
Dimension-Specific Outcomes”Health” incorporates different dimensions to make up the overall “health” of a person. Dimension-specific measures are meant to examine any one of those dimensions. Examples: McGill Pain Questionnaire
Beck Depression Inventory
Generic OutcomesAll the previous outcomes discussed have a tie-in to a specific context. Sometimes a specific measurement cannot be used to compare across different types of diseases or pathologies. A generic outcome measure can be used to assess health status and compare across different disease processes.Example: Short Form 36 (SF-36)
Global Rating of ChangeGlobal ratings of change assessments examine the patient’s perception of improvement over time. A clinician would determine the patient’s perception by asking them about a particular aspect, such as pain, weekly. The patient/client are provided with a scale for them to rate their change. Summary ScalesSummary scales only have 1-2 questions that ask about the patient/client’s health status of function. ExampleGeneral Household Survey
How Does This Apply to Research Methods? As a consumer of evidence, you need to be aware of the different types of outcomes are. In a good research question, PICO is used. The “O” in PICO is outcomes. The outcome that you have generated in your research question need to be reflected in the research you find and plan to apply. DataAs a general rule, I try not to talk about math. I’m just not a fan. Unfortunately for all of us, we do have to talk a little math…Nominal DataNominal data is just data that is put into a category. Nothing about the data can be manipulated. The data in each category can be counted.Examples:Breeds of dogs
Nationalities
Ordinal DataThis data is data that has a value but the numerical value has no value other than a rank vs the other data points.Examples:Pain scales from 0-10
Questionnaires with “Likert scales” (agree, disagree, neither agree or disagree, etc.)
Interval DataInterval data is “on a scale of measurement in which the intervals between points on the scale are fixed and equal” (Arnold & Schilling, 2017, p. 71). Interval scale values can be subtracted. Using the example of temperature scales listed below – if it is 60 degrees in Oklahoma City and 75 degrees in Lawton, there is a 15 degree difference between the two temperatures.Example:Fahrenheit and Celsius scales
Ratio DataRatio data is characterized by a scale with an absolute zero. With an absolute zero, calculations of comparison can be made.Examples:range of motion of right arm vs. left arm
blood pressure
Measures of Central TendencyMean, median, mode. Oh my!
ModeMode is the number (value) that occurs most often in a set of data points.Example:What is the most frequently thrown pitch by the other team’s pitcher?
MedianMedian in the data point that is in the middle of the set of values.Example:What is the median income of the NIL deals of your athletes? (usually accompanied by some kind of scale)
MeanMean is the most common of the three measures. Mean is the average value of all the data points. The mean can be misleading due to the presence of outliers that can skew the mean.Example:What is the average height of your basketball players?
VarianceMeasures of central tendency are useful, but it doesn’t give us all the information about the data set especially when there are outliers. Variance refers to the “variability of a group of scores around the group mean” (Arnold & Schilling, 2017, p. 75).Standard deviation provides an “average of scores around a group mean” (Arnold & Schilling, 2017, p. 75). This will be a common statistical measurement found in the research we review. When we are looking at a change to occur in our data because of an experimental treatment, the change can result from the experimental treatment OR it could be due to random error. A standard deviation of ±1 means that 68% of the data points will lay in that range. A standard deviation of ±2 means that 95% of the data points will lay in that range.
Confidence IntervalsAnother important statistical measure that you will find in exercise science literature is a confidence interval. In articles you will often see a confidence interval noted at CI95. A confidence interval indicates the level of confidence that the true value lies within a range of numbers. At CI95 , the confidence interval means that we are 95% confident the true score lies within the range of numbers that is provided.
ReliabilityIn the things we use to function in every day life, we expect them to be reliable. Whether its the alarm clock going off at the correct time each morning or the instrument panels on our car so we make it to work without running out of gas, on a flat tire, or without a speeding ticket. Reliability is an important aspect in the outcome measurements we used to determine true changes.
What Is Reliability?Let’s take one of the examples above – tire pressure. The air pressure in our tires should be at a recommended PSI (pounds per square inch). Many cars have a gauge on the instrument panel to read the PSI, but there are manual ways using an aptly named, tire pressure gauge.Let’s take the OG version of taking a tire pressure. In a perfect world, if I have 37 PSI in my tire, the tire pressure gauge should provide me with 37 PSI on the gauge. If I repeat the measure, a few minutes later and the tire pressure is still 37 PSI, the gauge should read 37 PSI. And, if I repeat this measure a third time with the tire having 37 PSI, the gauge should still read, you guessed it 37 PSI.So reliability is the ability of a measuring tool to measure to provide the relatively same score repeatedly when there is no true change in the true value. Reliability is the tool’s repeatability or “the measure’s ability to remain unchanged in the absence of real change” (Arnold & Schilling, 2017, p. 80). In other words, reliability is the precision of the measuring device.Types of ReliabilityThere are different types of reliability that need to be discussed. What if there is more than one person measuring? Not everything can be that exact all the time, right? What if it doesn’t make sense to measure the same thing after 2 minutes? Not to worry. There are different types of reliability for that.Test-Retest ReliabilityThis type of reliability is when there are repeated measures done at different time points. An instrument that can repeat the same score over a short or long time period to reflect a true change in score is ideal. If I use my tire gauge in the manner discussed above, or if I test my tire pressure today and then again next week, my tire pressure gauge should still give me a precise PSI value based on the true PSI in my tire.When there is little time between the repeated measures, this is referred to as intrasession reliability. If there is a longer period of time between the measurements, it is termed intersession reliability.How do you know how often to repeat your measures? Typically, the standard of care will dictate how often is appropriate for re-measurement. For example, physical therapists will measure a patient on their initial visit, and then again 6 weeks later.Intrarater vs. Interrater ReliabilityReliability also involves the number of testers using the measuring device. In the example above using the tire pressure gauge, it was only measure by one person. When there is only one person performing the measurement, it is referred to as intrarater reliability.If there is more than one person performing the measurement, it is known as interrater reliability. This is often seen at rehabilitation clinics to ensure that everyone is measuring the range of motion reliably.Internal ConsistencyIn research there is quantitative data and qualitative data. Quantitative data is something directly measurable that we can put a value on – range of motion, temperature, blood pressure, heart rate, etc.However, there are somethings that are just as important. If you remember back to our discussion on outcome measures, you must take into account the things that matter to a patient/client. Sometimes those things, like quality of life, cannot be directly measured. Researchers have to utilize surveys and questionnaires to ascertain that kind of information.Internal consistency is used to establish reliability of individual questions on a questionnaire or survey to establish consistency.Random ErrorIn a perfect world, when a repeated measurement is taken, the true value should be given every time. However, that is not always the case. The provided values may be clustered around the true score.In our tire pressure gauge example, I measure the tire pressure and get the following readings: 37.8, 36.9, and 38.2 PSI. This variability is referred to as random error. Some variability is expected because we do no live in a perfect world. Due to that fact, the size of the variability around the true score is important. A device that has a wide variability is not as reliable as one with small variability. This is referred to as the standard error of the measure.Example: Which Is More Reliable?The example below shows 10 trials of standing on a weight scale.In chart below, the true score body weight is 200 pounds (lbs). You can also notice that the variance surrounding the true score varies from 300 lbs to 170 lbs.
Identifying Reliability in an ArticleWithout going into too much detail and math regarding the calculations of reliability, I will quickly discuss ways to find the given reliability in a journal article.In the articles that we will utilize in this class, the outcome measures used in the study should be reliable and valid methods to assess a specific variable. The articles we look at (outside of this unit) will only report the statistics on the reliability and validity. You can find that In the methods section of an article.Indicators of reliability in an article would be the following: Pearson correlation coefficient or an interclass correlation coefficient (ICC). Most commonly it will be the ICC listed in parenthesis with a numerical value after the listed outcome measure. It will be a value between 0 and 1, with 1 being the most reliable and 0 being the least.
ValidityHow do we know a device’s data is actually giving us the correct data? Is it truly measuring what we want? Validity seeks to establish these concepts in an outcome measure.What Is Validity?Whereas reliability seeks to establish the precision of the device, validity ensures the device is measuring what it is supposed to measure. In essence, it is establishing the accuracy of the measure.Still not sure? Here is a little example involving ACL tears (its also provided in your textbook). What is the most accurate way to tell if someone has torn their ACL? A little spoiler alert…it’s not an MRI. The most accurate way to determine if someone has torn their ACL is to visualize the ACL by cutting someone open surgically. However, there are risks involved in surgery – infection, getting an unnecessary surgery when the ACL is intact just to name a couple. Wouldn’t it be nice if there was something a little less invasive to diagnose an ACL tear?What about an MRI, you ask? If there is a chance that my ACL is not torn, claustrophobia aside, I think I would want to have an MRI rather than surgery. In this scenario, the gold standard measure is the orthopedic surgery to visualize the ACL. To establish validity, an outcome measure must be compared against the gold standard to determine if the outcome is just as accurate as the OG device.So how did the experts determine the MRI could be an acceptable alternative to surgery to detect an ACL tear? The experts used the fancy math (statistics) to compare the correct diagnosis between the two options. The MRI showed it was similarly accurate as an orthopedist, so an MRI is done instead of surgery to determine if there is an ACL tear.Types of ValidityJust like reliability, there are different types of validity.Face ValidityFace validity is the most basic form of validity. It is also the weakest link of all the types of validity, mostly because it is subjective. Face validity is basically taking something at face value. Does it look good enough to measure strength? Okay, let’s roll with it.Criterion ValidityCriterion validity is where one outcome measure is compared against another similar outcome measure. The example provided above with the MRI vs. the orthopedic surgeon is an example of criterion validity.Concurrent ValidityConcurrent validity is a form of criterion validity. The example provided above with the MRI vs. the orthopedic surgeon is an example of concurrent validity.Predictive validityPredictive validity is a type of validity that determines the accuracy of a measure to predict future outcomes. There are several outcome measures that can fall into this category. Many outcomes that assess individuals for having an increased risk of some disease, disorder, or event would have predictive validity. Testing for the BRCA gene and risk of development of breast cancer is an example.Construct ValidityHow do you measure something like quality of life? There isn’t a meter that will register your quality of life by scanning it across your forehead. To measure something quantitative (a construct) into qualitative data, a measure would utilize construct validity. Usually sometime of survey is used to ask a variety of questions to estimate quality of life. Construct validity would establish the accuracy of that questionnaire in assessing that construct.*More of construct validity will be discussed in the Experimental Research Module.External ValidityRemember validity relates to the accuracy of the outcome measure in the data being given, but also when using evidence-based practice, we are applying research to our current practicing situation. External validity is, to an extent, if the outcome measure is accurate for our practice situation. Is it the right setting, clientele, equipment, etc.?Internal ValidityDuring the discussion on variables, I gave you the simplistic research equation: X + Y = changes in Z. X = young, healthy college students
Y = strength training program
Z = increased strength measured by a 1 rep max
Internal validity examines whether or not the the change we were expecting to happen was due to the program and not anything else.*More of external and internal validity will be discussed in the Experimental Research Module.BiasJust because an instrument is reliable, it does not mean it is valid. Reliability is if each time we used the instrument are we getting relatively the same score. Validity is the accuracy of the outcome, so how well the instrument is estimating the true score. How on target is the instrument from the true score?Let’s look at an example:Here is the picture from the Reliability lesson. We’ve already established that the measure is reliable because of the precision of the repeated measures.Now let’s look at this example:
This scale appears to have had something go awry. Is it reliable, yes? It’s measurements are fairly precise with little variability between the repeated measures. However, it is valid? No, it is not because it is overestimating the true score. It is not accurately estimating the true score.Anytime an instrument overestimates or underestimates the true score, there is bias that is occurring.

