A12 PREVMED MAIN HANDOUT APRIL 2024 DAWN CASUNCAD-16-20.pdf

TOPNOTCH MEDICAL BOARD PREP PREVENTIVE MEDICINE AND PUBLIC HEALTH MAIN HANDOUT BY DR. MANN For inquiries visit www.topnotchboardprep.com.ph or https://www.facebook.com/topnotchmedicalboardprep/ This handout is only valid for the October 2023 PLE batch. This will be rendered obsolete for the next bat...

TOPNOTCH MEDICAL BOARD PREP PREVENTIVE MEDICINE AND PUBLIC HEALTH MAIN HANDOUT BY DR. MANN For inquiries visit www.topnotchboardprep.com.ph or https://www.facebook.com/topnotchmedicalboardprep/ This handout is only valid for the October 2023 PLE batch. This will be rendered obsolete for the next batch since we update our handouts regularly. Step – 4: Choosing the study design • The research design is the blueprint or framework for fulfilling objectives and answering research questions. Step – 5: Deciding on the sample design • Sampling is an important and separate step in the research process. • The basic idea of sampling is that it involves any procedure that uses a relatively small number of items or portions (called a sample) of a universe (called population) to conclude the whole population. Step – 6: Collecting data • The gathering of data may range from simple observation to a large-scale survey in any defined population. • There are many ways to collect data. Step – 7: Processing and Analyzing Data • Data processing generally begins with the editing and coding of data. • Data are edited to ensure consistency across respondents and to locate omissions, if any. Step – 8: Writing the report – Developing Research Proposal, Writing Report, Disseminating and Utilizing Results • The entire task of a research study is accumulated in a document called a proposal. • A research proposal is a work plan, prospectus, outline, an offer, a statement of intent or commitment from an individual researcher or an organization to produce a product or render a service to a potential client or sponsor. • The proposal will be prepared to keep in view the sequence presented in the research process. The proposal tells us what, how, where, and to whom it will be done. • It must also show the benefit of doing it. It always includes an explanation of the purpose of the study (the research objectives) or a definition of the problem. • It systematically outlines the particular research methodology and details the procedures that will be utilized at each stage of the research process. When a researcher gives an active medication to one group of people and a placebo, or inactive medication, to another group of people, the independent variable is the medication treatment. Each person's response to the active medication or placebo is called the dependent variable. Dr. Mann EXAMPLE • A scientist studies the impact of a drug A on cancer B o The independent variables are the administration of the drug (manipulation of the dosage and the timing) o The dependent variable is the impact the drug has on cancer (with cure or no cure) • Chemoprotective effect of Oral VCO supplementation against breast cancer development o The independent variable is the oral administration of VCO (manipulation of the dosage in ml) o The dependent variable is the impact of oral VCO supplementation on breast cancer (preventive, not preventive) • CONSTANT – a phenomenon whose values remains the same: e.g. number of second in a minute, Pi, pull of gravity and speed of light A variable is a characteristic or feature that varies, or changes within a study. The opposite of variable is constant: something that doesn't change. In math, the symbols "x”, "y" or "b" represent variables in an equation, while "pi" is a constant Dr. Mann • SAMPLING – is the act of studying or examining only a segment of the population to represent the whole. • POPULATION o refers to entire group of individuals or items of interest in the study o collection of all elements under consideration in a statistical inquiry • SAMPLE – is a subset of the population BIOSTATISTICS DEFINITION OF TERMS • STATISTICS – science that deals with collection of data, organization of data, analysis of data, interpretation of data • BIOSTATISTICS – applications of statistical methods to the life sciences like medicine and public health. • VARIATION – refers to tendency of a measurable characteristic to change from one individual or one setting to another. Variation in clinical medicine may be caused by biologic differences or the presence or absence of disease, it also may result from differences in the techniques and conditions of measurement, errors in measurement, and random variation. Dr. Mann • DATA – the observed values of variable and or collection of observations • VARIABLE – a characteristic of