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165 Cards in this Set
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What is Health Research |
Process of systematically investigating a single well-defined aspect of physical, mental or social well-being |
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Research |
process of systematically and carefully investigating in order to learn or discover new info |
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Health |
construct that extends over all aspects of physical, mental and social well-being |
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What do health researchers examine? |
Biological, SES, and environmental factors that contribute to health and to disease, illness, etc. Studies range from lab research, clinical trials, or broad surveys |
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Lab studies vs population studies |
controlled setting vs human subjects |
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Objectives of Population health research |
ID and Classify new problems Determine RF for disease Evaluate impact of health policy on health outcomes Develop and test new interventions for preventing disease (IDED) |
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Examples of lab research |
Compare tests of air quality in several metro areas Analyze the biochem composition of foods Develop a new vaccine |
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Examples of pop research |
Conduct a vaccine trial ID RF acquiring drug resistant bacterial inft |
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Goal Health Research |
Make discoveries to benefit society as a whole, generally modest in contributions |
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Positive outcomes from research |
Acquire new skills Satisfy personal fulfillment of degree or work Publish possibility that this research may contribute to at lease some small way to making at least one person better |
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Social Benefits Vs personal benefits |
Social are overall whole pbig picture, personal is own personal goals, requirements, rewards (such as new knowledge) |
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Research requires |
patience, carefulness, attention to detail, perseverance, willingness to learn all requisite knowledge, ability to criticize and revise yourself |
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Research process |
ID study question Select study approach Design study and collect data Analyze data Report Findings |
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Publication depends on |
The appropriateness of the research topic for the whole audience How well designed the study is and whether it uses valid methods How compelling and well written
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ID Study Question |
Selecting a general topic Reviewing lit Focusing Assembling support team |
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Selecting a general topic |
Brainstorming and topic mapping, create long list of possible topics, refine by utilizing key word searches |
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Brainstorming |
Look at areas of value, skills, personal growth, connections, Job/course requirements, and Gaps in Literature |
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MeSH? |
Medical Subject Headings-database developed by the US Library of Medicine, can be helpful to narrow down scope of research |
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Exposure examples |
SES (income, wealth, educational level), HEalth related behaviors (diet, hygience, exercise), Health status (immune status, genetics, stress) or environmental (water, air, home, natural disasters) |
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Disease examples |
Injures, communicable diseases/infections, chronic diseases, neuropsychiatric disorders |
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Divide lists by |
one exposure, one disease/outcome and one population to hone research scope |
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Reviewing literature |
Purpose is to do background reading on topic. Start with informal and move onto formal to aim and scope our study question |
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Where to start reviewing lit? |
Factsheets (WHO, CDC) Websites, and informal sources. Disease prevention advocacy websites...always find the original source data. Next look at statistical reviews use web searches but trace back to original source. |
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Abstract database |
Allow you to sort through many abstracts through search...careful and comprehensive. PubMed, CINAHL, MEDLINE, are some good ones |
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Full Text Articles |
Full text articles follow abstract review. Reread abstract, look at figures and then read article |
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What makes research orginal |
inserting just one new dimension or rf or outcome...can make it original. E/D/P Look for a gap |
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Focusing Research Question |
Develop a specific, workable research question. Study approach decision, primary, secondary, or tertiary study. |
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Primary Study Approach features |
What are possible source populations, Will it be possible to have enough participants |
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Secondary Study Approach features |
What are usable data files. What questions can be explored with available data? |
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Tertiary Study Approach |
Does research have access to library. Can research reasonable expect to acquire ALL needed articles |
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Study Goals and specific objectives |
After determining overarching study goal, you should id at least three or more specific objectives, aims or hypotheses that stem from the main study goal. Measurable question or to statement (use action verbs). Provide a clear pathway to objective (QA) |
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Checklist for success |
Questions essential to success examples: What will study contribute? Do I have access to data or can I obtain data? Who is interested in findings? Will it get published? |
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Support team consists of: |
Supervisor or mentor (experienced researcher), expert on topic, expert on study design or methods, statistician other key contributors |
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Core collaborators |
lead researcher, advisor, study design/stats expert, topic expert (SME), cultural expert, other key contributors |
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Additional tech support |
