Evidence Based Practice: Module 1

• Research 400 FT/500 PT is the focus of Module 1

Evidence Informed Practice (EIP)

• EIP, or Evidence-Based Practice (EBP), relies on research evidence, clinical expertise, and client values for improved care
• Better research evidence increases confidence in clinical decisions
• Evidence alone is insufficient for making clinical decisions

Relevance to Registered Massage Therapists (RMTs)

• Adhering to evidence-informed standards benefits RMTs and their treatments
• Benefits include increased effectiveness and better support from insurance plans
• Treatments become more standardized, and therapists gain reputation in healthcare

Quantitative Methods

• Quantitative methods assume a measurable, uniform reality that can be expressed numerically
• They assume a linear cause and effect
• Includes testing hypotheses and summarizing information with numbers
• Researchers manipulate settings and participants
• Control is maximized in the environment
• Focus is on eliminating "rival explanations" for outcomes through managing confounding variables and statistical analysis

Qualitative Methods

• Qualitative methods assume observation influences what is being observed
• They allow for multiple descriptions that may be valid
• There is no assumption of a linear cause and effect
• Multiple factors may influence an outcome
• These methods emphasize naturalistic observation without controlled settings
• The observer is part of the process
• Information is gathered through interviews, direct observation, and documents

Quantitative and Qualitative Methods - Comparison

• Both methods have limitations, but each is a useful scientific research component
• Both are used to assess credibility, reliability, and validity of a study
• Some studies combine the two methods to answer research questions
• Qualitative analysis can help form quantifiable hypotheses
• Quantitative statistics can highlight patterns in qualitative studies
• Health research commonly utilizes quantitative methods

Descriptive Studies

• Descriptive studies characterize a group, sample, or population without further intention
• These do not test theories, but can set the stage for future testing
• A hypothesis is Formed using this type of study

Explanatory studies

• Explanatory studies make generalized statements and test hypothesis about a population based on a studied sample
• Explanatory studies can determine if a population benefits from an intervention
• Stronger cause and effect evidence and research question evidence is provided
• The studies are split into observational and experimental types

Descriptive vs Explanatory Studies - Evidence and Examples

• Descriptive studies show weaker evidence
• Limited control or comparison groups are used in Descriptive studies
• Descriptive Studies contribute to evidence when combined with consistent experimental study results
• They are the foundation for hypothesis creation based on observations
• Examples of descriptive studies: case studies, correlation studies, case series, and qualitative studies

Explanatory Studies - Evidence and Examples

• Better evidence is provided in explanatory studies, and it clarifies cause/effect relationships
• Evidence is provided about research questions like treatment efficacy of a disease
• Examples of explanatory studies include observational (cross-sectional, case-control, and cohort) and experimental (before/after treatment and clinical trials)

Types of Studies

• Study designs determine the quality of evidence, with meta-analyses at the top
• Meta-Analyses, Systematic Reviews, Critically Appraised Literature/Guidelines, RCTs, Non-Randomized Controlled Trials, cohort studies, case series, individual reports, and background information go into study designs
• Meta-analyses are studies grouped by questions and criteria
• Databases are used to find published articles, which can result in bias
• Criteria are usually used to reduce selection bias
• Estimations in treatment size are used to settle controversial dates

Systematic Review

• Systematic reviews are similar to meta-analyses but include non-published studies
• Publication bias with negative results gets eliminated with these types of studies
• The evaluation of context and validity, is used to assess inclusion
• Cochrane is a resource used for systematic reviews

RCT

• An RCT can also known as Randomized Trial, Clinical Trial, and/or Intervention Study
• Direct evidence is provided of an effect/cause relationship after treatment
• Participants get assigned into random treatment/control groups

Cohort Study

• Cohort studies are prospective, longitudinal, and observational and explains the relationship between treatment and outcome
• The outcome has not yet occurred in prospective studies
• Cohort studies study groups who receive the same treatment and/or exhibit the same characteristics
• Members of cohorts get observed for long periods of time to measure outcomes
• This has been shown to provide strong evidence of treatment/risk factors relationship, but take a long time and are expensive
• High attrition occurs

Before/After Studies

• Before/After studies without control determine hypothesis, eligibility criteria, methods; collect data; tx; measure outcome over patient series
• These are considered series case experimental studies
• Performance occurs by practitioners through weak risks
• Control groups will lack potentially over-estimated treatment effects
• Collection of Data can be subjective
• Findings don't generalize to outside of test group in this scenario
• The Before/After without Control show stronger studies but have limit use/control

Case report

• Case reports describe single patient care events
• They have thorough rationale with presentation, description with discussion
• They serve as a basis for a new hypothesis and adverse reaction reports
• The similar patients case study takes it a step farther to combine the individual case studies
• A first indication of new phenomena can be indicated

Anecdote

• Anecdotes are brief and reveal personal/incidental accounts
• They are not equal or related to cause and effect or evidence, or lack detail and rationale
• Can get used to create case reports/series

Correlation study

• Correlation studies include a population survey with pre-existing data with
• This data is not shown as evidence, because of the fact that it describes an association between exposure and the outcome
• Quick and inexpensive way to exposure/outcome see if there is an correlation or association

Components of a Research Article

• Abstracts offer a summary of the background, purpose, design, results, conclusion, discussion etc.
• Thorough description is provided of the research question/importance with literature review. The research question gets introduced
• The study gets carried out here using methods
• Strength and replicabilty are key here

Components of a Research Article - Conclusion and Interpretation

• Results and findings get analyzed in quantitative or qualitative qualities
• Objectveness doesn't dismiss or support a research question
• Interpretation is offered to answer the “so what?” conclusion
• Referencing other work and providing sources is key here

Hypothesis

• A Hypothesis is demonstrable to be true or false through methods and analysis of data
• A good hypothesis is an educated,testable, and measurable guess
• This contains an independent and dependent variable
• A null hypothesis are facts or commonly accepted concepts
• Disproving the null hypothesis is key through the alternate hypothesis

Variables

• Independent variable causes influence while dependent variables measure effect
• Measureable changes depend on the independent variable
• The confounding variable influences the independent variable and gets tested and controlled

Experimental Variable Setup

• The Independent variables change, while dependent change because of the independent one
• The Liquid is a key example
• Controlled variables should stay constant for example, pot size, soil type etc

Experiment Designs

• Can be by number of variables, simple (one variable), and complex (more than one variable)
• Between-subject design uses different subjects in groups
• Within subject includes same subjects in different groups
• Mixed design mixes the two concepts

Follow on Study

• Class two has statistics, validity, ethics and review