Here the instructions from my teacher for that assignment
Assignment Content
Question Article EvaluationRequirementsFind the article listed below to use for your evaluation
Evaluations must be in proper APA format and uploaded as a PDF
Use good grammar and writing mechanics
Include the following information in your analysis:
Background Information – history of the problem, gap in the research, purpose of the study, and hypothesis
The study design
Number of subjects
Demographics of the subjects
Inclusion and exclusion criteria
Duration of the data collection
IV
DV
The outcome measures for the DV
How could the information be used to a potential client
How this information applies to an SES profession
ArticleMaenhourt, A.G., Mahieu, N.N., De Muynck, M., De Wilde, L.F., & Cools, A.M. (2013). Does adding heavy load eccentric training to rehabilitation of patients with unilateral subacromial impingement result in better outcome? A randomized controlled trial. Knee Surgery, Sports Traumatology, Arthroscopy, 21(5), 1158-1167 below the materials from my clas that can be helpful with that article VariablesIn the Sports and Exercise Science discipline, the study design of choice is typically randomized controlled trials or some experimental design variation. There will be more explanation of the experimental study designs in Chapter 5. Variable as and adjective is defined as “able or apt to vary” or “subject to variation or changes” (Merriam-Webster, 2024). Therefore, in research you are looking for the things that change. Simple Research Design PrinciplesIn a VERY simplified way research is like this equation X + Y = changes in Z. X = young, healthy college students
Y = strength training program
Z = increased strength measured by a 1 rep max
So in our VERY simplified design, we take young, healthy college students and have them work out with an experimental strength training program. Half of them go to a group that does their usual daily activities. The other group will get your strength program. At the end, you compare the two groups to see if the changes in strength were better with those in your training program. So, there are a couple of things that will change or are variable in this example. The first one is the treatment. The treatment will potentially cause variation to occur in the participants. The second variable are changes that occur in the participants – so their strength. In experimental research, we see the variables as they relate to a cause and effect relationship. The variables that cause (strength training) the effect (increased strength, measured by a 1 RM). Independent VariablesIndependent variable (IV) is the variable that the researcher changes or manipulates. The researcher controls this variable. It is independent of other variables in the study (it is not influenced by anything but the researcher), so it is called the independent variable. Dependent VariablesDependent variables are effected by the independent variable. They are dependent upon the IV to change. These variables are measured by the researcher. You may see the DV referred to as outcomes. A quality research study will have chosen appropriate DV to establish the cause and effect relationship of the IV and DV. If we take the example above with our strength training program, we wouldn’t use range of motion (ROM) testing to determine the effectiveness of our strength training program because ROM assessments are not a good measure of strength in this example. Disablement ModelDisablement Models allow practitioners to look beyond a person’s disease or health condition and determine how that disease affected their daily lives. This guides treatment decision-making for practioners. WHO Disablement ModelThe most used Disablement Model used currently is the World Health Organization (WHO) Model. The WHO’s International Classification of Function, Disability, and Health (ICF) starts with the disease or health condition and then looks at how different domains (body function and structure, activity, and participation) are affected by that health condition. Body function and structure domain refers to the normal physiological processes in our body – that include organ function or musculoskeletal function. Activity and Participation are the next 2 domains. They may seem similar but are slightly different in the context of the ICF Model. Activity is the performance of a task such as eating, and participation is “involvement in life situations” (Jette, 2016). An example would be activity is eating and going out to a restaurant is the participation. If a person’s body functions, activity, or participation is restricted due to the health condition, this is referred to as an impairment. The contextual factors, environmental and personal, refer to how these two factors can effect their limitations or disabilities from the Health Condition. What type of environment do they live – alone, with other people; athletics participation – these are just a few examples. Personal factors could be anything about the person from age, race, ethnicity, employment, or coping skills. Any of these may hinder or help their function.What Does This Have to do With Outcomes? A disablement model helps guide research and practice by looking the person not the disease process. Yes, it is important to see changes in body functions such as strength when a patient is weak, however, the patient doesn’t see it that way. Patients/clients look through a lens of what they cannot do at home or in society which is more important that what we want as practitioners. As you are looking at research, the outcomes that are used to measure changes because of an experimental treatment will be looked at for the changes in body function, of course, but did they also look at the changes of the whole person?Outcome MeasuresReminder from IV and DVs. DVs are also known as the outcomes. DVs, or outcomes, are effected by the IV. If our IV is a strength training program and our DV is improved strength, how do we know that the strength changed? We have to have a measurement tool, outcome measure, to test the strength change. Types of Outcome MeasuresSports and Exercise Science encompasses a complex subject around health. “Health” is has different aspects that can be measured in very different ways. The meanings of the measurements may be very important to the clinician, but that same measurement tool may not mean much to the patient/client. Some may be important to both. It is important to look at the outcome measure to make sure the measure is an adequate indicator of is important to you, but more importantly, your patient/client. Some measurement tools may fit into more than one category.Disease-OrientedAs indicated by the name, disease-oriented outcome measures focus on the disease, or the Health Condition, activity, participation, or body structure/function of the ICF Model. It provides information on the progression of the disease process. These types of measures may not be of much importance to the patient/client. These outcome measures are more important for the clinician. Examples:blood pressure
bone density
range of motion (ROM)
strength
imaging studies
Patient-Oriented Evidence that Matters (POEM)POEM puts the focus on the patient’s health status and how that health condition effects their health status. Examples of outcome measures: quality of life
morbidity
mortality
Clinician-Based OutcomesClinician-based outcomes are performed by the clinician. These outcomes are evaluating the client’s response to the treatment that is being provided. These outcome measures typically evaluate functional limitations and impairments. These outcome measures are often measurements that can be classified as disease-oriented outcomes. Examples: ROM
strength
Patient-Based OutcomesPatient-based outcomes are usually surveys or questionnaires that the patient completes themselves. Since the patient/client are completing these the following items need to be considered: Readability: measures should be written at an average of an 8th grade level of reading
Time to complete: The time to fill out and score the survey should not take an excessive amount of time. Both your time and the time of your patient/client is important.
Disease-Specific OutcomesDisease specific outcomes are outcome measurements that are based on the perceived affect of the disease on the patient’s life. These outcome measures may be specific to a region in the body or a disease process. Examples include: Arthritis Impact Measurement Scale (AIMS): not body segment specific. Global rating of the effect of arthritis on function
Western Ontario Shoulder Instability Questionnaire (WOSI): shoulder and pathology specific
Region-Specific OutcomesThese outcomes assess the patient/clients perception of the disease process on function at a specific region of the body. Examples: WOSI
Oswestry Low Back Pain Disability Questionnaire
Disabilities of the Arm, Shoulder, and Hand Scoring System (DASH)
Dimension-Specific Outcomes”Health” incorporates different dimensions to make up the overall “health” of a person. Dimension-specific measures are meant to examine any one of those dimensions. Examples: McGill Pain Questionnaire
Beck Depression Inventory
Generic OutcomesAll the previous outcomes discussed have a tie-in to a specific context. Sometimes a specific measurement cannot be used to compare across different types of diseases or pathologies. A generic outcome measure can be used to assess health status and compare across different disease processes.Example: Short Form 36 (SF-36)
Global Rating of ChangeGlobal ratings of change assessments examine the patient’s perception of improvement over time. A clinician would determine the patient’s perception by asking them about a particular aspect, such as pain, weekly. The patient/client are provided with a scale for them to rate their change. Summary ScalesSummary scales only have 1-2 questions that ask about the patient/client’s health status of function. ExampleGeneral Household Survey
How Does This Apply to Research Methods? As a consumer of evidence, you need to be aware of the different types of outcomes are. In a good research question, PICO is used. The “O” in PICO is outcomes. The outcome that you have generated in your research question need to be reflected in the research you find and plan to apply. DataAs a general rule, I try not to talk about math. I’m just not a fan. Unfortunately for all of us, we do have to talk a little math…Nominal DataNominal data is just data that is put into a category. Nothing about the data can be manipulated. The data in each category can be counted.Examples:Breeds of dogs
Nationalities
Ordinal DataThis data is data that has a value but the numerical value has no value other than a rank vs the other data points.Examples:Pain scales from 0-10
Questionnaires with “Likert scales” (agree, disagree, neither agree or disagree, etc.)
Interval DataInterval data is “on a scale of measurement in which the intervals between points on the scale are fixed and equal” (Arnold & Schilling, 2017, p. 71). Interval scale values can be subtracted. Using the example of temperature scales listed below – if it is 60 degrees in Oklahoma City and 75 degrees in Lawton, there is a 15 degree difference between the two temperatures.Example:Fahrenheit and Celsius scales
Ratio DataRatio data is characterized by a scale with an absolute zero. With an absolute zero, calculations of comparison can be made.Examples:range of motion of right arm vs. left arm
blood pressure
Measures of Central TendencyMean, median, mode. Oh my!
ModeMode is the number (value) that occurs most often in a set of data points.Example:What is the most frequently thrown pitch by the other team’s pitcher?
MedianMedian in the data point that is in the middle of the set of values.Example:What is the median income of the NIL deals of your athletes? (usually accompanied by some kind of scale)
MeanMean is the most common of the three measures. Mean is the average value of all the data points. The mean can be misleading due to the presence of outliers that can skew the mean.Example:What is the average height of your basketball players?
VarianceMeasures of central tendency are useful, but it doesn’t give us all the information about the data set especially when there are outliers. Variance refers to the “variability of a group of scores around the group mean” (Arnold & Schilling, 2017, p. 75).Standard deviation provides an “average of scores around a group mean” (Arnold & Schilling, 2017, p. 75). This will be a common statistical measurement found in the research we review. When we are looking at a change to occur in our data because of an experimental treatment, the change can result from the experimental treatment OR it could be due to random error. A standard deviation of ±1 means that 68% of the data points will lay in that range. A standard deviation of ±2 means that 95% of the data points will lay in that range.
Confidence IntervalsAnother important statistical measure that you will find in exercise science literature is a confidence interval. In articles you will often see a confidence interval noted at CI95. A confidence interval indicates the level of confidence that the true value lies within a range of numbers. At CI95 , the confidence interval means that we are 95% confident the true score lies within the range of numbers that is provided.