population or sample that is of interest for us Independent Variable Dependent Variable Stimuli that researchers Effect of the action of independent; manipulate to create Responding behavior that a effect researcher wants to explain https://www.omniconvert.com/what-is/sample-size/ This is a diagram depicting the relationship between the population and sample. Dr. Mann Target Population Sampling Population Sampling Unit Elementary Unit or Element TYPES OF POPULATION group from which representative information is desired and to which interference will be made population from which a sample will actually be taken POPULATION CONCEPT • Unit of the population that we select in our sample • Sampling frame or frame: is a list or map showing all the sampling units in the population • Is a member of the population • an object or a person on which a measurement is actually taken or an observation is made SAMPLING DESIGNS • Is a mathematical function that gives you the probability of any given sample being drawn Office Of Research Integrity CRITERIA OF A GOOD SAMPLING DESIGN: (PERA) • Practical and feasible o Practicality and feasibility of the sampling procedure. This means that the sampling design should be sufficiently simple and straightforward so that it can be carried out substantially as planned. • Economy and efficiency o Economy and efficiency of the sampling design - that is, it must give the most information at the smallest cost. • Representative o The sample to be obtained should be representative of the population. This means that it should be reflect both the characteristics as well as the variability of the population being studied. • Adequate o The sample size should be adequate. Here, the relevant question to be answered is, “Is the sample size sufficiently large to permit reliable generalizations about the whole population?’ TOPNOTCH MEDICAL BOARD PREP PREVENTIVE MEDICINE AND PUBLIC HEALTH MAIN HANDOUT BY DR. MANN For inquiries visit www.topnotchboardprep.com.ph or email us at [email protected] This handout is only valid for the October 2023 PLE batch. This will be rendered obsolete for the next batch since we update our handouts regularly. Page 16 of 79 TOPNOTCH MEDICAL BOARD PREP PREVENTIVE MEDICINE AND PUBLIC HEALTH MAIN HANDOUT BY DR. MANN For inquiries visit www.topnotchboardprep.com.ph or https://www.facebook.com/topnotchmedicalboardprep/ This handout is only valid for the October 2023 PLE batch. This will be rendered obsolete for the next batch since we update our handouts regularly. PROBABILITY SAMPLING DESIGNS • Is a method of selecting sample wherein each element in the population has a known, non-zero chance of being included in the sample Sampling Design SIMPLE RANDOM SAMPLING (SRS) STRATIFIED SAMPLING SYSTEMATIC SAMPLING DESIGN CLUSTER SAMPLING MULTISTAGE SAMPLING DESIGN Description • Most basic type of sampling design. • Every element has equal chance to be included in sample population. • Used in studies involving relatively small populations within readily available sampling frame • Sampling method where we divide the population into nonoverlapping subpopulations or strata, and then select one sample from each stratum • The sample consist of all the samples in the different strata • Selection of the first element is at random and selection of the other elements is subsequently taking every k • Sampling interval is represented by k • kth element of the population is chosen (k=N/n, where N is the total population, and n is the sample size needed • The population is first divided into sampling units called clusters • A sample of clusters is selected • Every element found in each cluster is included in the study • There is hierarchical configuration of sampling units and we select sample of these units in stages • The population is 1st divided into a set of primary or first stage sampling units • Each primary sampling unit included in the sample is further subdivided into secondary or second stage sampling units, from which a sample will again be taken. • The procedures continue until the desired stage is reached ✔ GUIDE QUESTIONS SAMPLING DESIGNS Each individual of the total group has an equal chance of being selected. Households are selected at random, and every person in each household is included in the sample. Individuals are initially assembled according to some order in a group and then individuals are selected according to some constant determinant; for instance, every fourth subject is selected. Individuals are divided into subgroups on the basis of specified characteristics and then random samples are selected from each subgroup. A. Systemic Sampling B. Simple Random Sampling C. Stratified Sampling D. Cluster Sampling Advantages