Module 1 Quiz

• Evidence-Informed Practice (EIP) is a triad, involving the best available research evidence, professional/clinical expertise, and client values & individualized needs.
• Stronger research evidence leads to more confident clinical decisions.
• Evidence alone is insufficient for making clinical decisions.

Importance of EIP for RMTs

• Following EIP standards makes RMT treatments more effective.
• EIP leads to better support from extended benefits insurance plans.
• EIP standardizes practices among professionals.
• EIP enhances the reputation of RMTs in the healthcare community.

Quantitative vs. Qualitative Methods

• Both quantitative and qualitative methods have limitations but are useful in scientific research.
• Both assess the credibility of a study's reliability and validity.
• The choice of method depends on the research question.
• Qualitative analysis can help develop a specific and quantifiable hypothesis.
• Quantitative statistics can help illuminate patterns in qualitative studies.
• Most healthcare research uses quantitative methods.

Quantitative Methods

• Based on the assumption of a uniform reality that can be observed, measured, and expressed numerically.
• Assumes linear cause and effect.
• Used to test hypotheses and summarize information with numbers.
• Researchers manipulate the treatment setting and participants, and control the environment as much as possible.
• Focuses on ruling out "rival explanations" by accounting for confounding variables, then uses statistics to show probability of chance.
• Low probability of chance suggests outcomes should be reproducible.

Qualitative Methods

• Assumes any observation affects what is being observed and vice versa.
• Does not assume a single reality.
• Does not assume linear cause and effect.
• Places importance on observing in the natural setting.
• The observer is part of the process.
• Data is collected via interviews, direct observation, and documents.

Descriptive Studies

• Data is used to describe a group/sample/population, without intention of generalizing beyond that sect.
• These studies do not test a theory but set the stage for forming one.
• Forms a hypothesis.
• Considered weaker evidence due to lack of control or comparison groups, but still explores cause and effect relationships.
• Contribute to the weight of evidence when combined with consistent results from observation & experimental studies.
• Provide detailed information that helps to refine the design of explanatory studies.

Examples of Descriptive Studies

• Case studies: adverse response to treatment.
• Case series: "shiatsu used to treat 30 clients with migraine headaches".
• Correlation studies: "rates of population growth and contraceptive sales".
• Qualitative studies: "patients experience of the therapeutic relationship".

Explanatory Studies

• Studies seek to make generalized statements about a population based on a studied sample.
• Look to see if a population benefits from an intervention.
• Also known as inferential studies.
• Tests a hypothesis.
• Provide evidence about research questions
• Classified in observational and experimental

Observational Explanatory Studies

• Cross-sectional: survey of patients seeking treatment at a school clinic.
• Case-control: exercise patterns in type 2 diabetics vs. Non-diabetics.
• Cohort studies: development of repetitive use injuries in massage therapists.

Experimental Explanatory Studies

• Before and after treatment studies: effect of a single massage on pain.
• Clinical trials: P6 point stimulation for morning sickness.

Hierarchy of Study Designs (Best to Worst)

• Critical Appraisal
• Meta-analyses
• Systematic reviews
• Critically appraised literature
• Evidence based practice guidelines
• Randomised controlled trials
• Non-randomized controlled trials
• Cohort studies
• Cases series or studies
• Individual case reports
• Background information, expert opinion, non-EBM guidelines

Cohort Study

• Observational explanatory study.
• Prospective, longitudinal.
• Attempts to explain relationship b/w treatment and outcome.
• Prospective: outcome has not yet occurred.
• Cohort: a group who all experience the same treatment or exhibit the same characteristics.
• Members of the cohort are observed over a long period of time to see what the outcome is.

Pros & Cons of Cohort Studies

• Provide strong observational "evidence" of a relationship b/w treatment/risk factors and the outcome.
• Take a long time and are expensive.
• Attrition is often high.

Before/After without Control

• Experimental explanatory study.
• A type of case series.
• Practitioner determines hypothesis; sets eligibility criteria and methods; collects provides tx; measures outcome for a series of patients.
• Often performed by practitioners in their own practices.
• Lacks a control group for comparison; potentially over-estimates the treatment effect.
• Data collection may be subjective and patients may over-report good outcomes.
• May not be possible to generalize the findings to anyone outside the test group.

Before/After with Control

• More robust study due to the presence of a control group.

Case Report

• Descriptive study.
• 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.
• Can serve as the basis for a new hypothesis; but can be used to report adverse reactions to treatment.

Case Series

• Descriptive study.
• Combines individual case studies of similar patients.
• May be the first indication of a new phenomena.

Anecdote

• A brief, revealing account of an individual person or an incident.
• Not evidence.
• Lacks rationale, detail, and exploration.
• Can be used to create a case report/case series.

Correlation Study

• Descriptive Study
• Population survey using existing data about groups.
• Correlation does not equal causation.
• Describes an association b/w exposure and outcome.
• Quick way to see if there's an association/correlation between an exposure and an outcome.
• Relatively low cost, 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
• 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
• 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, its 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
  • References should provide a good source of further reading

Hypothesis

• A 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.
• Includes an independent and dependent variable.
• Must be technically disproven.

Null Hypothesis

• Commonly accepted fact/phenomenon.
• Assumes there is no relationship between two variables and that controlling one variable has no effect on the other.
• Researchers work to reject it by coming up with an alternate hypothesis that they believe explains a phenomenon and, therefore, rejects the null.

Examples of Null Hypotheses

• Cats show no preference for food based on shape.
• Plant growth is not affected by light color.
• Age has no effect on musical ability.

Variables

• Independent Variable
  • Cause
  • Influencer
  • Manipulating
  • Example: the liquid used to water each plant.
• Dependent Variable
  • Effect
  • What is being influenced
  • Measuring – any measurable changes depends on the independent variable
  • Example: the height or health of the plant
• Confounding 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.
• Controlled Variable
  • Everything you want to remain constant and unchanging.
  • Example: type of plant used, pot size, amount of liquid, soil type etc.

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
• Between-subjects designs:
  • Each participant participates in one and only one condition of the experiment
• Within-subjects designs:
  • All participants participate in all of the conditions of the experiments