ReliabilityIn the things we use to function in every day life, we expect them to be reliable. Whether its the alarm clock going off at the correct time each morning or the instrument panels on our car so we make it to work without running out of gas, on a flat tire, or without a speeding ticket. Reliability is an important aspect in the outcome measurements we used to determine true changes.
What Is Reliability?Let’s take one of the examples above – tire pressure. The air pressure in our tires should be at a recommended PSI (pounds per square inch). Many cars have a gauge on the instrument panel to read the PSI, but there are manual ways using an aptly named, tire pressure gauge.Let’s take the OG version of taking a tire pressure. In a perfect world, if I have 37 PSI in my tire, the tire pressure gauge should provide me with 37 PSI on the gauge. If I repeat the measure, a few minutes later and the tire pressure is still 37 PSI, the gauge should read 37 PSI. And, if I repeat this measure a third time with the tire having 37 PSI, the gauge should still read, you guessed it 37 PSI.So reliability is the ability of a measuring tool to measure to provide the relatively same score repeatedly when there is no true change in the true value. Reliability is the tool’s repeatability or “the measure’s ability to remain unchanged in the absence of real change” (Arnold & Schilling, 2017, p. 80). In other words, reliability is the precision of the measuring device.Types of ReliabilityThere are different types of reliability that need to be discussed. What if there is more than one person measuring? Not everything can be that exact all the time, right? What if it doesn’t make sense to measure the same thing after 2 minutes? Not to worry. There are different types of reliability for that.Test-Retest ReliabilityThis type of reliability is when there are repeated measures done at different time points. An instrument that can repeat the same score over a short or long time period to reflect a true change in score is ideal. If I use my tire gauge in the manner discussed above, or if I test my tire pressure today and then again next week, my tire pressure gauge should still give me a precise PSI value based on the true PSI in my tire.When there is little time between the repeated measures, this is referred to as intrasession reliability. If there is a longer period of time between the measurements, it is termed intersession reliability.How do you know how often to repeat your measures? Typically, the standard of care will dictate how often is appropriate for re-measurement. For example, physical therapists will measure a patient on their initial visit, and then again 6 weeks later.Intrarater vs. Interrater ReliabilityReliability also involves the number of testers using the measuring device. In the example above using the tire pressure gauge, it was only measure by one person. When there is only one person performing the measurement, it is referred to as intrarater reliability.If there is more than one person performing the measurement, it is known as interrater reliability. This is often seen at rehabilitation clinics to ensure that everyone is measuring the range of motion reliably.Internal ConsistencyIn research there is quantitative data and qualitative data. Quantitative data is something directly measurable that we can put a value on – range of motion, temperature, blood pressure, heart rate, etc.However, there are somethings that are just as important. If you remember back to our discussion on outcome measures, you must take into account the things that matter to a patient/client. Sometimes those things, like quality of life, cannot be directly measured. Researchers have to utilize surveys and questionnaires to ascertain that kind of information.Internal consistency is used to establish reliability of individual questions on a questionnaire or survey to establish consistency.Random ErrorIn a perfect world, when a repeated measurement is taken, the true value should be given every time. However, that is not always the case. The provided values may be clustered around the true score.In our tire pressure gauge example, I measure the tire pressure and get the following readings: 37.8, 36.9, and 38.2 PSI. This variability is referred to as random error. Some variability is expected because we do no live in a perfect world. Due to that fact, the size of the variability around the true score is important. A device that has a wide variability is not as reliable as one with small variability. This is referred to as the standard error of the measure.Example: Which Is More Reliable?The example below shows 10 trials of standing on a weight scale.In chart below, the true score body weight is 200 pounds (lbs). You can also notice that the variance surrounding the true score varies from 300 lbs to 170 lbs.
Identifying Reliability in an ArticleWithout going into too much detail and math regarding the calculations of reliability, I will quickly discuss ways to find the given reliability in a journal article.In the articles that we will utilize in this class, the outcome measures used in the study should be reliable and valid methods to assess a specific variable. The articles we look at (outside of this unit) will only report the statistics on the reliability and validity. You can find that In the methods section of an article.Indicators of reliability in an article would be the following: Pearson correlation coefficient or an interclass correlation coefficient (ICC). Most commonly it will be the ICC listed in parenthesis with a numerical value after the listed outcome measure. It will be a value between 0 and 1, with 1 being the most reliable and 0 being the least.
ValidityHow do we know a device’s data is actually giving us the correct data? Is it truly measuring what we want? Validity seeks to establish these concepts in an outcome measure.What Is Validity?Whereas reliability seeks to establish the precision of the device, validity ensures the device is measuring what it is supposed to measure. In essence, it is establishing the accuracy of the measure.Still not sure? Here is a little example involving ACL tears (its also provided in your textbook). What is the most accurate way to tell if someone has torn their ACL? A little spoiler alert…it’s not an MRI. The most accurate way to determine if someone has torn their ACL is to visualize the ACL by cutting someone open surgically. However, there are risks involved in surgery – infection, getting an unnecessary surgery when the ACL is intact just to name a couple. Wouldn’t it be nice if there was something a little less invasive to diagnose an ACL tear?What about an MRI, you ask? If there is a chance that my ACL is not torn, claustrophobia aside, I think I would want to have an MRI rather than surgery. In this scenario, the gold standard measure is the orthopedic surgery to visualize the ACL. To establish validity, an outcome measure must be compared against the gold standard to determine if the outcome is just as accurate as the OG device.So how did the experts determine the MRI could be an acceptable alternative to surgery to detect an ACL tear? The experts used the fancy math (statistics) to compare the correct diagnosis between the two options. The MRI showed it was similarly accurate as an orthopedist, so an MRI is done instead of surgery to determine if there is an ACL tear.Types of ValidityJust like reliability, there are different types of validity.Face ValidityFace validity is the most basic form of validity. It is also the weakest link of all the types of validity, mostly because it is subjective. Face validity is basically taking something at face value. Does it look good enough to measure strength? Okay, let’s roll with it.Criterion ValidityCriterion validity is where one outcome measure is compared against another similar outcome measure. The example provided above with the MRI vs. the orthopedic surgeon is an example of criterion validity.Concurrent ValidityConcurrent validity is a form of criterion validity. The example provided above with the MRI vs. the orthopedic surgeon is an example of concurrent validity.Predictive validityPredictive validity is a type of validity that determines the accuracy of a measure to predict future outcomes. There are several outcome measures that can fall into this category. Many outcomes that assess individuals for having an increased risk of some disease, disorder, or event would have predictive validity. Testing for the BRCA gene and risk of development of breast cancer is an example.Construct ValidityHow do you measure something like quality of life? There isn’t a meter that will register your quality of life by scanning it across your forehead. To measure something quantitative (a construct) into qualitative data, a measure would utilize construct validity. Usually sometime of survey is used to ask a variety of questions to estimate quality of life. Construct validity would establish the accuracy of that questionnaire in assessing that construct.*More of construct validity will be discussed in the Experimental Research Module.External ValidityRemember validity relates to the accuracy of the outcome measure in the data being given, but also when using evidence-based practice, we are applying research to our current practicing situation. External validity is, to an extent, if the outcome measure is accurate for our practice situation. Is it the right setting, clientele, equipment, etc.?Internal ValidityDuring the discussion on variables, I gave you the simplistic research equation: X + Y = changes in Z. X = young, healthy college students
Y = strength training program
Z = increased strength measured by a 1 rep max
Internal validity examines whether or not the the change we were expecting to happen was due to the program and not anything else.*More of external and internal validity will be discussed in the Experimental Research Module.BiasJust because an instrument is reliable, it does not mean it is valid. Reliability is if each time we used the instrument are we getting relatively the same score. Validity is the accuracy of the outcome, so how well the instrument is estimating the true score. How on target is the instrument from the true score?Let’s look at an example:Here is the picture from the Reliability lesson. We’ve already established that the measure is reliable because of the precision of the repeated measures.Now let’s look at this example:
This scale appears to have had something go awry. Is it reliable, yes? It’s measurements are fairly precise with little variability between the repeated measures. However, it is valid? No, it is not because it is overestimating the true score. It is not accurately estimating the true score.Anytime an instrument overestimates or underestimates the true score, there is bias that is occurring.

