Understanding Disease & Health Factors: Interventions, Validity, Bias & Study Types, Exams of Nursing

Download Understanding Disease & Health Factors: Interventions, Validity, Bias & Study Types and more Exams Nursing in PDF only on Docsity! NR-503 Midterm 2024 exam vital statistics - The collection, tabulation, and interpretation of data concerning birth, marriage, divorce, sickness, and death. Morbidity - presence of illness in population mortality - related to tracking of deaths in a population cases - people afflicted (those who are sick) social justice - justice in terms of the distribution of wealth, opportunities, and privileges within a society. Epidemiology - the branch of medicine that deals with the incidence, distribution, and possible control of diseases and other factors relating to health. Population Health - health outcomes of a group of people, and the distribution of those outcomes within the group Incidence - number of new cases Prevalence - The number or proportion of cases of a particular disease or condition present in a population at a within a specific time frame Outcomes - End result that follows an intervention Inter-professional collaboration - Health professionals work together in small groups providing care. Examples: oncology, OR, end of life or primary care. Healthy People 2020 - A set of disease prevention and health promotion objectives for Americans to meet during the second decade of the new millennium. Determinants of health - Factors that raise or lower a level of health in a population or individual. Determinants of health help to explain or predict trends in health and why some groups have better or worse health than others. Campaign for Action - mobilizes nurses, health providers, consumers to strengthen nursing through policy changes. Goal based on IOM future of nursing report. primary intervention - process of altering susceptibility or reducing exposure to prevent disease prior to the person getting it, ex: immunizations, tobacco prevention initiatives secondary intervention - early detection of disease or risk factors and intervention during an asymptomatic phase, ex: pap smear, rapid HIV, annual cholesterol test tertiary intervention - an intervention that occurs after the initial occurrence of symptoms but before irreversible disability occurs, ex: cardiac rehab programs aggregate - defined population community - composed of multiple aggregates high risk populations - Certain groups of people who have a higher risk of getting an illness than others Validity - The ability of a test to measure what it is intended to measure causation - A cause and effect relationship in which one variable controls the changes in another variable. Systematic (bias) error - occurs when selected subjects in a sample are not representative of the population of interest, makes it appear (falsely) that there is or is not an association between exposure and outcome non-probability sampling (non-random sampling) - members of target population do not share and equal chance of being selected, i.e. convenience sample or volunteers Exclusion bias - applying different eligibility criteria to cases and controls Withdrawal bias - patients who withdraw from a study are likely to differ from those who do not information bias - A prejudice in the data that results when either the respondent or the interviewer has an agenda and is not presenting impartial questions or responding with truly honest responses, respectively measurement bias - a form of inaccurate measurement in which the data consistently overestimate or underestimate the true value of an event calibration error - systematic error in which an object's quantitative data differs consistently from the true value on an interval level of measurement, ex: instrument is not sensitive enough to measure a difference misclassification bias - Occurs when either exposure or outcome is not identified correctly, or case or control is not identified appropriately Contamination bias - control group gets tx or intervention, thus decreases diff between control vs tx intent-to-treat principle - you assign patients to the original group you intended to treat them in from the start of the study recall bias - subjects fail to accurately recall events in the past example: - how many times last year did you kiss your mother? - likely problem in retrospective studies solution: confirmation of data from individual source reporting bias - occurs when a source has the required knowledge but we question his or her willingness to convey it accurately publication bias - journals are more likely to publish studies with statistically significant results than those that have null results errors of inference - people's tendencies an emphasis on other's characteristics in order to explain in a certain situation- not considering external factors of the person. Type I error (alpha) - False positive results ex: reject the null hypothesis when you should accept it Type II error (beta) - False negative results ex: accept the null hypothesis when you should reject it randomized controlled trial - an experiment in which participants are randomly assigned to different conditions for the purpose of examining the effectiveness of an intervention cohort study - study that measures variables of a group of people over time Case-control study - One type of epidemiological study design used to identify factors that may contribute to a medical condition by comparing a group of patients who have that condition with a group of patients who do not. scientific misconduct - fabrication, falsification, or plagiarism in proposing, performing, or reviewing research, or in reporting research results Confounding error - Data analysis error, where incorrect relationship is characterized Data may or may not be flawed Believing that an exposure causes the outcome alone, ignoring the possibility that confounding variable may have affected both the exposure and outcome Ex: Red hair is associated with increased pain tolerance Triple Aim - -Improve the health of the population -Enhance the patient experience of care -Reduce or control the per capita cost of care able to control intervention or tx randomized control trial weaknesses - labor intensive costly lengthy sometimes impractical or unethical to conduct Cohort Study Strengths - - Useful when the exposure is rare. - Can examine multiple effects of a single exposure. - If prospective, minimizes bias in the ascertainment of exposure. - Allows direct measure of incidence of disease in the exposed an unexposed groups. Cohort Study Weaknesses - - Inefficient for the evaluation of rare diseases unless attributable risk percent is high. - If prospective, can be extremely expensive and time consuming. - Potential bias in ascertainment of exposure, particularly if retrospective. - Potential bias in ascertainment of disease status (exposed may be actively seeking treatment). Case-control study strengths - - inexpensive - shorter time to completion - able to study variable with long latency or impact periods - provides a means to compare groups - able to calculate odds ratio - able to study rare or fatal disease - can study multiple exposures case-control study weaknesses - - risk of bias and confounding variables - sometimes unable to measure or determine exposure - selection bias - measurement error - recall bias - cannot assess risk Action model elements - Interventions, determinants of health, outcomes - assessment, monitoring, evaluation & dissemination Rapid Cycle Improvement - Use of the plan-do-study-act (PDSA) cycle in a streamlined approach, where changes are piloted on a small scale and incremental adjustments are made quickly based on collecting just enough data to assess the impact of the change and guide the next step. therapy and prevention study types - study types are: RCT, controlled trials diagnosis/assessment study types - study type is: instrument development research causation study types - study types are: Cohort, case-control study, descriptive or qualitative studies prognosis study types - study types are: cohort, descriptive studies meaning study types - study type is: qualitative studies Website credibility - who runs the site? why have they created the site? who is sponsoring the site? is it up to date? what is the privacy policy? SnOut - sensitivity is high, result is negative, rules out disease SpIn - specificity is high, results is positive, rules in disease