Lab techs, librarian, stats, other technical necessities |
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PErsonal support |
Friends/family and co-workers |
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Authorship ownership |
First author or lead author is person most involved, remaining are listed in order of contribution. Hash it out before starting |
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Conditions of authorship (three required) |
Substantial contributions to concept or design and/or acquisition of data, and/or analysis and interpretation of data AND drafting of article and/or revising it critically for intellectual content AND final approval of version to be published |
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ICMJE |
International Committee of Medical Journal Editors-established criteria for authorshipin health sciences. |
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Examples of authorship |
A person who conducts interviews but no further would not meet requirements, but a person who interviews and writes a paragraph would meet criteria. Lab tech that analyzes but no more would not be eligible, but analyzes and writes would be |
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Study approaches (8 types) |
Review/meta analysis (tertiary), ecological study (secondary), Case Series, Cross Sectional, Case-Control, Cohort, Experimental (all the rest are p/s) and Qualitative (primary) |
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Review/meta goal |
synthesis existing knowledge |
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Ecological or correlation study goal |
Compare average levels of exposure and disease in several populations |
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Case series goal |
describe a group of individuals with a disease |
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Cross Sectional Survey |
Descrive E and /or D status in a population (p study) |
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Case-control study goal |
Compare E histories in people with D (cases) and people without disease (controls) |
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Cohort study goal |
Compare rates of new (incident) disease in people with different exposure histories or follow a population forward in time to look for incident diseases |
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Experimental study goal |
Compare outcomes in participants assigned to an intervention or control group |
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Qualitative study goal |
Seek to understand how individuals and communities perceive and make sense of the world and their experiences |
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Which study designs select participants based on disease status |
w/out comparison group case series, w/comparison case-control study |
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Which study designs select participants based on exposure status? |
Cohort Study |
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Which study design select participants based population? |
Cross-sectional (one point in time), Cohort (multiple points in time, observe exposure) Experimental (multiple points in time, assign exposure) |
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Correlational (Ecological) Studies |
Uses population level data to examine the relationship between exposure rates and disease rates |
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Ecological study Objective, primary question, population |
Objective is to compare average levels of exposure and disease in several populations Primary question-Do populations with a higher rate of E have a higher rate of disease? Population-existing pop-level data, no individual participants |
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When to use Ecological approach |
When aim is to explore possible associations between an E and a D using pop level data. Do not do if topic has been previously explored using individual level data |
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First steps Ecological study |
Select data sources and decide on variables to include in analysis |
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What to watch out for in correlation studies |
Ecological fallacy, limited publication venues |
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Key statistical measure in correlational studies |
correlation |
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For Correlational studies the data is entered into the spreadsheet |
Population gets own row and each O/E gets its own column
Pop |
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Scatterplot tells correlations |
Strong-neatly in line Moderate-not neatly in line, but trend can be drawn Weak/nonexistent-random, no obvious line can be drawn |
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Slope in correlational studies on scatterplot |
positive slope is higher levels exposure liked to higher disesase negative slope is protective or higher levels of exposure are linked to lower levels of disease |
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Continuous variables vs ranked variables |
It can be plotted on number line, use Pearson correlation coefficient (r)-continuous Use Spearman rank-order correlation (r or rho) |
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Correlational variables and what they show |
range from -1,1. when r =-1 all points lie perfectly on a line with a negative slope, r=1 all points lie perfectly on a line with a positive slope, r=0 no association between e and o |
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Can report two or more variables using in correlational studies: |
r squared |
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R squared in correlational studies |
0,1 range 0 no association 1 strong association |
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Correlational studies do not measure |
intercorrelation or examining whether two or more variables part of a survey instrument measure the same thing |
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Age Adjustment in ecological studies: |
Use direct age adjustment requires knowing exposure and disease by age group in a pop Indirect age adjustment-know age distributions but not age-specific rates of exp/disease |
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Ecological Fallacy |
Compare groups in ecological studies not individuals, the incorrect attribution of population level associations to individuals |
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Case SEries |
It describes one person or patient, a case series describes two or more who have the same disease condition or who have undergone the same procedure |
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Case Series Objective |
Describe a group or individuals with a disease |