Here the instructions from my teacher for that assignment
Assignment Content
Question Article EvaluationRequirementsFind the article listed below to use for your evaluation
Evaluations must be in proper APA format and uploaded as a PDF
Use good grammar and writing mechanics
Include the following information in your analysis:
Background Information – history of the problem, gap in the research, purpose of the study, and hypothesis
The study design
Number of subjects
Demographics of the subjects
Inclusion and exclusion criteria
Duration of the data collection
IV
DV
The outcome measures for the DV
How could the information be used to a potential client
How this information applies to an SES profession
ArticleMaenhourt, A.G., Mahieu, N.N., De Muynck, M., De Wilde, L.F., & Cools, A.M. (2013). Does adding heavy load eccentric training to rehabilitation of patients with unilateral subacromial impingement result in better outcome? A randomized controlled trial. Knee Surgery, Sports Traumatology, Arthroscopy, 21(5), 1158-1167 below the materials from my clas that can be helpful with that article VariablesIn the Sports and Exercise Science discipline, the study design of choice is typically randomized controlled trials or some experimental design variation. There will be more explanation of the experimental study designs in Chapter 5. Variable as and adjective is defined as “able or apt to vary” or “subject to variation or changes” (Merriam-Webster, 2024). Therefore, in research you are looking for the things that change. Simple Research Design PrinciplesIn a VERY simplified way research is like this equation X + Y = changes in Z. X = young, healthy college students
Y = strength training program
Z = increased strength measured by a 1 rep max
So in our VERY simplified design, we take young, healthy college students and have them work out with an experimental strength training program. Half of them go to a group that does their usual daily activities. The other group will get your strength program. At the end, you compare the two groups to see if the changes in strength were better with those in your training program. So, there are a couple of things that will change or are variable in this example. The first one is the treatment. The treatment will potentially cause variation to occur in the participants. The second variable are changes that occur in the participants – so their strength. In experimental research, we see the variables as they relate to a cause and effect relationship. The variables that cause (strength training) the effect (increased strength, measured by a 1 RM). Independent VariablesIndependent variable (IV) is the variable that the researcher changes or manipulates. The researcher controls this variable. It is independent of other variables in the study (it is not influenced by anything but the researcher), so it is called the independent variable. Dependent VariablesDependent variables are effected by the independent variable. They are dependent upon the IV to change. These variables are measured by the researcher. You may see the DV referred to as outcomes. A quality research study will have chosen appropriate DV to establish the cause and effect relationship of the IV and DV. If we take the example above with our strength training program, we wouldn’t use range of motion (ROM) testing to determine the effectiveness of our strength training program because ROM assessments are not a good measure of strength in this example. Disablement ModelDisablement Models allow practitioners to look beyond a person’s disease or health condition and determine how that disease affected their daily lives. This guides treatment decision-making for practioners. WHO Disablement ModelThe most used Disablement Model used currently is the World Health Organization (WHO) Model. The WHO’s International Classification of Function, Disability, and Health (ICF) starts with the disease or health condition and then looks at how different domains (body function and structure, activity, and participation) are affected by that health condition. Body function and structure domain refers to the normal physiological processes in our body – that include organ function or musculoskeletal function. Activity and Participation are the next 2 domains. They may seem similar but are slightly different in the context of the ICF Model. Activity is the performance of a task such as eating, and participation is “involvement in life situations” (Jette, 2016). An example would be activity is eating and going out to a restaurant is the participation. If a person’s body functions, activity, or participation is restricted due to the health condition, this is referred to as an impairment. The contextual factors, environmental and personal, refer to how these two factors can effect their limitations or disabilities from the Health Condition. What type of environment do they live – alone, with other people; athletics participation – these are just a few examples. Personal factors could be anything about the person from age, race, ethnicity, employment, or coping skills. Any of these may hinder or help their function.What Does This Have to do With Outcomes? A disablement model helps guide research and practice by looking the person not the disease process. Yes, it is important to see changes in body functions such as strength when a patient is weak, however, the patient doesn’t see it that way. Patients/clients look through a lens of what they cannot do at home or in society which is more important that what we want as practitioners. As you are looking at research, the outcomes that are used to measure changes because of an experimental treatment will be looked at for the changes in body function, of course, but did they also look at the changes of the whole person?Outcome MeasuresReminder from IV and DVs. DVs are also known as the outcomes. DVs, or outcomes, are effected by the IV. If our IV is a strength training program and our DV is improved strength, how do we know that the strength changed? We have to have a measurement tool, outcome measure, to test the strength change. Types of Outcome MeasuresSports and Exercise Science encompasses a complex subject around health. “Health” is has different aspects that can be measured in very different ways. The meanings of the measurements may be very important to the clinician, but that same measurement tool may not mean much to the patient/client. Some may be important to both. It is important to look at the outcome measure to make sure the measure is an adequate indicator of is important to you, but more importantly, your patient/client. Some measurement tools may fit into more than one category.Disease-OrientedAs indicated by the name, disease-oriented outcome measures focus on the disease, or the Health Condition, activity, participation, or body structure/function of the ICF Model. It provides information on the progression of the disease process. These types of measures may not be of much importance to the patient/client. These outcome measures are more important for the clinician. Examples:blood pressure
bone density
range of motion (ROM)
strength
imaging studies
Patient-Oriented Evidence that Matters (POEM)POEM puts the focus on the patient’s health status and how that health condition effects their health status. Examples of outcome measures: quality of life
morbidity
mortality
Clinician-Based OutcomesClinician-based outcomes are performed by the clinician. These outcomes are evaluating the client’s response to the treatment that is being provided. These outcome measures typically evaluate functional limitations and impairments. These outcome measures are often measurements that can be classified as disease-oriented outcomes. Examples: ROM
strength
Patient-Based OutcomesPatient-based outcomes are usually surveys or questionnaires that the patient completes themselves. Since the patient/client are completing these the following items need to be considered: Readability: measures should be written at an average of an 8th grade level of reading
Time to complete: The time to fill out and score the survey should not take an excessive amount of time. Both your time and the time of your patient/client is important.
Disease-Specific OutcomesDisease specific outcomes are outcome measurements that are based on the perceived affect of the disease on the patient’s life. These outcome measures may be specific to a region in the body or a disease process. Examples include: Arthritis Impact Measurement Scale (AIMS): not body segment specific. Global rating of the effect of arthritis on function
Western Ontario Shoulder Instability Questionnaire (WOSI): shoulder and pathology specific
Region-Specific OutcomesThese outcomes assess the patient/clients perception of the disease process on function at a specific region of the body. Examples: WOSI
Oswestry Low Back Pain Disability Questionnaire
Disabilities of the Arm, Shoulder, and Hand Scoring System (DASH)
Dimension-Specific Outcomes”Health” incorporates different dimensions to make up the overall “health” of a person. Dimension-specific measures are meant to examine any one of those dimensions. Examples: McGill Pain Questionnaire
Beck Depression Inventory
Generic OutcomesAll the previous outcomes discussed have a tie-in to a specific context. Sometimes a specific measurement cannot be used to compare across different types of diseases or pathologies. A generic outcome measure can be used to assess health status and compare across different disease processes.Example: Short Form 36 (SF-36)
Global Rating of ChangeGlobal ratings of change assessments examine the patient’s perception of improvement over time. A clinician would determine the patient’s perception by asking them about a particular aspect, such as pain, weekly. The patient/client are provided with a scale for them to rate their change. Summary ScalesSummary scales only have 1-2 questions that ask about the patient/client’s health status of function. ExampleGeneral Household Survey
How Does This Apply to Research Methods? As a consumer of evidence, you need to be aware of the different types of outcomes are. In a good research question, PICO is used. The “O” in PICO is outcomes. The outcome that you have generated in your research question need to be reflected in the research you find and plan to apply. DataAs a general rule, I try not to talk about math. I’m just not a fan. Unfortunately for all of us, we do have to talk a little math…Nominal DataNominal data is just data that is put into a category. Nothing about the data can be manipulated. The data in each category can be counted.Examples:Breeds of dogs
Nationalities
Ordinal DataThis data is data that has a value but the numerical value has no value other than a rank vs the other data points.Examples:Pain scales from 0-10
Questionnaires with “Likert scales” (agree, disagree, neither agree or disagree, etc.)
Interval DataInterval data is “on a scale of measurement in which the intervals between points on the scale are fixed and equal” (Arnold & Schilling, 2017, p. 71). Interval scale values can be subtracted. Using the example of temperature scales listed below – if it is 60 degrees in Oklahoma City and 75 degrees in Lawton, there is a 15 degree difference between the two temperatures.Example:Fahrenheit and Celsius scales
Ratio DataRatio data is characterized by a scale with an absolute zero. With an absolute zero, calculations of comparison can be made.Examples:range of motion of right arm vs. left arm
blood pressure
Measures of Central TendencyMean, median, mode. Oh my!
ModeMode is the number (value) that occurs most often in a set of data points.Example:What is the most frequently thrown pitch by the other team’s pitcher?
MedianMedian in the data point that is in the middle of the set of values.Example:What is the median income of the NIL deals of your athletes? (usually accompanied by some kind of scale)
MeanMean is the most common of the three measures. Mean is the average value of all the data points. The mean can be misleading due to the presence of outliers that can skew the mean.Example:What is the average height of your basketball players?
VarianceMeasures of central tendency are useful, but it doesn’t give us all the information about the data set especially when there are outliers. Variance refers to the “variability of a group of scores around the group mean” (Arnold & Schilling, 2017, p. 75).Standard deviation provides an “average of scores around a group mean” (Arnold & Schilling, 2017, p. 75). This will be a common statistical measurement found in the research we review. When we are looking at a change to occur in our data because of an experimental treatment, the change can result from the experimental treatment OR it could be due to random error. A standard deviation of ±1 means that 68% of the data points will lay in that range. A standard deviation of ±2 means that 95% of the data points will lay in that range.
Confidence IntervalsAnother important statistical measure that you will find in exercise science literature is a confidence interval. In articles you will often see a confidence interval noted at CI95. A confidence interval indicates the level of confidence that the true value lies within a range of numbers. At CI95 , the confidence interval means that we are 95% confident the true score lies within the range of numbers that is provided.
ReliabilityIn the things we use to function in every day life, we expect them to be reliable. Whether its the alarm clock going off at the correct time each morning or the instrument panels on our car so we make it to work without running out of gas, on a flat tire, or without a speeding ticket. Reliability is an important aspect in the outcome measurements we used to determine true changes.
What Is Reliability?Let’s take one of the examples above – tire pressure. The air pressure in our tires should be at a recommended PSI (pounds per square inch). Many cars have a gauge on the instrument panel to read the PSI, but there are manual ways using an aptly named, tire pressure gauge.Let’s take the OG version of taking a tire pressure. In a perfect world, if I have 37 PSI in my tire, the tire pressure gauge should provide me with 37 PSI on the gauge. If I repeat the measure, a few minutes later and the tire pressure is still 37 PSI, the gauge should read 37 PSI. And, if I repeat this measure a third time with the tire having 37 PSI, the gauge should still read, you guessed it 37 PSI.So reliability is the ability of a measuring tool to measure to provide the relatively same score repeatedly when there is no true change in the true value. Reliability is the tool’s repeatability or “the measure’s ability to remain unchanged in the absence of real change” (Arnold & Schilling, 2017, p. 80). In other words, reliability is the precision of the measuring device.Types of ReliabilityThere are different types of reliability that need to be discussed. What if there is more than one person measuring? Not everything can be that exact all the time, right? What if it doesn’t make sense to measure the same thing after 2 minutes? Not to worry. There are different types of reliability for that.Test-Retest ReliabilityThis type of reliability is when there are repeated measures done at different time points. An instrument that can repeat the same score over a short or long time period to reflect a true change in score is ideal. If I use my tire gauge in the manner discussed above, or if I test my tire pressure today and then again next week, my tire pressure gauge should still give me a precise PSI value based on the true PSI in my tire.When there is little time between the repeated measures, this is referred to as intrasession reliability. If there is a longer period of time between the measurements, it is termed intersession reliability.How do you know how often to repeat your measures? Typically, the standard of care will dictate how often is appropriate for re-measurement. For example, physical therapists will measure a patient on their initial visit, and then again 6 weeks later.Intrarater vs. Interrater ReliabilityReliability also involves the number of testers using the measuring device. In the example above using the tire pressure gauge, it was only measure by one person. When there is only one person performing the measurement, it is referred to as intrarater reliability.If there is more than one person performing the measurement, it is known as interrater reliability. This is often seen at rehabilitation clinics to ensure that everyone is measuring the range of motion reliably.Internal ConsistencyIn research there is quantitative data and qualitative data. Quantitative data is something directly measurable that we can put a value on – range of motion, temperature, blood pressure, heart rate, etc.However, there are somethings that are just as important. If you remember back to our discussion on outcome measures, you must take into account the things that matter to a patient/client. Sometimes those things, like quality of life, cannot be directly measured. Researchers have to utilize surveys and questionnaires to ascertain that kind of information.Internal consistency is used to establish reliability of individual questions on a questionnaire or survey to establish consistency.Random ErrorIn a perfect world, when a repeated measurement is taken, the true value should be given every time. However, that is not always the case. The provided values may be clustered around the true score.In our tire pressure gauge example, I measure the tire pressure and get the following readings: 37.8, 36.9, and 38.2 PSI. This variability is referred to as random error. Some variability is expected because we do no live in a perfect world. Due to that fact, the size of the variability around the true score is important. A device that has a wide variability is not as reliable as one with small variability. This is referred to as the standard error of the measure.Example: Which Is More Reliable?The example below shows 10 trials of standing on a weight scale.In chart below, the true score body weight is 200 pounds (lbs). You can also notice that the variance surrounding the true score varies from 300 lbs to 170 lbs.
