Lecture 5: Interventions Studies Flashcards
What study type is typically utilized when doing intervention studies?
RTC’s
RTCs:
Always has to be a comprassion, even if were comparing to nothing
Theres an intervention group and a control group (or standard care)
Compares the change of a dependent variable between
* Intervention group
* Control/Standard care group
What is a Superiority intervention study for?
used to see if one intervention is better than another (its superior)
What is an equivalence intervention study for?
To see if treatment A and treatment B produce the same results
* This can be helpful is one is cheaper to make
* Maybe one has side effects and the other doesnt
* dosage might need to be lower in one than the other
What is a non-inferiority intervention study for?
Looking at the side effects that could occur
* looking at the overall outcomes that w/ each treatment
* with equivilance were getting pretty much the same result
* with non-inferiority one could be a little bit higher than another (better outcome) but not enough to say its superior
Basically just saying that one treatment is not worse than another (they’re pretty close or about the same)
* one treatment may get you a little bit better, but the adverse events are about the same
Used to determine whether a new treatment or intervention is not significantly worse than an existing treatment (the standard of care) by a pre defined margin. Instead of trying to prove that the new treatment is better, the goal is to show that it is at least as effective as the existing treatment
Intervention focused studies can also be cohort/case control or Case study/case series
Cohort study/Case-Control:
* Exposure = treatment
* Non-exposed = non treatment/other treatment group
Dependent variable will be some kind of outcome in a dichotomous format
* Fall risk: yes/no
* Fracture: yes/no
* LEFS increased by > 15 points yes/no
NOTE: w/ case contorl you would either work backwards (sort them into whose at high fall risk and who isnt) then look in the past who did strength training and who didnt
* however, most of the time these are going to be cohort studies in the prospective direction
Case Study/Case Series
Looking at one / several patients
typically a rare unique condition that is uncommon or very challenging to collect a large # of patients for the study (think trying a new manual technique in pro baseball players)
RTCs:
Has to be a randomized scheme (thats why they’re called randomized control trials)
* the same population is randomized
Also named for the # of independent variables being looked at
Single factor design would be 1 independent variable
EX: Pediatric pt’s w/ cerebral palsy
* Depdent variable = grip strength
* Intervention (independent variable) = play program that involves carrying/throwing
This is considered one indpdent variable
* treatment vs control
Single factor design = 1 intervention 2 levels
Single factor design involes on independent variable (or factor) that has multiple levels (or conditions). In this this type of study you’re looking to see how changes in that single factor affect the outcome
EX: Imagine you’re testing a new educational program to see how different study methods impact student performance. Your single factor (independent variable) is the study method, and it has 3 levels
1) Method A: Flashcards
2) Method B: Group study
3) Method C: Online quizzes
You would randomly assign participants to one of these study methods and measure their performance (the dependent variable) after a certain period. This design helps you understand if one study method is more effective than the others
So this is single factor but multiple (3) levels
RTC multi factor design: Involves two or more independent variables. This design allows you to examine not only the main effects of each factor but also any potential interactions between them. An interaction occurs when the effect of one factor depends on the level of another factor.
* 2 or more interventions vs each other
* Compares interaction between combinations of interventions
EX: Let’s expand on the pervious scenarior and introduce a second factor: motivational level (high vs low). Now; you have two factors
1) Study method (3 levels: flashcards, group study, online quizzes)
2) Motivation level (2 levels; high, low)
In this case, you would have a total of 6 conditions (3 study methods x 2 motivation levels). Participants would be randomly assigned to one of these combinations, and you would measure their performance as before
* so now you’re seeing if theres some magic combination of treatment that incombination see great outcomes
* Great when wanting to see combination of interventions (because were not just doing 1 treatment in our hour w/ pts)
Summary:
* Single factor Design: one independent vriable w/ multiple levels; helps assess the effect of that single variable
* Multi factor design: two or more independent variables; helps assess main effects and interactions between factors
This is an example of a RTC intervention study.
* This has a single factor (1 intervention type) = strength training
* 3 levels (RPE 5,7,9)
* Want to see who progressed the most in the 6 weeks of training
This is an intervention study RTC. This is multifactor (joint protection leaflet and exercise group)
* 2 levels in each one (yes or nointervention)
Good for comparing to see the best combination of interventions
RTC’s can also be named based on the # of measurements are taken over the study.
