Exam 2 Review (Chapters 6, 9, 10, 11)

Critical Appraisal

judging a study’s quality, credibility, relevance, and applicability to practice before using it

Parts of an article include…

abstract, introduction, methods, results, discussion

Abstract

brief summary: aims, methods, results, conclusions and helps filter

Introduction

background, problem, knowledges gap; justifies why the study was needed

Methods

design, sample. measures, procedures, participant protection

Results

findings only, no interpretation; statistics/p-values

Discussion

meaning of results; ties to intro; also includes limitations, bias, clinical significance

Validity

whether an instrument measures what it is intended to measure

Reliability

consistent results; does not mean valid!

Selection bias

the sample is not representative of entire population

Attrition bias

dropouts differ from completers

Measurement bias

flawed tools or procedures

Researcher bias

expectations shape findings

Participant Withdrawal

dropouts may differ from those who stay and skew the results, so they should always be reported how many left and why

Survey and COI red flags

leading, vague, double-barreled, absolute questions bias answers + funding ties and COI must be disclosedRandomization

Randomization

assigning participants to study groups by chance

Blinding

keeping participants, researchers, outcome assessors, or others unaware of study-group assignments

Statistical Significance

whether the observed findings are statistically inconsistent with the null hypothesis at a specified significance level

Clinical significance

whether the findings represent a meaningful difference in patient outcomes or clinical practice

Applicability

the sample/setting should match your patients, check before implementing in practice

Research

systemic investigation to generate knowledge or answer questions; produces the evidence

Translational Research

moves findings toward clinical application

EBP

integrating the best available evidence, clinical expertise, and patient values and preferences to guide clinical decisions

Quantitative Research

uses numerical data, measures variables, often uses structured data collection and standardized instruments, uses statistical analysis; may examine relationships, compare groups, or test hypotheses; Deductive (theory → specific hypothesis to test)

Qualitative Research

explores experiences, perceptions, meaning/process; commonly uses interviews and descriptive data and examines experiences/perspectives; identifies patterns and themes in data; Inductive (specific observations → broader pattern or theory)

Inductive Reasoning

moves from specific observations to broader patterns, concepts, or theories; commonly associated with qualitative research

Deductive Reasoning

begins with a theory or general principle and develops specific predictions or hypotheses to test; commonly associated with quantitative research

Confounding/extraneous variable

outside factors that distort or add error and can relate to both DV or IV (handle by randomizing, matching, adjusting)

Experimental research

includes manipulation of an IV, random assignment to study groups, can include a control/comparison group; is designed to evaluate intervention effects while controlling alternative explanations

Quasi-experimental research

includes intervention/manipulation, does not use random assignment, may use a control or comparison group; has greater potential for confounding than a well-designed randomized experiment

Non-experimental research

no intervention assigned, oversees variables as they occur, described/finds associations; cannot establish causation based on an observed association alone

Control group

shows what happens without the intervention, so outcomes can be compared

Correlation

association between two variables

Casuation

a cause-and-effect relationship in which a change in one variable produces a change in another

Statistical significance

results are unlikely due to chance; does not prove causation or clinical importance

Primary data

directly collected by researches for their study

Secondary data

existing data used to answer a new question

Generalizability

applying quantitative findings to a broader population; affected by sampling, setting, inclusion criteria

Phenomenology

qualitative research approach that focuses on lived experiences and explores how individuals experience and interpret a particular phenomenon

Ethnography

qualitative research approach that focuses on the culture, beliefs, practices, and life ways of a group and may involve interviews, observations, and immersion in the group's settingG

Grounded theory

focuses on developing a theory that explains a process or pattern of behavior and uses both systematic data collection and analysis to develop concepts and relationships

Coding

organizes qualitative data into categories

Themes

broader patterns of meaning in qualitative data

Data saturation

occurs when additional data no longer produce meaningful new information, concepts, or themes relevant to the research question

Four criteria of trustworthiness in qualitative research

credibility, transferability, dependability, and confirmability

Credibility

the extent to which findings provide a believable and well-supported representation of participants' experiences

Transferability

the extent to which findings may be relevant to other settings or contexts

Dependability

the consistency and transparency of the research process

Confirmability

he extent to which findings are grounded in the data rather than primarily reflecting researcher bias

Triangulation

using multiple data sources, methods, or perspectives can provide a more comprehensive understanding of a phenomenon

Audit Trial

documentation of research decisions and procedures supports transparency

Reflexivity

researchers should consider how their assumptions, experiences, and perspectives may influence the research process

Thick description

detailed descriptions of participants, settings, and circumstances help readers evaluate the transferability of findings

Mixed Methods research

intentionally combines quantitative and qualitative approaches within a study or coordinated series of studies

Advantages of mixed methods research

combines numerical outcomes with people’s experiences, provides context for quantitive findings, can help explain why can outcome occurred, can help identify barriers, provides a more comprehensive understanding of complex research problems

Integration

researchers must bring quantitative and qualitative findings together to develop a more complete interpretation; gives context, explains why, finds barriers

Explanatory sequential

quantitive data first then qualitative; the qualitative data explains the numbers

Exploratory sequential

qualitative data first then quantitive; interviews shape the survey