Disadvantages • Analysis of data is simple and Sampling frame is necessary easy • Sample chosen may be widely spread, thus entailing higher cuts • Drawing the sample is easy • Probability of obtaining an unrepresentative sample is higher, especially in studies of small size • Resorted to in order to increase • High transportation cost if elements the precision of the estimates of are widely spread geographically, the parameters being considered unless there are field offices in each geographic area • Drawing a sample is easier • Easy to administer in the field. • A sampling frame is may not be necessary • Gives more precise estimates than simple random sampling • May give poor precision when unsuspected periodicity is present in the population • Does not require a sampling frame of all elementary units; • Only population list of clusters is needed • Listing cost and transportation are reduced • Can be more efficient that simple random sampling, especially where a study takes place over a wide geographical region • Greater efficiency, lower cost per unit of inquiry • Sampling frame is needed in first stage sampling units • May need a bigger sample size for the study • Analysis is more difficult • May have bias • Increased rate of homogeneity (similarities and or characteristics of elements) among elements within a cluster • More complex design • Analysis may become complicated too • Quota – Sample section is based on the given quota to meet, which researchers look for a specific characteristic in their respondents, and then take a tailored sample that is in proportion to a population of interest BRANCHES OF BIOSTATISTICS Descriptive Statistics Refers to the different methods applied to summarize and present data in a form to make them easier to analyze and interpret by using methods of: • Tabulation • Graphical representation • Summary measures Inferential Statistics Methods involved in order to make generalizations and conclusions about a target population, based on result from a sample, includes: • Estimation of parameters • Testing of hypothesis DESCRIPTIVE STATISTICS Answers: BDAC TYPES OF DATA QUANTITATIVE VS. QUALITATIVE Quantitative Qualitative Categorical observation Numerical observations Provide depth and detail through Computed thru arithmetic direct quotation and careful calculations description of situations, events (numerical) interactions Interval or Ratio Nominal or ordinal (Discrete VS. Continuous) (sex, occupation, disease status) NON-PROBABILITY SAMPLING DESIGNS • The probability of each member of the population to be selected in the sample is difficult to determine or cannot be specified • Used only for descriptive purposes rather than for making generalizations or interferences about the target population. o Purposive or judgment – sample selection is based on expert’s subjective judgment or on some pre-specified criteria o Accidental or Haphazard or convenience – sample selection based on whatever item comes at hand or whoever is available o Snowballing – target population is small or hard to locate; uses chain referral technique (e.g. IV drug users) o Voluntary response – Similar to a convenience sample, a voluntary response sample is mainly based on ease of access. Instead of the researcher choosing participants and directly contacting them, people volunteer themselves TOPNOTCH MEDICAL BOARD PREP PREVENTIVE MEDICINE AND PUBLIC HEALTH MAIN HANDOUT BY DR. MANN For inquiries visit www.topnotchboardprep.com.ph or email us at [email protected] This handout is only valid for the October 2023 PLE batch. This will be rendered obsolete for the next batch since we update our handouts regularly. Page 17 of 79 TOPNOTCH MEDICAL BOARD PREP PREVENTIVE MEDICINE AND PUBLIC HEALTH MAIN HANDOUT BY DR. MANN For inquiries visit www.topnotchboardprep.com.ph or https://www.facebook.com/topnotchmedicalboardprep/ This handout is only valid for April 2024 PLE batch. This will be rendered obsolete for the next batch since we update our handouts regularly. DISCRETE VS. CONTINUOUS Discrete Continuous • Finite number of values • Usually associated with possible physical measurement • Use of whole number • Take on values that are fractions or decimals It can assume only integral It can attain any value values or whole numbers including fraction or decimals • Hospital bed capacity • Birth weight • Household-size (members) • Arm circumference SCALES USED TO MEASURE DATA • Naming or categoric variables that are not based on measurement scales or rank order. • # or symbols are assigned. Lowest form of variable: Nominal (e.g., Gender, Color, Province, occupation, skin color and blood group) • Dichotomous (binary) – which has only two levels (e.g., Yes or No, Normal