Research 400 FT/500 PT: Module 1 PDF

Research 400 FT/500 PT: Module 1 What is Evidence Informed Practice (EIP)?  Why Does This Matter to RMTs? By following evidence-informed/evidence-based standards of care, RMTs and their treatments will be: More effective Better supported by extended benefits insu...

Research 400 FT/500 PT: Module 1 What is Evidence Informed Practice (EIP)?  Why Does This Matter to RMTs? By following evidence-informed/evidence-based standards of care, RMTs and their treatments will be: More effective Better supported by extended benefits insurance plans More standardized among members of the profession More reputable members of the health care community Quantitative vs Qualitative Methods Quantitative vs Qualitative Methods Quantitative methods are based on the assumption that there is a uniform reality that can be observed, measured, and expressed in numbers Also assumes linear cause and effect (i.e. a specific treatment causes a specific outcome) Test hypotheses and use numbers to summarize information Researchers manipulate the treatment setting and participants They control as much of environment as possible Major focus on ruling out “rival explanations” for outcomes That is, accounting for confounding variables (more to come…) Then use statistics to show probability of chance If there is a low probability of chance, outcomes should be reproducable Quantitative vs Qualitative Methods Qualitative methods assume that any observation effects what is being observed and vise versa No assumption of a single reality Any description is one of several realities that may be valid No assumption of linear cause and effect Multiple factors/causes may influence an outcome Importance is placed on observing in the natural setting (i.e. there is no controlled setting) Observer is part of the process Data is collected via interviews, direct observation, and documents (such as journals, correspondence, and questionnaires/surveys) Quantitative vs Qualitative Methods Both have limitations, but both are useful parts of scientific research Both assess the credibility of a study’s reliability and validity Depending on the question being asked, some studies use both methods Qualitative analysis often helps develop a specific and quantifiable hypothesis Quantitative statistics can help illuminate patterns in qualitative studies However, most of health care research utilizes quantitative methods  Descriptive vs Explanatory Studies Data used to describe a group/sample/population, with no intention of going beyond that sect, it is a descriptive study. These studies do not test a theory, nor are they used to learn more about the sect. These studies set the stage to eventually test a theory by first forming one. Studies that seek to make generalized statements about a population based on a studied sample are explanatory or inferential studies. These studies look to see if, for  Descriptive vs Explanatory Studies Descriptive studies FORM a hypothesis Weaker evidence due to lack of control or comparison groups, but still explore cause and effect relationships However, contribute to the weight of evidence when combined with consistent results from observational and experimental studies Foundation for hypothesis based on observations Provide detailed information that helps to refine the design of explanatory studies Examples: case studies, case series, correlation studies, qualitative studies  Descriptive vs Explanatory Studies Explanatory studies TEST a hypothesis Stronger evidence that clarifies or establishes cause and effect relationships Provide evidence about research questions (i.e. disease prevalence or treatment efficacy) Examples are divided in observational and experimental Observational: cross-sectional, case-control, cohort studies Experimental: before and after treatment studies, clinical trials Study Designs  Types of Studies Metanalysis Studies focused on a particular question are grouped based on certain criteria One or more databases are used to find all published articles meeting the criteria This can result in publication bias Well defined criteria helps to reduce selection bias Used to estimate size of treatment effect and/of settle any contradictory or inconclusive date  Types of Studies Systematic Review Similar to a meta-analysis, but includes non-published studies This is important to note, as meta-analysis may have a publication bias, as studies with negative results often do not get published This type of study helps to eliminate the publication bias Best evidence synthesis: draws on a wide range of evidence and explores the impact of context, while also assessing validity, to determine inclusion For example, with LBP, when studies are too different from one another to be pooled, yet all address LBP, reviewers evaluate the selected studies by individually assessing each one for its validity Cochrane is a great resource for systematic reviews  Types of Studies RCT Also known as randomized trial, clinical trial, and/or intervention study Provides most direct evidence of a cause-and-effect relationship following treatment Powerful because study participants are randomly assigned to treatment or control group  Types of Studies Cohort Study Prospective, longitudinal, observational studies Attempt to explain relationship between treatment and outcome Prospective = outcome has not yet occured Cohort = a group who all experience the same