Identifying Reliability in an ArticleWithout going into too much detail and math regarding the calculations of reliability, I will quickly discuss ways to find the given reliability in a journal article.In the articles that we will utilize in this class, the outcome measures used in the study should be reliable and valid methods to assess a specific variable. The articles we look at (outside of this unit) will only report the statistics on the reliability and validity. You can find that In the methods section of an article.Indicators of reliability in an article would be the following: Pearson correlation coefficient or an interclass correlation coefficient (ICC). Most commonly it will be the ICC listed in parenthesis with a numerical value after the listed outcome measure. It will be a value between 0 and 1, with 1 being the most reliable and 0 being the least.
ValidityHow do we know a device’s data is actually giving us the correct data? Is it truly measuring what we want? Validity seeks to establish these concepts in an outcome measure.What Is Validity?Whereas reliability seeks to establish the precision of the device, validity ensures the device is measuring what it is supposed to measure. In essence, it is establishing the accuracy of the measure.Still not sure? Here is a little example involving ACL tears (its also provided in your textbook). What is the most accurate way to tell if someone has torn their ACL? A little spoiler alert…it’s not an MRI. The most accurate way to determine if someone has torn their ACL is to visualize the ACL by cutting someone open surgically. However, there are risks involved in surgery – infection, getting an unnecessary surgery when the ACL is intact just to name a couple. Wouldn’t it be nice if there was something a little less invasive to diagnose an ACL tear?What about an MRI, you ask? If there is a chance that my ACL is not torn, claustrophobia aside, I think I would want to have an MRI rather than surgery. In this scenario, the gold standard measure is the orthopedic surgery to visualize the ACL. To establish validity, an outcome measure must be compared against the gold standard to determine if the outcome is just as accurate as the OG device.So how did the experts determine the MRI could be an acceptable alternative to surgery to detect an ACL tear? The experts used the fancy math (statistics) to compare the correct diagnosis between the two options. The MRI showed it was similarly accurate as an orthopedist, so an MRI is done instead of surgery to determine if there is an ACL tear.Types of ValidityJust like reliability, there are different types of validity.Face ValidityFace validity is the most basic form of validity. It is also the weakest link of all the types of validity, mostly because it is subjective. Face validity is basically taking something at face value. Does it look good enough to measure strength? Okay, let’s roll with it.Criterion ValidityCriterion validity is where one outcome measure is compared against another similar outcome measure. The example provided above with the MRI vs. the orthopedic surgeon is an example of criterion validity.Concurrent ValidityConcurrent validity is a form of criterion validity. The example provided above with the MRI vs. the orthopedic surgeon is an example of concurrent validity.Predictive validityPredictive validity is a type of validity that determines the accuracy of a measure to predict future outcomes. There are several outcome measures that can fall into this category. Many outcomes that assess individuals for having an increased risk of some disease, disorder, or event would have predictive validity. Testing for the BRCA gene and risk of development of breast cancer is an example.Construct ValidityHow do you measure something like quality of life? There isn’t a meter that will register your quality of life by scanning it across your forehead. To measure something quantitative (a construct) into qualitative data, a measure would utilize construct validity. Usually sometime of survey is used to ask a variety of questions to estimate quality of life. Construct validity would establish the accuracy of that questionnaire in assessing that construct.*More of construct validity will be discussed in the Experimental Research Module.External ValidityRemember validity relates to the accuracy of the outcome measure in the data being given, but also when using evidence-based practice, we are applying research to our current practicing situation. External validity is, to an extent, if the outcome measure is accurate for our practice situation. Is it the right setting, clientele, equipment, etc.?Internal ValidityDuring the discussion on variables, I gave you the simplistic research equation: X + Y = changes in Z. X = young, healthy college students
Y = strength training program
Z = increased strength measured by a 1 rep max
Internal validity examines whether or not the the change we were expecting to happen was due to the program and not anything else.*More of external and internal validity will be discussed in the Experimental Research Module.BiasJust because an instrument is reliable, it does not mean it is valid. Reliability is if each time we used the instrument are we getting relatively the same score. Validity is the accuracy of the outcome, so how well the instrument is estimating the true score. How on target is the instrument from the true score?Let’s look at an example:Here is the picture from the Reliability lesson. We’ve already established that the measure is reliable because of the precision of the repeated measures.Now let’s look at this example:
This scale appears to have had something go awry. Is it reliable, yes? It’s measurements are fairly precise with little variability between the repeated measures. However, it is valid? No, it is not because it is overestimating the true score. It is not accurately estimating the true score.Anytime an instrument overestimates or underestimates the true score, there is bias that is occurring.

Here the instructions from my teacher for that assignment
Assignment Content
Question Article EvaluationRequirementsFind the article listed below to use for your evaluation
Evaluations must be in proper APA format and uploaded as a PDF
Use good grammar and writing mechanics
Include the following information in your analysis:
Background Information – history of the problem, gap in the research, purpose of the study, and hypothesis
The study design
Number of subjects
Demographics of the subjects
Inclusion and exclusion criteria
Duration of the data collection
IV
DV
The outcome measures for the DV
How could the information be used to a potential client
How this information applies to an SES profession
ArticleMaenhourt, A.G., Mahieu, N.N., De Muynck, M., De Wilde, L.F., & Cools, A.M. (2013). Does adding heavy load eccentric training to rehabilitation of patients with unilateral subacromial impingement result in better outcome? A randomized controlled trial. Knee Surgery, Sports Traumatology, Arthroscopy, 21(5), 1158-1167 below the materials from my clas that can be helpful with that article VariablesIn the Sports and Exercise Science discipline, the study design of choice is typically randomized controlled trials or some experimental design variation. There will be more explanation of the experimental study designs in Chapter 5. Variable as and adjective is defined as “able or apt to vary” or “subject to variation or changes” (Merriam-Webster, 2024). Therefore, in research you are looking for the things that change. Simple Research Design PrinciplesIn a VERY simplified way research is like this equation X + Y = changes in Z. X = young, healthy college students
Y = strength training program
Z = increased strength measured by a 1 rep max
So in our VERY simplified design, we take young, healthy college students and have them work out with an experimental strength training program. Half of them go to a group that does their usual daily activities. The other group will get your strength program. At the end, you compare the two groups to see if the changes in strength were better with those in your training program. So, there are a couple of things that will change or are variable in this example. The first one is the treatment. The treatment will potentially cause variation to occur in the participants. The second variable are changes that occur in the participants – so their strength. In experimental research, we see the variables as they relate to a cause and effect relationship. The variables that cause (strength training) the effect (increased strength, measured by a 1 RM). Independent VariablesIndependent variable (IV) is the variable that the researcher changes or manipulates. The researcher controls this variable. It is independent of other variables in the study (it is not influenced by anything but the researcher), so it is called the independent variable. Dependent VariablesDependent variables are effected by the independent variable. They are dependent upon the IV to change. These variables are measured by the researcher. You may see the DV referred to as outcomes. A quality research study will have chosen appropriate DV to establish the cause and effect relationship of the IV and DV. If we take the example above with our strength training program, we wouldn’t use range of motion (ROM) testing to determine the effectiveness of our strength training program because ROM assessments are not a good measure of strength in this example. Disablement ModelDisablement Models allow practitioners to look beyond a person’s disease or health condition and determine how that disease affected their daily lives. This guides treatment decision-making for practioners. WHO Disablement ModelThe most used Disablement Model used currently is the World Health Organization (WHO) Model. The WHO’s International Classification of Function, Disability, and Health (ICF) starts with the disease or health condition and then looks at how different domains (body function and structure, activity, and participation) are affected by that health condition. Body function and structure domain refers to the normal physiological processes in our body – that include organ function or musculoskeletal function. Activity and Participation are the next 2 domains. They may seem similar but are slightly different in the context of the ICF Model. Activity is the performance of a task such as eating, and participation is “involvement in life situations” (Jette, 2016). An example would be activity is eating and going out to a restaurant is the participation. If a person’s body functions, activity, or participation is restricted due to the health condition, this is referred to as an impairment. The contextual factors, environmental and personal, refer to how these two factors can effect their limitations or disabilities from the Health Condition. What type of environment do they live – alone, with other people; athletics participation – these are just a few examples. Personal factors could be anything about the person from age, race, ethnicity, employment, or coping skills. Any of these may hinder or help their function.What Does This Have to do With Outcomes? A disablement model helps guide research and practice by looking the person not the disease process. Yes, it is important to see changes in body functions such as strength when a patient is weak, however, the patient doesn’t see it that way. Patients/clients look through a lens of what they cannot do at home or in society which is more important that what we want as practitioners. As you are looking at research, the outcomes that are used to measure changes because of an experimental treatment will be looked at for the changes in body function, of course, but did they also look at the changes of the whole person?Outcome MeasuresReminder from IV and DVs. DVs are also known as the outcomes. DVs, or outcomes, are effected by the IV. If our IV is a strength training program and our DV is improved strength, how do we know that the strength changed? We have to have a measurement tool, outcome measure, to test the strength change. Types of Outcome MeasuresSports and Exercise Science encompasses a complex subject around health. “Health” is has different aspects that can be measured in very different ways. The meanings of the measurements may be very important to the clinician, but that same measurement tool may not mean much to the patient/client. Some may be important to both. It is important to look at the outcome measure to make sure the measure is an adequate indicator of is important to you, but more importantly, your patient/client. Some measurement tools may fit into more than one category.Disease-OrientedAs indicated by the name, disease-oriented outcome measures focus on the disease, or the Health Condition, activity, participation, or body structure/function of the ICF Model. It provides information on the progression of the disease process. These types of measures may not be of much importance to the patient/client. These outcome measures are more important for the clinician. Examples:blood pressure
bone density
range of motion (ROM)
strength
imaging studies
Patient-Oriented Evidence that Matters (POEM)POEM puts the focus on the patient’s health status and how that health condition effects their health status. Examples of outcome measures: quality of life
morbidity
mortality
Clinician-Based OutcomesClinician-based outcomes are performed by the clinician. These outcomes are evaluating the client’s response to the treatment that is being provided. These outcome measures typically evaluate functional limitations and impairments. These outcome measures are often measurements that can be classified as disease-oriented outcomes. Examples: ROM
strength
Patient-Based OutcomesPatient-based outcomes are usually surveys or questionnaires that the patient completes themselves. Since the patient/client are completing these the following items need to be considered: Readability: measures should be written at an average of an 8th grade level of reading
Time to complete: The time to fill out and score the survey should not take an excessive amount of time. Both your time and the time of your patient/client is important.