and Abnormal, Male and Female) • Arranged in rank ordered categories Ordinal • (E.g., Social class, Likert scale, Satisfactory scale, agree to disagree, murmur range, level of edema) • Value of zero is arbitrary (E.g., Fahrenheit & Interval Celsius) • (+) properties of all variables; zero is fixed / Ratio absolute; Highest form; (E.g., Age, metric system) ✔ GUIDE QUESTIONS Identify whether these variables are quantitative or qualitative. If it is a quantitative variable, identify if it is discrete or continuous. If it is a qualitative variable, identify if it is nominal or ordinal. QUANTITATIVE OR QUALITATIVE? DISCRETE OR CONTINUOUS? NOMINAL OR ORDINAL? Cell counts Drug concentration Disease status Socioeconomical status Answers discussed in lecture video DATA COLLECTION • SOURCE o Primary § data obtained firsthand by the investigator for his specific purpose § data documented by the primary resource § data collectors themselves documented this o Secondary § already existing data § data that have been obtained by some other people for purposes not necessarily those of the investigators PRIMARY • Information in its original form • Reflect the view point of participant or observer of an event or phenomenon • Has not been previously interpreted, commentated or translated • Can also be sets of data which have been tabulated but not interpreted Example: National Statistics Office (now PSA) primary source of data on population, housing, and establishment You can consider a data primary if it is a raw data coming from any sources given that the data has no interpretation or analysis. SECONDARY • Provide analysis & interpretation of event or phenomenon • Subsequent interpretations or studies that are based on primary sources Example: A medical researcher’s documented data for his research paper, which were originally collected by the DOH Dr. Mann SOURCES OF DATA MOST COMMON • Censuses • Sample surveys • Registration system • Medical Records • Claims Data • Vital Records • Surveillance LESS COMMON • Continuing population registers • Voter’s registry • School roster METHODS OF DATA COLLECTION • Observation – method of collecting data on the phenomenon of interest by recording the observations made about the phenomenon or point of interest o Structured – a researcher designs a rigorous plan and formal instruments for recording interest before the actual data collection o Non-structured – the researcher has complete flexibility in performing the study and can modify the original plan at any stage of the study • Review of documents • Enumeration – Census and Sample survey o Survey – a method of collecting data on variable of interest by asking people questions. o Census – when data came from asking all the people in the population then the study is called a census o Sample survey – when data came from asking a sample of people selected from a well-defined population • Interview – formal or informal o In-person interview, telephone interview, online, mailed questionnaire, focus group • Experiments and or clinical trials – controlled study of group, method of collecting data where there is direct human intervention on the conditions that may affect the values of the variable of interest. o Registry o Case record INSTRUMENTS FOR DATA COLLECTION • Questionnaire Types: Contents: a. Self• Open-ended items: subjects use their administered own words for responses b. Mailed • Close-ended Items: have a fixed c. Face-to-face number of answer choices for interview responses d. Online • Rating scale: provides a graded scale survey showing all possible directions and e. Telephone intensity of attitude of a respondent on a interview particular question or statement • Test devices – Ex: Weighing scale, BP app, Glucometer • Checklist (for observation) CHARACTERISTICS IMPORTANT IN DATA COLLECTION 1. ACCURACY/ACCURATE o The closeness of a measured or computed value to its true value. o Trueness of test measurements The true value is sometimes called the theoretical value Dr. Mann 2. PRECISION/PRECISE o how close measurements of the same item are to each other o Consistency and reproducibility of a test o Absence of random variation in a test Remember the definition of VARIATION – refers to tendency of a measurable characteristic to change from one individual or one setting to another. Dr. Mann SUPPLEMENT: ACCURACY VS PRECISION • A classic way of demonstrating the difference between precision and accuracy is with a dartboard. Think of the Statistical data like number of bullseye (center) of a dartboard as the true value. The closer population primary lang ito dahil walang interpretation, synthesis darts land to the bullseye, the more accurate they are. or commentary from a researcher • If