Basis Glossary
Actor-observer effect: The tendency to attribute our own behavior to situational causes and the behavior of others to personal factors.
Attributions: Inferences people make about the causes of behavior or events; explanations for why behaviors or events occur.
Attribution theory: The study of how people understand and explain the causes of behavior.
Bogus pipeline: An experimental paradigm where researchers claim to have the ability to measure accurately or to confirm hidden information about the participants. This approach is based on the idea that participants who believe researchers will be able to expose any untruthful responses are more likely to be truthful in their answers and open about socially undesirable attitudes.
Chi-square test: A statistical tool that determines the probability of obtaining the observed results by chance under a specific hypothesis, or proposed assumption
Closed (close-ended) question: A type of question asking the respondent to choose an answer from a specified list.
Cognitive disinhibition: A personality trait characterized by impulsive behavior, sensation seeking, and disregard for consequences. Cognitive disinhibition is independent of behavioral disinhibition – the ability to inhibit responses.
Cognitive restructuring: A method of treatment in which participants are taught to recognize and correct distorted cognitions that contribute to their problem.
Confidence Interval: The range of values that will include the population parameter based on information from a single sample of the population. The population estimate from a sample is only one of the many estimates possible from all samples of the same size drawn from the same population. The sampling error or standard error estimates the amount of variation in the sample estimates. Random errors follow a normal (bell-shaped) distribution and therefore, the proportion of observations within segments can be calculated. For example, 95% of all the values are in a range that is 1.96 standard units on either side of the midpoint. A 95% confidence interval indicates that there is a 95% chance that the interval contains the actual population value.
Confirmation bias: The tendency to seek, interpret, and create information that verifies existing beliefs.
Confounding: This occurs when the apparent relationship between a predictor and outcome is influenced by other factors, some of which might be unmeasured or unrealized. Scientists can use study designs and analytic strategies to control for confounding in their research.
Control: Researchers design experiments to eliminate (control for) the effect of non-experimental variables on the results. For example, a study may compare the outcomes of two groups that differ only because one received the experimental condition and the other did not (the control group). Medication trials are often “placebo controlled” by using a control group that is treated similarly in all ways except they receive a non-active medication (placebo) instead of the active medication being studied.
Cross-sectional study design: A survey of a population measuring risk factors and disease outcome at the same moment in time.
d score: Cohen (1988) defined d as the difference between the means.
DeFries-Fulker regression model: Used to estimate genetic heritability of and shared environmental influences on a behavior. The model uses one sibling’s behavior (S1) and the degree of genetic relation between siblings to predict the other sibling’s behavior (S2). The unstandardized coefficient associated with S1 provides the amount of variance in S2 accounted for by shared environment, and the unstandardized coefficient associated with the interaction between S1 and sibling relationship provides the amount of variance in S2 accounted for by heritability.
Dizygotic: Derived from two separately fertilized eggs
Dorsolateral: Of, relating to, or involving both the back and the sides.
Double-blind:: Neither researcher nor participant know experimental condition.
DSM-IV: Diagnostic and Statistical Manual aims to systematize and standardize the definitions of mental disorders developed by the American Psychiatric Association.
Dysthymia: A mood disorder characterized by long-term depression.
Ego-defensive bias: The tendency to take more credit for success or good behavior than for failure or bad behavior.
Enzyme: Any of numerous complex proteins that are produced by living cells and catalyze specific biochemical reactions.
Epidemiological study: Research on the incidence, distribution, control, and/or cause of diseases, health trends, or disorders by studying populations.
Excitatory: Promoting the action of (an)other neuron(s); increasing the probability that a postsynaptic neuron will fire.
fMRI: (Functional Magnetic Resonance Imaging) An imaging of the brain using MRI technology, fMRI scan uses radio waves and a strong magnetic field to measure the levels of blood in specific parts of the brain.