treatment (or other variable); or exhibit the same characteristics (e.g. risk factor for cardiovascular disease) Members of the cohort are observed over a long period of time to see what the outcome is – e.g. some develop cardiovascular disease, others don’t, etc. Pros: provide strong observational “evidence” of a relationship between treatment/risk factors and the outcome Cons: take a long time and are expensive Attrition is often high (e.g. participants drop out, die, move out of the region, etc)  Types of Studies Before/After without Control A type of case series, but rather than just observing an outcome, practitioner determines hypothesis; sets eligibility criteria and methods; collects baseline data; provides tx; measures outcome for a series of patients (making it an experimental case series) Often performed by practitioners in their own practices Risk of many weaknesses Lacks a control group for comparison; potentially over-estimates the treatment effect Data collection may be subjective and patients may over-report good outcomes (possibly because they already have a relationship with the practitioner) May not be possible to generalize the findings to anyone outside the test group Before/After with Control Same, but less limitation d/t use of control, making it a stronger study  Types of Studies Case Report Describes events related to the care of a single patient Better than anecdote, d/t thorough rationale with presentation, description, detail, and discussion along with directions for future investigation Pros: can serve as the basis for a new hypothesis; can be used to report adverse reactions to treatment Case series Takes the case study a step further by combining individual case studies of similar patients Pros: may be the first indication of a new phenomena  Types of Studies Anecdote A brief, revealing account of an individual person or an incident Not evidence, as there cause does not equal effect; lacks rationale, detail, and exploration Can be used to create a case report/case series  Types of Studies Correlation Study Population survey using existing data about groups NOT evidence, as correlation does not equal causation It does not prove cause and effect. It describes an association between exposure and outcome. Pros: quick way to see if there’s an association/correlation between an exposure and an outcome Pros: relatively low cost study; simple and quick to conduct  Components of a Research Article Abstract Summary including background, purpose, design, methods, results, conclusion, and discussion Introduction Thorough description of the purpose/importance, states the research question, and includes a literature review (which places a study in context) States the purpose for conducting the research Introduces the research question which the study addresses (sometimes the hypothesis) Methods Detailed description of how the study was carried out Readers should be able to decide if other explanations exist that explain the findings, or if the authors’ conclusions are strong Method should be so exact that the study is replicable by other researchers  Components of a Research Article Results/Findings Description of the analysis of the study data Can be qualitative or quantitative Objective; neither supports nor dismisses the hypothesis or research question Conclusion/Discussion Answers the question, “so what do these results mean in terms of the research question?” Authors interpret the research results As the discussion sometimes puts forward the authors’ informed opinions, it’s good when they cite other studies that point to similar results References Listing of other research, articles, etc that the authors consulted while preparing the article you’re reading References should provide a good source of further reading  Hypothesis Hypothesis: statement that can be demonstrated to be true or false through the methodical gathering and analysis of empirical information or data. An educated guess on how things work Should be testable and measurable Will have a: 1) independent variable - thing to be changed 2) dependent variable - thing to be measured The null hypothesis is the commonly accepted fact; it is the opposite of the alternate hypothesis. Researchers work to reject, nullify or disprove the null hypothesis by coming up with an alternate hypothesis that they believe explains a phenomenon and, therefore, rejects the null. Technically, researches do not prove a hypothesis, but disprove a null. Hypothesis vs Null Hypothesis Hypothesis vs Null Hypothesis  Variables Independent Variable Dependent Variable Cause Effect Influencer What is being influenced Manipulating Measuring Any measurable changes *depend* on the independent variable ***Confounding variable (aka: extraneous variable): any variable other than the independent variable that influences the dependent variable… can/should be controlled or tested itself in a high quality study.  Types of Experiment Designs By number of independent variables Simple (1 independent variable) vs complex (>1 independent variable) By subject assignment Between-subjects designs (independent designs): different subjects are used in each group Within-subjects designs (repeated measures designs): the same subjects are used in each group Mixed designs: include both between and within-subject components  Class #2 Statistics Internal vs External Validity Ethics and Peer Review Critiquing an Article