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Case Series STudy Question and Populations are |
What are the key characteristics of the cases in the study? All individuals in the study must have the same disease or be undergoing the same procedure |
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When to use case series approach and requirements of a case series |
Use it when a source of cases is available and no comparison group is available or required Must have an appropriate source of cases |
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Steps of case series: |
1. Specify what new and important info the analysis will provide 2. ID Source of cases 3. Assign a case Definition 4. Decide on the characteristics of the study population |
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What to watch out for in case series and key statistical measure |
A lack of generalize ability Uses only descriptive stats |
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Case Definition in case series: |
Use existing ICD codes or international classification of diseases codes and add to it items such as person place time characteristics relevant to disease. If doing outbreak investigation must have this no matter what approach |
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Case series special considerations |
Can be primary or secondary data. Using interviews or qualitative techniques. Supplemented with medical records (can be limiting as they are geared towards time of appointment/collection of data). |
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Case series special requirements: |
Must be approved by ethics committee, informed consent from participants and/or the careful use of existing records. Protect ID of participants. Really important when rare disease is being looked at and it would be easy to establish who is who from the study |
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Case series Analysis |
Most case series do not require numbers are more descriptive, but can benefit from mortality and morbidy measures |
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Case Fatality rate is: |
proportion of persons with a particular disease who die as a result of that condition |
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Crude mortality rate |
proportion of general pop who die of any condition during a specified period of time |
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Proportionate mortality rate |
proportion of deceased members of a pop whose death was attributable to a particular cause |
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Cross sectional Study Approach |
Survey provides a snapshot of the health status of a population at one point in time. Prevelance studies are among the most popular study approaches in health sciences because of a rapid collection of data (in comparison) |
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Cross Sectional objective and primary study question. |
Describe the E and/or D status in a populations What is the prev of the E and/or D in the population? |
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What is a cross sectional population, when do you use this approach, and what are the requirements |
Rep of the pop from which drawn for study Time is limited and or budget is small use this E/O are common and likelihood you could recruit several hundred is high |
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Steps cross sectional population |
Define source pop, develop a strategy for recruiting rep sample and decide on methods to collect data |
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Cross sectional survey, what to watch out for and key measure of stats |
Non reps of study pop prev |
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Prevelance rate in cross sectional studies |
Measure prev of various demographic characteristics, exposure histories and disease status. Reported as prev rate or proportion of the population with a given trait at the time of survey (point in time study) |
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Comparative measures in cross sectional surveys |
Prev ratios may be used to compare prev of a characteristic in two population subgroups. No time=no causality use...associated or related to a disease, not cause |
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Case-Control Studies |
Case control study compares the exposure histories of people with and without a particular disease in order to id likely rf for disease |
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Case-control object, study question and population |
Objective: Compare E histories in people with D and people without D Question: Do cases and controls have different exposure histories Population: Cases and controls must be similar except for the D status |
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When to use case control |
Rare D, but source is available |
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Requirement and steps to case control |
A source of cases available ID source of cases Assign case definition Decide what type of control pop will be appropriate matching decision (three types) |
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What to watch for in case control |
REcall bias and misclassification bias |
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Key stat measure for case contrl |
OR ac/bd as
disease exposure yes no yes a b no c d |
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Case control overview |
Best approach for RFs, rare D this is esp true Uses OR, selects based on disease status (yes=cases; no=controls) |
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Cases vs controls |
Cases are selected first from source (such as hospitals, disease registries, specialty clinic---be aware PII and HIPPA); inclusion and exclusion same for both except D status or D related characteristics |
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Matching types (no matching and frequency (group) matching |
no matching-duh (assumed that the inclusion and exclusion take care of distributing cases and controls similarly in study) frequency (group) matching-few variables to ensure comparable case and control variables. (like selecting based on sex, same week of exposure or hospital admittance, and close or similar age), no individual matching occurs
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Last type of matching matched pairs (individual matching) |
particular to genetic studies, matches siblings...personally linked cases to controls |
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Misclassification bias |
Cases classified as controls and vice versa. Combat with questionnaire and practices to ensure correctly classified |
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Recall bias |
situation that occurs within cases being more concerned about finding out why and recalling things more so than controls or wanting to recall things and thinking of it incorrectly |