Factor Analysis: Data reduction technique that analyzes the relationships among a set of variables in order to identify clusters that vary together as a group. Each cluster consists of several measures of the same underlying dimension (or factor) and the common information can be largely or entirely explained by a single composite of the several variables in the cluster
False consensus effect: The tendency to overestimate the consensus of our own opinions, attributes, and behaviors
Fisher’s exact test: This statistical test measures the likelihood that the proportion of cases distributed across two cells (e.g., Yes or No) in two independent groups (A and B) could have happened by chance if the two groups were sampled from the same population. Fisher's exact test computes the probability (p) of obtaining the observed arrangement of “yeses” as compared to obtaining each of all the possible arrangements of “yeses” in the two groups. In the case below (see figure 1), the probability of observing a difference in proportions as great or greater than 2 of 8 versus 3 of 7 is .427. Fisher’s test is an “exact” test because the actual number of ways in which the “yeses” and “nos” can be arranged is an exact calculation (particularly with small samples, the most common use of the test).
Figure 1 - Fisher’s Exact Test
Fundamental attribution error: The tendency to focus on the role of personal causes and underestimate the impact of situations on other people’s behavior
Gambling levels: Public health systems often assign levels to phenomena of interest; For example first and second degree burns. The gambling level system is a public health tool that classifies people along a gambling involvement continuum. This continuum often begins with healthy gambling behavior that does not produce any adverse reactions. On the other end of the continuum is gambling behavior with the most serious adverse consequences.
Level 0: People who do not gamble
Level 1: People who gamble with no adverse consequences
Level 2: People who gamble with any of a wide-range of adverse reactions or consequences that do not qualify the gambler for the most serious form of gambling disorder; level 2 gamblers represent people who may be moving in either of two directions: toward an increasingly disordered state (level 3) or toward a healthier level of gambling (level 1)
Level 3: People who gamble with adverse consequences that are sufficiently serious and co-occurring so as to meet diagnostic criteria
Level 4: People who seek help for gambling problems regardless of the extent of their problems or distress
Generalizable: Result of a study are generalizable if they can be applied to populations other than just the study sample.
Gold standard: An independent criterion that can validate the presence or absence of a disordered state.
Hazard rate: This statistic is the probability per unit of time that a case will exhibit the target condition in a given time interval. The hazard rate is computed as the number of failures per time unit in the time interval, divided by the average number of surviving cases at the mid-point of the interval. For example, if 100 cases were followed for seven years and an average of one person per year failed (exhibited the condition) you could easily estimate that the probability of getting the condition is 1 in 100 annually. However, the denominator (100) is not quite right because after the first year there were only 99 people at risk, and only 98 after the second year, etc. So using as a denominator the number of survivors at the mid-point (in this case, 97) corrects for the difference in denominators from year to year.
Hazard ratio: The relative difference in the Hazard Rates of separate groups can be expressed as the ratio of one to the other. (see also Odds Ratio)
Hazard ratio, adjusted: Variables other than the test condition may influence the Hazard Ratio. The Hazard Rates can be adjusted for these influential but perhaps independent measures. For example, gender may influence the likelihood of an event and comparison groups may have different gender distributions. The hazard rate could be defined based on the risk attributable to both the comparison condition and for gender and the aggregated statistics adjusted for group differences on the covariates.
Humanities: Those branches of knowledge, such as philosophy, literature, and art, that are concerned with human thought and culture; the liberal arts. (Source: The American Heritage® Dictionary of the English Language, Fourth Edition. Copyright © 2000 by Houghton Mifflin Company.)
Iatrogenic: Illness resulting from a physician’s professional activity or from the activity of other health professionals.
Illusion of control: A belief in our ability to influence events over which we have no control.
Inhibitory: Modifying, inhibiting, or suppressing the action of (an)other neuron(s); reducing the probability that a post-synaptic neuron will fire.
Intent to treat analysis: A procedure in the conduct and analysis of randomized trials. All patients allocated to each arm of the treatment regimen are analyzed together as representing that treatment arm, whether or not they received or completed the prescribed regimen. Failure to follow this step defeats the main purpose of random allocation and can invalidate the results.