Below is a pre test post test study
* baseline measurement, then 6 weeks of treatment then a final measurement (pre test, post test)
* This is a pre test post test design
If theres a control group it will either be:
* Placebo
* No intervention
* Standard care (basically just comparing to the norm)
This is an exaplne of a posttest only design - only testing at the end
So the dependent variable is only measured at the end
If your study has a really strong inclusion and exclusion criteria you’re essentially gaurinteeing that your participants will all be starting in about the same spot
Due to random assignment internal validity is still strong (techniqually you dont need that baseline measurement)
Utilized primarily in really large groups where getting 2 measurements would be really difficult
Reduces bias of participants from multiple tests (getting better at the test because they’ve already had practice doing it once)
RTC’s can also be repeated measures tests
Typically we want to know what will help patients in the short term, medium term, and long term. We won’t know those things unless we take multiple measurements. (if I just take my initial baseline test, and compare it to the end, it wont show you the journey)
Often done w/ mobility and pain because we want to get rid of those things right away
This is taking a multiple measurements (every week for 9 weeks) - essentailly adding a measurement other than just pre and post test. 3 or moremeasurements
It would be really helpful to know that ultrasound helps pain w/ epicondylitits in the first ~1 week but after that it wont have any affect
* So we wouldve done those repeated measures for lots of weeks after and found that this modalitity only helps in the short term (so we now understand the journey)
* Whereas if we had only done the pre and post test we wouldnt have known that that ultrasound only helped in the first week then had no effect after that - all we would’ve known is that at some points the ultrasound helped (not when it helped)
* This is going to tell me i should use ultrasound early on, not later on (wont help later on)
NOTE: this is a one way repeated measures example
* 1 group of participants going through the same senario
* NOTE: we can have repeated measures in a multifactorial design etc..
The example below shows the same group and doing different things with them and measuring the difference
* EX: Chronic LBP w/ 50 people and measure their walking (gait quality)
* Then I want to see which medication for pain reduces their fall risk the most
* Condition 1 = baseline (no medication)
* Condition 2 = muscle relaxor –> measure walking
* Condition 3 = oxycodine –> measure walking
Now compare secanrioes to see which ones had the greatest fall risk
* this is one way repeated measures
* patients all togther are having 1 experience
Limitations:
* Practice Effects (have done that walking test multiple times and might’ve gotten better at the test were using)
* Carryover effects (meaning if im doing the same thing over and over again, there are effects from just performing it) - think testing squat deph over and over. however, if you’re doing that ROM over and over again you’re proably increasing your flexibilit by just doing the test.
carry over affects: occur when the effects of a treatment or condition persist and influence respone in subsequent measurements or trials. This is often seen in crossover designs where participants recieve multiple treatments (can also be this repeated measure design)
* EX: if a participant undergoes a medication trial and experiences lasting effects from the first medication, this might impact their responses in the second treatment phase, making it difficult to isolate the effects of each treatment
* So its basically the intervention lasting and benefiting them until the next trial so they’re all mixed up
Practice effects = improvements in performance that occur due to repeated exposure to the task or measurement rather than the treatment itself. This often happens when participants becoming more familar with the tasks or tests over time.
* EX: If the participants take a cognitive test muktiple times, they may score higher on subsequent tests simply because they’ve practiced the test format, not because of any actual improvement in cognitive function.
RTC cross over design
We have two different groups of people and we want to maximize the participation
* This is good when we have a smaller group of people we want to be looking at
So we only had a total of 30 people consent to a study
* to maximize people we could split them into two groups (15 and 15)
* We pre test then do the intervention, then post test groups 1 and 2 at the same time. Then allow for a washout period, then switch groups 1 and two
Washout period: time it takes to negate the drug/intervention in period 1
* enough time for the effects of treatment 1 to go away
* If i was doing a strength training intervention I would need to allow enough time for DOMs to go away
USE THIS TO MAXIMZE THE PATIENT POPULATION YOU HAVE
* also good to see the interventions in each group
Repeated Measures Mixed Method
* multifactor design w/ repeated measures
* So we get the journey of the treatment (do the results happen quickly? do they last long? whats that process like?) and we can see if theres an ultimate treatment combination
3 factors
* Exercise
* Manual
* Balance
Levels (3)
* Exercise Yes, Balance Yes, Manual No
* Exercise Yes, Balance No, Manual Yes
* Exercise Yes, Balance No, Manual No
Then we have repeated measures along the way
named 3x4 by how many measurements are taken and how many variables there are (3 variables [3 different groups], across 4 measurements)
NOTE: exercise is the common thread between all 3 groups (doing the same exercise then 2 groups are adding something else)
No washout period needed
Each group is doing the same intervention the entire time. Theres just repeated measures
* were looking to see if theres some magic combo between exercise and manual and balance thats best