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OR |
OR >1 risk OR<1 protective OR =1 same for controls and cases |
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CI |
CI that overlaps OR=1 means no stat sign or association CI >1 risky OR is stat sign CI <1 protective OR is stat sign |
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Case Control rates of disease |
Cases and controls not rep of entire pop so rates are not calculated |
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Case controls measure |
The odds of exposure among the diseased and not diseased...i.e. those with X exposure have greater odds of having D or no D |
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Matched case OR |
Because are matched and have same history of exposure, use the just b/c, but only when discordant exposure status are available |
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Qualitative Study |
Looks for themes and meanings that emerge from the observation and evaluation of a situation or context |
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Particpant observor |
when research gains access to community and immerses in it to collect and understand |
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Phenomenology |
seeks to understand how participants understand, interpret, and find meaning in their own life experiences and feelings |
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Grounded Theory |
inductive reasoning process that uses obs to develop general theories to explain human behavior |
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Ethnography |
develop an insider's view (emic) rather than an etic or outsider's view of how members of a particular group see the world |
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Two common ways to collect qualitative data are: |
Focus groups and indepth and semi structured interviews |
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Focus groups |
4-12 people are moderated discussion led by led by research team facilitator. Encourage interaction and dialogue, record and interpret from these |
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interviews (indepth and semi structured |
open-ended questions to explore views and gain fuller understadings |
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Qualitative research uses |
STand alone or use in conjunction with quantitative |
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Consensus methods |
Used as a way to deliberate common areas of thought and contentious ones. The reults are used to select research priorities, id best practices, or agree on POA |
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Delphi method |
Consensus method that structures decision making and forecasting process to engage participants of panel in individual questionaires, facilitator summaries and sharing of responses and panelist reconsidering perspectives after listening to opinions of others. Goal is to move closer to agreement |
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Program evaluation |
approaches for examining the goals, process, and/or outcomes of projects, programs, or policies |
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Goal of program evaluation |
Provide feedback about what is working well and what can and should be improved, no just a simple ID correct and incorrect |
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SWOT |
Strenghts (internal strengths), Weakness (internal limitations), Opportunities (external strengths), Threats (external limitations) |
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Cohort Studies Types |
Prospective, Retrospective, Longitudinal |
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Prospective/Retrospective Objective, study question, population |
Ob: Compare rates of new (incident) d in people with different exposure histories Question: Is E associated with an increased incidence of D Population: Similar except E status, no d at start |
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Longitudinal Objective, study question, population |
Ob: Follow a pop fwd in time to look for new (incident) D Q: Is E associated with an increase in I of D P: Followup availability for participants, reasonable rep sample |
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When to use longitudinal vs retro/pro |
R/P use when exposure is uncommon, but you have a source and Long when looking at multiple E and have time and money |
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Cohort What to watch out for |
Dropouts of study, Information bias in R/P studies. Calculating Risk Ratio or RR |
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Cohort measurement time minimums |
One at baseline and one at followup (to determine E and D status) |
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Retro/Pro |
Exposure in search of a Disease (recruited based on exposure status (cases are E) and controls are without E. |
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Difference b/w Retro and Pro |
When baseline measurements are established...in retro baseline was collected some time in the past, pro at baseline it is collected and followed forward. |
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Longitudinal |
Follow people forward, but do not recruit based on exposure status, recruited based on membership in a well defined population. Must be a rep sample of study pop |
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Fixed vs Dynamic pop in longitudinal |
fixed one time shot at participation, dynamic is rolling and followup is measured at intervals not fixed times |
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Special considerations |
Retro-based on availability of data and results or on how likely you can get people to participate and contact them. Pro-do you have an E source and -E source Long-do you have a source population How often and when to collect data for followup |
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Information bias |
Exposed are vetted harder than unexposed |
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Incidence rate information |
Goal of Cohort Studies Number of new cases/number of people at risk during specified period of time Uses person years as a way to account for it...follow how you determine years of contribution |
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Attributable Risk Percent and Attributable risk |
proportion of Incident cases amount the exposed that are due to exposure. (Ie-Ine)/Ie AR is Excess Risk, and is Ie-Ine how much is attributable to the exposure (how much can we get rid of) |
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RR (rate ratio, relative risk, risk ratio, or relative rate) |
Ie/Ine...RR=1 no association RR>1 risky Ie was higher that Ine RR<1 protective, Ie was lower than Ine |
