MEASUREMENT OF ORAL DISEASE Chapter 14

EPIDEMIOLOGY AND PRACTITIONER A patient is more likely to exhibit a particular disease if he/she exhibits certain characteristics Example: an elderly man who smokes and drinks heavily is more at risk of oral cancer than one who does not CAN A PRACTITIONER GENERALIZE FROM THE RESULTS OF A CLIENT’S TREATMENT TO THE POPULATION AT LARGE?

EPIDEMIOLOGY & THE PRACTITIONER During diagnostic examination, a dental practitioner looks for existing disease and looks ahead for possibility of future disease Appropriate controls and designs allow for effective prevention and treatment

INFLUENCES IN EPIDEMIOLOGY HEREDITY BIOLOGY PHYSICAL ENVIRONMENT SOCIAL ENVIRONMENT LIFESTYLE

METHODS OF MEASURING ORAL DISEASES COUNTS PROPORTIONS RATES INDEXES

COUNTS The simplest form of measuring oral disease Most useful with unusual conditions of low prevalence Becomes less useful as prevalence escalates

PROPORTIONS A count can be transformed into a proportion by adding a denominator, thus determining prevalence Example: 22 cases of cancer in a population of 845 men (ages 55-65) yields a prevalence of 2.6%

RATES A proportion that utilizes a standardized denominator including a time dimension Example: infant mortality rate for white children declined (1985 - 9.2 per 1000 live births) (1992 - 6.9 per 1000 live births)

REVERSIBLE INDEX IRREVERSIBLE INDEX measures cumulative conditions that CAN be reversed measures cumulative conditions that CANNOT be reversed

PROPERTIES OF AN IDEAL INDEX VALIDITY RELIABILITY CLARITY & SIMPLICITY QUANTIFIABILITY SENSITIVITY ACCEPTABILITY

VALIDITY Measures what it is intended to measure CONTENT VALIDITY - measures extent to which an instrument thoroughly represents knowledge in the selected content area CRITERION VALIDITY - compares newly developed instrument with pre-existing valid and reliable instrument in order to evaluate accuracy and appropriateness of new instrument

RELIABILITY Measures consistently at different times Example: Two examiners must find the same 3 occlusal caries on 1st molars in Child A. If they examine Child A an hour later, they should still find the same occlusal caries as detected previously

INTRARATER & INTRAEXAMINER RELIABILITY Each examiner is scoring equivalently (consistently) time and time again with each measurement taken This has been described as “the extent to which the same investigator remains consistent in scoring techniques when using a data collection instrument” (Drury) Example: examiner records conditions in a group of 10 to 20 individuals and then repeats the process a few hours or days later

INTERRATER & INTEREXAMINER RELIABILITY Consistency exists between examiners If different examiners were to measure the same population, the data (results) collected would be the same Examiners must have an initial and continued agreement on interpretation of evaluative criteria Training with repeated use of dental index on subjects is required to achieve reliability Calibration among examiners ensures that each will measure the data in the exact same manner

TYPES OF SCALES USED TO MEASURE DISEASE NOMINAL – observations fitted into mutually exclusive categories ORDINAL – ranking characteristics INTERVAL – equal intervals along scale – has no absolute 0 RATIO – presence of absolute 0 Nominal – republicans/ democrats; males/females; smokers/non-smokers; pass/fail; normal/abnormal Ordinal – student A highest score 1/ student B second best 2; strongly disagree, disagree, agree, strongly agree (Likert scales) Interval – Fareinheit thermometer Ratio – age, weight, height

TYPES OF SAMPLING METHODS IN THE COMMUNITY PROBABILITY NONPROBABILITY SIMPLE RANDOM STRATIFIED RANDOM CLUSTER SYSTEMATIC QUOTA CONVENIENCE

NONPROBABILITY SAMPLING Different units in the population have equal probabilities of being chosen NONPROBABILITY SAMPLING Cannot identify or do not have access to the entire population of interest

SIMPLE RANDOM SAMPLING Each item or person in the population of interest has an equal chance of being selected A fair way to select a sample Not the most statistically efficient method of sampling since you may not get good representation of subgroups in a population.

STRATIFIED RANDOM SAMPLING Method of sampling used to represent subgroups proportionately in the sample when they are known to exist in the population Would you rather use Stratified Random Sampling in the community over Simple Random Sampling? If so, why?

CLUSTER SAMPLING Drawback: When sampling a population that is disbursed across a wide geographic region, a lot of ground geographically will have to be covered in order to get to each of the units sampled.

SYSTEMATIC SAMPLING This is a random sampling with a system It spreads the sample more evenly over the population Example: drawing every ‘nth” subject from a list of the total population Example: want to sample 8 houses from a street of 120 houses; every 15th house is chosen

QUOTA SAMPLING Like stratified sampling, the researcher first identifies the stratums and their proportions as they are represented in the population Then convenience or judgment sampling is used to select the required number of subjects from each stratum Quota Sampling is a type of CONVENIENCE SAMPLING

CONVENIENCE SAMPLE Subjects are recruited as they arrive and the researcher will assign them to demographic groups based on variables like age and gender. When the quota for a given demographic group is filled, the researcher will stop recruiting subjects from that particular group. This type of method is often used during preliminary research efforts to get a gross estimate of the results – saves cost and time This is done when access to total population is not feasible

EXAMINATION TO CHECK RELIABILITY Consist of repeat examinations only hours apart; too close together for real change to occur OCCURRENCE OF NEGATIVE & POSITIVE REVERSAL Occur over a period of time long enough for real change to occur

CRITERIA FOR IDEAL DIAGNOSTIC TESTS Simple Inexpensive Acceptable to Client Valid Reliable Sensitive Specific