Disease-Specific OutcomesDisease specific outcomes are outcome measurements that are based on the perceived affect of the disease on the patient’s life. These outcome measures may be specific to a region in the body or a disease process. Examples include: Arthritis Impact Measurement Scale (AIMS): not body segment specific. Global rating of the effect of arthritis on function
Western Ontario Shoulder Instability Questionnaire (WOSI): shoulder and pathology specific
Region-Specific OutcomesThese outcomes assess the patient/clients perception of the disease process on function at a specific region of the body. Examples: WOSI
Oswestry Low Back Pain Disability Questionnaire
Disabilities of the Arm, Shoulder, and Hand Scoring System (DASH)
Dimension-Specific Outcomes”Health” incorporates different dimensions to make up the overall “health” of a person. Dimension-specific measures are meant to examine any one of those dimensions. Examples: McGill Pain Questionnaire
Beck Depression Inventory
Generic OutcomesAll the previous outcomes discussed have a tie-in to a specific context. Sometimes a specific measurement cannot be used to compare across different types of diseases or pathologies. A generic outcome measure can be used to assess health status and compare across different disease processes.Example: Short Form 36 (SF-36)
Global Rating of ChangeGlobal ratings of change assessments examine the patient’s perception of improvement over time. A clinician would determine the patient’s perception by asking them about a particular aspect, such as pain, weekly. The patient/client are provided with a scale for them to rate their change. Summary ScalesSummary scales only have 1-2 questions that ask about the patient/client’s health status of function. ExampleGeneral Household Survey
How Does This Apply to Research Methods? As a consumer of evidence, you need to be aware of the different types of outcomes are. In a good research question, PICO is used. The “O” in PICO is outcomes. The outcome that you have generated in your research question need to be reflected in the research you find and plan to apply. DataAs a general rule, I try not to talk about math. I’m just not a fan. Unfortunately for all of us, we do have to talk a little math…Nominal DataNominal data is just data that is put into a category. Nothing about the data can be manipulated. The data in each category can be counted.Examples:Breeds of dogs
Nationalities
Ordinal DataThis data is data that has a value but the numerical value has no value other than a rank vs the other data points.Examples:Pain scales from 0-10
Questionnaires with “Likert scales” (agree, disagree, neither agree or disagree, etc.)
Interval DataInterval data is “on a scale of measurement in which the intervals between points on the scale are fixed and equal” (Arnold & Schilling, 2017, p. 71). Interval scale values can be subtracted. Using the example of temperature scales listed below – if it is 60 degrees in Oklahoma City and 75 degrees in Lawton, there is a 15 degree difference between the two temperatures.Example:Fahrenheit and Celsius scales
Ratio DataRatio data is characterized by a scale with an absolute zero. With an absolute zero, calculations of comparison can be made.Examples:range of motion of right arm vs. left arm
blood pressure
Measures of Central TendencyMean, median, mode. Oh my!
ModeMode is the number (value) that occurs most often in a set of data points.Example:What is the most frequently thrown pitch by the other team’s pitcher?
MedianMedian in the data point that is in the middle of the set of values.Example:What is the median income of the NIL deals of your athletes? (usually accompanied by some kind of scale)
MeanMean is the most common of the three measures. Mean is the average value of all the data points. The mean can be misleading due to the presence of outliers that can skew the mean.Example:What is the average height of your basketball players?
VarianceMeasures of central tendency are useful, but it doesn’t give us all the information about the data set especially when there are outliers. Variance refers to the “variability of a group of scores around the group mean” (Arnold & Schilling, 2017, p. 75).Standard deviation provides an “average of scores around a group mean” (Arnold & Schilling, 2017, p. 75). This will be a common statistical measurement found in the research we review. When we are looking at a change to occur in our data because of an experimental treatment, the change can result from the experimental treatment OR it could be due to random error. A standard deviation of ±1 means that 68% of the data points will lay in that range. A standard deviation of ±2 means that 95% of the data points will lay in that range.
Confidence IntervalsAnother important statistical measure that you will find in exercise science literature is a confidence interval. In articles you will often see a confidence interval noted at CI95. A confidence interval indicates the level of confidence that the true value lies within a range of numbers. At CI95 , the confidence interval means that we are 95% confident the true score lies within the range of numbers that is provided.
ReliabilityIn the things we use to function in every day life, we expect them to be reliable. Whether its the alarm clock going off at the correct time each morning or the instrument panels on our car so we make it to work without running out of gas, on a flat tire, or without a speeding ticket. Reliability is an important aspect in the outcome measurements we used to determine true changes.
What Is Reliability?Let’s take one of the examples above – tire pressure. The air pressure in our tires should be at a recommended PSI (pounds per square inch). Many cars have a gauge on the instrument panel to read the PSI, but there are manual ways using an aptly named, tire pressure gauge.Let’s take the OG version of taking a tire pressure. In a perfect world, if I have 37 PSI in my tire, the tire pressure gauge should provide me with 37 PSI on the gauge. If I repeat the measure, a few minutes later and the tire pressure is still 37 PSI, the gauge should read 37 PSI. And, if I repeat this measure a third time with the tire having 37 PSI, the gauge should still read, you guessed it 37 PSI.So reliability is the ability of a measuring tool to measure to provide the relatively same score repeatedly when there is no true change in the true value. Reliability is the tool’s repeatability or “the measure’s ability to remain unchanged in the absence of real change” (Arnold & Schilling, 2017, p. 80). In other words, reliability is the precision of the measuring device.Types of ReliabilityThere are different types of reliability that need to be discussed. What if there is more than one person measuring? Not everything can be that exact all the time, right? What if it doesn’t make sense to measure the same thing after 2 minutes? Not to worry. There are different types of reliability for that.Test-Retest ReliabilityThis type of reliability is when there are repeated measures done at different time points. An instrument that can repeat the same score over a short or long time period to reflect a true change in score is ideal. If I use my tire gauge in the manner discussed above, or if I test my tire pressure today and then again next week, my tire pressure gauge should still give me a precise PSI value based on the true PSI in my tire.When there is little time between the repeated measures, this is referred to as intrasession reliability. If there is a longer period of time between the measurements, it is termed intersession reliability.How do you know how often to repeat your measures? Typically, the standard of care will dictate how often is appropriate for re-measurement. For example, physical therapists will measure a patient on their initial visit, and then again 6 weeks later.Intrarater vs. Interrater ReliabilityReliability also involves the number of testers using the measuring device. In the example above using the tire pressure gauge, it was only measure by one person. When there is only one person performing the measurement, it is referred to as intrarater reliability.If there is more than one person performing the measurement, it is known as interrater reliability. This is often seen at rehabilitation clinics to ensure that everyone is measuring the range of motion reliably.Internal ConsistencyIn research there is quantitative data and qualitative data. Quantitative data is something directly measurable that we can put a value on – range of motion, temperature, blood pressure, heart rate, etc.However, there are somethings that are just as important. If you remember back to our discussion on outcome measures, you must take into account the things that matter to a patient/client. Sometimes those things, like quality of life, cannot be directly measured. Researchers have to utilize surveys and questionnaires to ascertain that kind of information.Internal consistency is used to establish reliability of individual questions on a questionnaire or survey to establish consistency.Random ErrorIn a perfect world, when a repeated measurement is taken, the true value should be given every time. However, that is not always the case. The provided values may be clustered around the true score.In our tire pressure gauge example, I measure the tire pressure and get the following readings: 37.8, 36.9, and 38.2 PSI. This variability is referred to as random error. Some variability is expected because we do no live in a perfect world. Due to that fact, the size of the variability around the true score is important. A device that has a wide variability is not as reliable as one with small variability. This is referred to as the standard error of the measure.Example: Which Is More Reliable?The example below shows 10 trials of standing on a weight scale.In chart below, the true score body weight is 200 pounds (lbs). You can also notice that the variance surrounding the true score varies from 300 lbs to 170 lbs.
Identifying Reliability in an ArticleWithout going into too much detail and math regarding the calculations of reliability, I will quickly discuss ways to find the given reliability in a journal article.In the articles that we will utilize in this class, the outcome measures used in the study should be reliable and valid methods to assess a specific variable. The articles we look at (outside of this unit) will only report the statistics on the reliability and validity. You can find that In the methods section of an article.Indicators of reliability in an article would be the following: Pearson correlation coefficient or an interclass correlation coefficient (ICC). Most commonly it will be the ICC listed in parenthesis with a numerical value after the listed outcome measure. It will be a value between 0 and 1, with 1 being the most reliable and 0 being the least.
ValidityHow do we know a device’s data is actually giving us the correct data? Is it truly measuring what we want? Validity seeks to establish these concepts in an outcome measure.What Is Validity?Whereas reliability seeks to establish the precision of the device, validity ensures the device is measuring what it is supposed to measure. In essence, it is establishing the accuracy of the measure.Still not sure? Here is a little example involving ACL tears (its also provided in your textbook). What is the most accurate way to tell if someone has torn their ACL? A little spoiler alert…it’s not an MRI. The most accurate way to determine if someone has torn their ACL is to visualize the ACL by cutting someone open surgically. However, there are risks involved in surgery – infection, getting an unnecessary surgery when the ACL is intact just to name a couple. Wouldn’t it be nice if there was something a little less invasive to diagnose an ACL tear?What about an MRI, you ask? If there is a chance that my ACL is not torn, claustrophobia aside, I think I would want to have an MRI rather than surgery. In this scenario, the gold standard measure is the orthopedic surgery to visualize the ACL. To establish validity, an outcome measure must be compared against the gold standard to determine if the outcome is just as accurate as the OG device.So how did the experts determine the MRI could be an acceptable alternative to surgery to detect an ACL tear? The experts used the fancy math (statistics) to compare the correct diagnosis between the two options. The MRI showed it was similarly accurate as an orthopedist, so an MRI is done instead of surgery to determine if there is an ACL tear.Types of ValidityJust like reliability, there are different types of validity.Face ValidityFace validity is the most basic form of validity. It is also the weakest link of all the types of validity, mostly because it is subjective. Face validity is basically taking something at face value. Does it look good enough to measure strength? Okay, let’s roll with it.Criterion ValidityCriterion validity is where one outcome measure is compared against another similar outcome measure. The example provided above with the MRI vs. the orthopedic surgeon is an example of criterion validity.Concurrent ValidityConcurrent validity is a form of criterion validity. The example provided above with the MRI vs. the orthopedic surgeon is an example of concurrent validity.Predictive validityPredictive validity is a type of validity that determines the accuracy of a measure to predict future outcomes. There are several outcome measures that can fall into this category. Many outcomes that assess individuals for having an increased risk of some disease, disorder, or event would have predictive validity. Testing for the BRCA gene and risk of development of breast cancer is an example.Construct ValidityHow do you measure something like quality of life? There isn’t a meter that will register your quality of life by scanning it across your forehead. To measure something quantitative (a construct) into qualitative data, a measure would utilize construct validity. Usually sometime of survey is used to ask a variety of questions to estimate quality of life. Construct validity would establish the accuracy of that questionnaire in assessing that construct.*More of construct validity will be discussed in the Experimental Research Module.External ValidityRemember validity relates to the accuracy of the outcome measure in the data being given, but also when using evidence-based practice, we are applying research to our current practicing situation. External validity is, to an extent, if the outcome measure is accurate for our practice situation. Is it the right setting, clientele, equipment, etc.?Internal ValidityDuring the discussion on variables, I gave you the simplistic research equation: X + Y = changes in Z. X = young, healthy college students
Y = strength training program
Z = increased strength measured by a 1 rep max
Internal validity examines whether or not the the change we were expecting to happen was due to the program and not anything else.*More of external and internal validity will be discussed in the Experimental Research Module.BiasJust because an instrument is reliable, it does not mean it is valid. Reliability is if each time we used the instrument are we getting relatively the same score. Validity is the accuracy of the outcome, so how well the instrument is estimating the true score. How on target is the instrument from the true score?Let’s look at an example:Here is the picture from the Reliability lesson. We’ve already established that the measure is reliable because of the precision of the repeated measures.Now let’s look at this example:
This scale appears to have had something go awry. Is it reliable, yes? It’s measurements are fairly precise with little variability between the repeated measures. However, it is valid? No, it is not because it is overestimating the true score. It is not accurately estimating the true score.Anytime an instrument overestimates or underestimates the true score, there is bias that is occurring.