Intraclass correlation: A type of correlation used when members of a pair can not be assigned to distinct variables. For example, data for wives and husbands could be organized by the two variables “wife data” and “husband data,” but data for two same sex siblings could not be assigned to variables in any non-arbitrary way. If a regular Pearson correlation were used in the latter case, it would change depending on which sibling was labeled sibling 1 or sibling 2. The intraclass correlation does not rely on the order of the variables, and is thus more appropriate in the latter case. Also see: http://www.uvm.edu/~dhowell/StatPages/More_Stuff/icc/icc.html for a good reference.
Learned helplessness: The phenomenon in which experience with an uncontrollable event creates passive behavior toward a subsequent threat to well-being
Loss aversion: The tendency for people to assign greater weight to losses than gains when considering a risky proposition
Magical thinking: Belief in causal forces beyond the scope of physical reality (e.g., luck).
Mean: One of several statistics that describe the central tendency in a group. Other measures of central tendency include the median and the mode. The mean is simply the average of all the measures; the average is the sum of all measures divided by the number of these measures. The presence of a few extreme values can result in a mean that is not a good description of the central tendency of the group as a whole.
Median: One of several statistics that describe the central tendency in a group. Other measures of central tendency include the mean and the mode. The median is the middle value of all measures in a group. Generally, the number of people in the group with values above the median will equal the number with values below the median. To achieve this, the median might need to be a fictitious value. The median number of legs in a group made up equally of hens and cows is three.
Mediator: A variable that represents the causal mechanism through which variable A influences variable B. For example, if an intervention with adolescents (variable A) reduces substance use (variable B), that relationship might be mediated by the change in interpersonal skills (Mediator) the intervention effects. For a variable to be a mediator, it must replace (or greatly diminish) the direct relationship of A & B when entered into the equation.
Meta-analysis: A statistical synthesis of data from separate but similar (i.e., comparable) studies, leading to a quantitative summary of pooled results.
Middle frontal, inferior frontal, orbital gyrus: Areas of the frontal lobe of the brain where decision making is thought to be localized.
Mode: One of several statistics that describe the central tendency in a group. Other measures of central tendency include the mean and the median. The mode is the most frequent value observed in the group. Generally, the mode is used to describe the group tendency when there are only a few possible values.
Monozygotic: Derived from a single fertilized ovum or embryonic cell mass.
Natural laboratory: A laboratory setting that is, or appears to be, a naturally occurring setting.
Neurotransmitter: A chemical in the body which moves between neurons and communicates chemical messages such as pain, pleasure, emotion, and touch sensation. Some common neurotransmitters are serotonin, dopamine, and norepinephrine.
Nucleus accumbens: Area of the brain’s reward pathway associated with feelings of pleasure.
H0: Null hypothesis: The purpose of most statistical tests is to determine the likelihood that the observed results could have happened by chance given the hypothesis to be tested. The “null” version of a hypothesis (usually a difference in outcome due to difference in conditions) expects no difference. If the statistical test indicates that, given the hypothesis, the observed difference was not likely to have happened by chance, we can reject the hypothesis. Rejecting the null hypothesis rejects the expectation of no effect and encourages acceptance of an effect.
Observer bias: Systematic difference between a true value and that actually reported by the observer, due to a failure of the observer to measure or identify a phenomenon accurately.
Odds: The ratio of the number of specific events to the number of other events (i.e., odds = # specific / # other). The odds of an event differ from the probability of an event in that the denominator for calculating odds is the non-events and the denominator for probability is the total of all events.
Odds ratio: The odds ratio (OR) could have been termed “relative odds” to indicate the similarity to relative risk. It is the ratio of the odds of an event under one condition (or group) to the odds under another condition. Relative risk is a similar ratio using probabilities rather than odds. OR is a comparative quantity of the odds of an event occurring in one group compared to the odds of the event occurring in the other group. It is interesting to note that the OR also can be computed from the ratio of the RR between groups of the event occurring to the RR of the event not occurring. ORs are preferred to RR if the probability of an event is small, in case-controlled studies, and retrospective examinations when prospective studies would be impractical (e.g., the OR of getting lung cancer comparing long-time cigarette smokers to persons who never smoked cigarettes).