the darts are neither close to the bullseye, nor close to each Dr. Mann other, there is neither accuracy, nor precision (Fig. A). • If all of the darts land very close together, but far from the bullseye, there is precision, but not accuracy (Fig. B). TOPNOTCH MEDICAL BOARD PREP PREVENTIVE MEDICINE AND PUBLIC HEALTH MAIN HANDOUT BY DR. MANN Page 18 of 79 For inquiries visit www.topnotchboardprep.com.ph or email us at [email protected] This handout is only valid for the April 2024 PLE batch. This will be rendered obsolete for the next batch since we update our handouts regularly. TOPNOTCH MEDICAL BOARD PREP PREVENTIVE MEDICINE AND PUBLIC HEALTH MAIN HANDOUT BY DR. MANN For inquiries visit www.topnotchboardprep.com.ph or https://www.facebook.com/topnotchmedicalboardprep/ This handout is only valid for April 2024 PLE batch. This will be rendered obsolete for the next batch since we update our handouts regularly. SUPPLEMENT: ACCURACY VS PRECISION • If the darts are all about an equal distance from and spaced equally around the bullseye there is mathematical accuracy because the average of the darts is in the bullseye. This represents data that is accurate, but not precise (Fig. C). • If the darts land close to the bullseye and close together, there is both accuracy and precision (Fig. D). Image by Byron Inouye Precision is independent of accuracy. That means it is possible to be very precise but not very accurate, and it is also possible to be accurate without being precise. The best quality scientific observations are both accurate and precise. Dr. Mann Note: random error entails reduced precision in a test while systematic error entails reduced accuracy in a test. 3. VALIDITY o refers to the extent to which an observation reflects the "truth" of the phenomenon being measured o the data/technique should measure what it is supposed to measure • Internal validity is the extent to which the experiment is free from errors and any difference in measurement is due to independent variable and nothing else. • External validity is the extent to which the research results can be inferred to world at large – generalizability DATA PRESENTATION 1. TEXTUAL OR NARRATIVE o Discussion, analysis, and synthesis of data o Data is simply narrated, story-fashion o Used for small data sets and limited summaries 2. TABULAR APPROACH o A table is a brief and concise way of presenting large sets of detailed information using rows and columns. o It shows trends, comparisons, and interrelationships among variables. o It should be simple, direct and clear o Tables usually serve as the basis for preparing more visual presentation of data such as graphs and charts Characteristics of an Effective Table • Simple with 2-3 variables • Self-explanatory • Codes, abbreviations, and symbols should be explained in detail in a footnote • Specific units of measure for the data should be given • Totals should be provided • If the data is not original, source should be provided in a footnote at the bottom of the table Type of Table Description • Brief and simple • Not identified by table number • Seen as continuation of text, they have no ruled frame around them • number and title of the table is placed above • tables are numbered consecutively • Types 1. Master table 2. Summary table 3. Dummy table 4. Contingency table Informal table Dr. Mann 4. RELIABILITY o Reliability refers to the extent to which repeated measurements of a relatively stable phenomenon fall closely to each other o refers to consistency, reproducibility, repeatability of results; similar information is supplied when a measurement is performed more than once You measure the temperature of a liquid sample several times under identical conditions. The thermometer displays the same temperature every time, so the results are reliable. Valid Measurements = Reliable Measurements Reliable Measurements NOT ALWAYS Valid Measurements Suppose your bathroom scale was reset to read 10-pound lighter. The weight it reads will be reliable (the same every time you step on it) but will not be valid, since it is not reading your actual weight Formal table 3. GRAPHICAL APPROACH • A graph is a method of showing quantitative data using the x-y coordinate system. • The x-axis is used for classification (independent variable, e.g., time) • y-axis is used to show frequency (dependent variable, e.g., no. of cases) Dr. Mann 5. OBJECTIVITY 6. COMPLETENESS o adequacy and representativeness of the sample size o completeness of coverage o completeness in accomplishing all items in every form ✔ GUIDE QUESTIONS QUESTION https://www4.uwsp.edu/psych/stat/4/graphing.htm PARAMETER DEFINED BY THE QUESTION How close a measurement is to the true value? How close the measurements