Here the instructions from my teacher for that assignment
Assignment Content
Question Article EvaluationRequirementsFind the article listed below to use for your evaluation
Evaluations must be in proper APA format and uploaded as a PDF
Use good grammar and writing mechanics
Include the following information in your analysis:
Background Information – history of the problem, gap in the research, purpose of the study, and hypothesis
The study design
Number of subjects
Demographics of the subjects
Inclusion and exclusion criteria
Duration of the data collection
IV
DV
The outcome measures for the DV
How could the information be used to a potential client
How this information applies to an SES profession
ArticleMaenhourt, A.G., Mahieu, N.N., De Muynck, M., De Wilde, L.F., & Cools, A.M. (2013). Does adding heavy load eccentric training to rehabilitation of patients with unilateral subacromial impingement result in better outcome? A randomized controlled trial. Knee Surgery, Sports Traumatology, Arthroscopy, 21(5), 1158-1167 below the materials from my clas that can be helpful with that article VariablesIn the Sports and Exercise Science discipline, the study design of choice is typically randomized controlled trials or some experimental design variation. There will be more explanation of the experimental study designs in Chapter 5. Variable as and adjective is defined as “able or apt to vary” or “subject to variation or changes” (Merriam-Webster, 2024). Therefore, in research you are looking for the things that change. Simple Research Design PrinciplesIn a VERY simplified way research is like this equation X + Y = changes in Z. X = young, healthy college students
Y = strength training program
Z = increased strength measured by a 1 rep max
So in our VERY simplified design, we take young, healthy college students and have them work out with an experimental strength training program. Half of them go to a group that does their usual daily activities. The other group will get your strength program. At the end, you compare the two groups to see if the changes in strength were better with those in your training program. So, there are a couple of things that will change or are variable in this example. The first one is the treatment. The treatment will potentially cause variation to occur in the participants. The second variable are changes that occur in the participants – so their strength. In experimental research, we see the variables as they relate to a cause and effect relationship. The variables that cause (strength training) the effect (increased strength, measured by a 1 RM). Independent VariablesIndependent variable (IV) is the variable that the researcher changes or manipulates. The researcher controls this variable. It is independent of other variables in the study (it is not influenced by anything but the researcher), so it is called the independent variable. Dependent VariablesDependent variables are effected by the independent variable. They are dependent upon the IV to change. These variables are measured by the researcher. You may see the DV referred to as outcomes. A quality research study will have chosen appropriate DV to establish the cause and effect relationship of the IV and DV. If we take the example above with our strength training program, we wouldn’t use range of motion (ROM) testing to determine the effectiveness of our strength training program because ROM assessments are not a good measure of strength in this example. Disablement ModelDisablement Models allow practitioners to look beyond a person’s disease or health condition and determine how that disease affected their daily lives. This guides treatment decision-making for practioners. WHO Disablement ModelThe most used Disablement Model used currently is the World Health Organization (WHO) Model. The WHO’s International Classification of Function, Disability, and Health (ICF) starts with the disease or health condition and then looks at how different domains (body function and structure, activity, and participation) are affected by that health condition. Body function and structure domain refers to the normal physiological processes in our body – that include organ function or musculoskeletal function. Activity and Participation are the next 2 domains. They may seem similar but are slightly different in the context of the ICF Model. Activity is the performance of a task such as eating, and participation is “involvement in life situations” (Jette, 2016). An example would be activity is eating and going out to a restaurant is the participation. If a person’s body functions, activity, or participation is restricted due to the health condition, this is referred to as an impairment. The contextual factors, environmental and personal, refer to how these two factors can effect their limitations or disabilities from the Health Condition. What type of environment do they live – alone, with other people; athletics participation – these are just a few examples. Personal factors could be anything about the person from age, race, ethnicity, employment, or coping skills. Any of these may hinder or help their function.What Does This Have to do With Outcomes? A disablement model helps guide research and practice by looking the person not the disease process. Yes, it is important to see changes in body functions such as strength when a patient is weak, however, the patient doesn’t see it that way. Patients/clients look through a lens of what they cannot do at home or in society which is more important that what we want as practitioners. As you are looking at research, the outcomes that are used to measure changes because of an experimental treatment will be looked at for the changes in body function, of course, but did they also look at the changes of the whole person?Outcome MeasuresReminder from IV and DVs. DVs are also known as the outcomes. DVs, or outcomes, are effected by the IV. If our IV is a strength training program and our DV is improved strength, how do we know that the strength changed? We have to have a measurement tool, outcome measure, to test the strength change. Types of Outcome MeasuresSports and Exercise Science encompasses a complex subject around health. “Health” is has different aspects that can be measured in very different ways. The meanings of the measurements may be very important to the clinician, but that same measurement tool may not mean much to the patient/client. Some may be important to both. It is important to look at the outcome measure to make sure the measure is an adequate indicator of is important to you, but more importantly, your patient/client. Some measurement tools may fit into more than one category.Disease-OrientedAs indicated by the name, disease-oriented outcome measures focus on the disease, or the Health Condition, activity, participation, or body structure/function of the ICF Model. It provides information on the progression of the disease process. These types of measures may not be of much importance to the patient/client. These outcome measures are more important for the clinician. Examples:blood pressure
bone density
range of motion (ROM)
strength
imaging studies
Patient-Oriented Evidence that Matters (POEM)POEM puts the focus on the patient’s health status and how that health condition effects their health status. Examples of outcome measures: quality of life
morbidity
mortality
Clinician-Based OutcomesClinician-based outcomes are performed by the clinician. These outcomes are evaluating the client’s response to the treatment that is being provided. These outcome measures typically evaluate functional limitations and impairments. These outcome measures are often measurements that can be classified as disease-oriented outcomes. Examples: ROM
strength
Patient-Based OutcomesPatient-based outcomes are usually surveys or questionnaires that the patient completes themselves. Since the patient/client are completing these the following items need to be considered: Readability: measures should be written at an average of an 8th grade level of reading
Time to complete: The time to fill out and score the survey should not take an excessive amount of time. Both your time and the time of your patient/client is important.
Disease-Specific OutcomesDisease specific outcomes are outcome measurements that are based on the perceived affect of the disease on the patient’s life. These outcome measures may be specific to a region in the body or a disease process. Examples include: Arthritis Impact Measurement Scale (AIMS): not body segment specific. Global rating of the effect of arthritis on function
Western Ontario Shoulder Instability Questionnaire (WOSI): shoulder and pathology specific
Region-Specific OutcomesThese outcomes assess the patient/clients perception of the disease process on function at a specific region of the body. Examples: WOSI
Oswestry Low Back Pain Disability Questionnaire
Disabilities of the Arm, Shoulder, and Hand Scoring System (DASH)
Dimension-Specific Outcomes”Health” incorporates different dimensions to make up the overall “health” of a person. Dimension-specific measures are meant to examine any one of those dimensions. Examples: McGill Pain Questionnaire
Beck Depression Inventory
Generic OutcomesAll the previous outcomes discussed have a tie-in to a specific context. Sometimes a specific measurement cannot be used to compare across different types of diseases or pathologies. A generic outcome measure can be used to assess health status and compare across different disease processes.Example: Short Form 36 (SF-36)
Global Rating of ChangeGlobal ratings of change assessments examine the patient’s perception of improvement over time. A clinician would determine the patient’s perception by asking them about a particular aspect, such as pain, weekly. The patient/client are provided with a scale for them to rate their change. Summary ScalesSummary scales only have 1-2 questions that ask about the patient/client’s health status of function. ExampleGeneral Household Survey
How Does This Apply to Research Methods? As a consumer of evidence, you need to be aware of the different types of outcomes are. In a good research question, PICO is used. The “O” in PICO is outcomes. The outcome that you have generated in your research question need to be reflected in the research you find and plan to apply. DataAs a general rule, I try not to talk about math. I’m just not a fan. Unfortunately for all of us, we do have to talk a little math…Nominal DataNominal data is just data that is put into a category. Nothing about the data can be manipulated. The data in each category can be counted.Examples:Breeds of dogs
Nationalities
Ordinal DataThis data is data that has a value but the numerical value has no value other than a rank vs the other data points.Examples:Pain scales from 0-10
Questionnaires with “Likert scales” (agree, disagree, neither agree or disagree, etc.)
Interval DataInterval data is “on a scale of measurement in which the intervals between points on the scale are fixed and equal” (Arnold & Schilling, 2017, p. 71). Interval scale values can be subtracted. Using the example of temperature scales listed below – if it is 60 degrees in Oklahoma City and 75 degrees in Lawton, there is a 15 degree difference between the two temperatures.Example:Fahrenheit and Celsius scales
Ratio DataRatio data is characterized by a scale with an absolute zero. With an absolute zero, calculations of comparison can be made.Examples:range of motion of right arm vs. left arm
blood pressure
Measures of Central TendencyMean, median, mode. Oh my!
ModeMode is the number (value) that occurs most often in a set of data points.Example:What is the most frequently thrown pitch by the other team’s pitcher?
MedianMedian in the data point that is in the middle of the set of values.Example:What is the median income of the NIL deals of your athletes? (usually accompanied by some kind of scale)
MeanMean is the most common of the three measures. Mean is the average value of all the data points. The mean can be misleading due to the presence of outliers that can skew the mean.Example:What is the average height of your basketball players?
VarianceMeasures of central tendency are useful, but it doesn’t give us all the information about the data set especially when there are outliers. Variance refers to the “variability of a group of scores around the group mean” (Arnold & Schilling, 2017, p. 75).Standard deviation provides an “average of scores around a group mean” (Arnold & Schilling, 2017, p. 75). This will be a common statistical measurement found in the research we review. When we are looking at a change to occur in our data because of an experimental treatment, the change can result from the experimental treatment OR it could be due to random error. A standard deviation of ±1 means that 68% of the data points will lay in that range. A standard deviation of ±2 means that 95% of the data points will lay in that range.
Confidence IntervalsAnother important statistical measure that you will find in exercise science literature is a confidence interval. In articles you will often see a confidence interval noted at CI95. A confidence interval indicates the level of confidence that the true value lies within a range of numbers. At CI95 , the confidence interval means that we are 95% confident the true score lies within the range of numbers that is provided.
