Evidence Informed Practice for RMTs

Evidence Informed Practice (EIP)

• EIP is a triad of best available research evidence, professional/clinical expertise, and client values & individualized needs
• Core principles of EIP highlight that better research evidence leads to more confident clinical decisions, but evidence alone isn't sufficient
• EIP improves client care

Why EIP Matters to RMTs

• Following evidence-informed/evidence-based standards of care will lead to more effective treatments
• RMTs will be better supported by extended benefits insurance plans
• Standardization among RMTs will increase
• RMTs will be more reputable members of the healthcare community

Quantitative vs Qualitative Methods

• Quantitative methods assume a uniform reality that can be observed, measured, and expressed in numbers. It assumes a linear cause & effect relationship.
• Quantitative methods use hypotheses and numbers to summarize findings. Researchers manipulate treatment and control for other variables
• Qualitative methods assume that observations affect what is being observed and consider any description to be one of many realities. It does not assume a linear cause & effect relationship.
• Qualitative data is collected through interviews, observations, and documents

Quantitative vs Qualitative Methods (page 5)

• Quantitative methods rely on the assumption of a uniform reality
• Quantitative methods assume linear cause and effect where a particular treatment causes a specific outcome
• Researchers test hypotheses using numbers and control as much of the environment and participants as possible.
• The primary aim is to rule out rival explanations (confounding variables).
• Outcomes should be reproducible if the probability of chance is low

Quantitative vs Qualitative Methods (page 6)

• Qualitative methods assume that observation affects what's being observed. No singular reality exists
• Qualitative methods do not presume a linear cause-and-effect relationship
• Multiple factors can influence an outcome and importance is on observing in a natural setting

Quantitative vs Qualitative Methods (page 7)

• Both quantitative and qualitative methods have limitations but are useful parts of scientific research
• Both methods assess study reliability and validity
• Some studies use both methods (qualitative & quantitative)
• Qualitative methods aid in developing quantifiable hypotheses and help illuminate patterns.
• Most healthcare research utilizes quantitative methods

Descriptive vs Explanatory Studies

• Descriptive studies describe a group, population, or sample without testing a theory
• Descriptive studies help researchers set up for hypothesis testing
• Explanatory studies test hypotheses that can be generalized about a population based on a studied sample

Descriptive vs Explanatory Studies (page 9)

• Descriptive studies formulate hypotheses and identify cause and effect relationships which are aided by observations in combination with experimental and observational findings
• Descriptive studies serve as a good foundation for hypothesis-based information and help to develop rigorous designs of explanatory studies

Descriptive vs Explanatory Studies (page 10)

• Explanatory studies test hypotheses - a stronger evidence base that clarifies cause and effect
• This includes disease prevalence and treatment efficacy
• Types include observational (cross-sectional, case-control, cohort studies), and experimental (before and after, clinical trials)

Study Designs

• Study designs, in order of increasing rigor, include background information, expert opinion, non-EBM guidelines, individual case reports, case series, cohort studies, non-randomized controlled trials, randomized controlled trials, critically appraised literature, evidence-based guidelines, systematic reviews, and meta-analyses.

Types of Studies (page 12)

• Meta-analysis groups studies focused on a certain topic based on criteria from one or more databases
• Meta-analysis minimizes publication bias and helps estimate treatment effects by settling contradictory/inconclusive data
• Well-defined criteria reduces the selection bias

Types of Studies (page 13)

• Systematic reviews incorporate non-published studies for a broader, more inclusive evidence base
• Systematic reviews assess study validity individually
• Systematic reviews address a wide range of evidence when determining inclusion criteria
• Cochrane is helpful for systematic reviews

Types of Studies (page 14)

• RCTs, also called randomized trials or clinical trials, provide the strongest cause and effect evidence
• RCTs are powerful because the participants are randomly assigned to treatment/control groups

Types of Studies (page 15)

• Cohort studies examine relationships between treatment and outcome (typically over a long period) by following a set of participants
• Cohort studies attempt to establish relationships between treatment and outcome over time.
• Cohort studies have strengths in observational evidence but come with the expensive and time-consuming disadvantage of length

Types of Studies (page 16)

• Before/after studies are a type of case series that track treatment effect
• Lack a control group potentially overestimating the efficacy, and is subjective because of potentially overreporting good outcomes

Types of Studies (page 17)

• Case reports describe events in a single patient's care
• Case reports can be used to develop new hypotheses and describe adverse reactions
• Case series involve combining individual case studies of similar patients

Types of Studies (page 18)

• Anecdotes are brief accounts of incidents that aren't evidence-based due to lack of proper rationale, detail, or empirical testing

Types of Studies (page 19)

• Correlation studies examine the association between exposures and outcomes using existing data and a population survey

Components of a Research Article (page 20)

• Abstracts summarize background, purpose, design, methods, results, conclusions, and discussion
• Introductions detail the purpose, importance, and research question(s), and include a relevant literature review
• Methods section provide detailed information on the research design's execution and should allow readers to replicate the study

Components of a Research Article (page 21)

• Results describe the data analysis (qualitative or quantitative).
• Conclusions/discussion interpret the results in relation to the research question and might include expert opinions
• References cite other relevant sources

Hypothesis (page 22)

• Hypotheses are testable statements about how things work; they represent educated guesses
• A good hypothesis is measurable and has an independent (changeable) and dependent (measured) variable

Hypothesis vs Null Hypothesis (page 23)

• The null hypothesis assumes no relationship between variables
• Example null hypotheses are: cats show no preference for food based on shape, plant growth is not affected by light color, and age has no effect on musical ability

Hypothesis vs Null Hypothesis (page 24)

• The alternative hypothesis is what the researcher aims to prove; the alternate hypothesis is the opposite of the null hypothesis
• The null hypothesis is what the researcher aims to disprove, nullify, or reject; it is the opposite of the alternative hypothesis

Variables (page 25)

• Independent variables are the cause or influencer being manipulated
• Dependent variables are the changes or effects measured in the study
• Confounding variables are extraneous variables that can influence a dependent variable

Effect of Bio-fertilizer 'x' on Plant growth (page 26)

• Alternative hypothesis: The application of biofertilizer increases plant growth
• Null Hypothesis: The application of biofertilizer does not increase plant growth

Independent, Dependent, Controlled Variables (page 27)

• Independent variable: the manipulated variable
• Dependent variable: the measured outcome
• Controlled variable: factors kept constant across all groups or conditions

Types of Experiment Designs (page 28)

• Experiment designs are classified by the number of independent variables (simple vs complex).
• Subject assignment in research experiments includes between-subjects (different people in each condition) and within-subjects (same people in each condition) designs.

Types of Experiment Designs (page 29)

• Between-subjects: each participant in one and only one condition
• Within-subjects: all participants participate in all conditions

Class #2 (page 30)

• Class topics include statistics, internal versus external validity, ethics and peer review, and critiquing an article.