ANM100 AY2324 Week 13 Research 1 PDF

ART AND PRACTICE: RESEARCH WEEK 1 DR. MONIQUE AUCOIN ND MSc ANM 100 Week 12 SOME RESEARCH HUMOR John Oliver Clip about research communication in the news OUTCOMES Explore the underlying concepts of Evidence-Based Medicine, including its strengths and limitations. Review the scientific method and its...

ART AND PRACTICE: RESEARCH WEEK 1 DR. MONIQUE AUCOIN ND MSc ANM 100 Week 12 SOME RESEARCH HUMOR John Oliver Clip about research communication in the news OUTCOMES Explore the underlying concepts of Evidence-Based Medicine, including its strengths and limitations. Review the scientific method and its value and application in clinical practice. Explore and evaluate the need for critical appraisal of published health research. Describe the principles of causation and correlation. Describe and identify bias, chance, confounding, and association and know how this can influence the validity and reliability of research findings. Identity examples of bias, confounding, correlation and causation in sample research studies WHAT IS EVIDENCE INFORMED PRACTICE? What does it mean to you? HISTORY & PURPOSE 1972 Archie Cochrane: most treatment decisions not based on systematic review of evidence Term “Evidence-Based Medicine” introduced in 1992 Purpose: Shift decision making from “intuition, unsystematic clinical experience, and pathophysiologic rationale” to increase used of scientific, clinically relevant research Research/practice gap: 17 years EVIDENCE-INFORMED PRACTICE A ROSE BY ANY OTHER NAME… Evidence Based Medicine Evidence Based Practice Evidence Informed Practice WHAT ARE THE BENEFITS OF EBP? WHAT ARE THE DOWN SIDES OF EBP? ARGUMENTS FOR Avoid (or decrease) biases from clinical experience alone: false attribution, lack of follow up, small sample size, rose-coloured glasses Use the vast amount of literature that exists, use of more credible sources (vs “just google it”) Efficient use of resources Improved clinical care (which treatment is most effective, safest) Shaughnessy et al. Clinical Jazz: Harmonizing Clinic Experience and EBM. 1998 Ooi SL, Rae J, Pak SC. Implementation of evidence-based practice: A naturopath perspective. Complementary therapies in clinical practice. 2016 Feb 1;22:24-8. ARGUMENTS FOR Stop ineffective practices (treatments, diagnostic tools) Consistency within/across professions, communication and collaboration Promotes inquiry, continual improvement (We can’t possibly be taught everything!) Links for above examples here: The Star and The Globe And Mail ARGUMENTS AGAINST “practitioner uses only modalities or treatments that have been proven effective by empirical means” – Misconception May reduce treatment options (under studies modalities) Challenging to study complex clinical situation, complex interventions Excluded factors: can’t apply results to complex clinical situations Concerns about undermining naturopathic philosophy (less individualization, ‘lost art’) Greenhalgh. How the Read a Paper. 2001 Steel A et al. The role and influence of traditional and scientific knowledge in naturopathic education: A qualitative study. The Journal of Alternative and Complementary Medicine. 2019 Feb 1;25(2):196-201. ARGUMENTS AGAINST/LIMITATIONS OF USING EVIDENCE ALONE Studies show that on average improvement was seen, doesn’t mean your patient will benefit Doesn’t capture significance, meaning to the patient Gold standard studies are expensive and don’t always exist (undermines other type of evidence) Reduced emphasis on professional judgement, creativity DOING EIP 1. 2. 3. 4. Formulate an answerable research question (Ask) Find the best available evidence (Acquire) Critically appraise/evaluate the evidence (Appraise) Apply the evidence by integrating with clinical expertise and patient’s values (Apply) 5. Evaluate performance (Assess) CRITICAL APPRAISAL Essential to understand and critically evaluate research in order to apply it properly Conclusions from research studies may be reflect the truth All research is open to bias Presentation in the media aimed at generating attention and interest rather than accuracy FUNNY, BUT ALSO NOT FUNNY Exciting Headlines: “Study reveals that smelling your partner's farts is the secret to a longer life” Synthetic hydrogen sulphide doner chemical protects mitochondria from oxidative damage ALSO, FUNDING Bhandari M, Busse JW, Jackowski D, et al. Association between industry funding and statistically significant pro-industry findings in medical and surgical randomized trials. CMAJ. 2004 Feb 17;170(4):477-80. BACKGROUND: In this study, we examine the association between industry funding and the statistical significance of results in recently published medical and surgical trials. RESULTS: Among the 332 randomized trials, there were 158 drug trials, 87 surgical trials and 87 trials of other therapies. An unadjusted analysis of this sample of trials revealed that industry funding was associated with a statistically significant result in favour of the new industry product (odds ratio [OR] 1.9, 95% confidence interval [CI] 1.3-3.5). The association remained significant after adjustment for study quality and sample size (adjusted OR 1.8, 95% CI 1.1-3.0). There was a nonsignificant difference between surgical trials (OR 8.0, 95% CI 1.1-53.2) and drug trials (OR 1.6, 95% CI 1.1-2.8), both of which were likely to have a pro-industry result. Interpretation: Industry-funded trials are more likely (almost twice as likely) to be associated with statistically significant pro-industry findings in medical trials. SCIENCE, RESEARCH, SOME BASIC CONCEPTS SCIENCE Systematic study of the structure and behaviour of the physical and natural world through observation and experimentation. Empirical method of acquiring knowledge (accessible to sense experience or experimental procedures) SCIENTIFIC METHOD CORRELATION (VS CAUSATION) Correlation: a measurement of the size and direction of the relationship