are to each other Are the values describing what was supposed to be measured? Are the results valid for the study subjects? Are the results valid for the population from which the sample was drawn? Will one get the same values if the measurements are repeated? Random errors decrease what? Systematic errors decrease what? I know this is very basic, pero baka sa kaba mo makalimutan mo (hehehe) Y axis yung pataas, tignan mo ang letter “Y” patayo (hahahahha) tapos yung “X” axis siya yung nakahiga na line. (Yung EX mo na mahilig humiga) Dr. Mann Characteristics of an Effective Graph • It should be simple and self-explanatory • Label titles, axes, source, scales and legends • Each variable should be clearly differentiated by legends • Ensure that scales for each axes is appropriate for the data • Minimize the number of coordinate lines • Define all abbreviations and symbols • Note all data exclusions • If the data is not original, source should be provided in a footnote at the bottom of the table Answers discussed in lecture video TOPNOTCH MEDICAL BOARD PREP PREVENTIVE MEDICINE AND PUBLIC HEALTH MAIN HANDOUT BY DR. MANN For inquiries visit www.topnotchboardprep.com.ph or email us at [email protected] This handout is only valid for the April 2024 PLE batch. This will be rendered obsolete for the next batch since we update our handouts regularly. Page 19 of 79 TOPNOTCH MEDICAL BOARD PREP PREVENTIVE MEDICINE AND PUBLIC HEALTH MAIN HANDOUT BY DR. MANN For inquiries visit www.topnotchboardprep.com.ph or https://www.facebook.com/topnotchmedicalboardprep/ This handout is only valid for April 2024 PLE batch. This will be rendered obsolete for the next batch since we update our handouts regularly. Type of Graph Nature of Variable Function This is the simplest and most effective way to present comparative data. It uses bars of the same width to represent different categories of a factor Qualitative-categorical or Discrete Quantitative • Comparison of absolute or relative counts, rates etc. between Categories Qualitative variable • Comparison between 2 population or distribution; alternative to pie charts Bar Graph Dr. Mann COMPONENT/STACKED bar graph Rural Urban HORIZONTAL BAR Qualitative • E.g. Leading cause of mortality • usually presented as Counts 2… 2… Quantitative variable showing changes with passage of time • Design with spaces in between bar because variable is discrete; use to show trends Qualitative • Breakdown of a group or total where the number of categories is not too many (<6 categories) • Sum of all proportion must be equal to 100% • Conventionally, pie charts begin at 12 o’clock. • The wedges should be labeled and arranged from largest to smallest, proceeding clockwise, although the “other” or “unknown” may be last. • Shading may be used to distinguish between slices but is not always necessary. Continuous quantitative • Frequency distribution of continuous variable or measurement including age group; 1 population, 1 distribution • E.g.: income • Used to analyze outbreak data and to show an epidemic curve 5/ 1/ 2… 4/ 1/ 2… 3/ 1/ 2/ 1/ 2… VERTICAL BAR GRAPH 1/ 1/ a. PIE CHART • A pie chart is a chart in which the sizes of the slices show the proportional contribution of each component part • Since it is difficult to gauge the area of the slices, it is important to indicate what percentage each slice represents. • The whole chart should total 100 percent Dr. Mann HISTOGRAM a graph wherein the frequency distribution is represented by adjoining vertical bars where in the cases are stacked in adjoining columns Dr. Mann LINE GRAPH Quantitative variable Time series • Trend data or changes with time or age with respect to other variables FREQUENCY POLYGON a graph created from a histogram by connecting the midpoints of the interval using a straight line instead of making a bar or filling in squares. It is very useful in comparing frequency distribution from different sets of data Quantitative continuous • Comparison of 2 population • E.g.: comparison of income in ERAP era as the income in GMA era Dr. Mann SCATTERPLOT/ SCATTER POINT/ DOT DIAGRAM Quantitative • Correlation between two quantitative variables • E.g.: comparison of birth weight to AOG Single blue square represents a single sample. Dr. Mann PICTOGRAPH Qualitative Nominal • Uses symbols or pictures. Used in showing the distribution of morbidity across a geographic area. TOPNOTCH MEDICAL BOARD PREP PREVENTIVE MEDICINE AND PUBLIC HEALTH MAIN HANDOUT BY DR. MANN For inquiries visit www.topnotchboardprep.com.ph or email us at [email protected] This handout is only valid for the April 2024 PLE batch. This will be rendered obsolete for the next batch since we update our handouts regularly. Page 20 of 79