Open (open-ended) question: This type of question asks the respondent to answer in sentence or phrase form.
Orbital: Pertaining to the region above the eyes.
P-value: A term for the probability that an event will occur. In common research terminology, the p-value of an inferential statistic is the probability that an observed outcome—and more extreme outcomes—could have happened by chance under the null hypothesis that there was no effect. Small p-values such as five times in a hundred (p = .05) are used benchmarks to distinguish effects that could have happened by chance from effects unlikely to happen by chance.
Pilot study: A preliminary study with fewer subjects and/or simplified methods. Researchers conduct a pilot study to inform the design and conduct of a planned experiment
Population: The entire collection of observations to which the study results generalize. The study sampling procedures will define the accessible study population. Note that the characteristics of the population are called the population “parameters.” The population parameters are usually estimated from the “statistics” observed in a sample of the population.
Primary prevention strategy: Primary prevention aims to reduce the incidence of disease.
µ (Population mean): By convention, lower case Greek letters are often used to indicate population parameters (the letter “mu” for mean) and upper case English letters indicate the sample parameters (capital M for mean).
Prefrontal cortex: The area of the cortex most advanced in humans compared with other animals. This area primarily provides executive functions over other areas of the brain.
Probability: The ratio of the number of specific events to the number of all possible events (i.e., p = # specific / # specific + # other). Probabilities can range from zero (i.e., impossible) to one (i.e., every time). The probability of an event differs from the odds of an event in that the denominator for calculating odds is the non-events and the denominator for probability is the total of all events.
Quartile: The segment of a sample representing a sequential quarter (25%) of a frequency distribution. The boundaries are at the 25th, 50th, and 75th percentiles.
Random error: A wrong result due to chance. Unknown sources of variation are equally likely to distort the result in any direction.
Randomized controlled trial: A randomized controlled trial is a rigorous scientific experiment where study subjects are randomly allocated into groups to receive or not to receive the medication/intervention under investigation.
Recall bias: Bias due to differences in accuracy or completeness of memory.
Regression to the mean: In statistics, the tendency of extreme values to become less extreme (closer to the average) when they are reassessed.
Relative risk: Relative risk (RR) could, and perhaps should, have been termed “relative probability.” It is the ratio of the probability of an event under one condition (or group) to the probability under another condition. RR is interpretable as a comparative quantity; the RR comparing Group A with an event probability of .6 to Group B with a probability of .3 is 2.0. The same RR would result if the probabilities were ten times smaller (i.e., .06 to .03). In both comparisons, the RR indicates that the event is twice more likely to occur in Group A than Group B. Depending on the choice of the event, RR could be a “risk” if the event is untoward, cancer say, or it could be a “benefit” if the event was desired, not getting cancer.
Resilience: A person's ability to adapt positively (i.e. not engaging in risky behavior) in the face of adversity (i.e. prior exposure to risky behavior).
Reward pathway: The dopaminergic pathway in the brain that prompts positive feelings in response to certain behaviors or events. Areas of the brain found along the reward pathway include, among others, the ventral tegmentum, the nucleus accumbens, and the prefrontal cortex.
Risk factor: A behavior or characteristic that is shown to be associated with health conditions.
Sample: A group of observations selected from the study population. The sample may not be representative of a defined study population if the sampling strategy or recruiting procedures are flawed.
Secondary prevention strategy: Secondary prevention aims to reduce the prevalence of disease by shortening its duration.
Selection bias: Error due to systematic differences in characteristics between those who take part in a study and those who do not. Selection bias affects conclusions and generalizations that are made regarding the study sample.