between 2 or more variables. Example of positive correlation: height and weight, taller people tend to be heavier Example of negative correlation: mountain altitude and temperature, as you climb higher it gets colder CORRELATION – VISUALLY As margarine consumption decreased, divorce rate also decreased Random chance?? SUGAR INTAKE AND RATES OF DIABETES IN THE UK SOME MORE EXAMPLES Studies show that people who have more birthdays live longer Reverse causality Days with higher ice cream sales have more cases of drowning Confounding Factor: People with depression eat a lower quality diet than people without depression Warm weather, Swimming ?? CONFOUNDING A additional variable causes the change in the dependent variable More ice cream sales → more drowning Nice weather/swimming Over weight → Life expectancy Heart Disease/diabetes CAUSATION A relationship where one variable (independent variable) CAUSES (is responsible for the occurrence) the other (dependent variable) Ex. decapitation causes death Generally, very difficult to prove a causal relationship NOT ALL ASSOCIATIONS ARE CAUSAL Associations may APPEAR causal due to: Confounding Chance: ever present randomness. Ex. flip a coin 100 times, may get 58 heads and 42 tails Bias BIAS Anything that systematically influences the conclusion or distorts comparisons Can impact any kind of research study TYPES OF BIAS: SELECTION BIAS Systematic differences between groups Likely due to inadequate randomization Ex. Research study with 2 locations: 1 location is in an upscale neighbourhood, these participants get the treatment. The other location is in an inner city neighbourhood, these participants get the placebo. Ex2. Survey of the naturopathic profession about evidence based practice. 100 NDs respond, overall largely favourable views of EBP TYPES OF BIAS: PERFORMANCE BIAS Systematic differences in the care provided apart from the intervention being assessed Ex. Participants in the treatment group spend 10 hours with the researchers, control group spends 1 hour TYPES OF BIAS: ATTRITION BIAS Systematic difference in withdrawals from the trial Ex. Participants who have a negative reaction (or no benefit) from the study treatment drop out more often than the people who find the treatment helpful. TYPES OF BIAS: DETECTION BIAS Systematic differences in outcome assessment Ex. Study of the effects of working with radioactive material on skin cancer risk. More cases of skin cancer discovered in patients who report working with radioactive material. Ex 2. A research genuinely believes that the study drug will help psoriasis. If they know who is receiving the real drug, they may underestimate when measuring the psoriasis skin lesion. TYPES OF BIAS: OBSERVATION BIAS When participants are aware of being observed, they alter their behaviour Ex. DIET DIARY! TYPES OF BIAS: PUBLICATION BIAS Studies with negative findings less likely to be submitted and published TYPES OF BIAS: RECALL BIAS When asked about things in the past, may have difficulty remembering and respond in an inaccurate way Ex. What did you eat for breakfast 10 years ago? BIAS – KEY IS “SYSTEMATIC” There will be always be random factors Ex. One day the research is tired and less observant, notices less cancer lesions (variation in detection) Ex. Some people in a study group with move away, loose interest etc ( attrition) Ex. Some people over/under-estimate their vegetable servings PRINCIPLES OF CAUSATION Temporality Strength Dose-response Reversibility Consistency Biological plausibility Specificity Analogy TEMPORALITY Cause came before the effect Some study types limited in ability to detect this (crosssectional, case-control) Ex. may do a survey of men who currently have prostate cancer and find higher fish intake – does dietary fish cause prostate cancer? VS measure fish intake and follow over time to see who develops cancer STRENGTH OF ASSOCIATION Stronger association is better evidence of cause/effect relationship DOSE RESPONSE RELATIONSHIP Varying amounts of the cause result in varying amounts of the effect A dose-response relationship is good evidence of cause/effect relationship Ex. number of cigarettes smoked per day and lung cancer risk BUT risk of confounding: heavy smokers more likely to consume more alcohol REVERSIBILITY The association between the cause and the effect is reversible Ex. people who quit smoking have a low risk of cancer STILL think about confounding: people who quit may start other healthy lifestyle behaviours too! CONSISTENCY Several studies conducted at different times, in different settings and with different kinds of patients all come to the same conclusions Some inconsistency does not invalidate other trials – look at trial design and quality BIOLOGICAL PLAUSIBILITY If the relationship between cause and effect is consistent with our current knowledge of mechanisms of disease When present, strengthens the cause for cause/effect Ex. cigarette ingredients cause cancer in cell cultures, animal models Challenges with homeopathy, energy medicine SPECIFICITY One cause → one effect (A only causes B) Vitamin c deficiency → scurvy Absence of specificity is weak evidence against cause; ex, smoking causes cancer, bronchitis, periodontal disease ANALOGY Cause and effect relationship is strengthened if there are examples of well established causes that are analogous to the one in question Ex. if we know a virus can cause chronic, degenerative CNS disease (Subacute Sclerosing Panencephalitis) it is easier to accept that another virus might cause degeneration of the immunologic system (e.g. HIV and AIDS) Analogy is weak evidence for cause GROUP ACTIVITY A few sample observational studies: think about possible confounding factors Assess studies based on the principles of causation Consider the types of conclusions that can be drawn WRAP UP AND QUESTIONS ANY THOUGHTS OR INSIGHTS OR N E W P E R S P E C T I V E F R O M T O D AY ’ S M AT E R I A L ?