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RR CI |
same as OR |
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Experimental Study Objective, question, pop, and when to use |
OB: Compare outcomes in participants assigned to an intervention or control group Q: Does E cause the outcome Pop: similar pop are randomly assigned Case or control or intervention or control When: Assessing Causality |
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Requirement Experimental STudy |
Ethically Justifiable |
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Key stat measure for exp |
Efficacy |
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Exp vs Obs |
Exp does things to participant, obs does not. Exp assigns an exposure and measures, obs looks for an exposure and measures |
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Experimentals is the gold standard for |
Causality |
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Randomized Controlled Trial (RCT) |
Randomly assigned to an active intervention group, remaining are control group, follow forward in time and see who has favorable outcome and who does not |
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RCT Definitions |
Intervention, how participants are randomized, control is appropriate, and favorable outcome criteria |
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Most Exp are designed to show: |
superiority, showing a new intervention is better than some type of control |
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Types of successes |
Superiority-intervention > control Noninferiority trial-intervention is not worse than the control Equivalence trial-intervention=control |
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Must carefully define what makes a favorable outcome... example
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Favorable outcome could be weight loss and maintain a certain percentage, better quality of life, infection incidence is lower in trial than control |
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Types of controls |
Placebo (sugar pill, sham intervention, saline injections) Standard of care (active comparison) when ethically correct to do Dose response-some dose some period of timevs alternate doses and alternate periods of time No intervention-new alternative vs maintaining Self-new intervention-stop at some point comp |
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Hawthorne effect |
participants change behavior during study and skew results |
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Crossover Design |
Assign some new and some control then swap and compare individuals |
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Blinding or masking |
Single blind and double blind to ensure information bias is minimized (single is patient does not know and double is patient and researcher does not know which intervention is received |
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When blinding is not possible what do you do? |
Establish concrete objective measurements (lab tests) to determine favorability and do not rely on self reported feelings or subjective outcomes |
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Randomizing types |
Simple-coin Block-randomly assigns groups of people to a control group (good for population comparisons like schools or communities) Stratified-block and then simple. Assign individuals in study to subgroups such as males or females, ages...etc) and then use simple randomization with each block |
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Ethical principles |
Equipoise, distributive justice, respect for persons, beneficence and nonmaleficence considerations |
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Equipoise is: |
only conduct experimental research when genuine uncertainty about which treatment is better |
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Distributive justice |
implies that source pop must be an appropriate one and that the research will not exploit one group low income, that can't access continuation of care if treatment works |
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Respect for persons |
1) volunteer without being bribed 2) understand that they are a research subject and may be assigned control as opposed to new intervention |
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Beneficence and nonmaleficence |
Requires researcher to balance benefits and risks of study. Moniter for adverse reactions and know when to stop. Are the benefits of the new intervention so successful that keeping it from the control would be unethical. Are the outcomes of the control group so impacted that discontinuation is necessary |
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Measures of exp |
Efficacy-proportion of individuals in control group that experience unfavorable outcome that would have experienced favorable in control group. NNT or number needed to treat tells us how many people are expected to have treatment to prevent an unfavorable outcome in one person-small indicates more effective |
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NNH number needed to harm |
number of people who would need to receive treatment in order to expect that one of them would have an adverse outcome. Large NNH indicates effective treatment (fewer people harmed) |
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Ways to measure Treatment received vs treatment assigned |
treatment received only measures those that who followed all protocols, treatment assigned includes all participants. Received is an idealistic measurement and assigned is more real-world oriented measurement |
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Sensitivity |
proportion of people who actually have D that test P: Test positive and are positive/(Test positive with disease+test negative with disease) so it is the number that test positive and are positive over the total number with disease |
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Specificity |
proporition of people who do not have D that test N. Test Negative and are negative/(test negative and are negative + test positive but are negative). |
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Positive predictive value |
proportion of those who test positive that actually have disease. Test positive are positive/(test positive are positive+test positive are negative (False Positive) |
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Negative predictive value |
proportion of those that test negative and are negative. Test negative are negative/(test neg are neg+test neg are positive) |
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Kappa STatisitic |
Used to determine how closely two independent assessors reach similar conclusions |
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Inter-observer agreement orconcordance |
MEasures validity and consistency of assessment tools |