Self-fulfilling prophecy: The process by which one’s expectations about a person eventually lead that person to behave in ways that confirm those expectations
Self-selection: When eligibility for membership in sample or a study group is based on an individual characteristic, the sampling procedure is usually termed “self-selection.” For example, participants in a study comparing smokers to non-smokers would be assigned to one group or the other depending on their own decision to smoke or not. Self-selection generally precludes being able to control for the effect of other variables and observed group differences may not be due to the characteristic that determined selection.
Selection and assignment: Selection refers to the process by which a sample is recruited from a population. A random selection of observations from the population will generally yield a sample that is representative of the entire population. Self-selection and other non-random recruitments will constrain the population and therefore, the ability to generalize the study findings. Assignment refers to the process by which the sample is further divided into experimental and control groups. A random assignment of the sample will generally yield groups that are similar to each other and the difference among them will be attributable to the experimental conditions. Non-random assignment procedures limit a study’s ability to control for non-experimental characteristics.
Sensitivity: An instrument’s ability to identify people who have the characteristic under investigation.;( % of people w/ characteristic who are correctly identified by instrument)/(# of people w/ characteristic)
Single-blind: Researcher knows placebo condition, but participant does not.
Snowball sampling: A method of selecting for study the members of a “hidden” population (e.g., illicit drug users). Those participants initially identified are asked to name acquaintances who are added to the sample; these, in turn, are asked to name further acquaintances until enough participants are added for sufficient power for the proposed study.
Somatic marker hypothesis: Affective states associated with former experience (reward or punishment) are unconsciously encoded as somatic markers. The somatic markers are activated when we face a similar situation and help us guide decisions without any conscious effort.
Somatic states: The physiological changes that occur in the body in response to an emotionally charged stimulus that is present in the environment, or to a thought (memory) that has some emotional significance.
Specificity: An instrument’s ability to rule out people who do not have the characteristic under investigation.;( % of people w/out characteristic who are correctly identified by instrument)/(# of people w/out characteristic)
Spurious: A situation in which an apparent relationship between two or more variables is lacking validity.
Standard error: Statistics from a sample of the population will vary from sample to sample. The standard error is a measure of the size of the variation in the sample statistic over all samples of the same size as the study sample. The greater the study sample size, the smaller the variation across samples. The size of the standard error determines the range of values that will include the population parameter. Smaller standard errors lead to more precise estimates of the characteristic in the population.
Statistical power: The probability that an experiment will find an effect if that effect exists in the total population. The number of observations in the study sample greatly influences statistical power.
Subclinical: A condition where the disease is detectable by certain tests but signs or symptoms are not revealed.
Systematic error: A wrong result due to bias. Sources of variation will distort the result in one direction.
Tertiary prevention strategy: Aims to reduce the number and/or impact of disease complications.
Tetrachoric correlation: Assesses the relationship between dichotomous variables (i.e. variables with only two possible responses, such as yes or no). These correlations assume an underlying continuous distribution of dichotomous variables.
Titration: Adjustment of dosage to obtain best serum level to get efficacy with the least side effects
Type I error (a): Incorrectly rejecting the null hypothesis when it is true.
Type II error (ß): Failing to reject the null hypothesis when it is false.
Two-stage cluster sample: Consists of selecting a, usually random, sample of natural clusters of people such as households or schools and then selecting a random, representative sample of one or more people within these clusters.
Ventromedial: Of, relating to, or involving both the front and the middle.
Z score: Identifies the distance that an original (raw) score is from the mean. The distance is measure in standard deviation units, e.g., a Z score of 1.0 indicates that the raw score was one standard deviation greater than the mean.
References
Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Hillsdale, NJ: Lawrence Earlbaum Associates.
Last, John M. (2001) A Dictionary of Epidemiology (fourth edition). Oxford: Oxford University Press
Evidence Based Medicine Glossary (2002). Medical University of South Carolina. Retrieved November 27, 2002, from the World Wide Web: http://www.musc.edu/dc/icrebm/glossary.html