ReliabilityIn the things we use to function in every day life, we expect them to be reliable. Whether its the alarm clock going off at the correct time each morning or the instrument panels on our car so we make it to work without running out of gas, on a flat tire, or without a speeding ticket. Reliability is an important aspect in the outcome measurements we used to determine true changes.
What Is Reliability?Let’s take one of the examples above – tire pressure. The air pressure in our tires should be at a recommended PSI (pounds per square inch). Many cars have a gauge on the instrument panel to read the PSI, but there are manual ways using an aptly named, tire pressure gauge.Let’s take the OG version of taking a tire pressure. In a perfect world, if I have 37 PSI in my tire, the tire pressure gauge should provide me with 37 PSI on the gauge. If I repeat the measure, a few minutes later and the tire pressure is still 37 PSI, the gauge should read 37 PSI. And, if I repeat this measure a third time with the tire having 37 PSI, the gauge should still read, you guessed it 37 PSI.So reliability is the ability of a measuring tool to measure to provide the relatively same score repeatedly when there is no true change in the true value. Reliability is the tool’s repeatability or “the measure’s ability to remain unchanged in the absence of real change” (Arnold & Schilling, 2017, p. 80). In other words, reliability is the precision of the measuring device.Types of ReliabilityThere are different types of reliability that need to be discussed. What if there is more than one person measuring? Not everything can be that exact all the time, right? What if it doesn’t make sense to measure the same thing after 2 minutes? Not to worry. There are different types of reliability for that.Test-Retest ReliabilityThis type of reliability is when there are repeated measures done at different time points. An instrument that can repeat the same score over a short or long time period to reflect a true change in score is ideal. If I use my tire gauge in the manner discussed above, or if I test my tire pressure today and then again next week, my tire pressure gauge should still give me a precise PSI value based on the true PSI in my tire.When there is little time between the repeated measures, this is referred to as intrasession reliability. If there is a longer period of time between the measurements, it is termed intersession reliability.How do you know how often to repeat your measures? Typically, the standard of care will dictate how often is appropriate for re-measurement. For example, physical therapists will measure a patient on their initial visit, and then again 6 weeks later.Intrarater vs. Interrater ReliabilityReliability also involves the number of testers using the measuring device. In the example above using the tire pressure gauge, it was only measure by one person. When there is only one person performing the measurement, it is referred to as intrarater reliability.If there is more than one person performing the measurement, it is known as interrater reliability. This is often seen at rehabilitation clinics to ensure that everyone is measuring the range of motion reliably.Internal ConsistencyIn research there is quantitative data and qualitative data. Quantitative data is something directly measurable that we can put a value on – range of motion, temperature, blood pressure, heart rate, etc.However, there are somethings that are just as important. If you remember back to our discussion on outcome measures, you must take into account the things that matter to a patient/client. Sometimes those things, like quality of life, cannot be directly measured. Researchers have to utilize surveys and questionnaires to ascertain that kind of information.Internal consistency is used to establish reliability of individual questions on a questionnaire or survey to establish consistency.Random ErrorIn a perfect world, when a repeated measurement is taken, the true value should be given every time. However, that is not always the case. The provided values may be clustered around the true score.In our tire pressure gauge example, I measure the tire pressure and get the following readings: 37.8, 36.9, and 38.2 PSI. This variability is referred to as random error. Some variability is expected because we do no live in a perfect world. Due to that fact, the size of the variability around the true score is important. A device that has a wide variability is not as reliable as one with small variability. This is referred to as the standard error of the measure.Example: Which Is More Reliable?The example below shows 10 trials of standing on a weight scale.In chart below, the true score body weight is 200 pounds (lbs). You can also notice that the variance surrounding the true score varies from 300 lbs to 170 lbs.
Identifying Reliability in an ArticleWithout going into too much detail and math regarding the calculations of reliability, I will quickly discuss ways to find the given reliability in a journal article.In the articles that we will utilize in this class, the outcome measures used in the study should be reliable and valid methods to assess a specific variable. The articles we look at (outside of this unit) will only report the statistics on the reliability and validity. You can find that In the methods section of an article.Indicators of reliability in an article would be the following: Pearson correlation coefficient or an interclass correlation coefficient (ICC). Most commonly it will be the ICC listed in parenthesis with a numerical value after the listed outcome measure. It will be a value between 0 and 1, with 1 being the most reliable and 0 being the least.
ValidityHow do we know a device’s data is actually giving us the correct data? Is it truly measuring what we want? Validity seeks to establish these concepts in an outcome measure.What Is Validity?Whereas reliability seeks to establish the precision of the device, validity ensures the device is measuring what it is supposed to measure. In essence, it is establishing the accuracy of the measure.Still not sure? Here is a little example involving ACL tears (its also provided in your textbook). What is the most accurate way to tell if someone has torn their ACL? A little spoiler alert…it’s not an MRI. The most accurate way to determine if someone has torn their ACL is to visualize the ACL by cutting someone open surgically. However, there are risks involved in surgery – infection, getting an unnecessary surgery when the ACL is intact just to name a couple. Wouldn’t it be nice if there was something a little less invasive to diagnose an ACL tear?What about an MRI, you ask? If there is a chance that my ACL is not torn, claustrophobia aside, I think I would want to have an MRI rather than surgery. In this scenario, the gold standard measure is the orthopedic surgery to visualize the ACL. To establish validity, an outcome measure must be compared against the gold standard to determine if the outcome is just as accurate as the OG device.So how did the experts determine the MRI could be an acceptable alternative to surgery to detect an ACL tear? The experts used the fancy math (statistics) to compare the correct diagnosis between the two options. The MRI showed it was similarly accurate as an orthopedist, so an MRI is done instead of surgery to determine if there is an ACL tear.Types of ValidityJust like reliability, there are different types of validity.Face ValidityFace validity is the most basic form of validity. It is also the weakest link of all the types of validity, mostly because it is subjective. Face validity is basically taking something at face value. Does it look good enough to measure strength? Okay, let’s roll with it.Criterion ValidityCriterion validity is where one outcome measure is compared against another similar outcome measure. The example provided above with the MRI vs. the orthopedic surgeon is an example of criterion validity.Concurrent ValidityConcurrent validity is a form of criterion validity. The example provided above with the MRI vs. the orthopedic surgeon is an example of concurrent validity.Predictive validityPredictive validity is a type of validity that determines the accuracy of a measure to predict future outcomes. There are several outcome measures that can fall into this category. Many outcomes that assess individuals for having an increased risk of some disease, disorder, or event would have predictive validity. Testing for the BRCA gene and risk of development of breast cancer is an example.Construct ValidityHow do you measure something like quality of life? There isn’t a meter that will register your quality of life by scanning it across your forehead. To measure something quantitative (a construct) into qualitative data, a measure would utilize construct validity. Usually sometime of survey is used to ask a variety of questions to estimate quality of life. Construct validity would establish the accuracy of that questionnaire in assessing that construct.*More of construct validity will be discussed in the Experimental Research Module.External ValidityRemember validity relates to the accuracy of the outcome measure in the data being given, but also when using evidence-based practice, we are applying research to our current practicing situation. External validity is, to an extent, if the outcome measure is accurate for our practice situation. Is it the right setting, clientele, equipment, etc.?Internal ValidityDuring the discussion on variables, I gave you the simplistic research equation: X + Y = changes in Z. X = young, healthy college students
Y = strength training program
Z = increased strength measured by a 1 rep max
Internal validity examines whether or not the the change we were expecting to happen was due to the program and not anything else.*More of external and internal validity will be discussed in the Experimental Research Module.BiasJust because an instrument is reliable, it does not mean it is valid. Reliability is if each time we used the instrument are we getting relatively the same score. Validity is the accuracy of the outcome, so how well the instrument is estimating the true score. How on target is the instrument from the true score?Let’s look at an example:Here is the picture from the Reliability lesson. We’ve already established that the measure is reliable because of the precision of the repeated measures.Now let’s look at this example:
This scale appears to have had something go awry. Is it reliable, yes? It’s measurements are fairly precise with little variability between the repeated measures. However, it is valid? No, it is not because it is overestimating the true score. It is not accurately estimating the true score.Anytime an instrument overestimates or underestimates the true score, there is bias that is occurring.

Do not use AI to write this paper.
Read the two articles I attached below find two pre-participation screen approaches, and explain them (purpose, method, why use this approach, and why it is important).
Compare these two pre-screen approaches with three factors(pro&con)
The paper length should be about 2 pages.

Standards Assignment- middle school
Society of Health And Physical Educators- SHAPE
A curriculum should include SHAPE America’s National Standards and Grade-Level Outcomes for goals, content, and curriculum assessments.
1. Write down a Learning Indicator (Grade Level Outcome) that pertains to Team Handball
2. This assignment is worth 20 points
Standard 1- Develop a variety of motor skills
•
•
Standard 2- Applies knowledge related to movement and
fitness concepts
•
•
Standard 3- Develops social skills though movement
•
•
Standard 4- Develops personal skills, identifies personal
beliefs of movement, and chooses to engage in
physical activity
•
•

Measurement, Evaluation, & Reporting
These are instructions from my teacher :
You must follow also all the rules in the first attachment below:
the second attachment is excel where you will doo this work
For this assignment, you will practice your evaluation and interpretation skills. In the provided document below you will find more detailed instructions. Briefly, you will practice converting data to the appropriate SI units, practice calculating/utilizing basic statistical procedures, practice creating tables and figures to display data, and finally practice your data interpretation skills. A written (typed) report in paragraph form is required for this assignment. Please download the attached file for full assignment instructions and grading criteria. A grading rubric is provided in Blackboard as well. Submit below when completed.
Last 2 attachments are powerpoints and another one explanation how to measure
Rubric criteria:
ExcellentTable representing statistical data is provided, data is accurate
ExcellentBar graph(s) are included, are correct, and have all necessary elements included
ExcellentScatterplots are included, are correct, and have all necessary elements included
ExcellentReport is well written, with accurate data, written text references tables/graphs/research when necessary, provides an accurate interpretation of the data

Answer all of the following questions in one organized response. Your response should be between 500-750 words max and should focus on the implications of the readings. The discussion assignments should NOT be a simple summary of the main ideas and findings in the readings. Again, I want to stress this is not a summary activity but a critical thinking exercise. Use good English grammar, correct punctuation, and complete sentences. While your answers will mostly be judged on their thoughtfulness and completeness, I reserve the right to take off points for grammatical errors, especially if they interfere with the clarity of the submission.
Discussion QuestionsWhat are five functions of a trademark?
Explain how fanciful, arbitrary, and suggestive marks differ and why they are considered distinct.
What is the importance of secondary meaning?
Could parody be a defense in trademark case? Why or why not?
What is the purpose of copyright law?
How does fixation relate to copyright?
What is the copyright tribunal?
What are some factors considered when determining the fair use of copyrights?
use this book: https://books.google.nl/books?id=UzErDwAAQBAJ&prin…