Glossary

A summary of a research paper.

An implementation outcome:the perception among stakeholders that an intervention is agreeable 

Adaptation and Sustainability involves recognizing that context varies across different settings, implementation science also explores how interventions can be adapted to fit local needs and conditions while maintaining their effectiveness and sustainability.

An implementation outcome: the intention, decision, or action to try to implement an intervention.

An aim identifies the purpose of the investigation or research study.

Research conducted primarily to address some practical problem.

An implementation outcome:the perceived fit, suitability, or relevance of an intervention in a particular setting or for a particular target audience.

The relationship between objects or variables. Two variables are positively associated when the values of one increase as the values of the other increases. They are negatively associated when the values of one decrease as the values of the other increase. Also known as correlation.

Factors that influence the results of a research study. These can be from the researcher, the participant, the data collection methods and the study design.

Compares patients who have a disease or outcome of interest (cases) with patients who do not have the disease or outcome (controls),

A study design that presents observations on a series of individuals with similar characteristics or outcomes, providing descriptive data from a number of case studies.

An in-depth examination of a particular individual, group, or situation, to explore complex phenomena within its real-life context.

This data type is made up of categorical variables that show things like a person’s gender, hometown, nationality, favourite icecream and so on. Categorical measurements are not given in numbers but rather in natural language descriptions. Numbers can sometimes represent it, but those numbers don’t mean anything mathematically.

means Inferring causation in simple terms means figuring out if one thing actually causes another. – figure out if your experiment variable causes your change.

Questions which can be answered with a simple one-word answer e.g. “yes” or “no”.

A group of people sharing a common demographic, characteristic or experience who are observed through time.

A cohort study uses one or more cohorts (groups of individuals) to look at how events differ within the group, they can be prospective or retrospective

Confirmation Bias: This occurs when researchers interpret evidence in a way that confirms their preconceptions or hypotheses, while ignoring or downplaying evidence that contradicts them.

Confounding variables are extra factors that can mix up the results of a study by being related to both the thing you’re studying and the outcome you’re looking at. If you don’t deal with these extra factors (variables), you might end up thinking there’s a connection between your study topic and the outcome when there isn’t. To fix this, researchers use different methods to make sure they’re only looking at the real relationship between what they’re studying and what they’re measuring.

Confounding variable: A variable that is not included in an experiment, yet affects the relationship between the two variables in an experiment. This type of variable can confound the results of an experiment and lead to unreliable findings

The relationship between objects or variables. Two variables are positively correlated when the values of one increase as the values of the other increases. They are negatively correlated when the values of one decrease as the values of the other increase. Also known as association.

A study design that collects data from a population at a single point in time to examine relationships or differences between variables without following individuals over time.

The extent to which an intervention achieves its intended outcomes or goals when implemented in real-world settings, often measured in terms of its impact on health, behavior change, or system improvements.

This is taken from Implementation Science Research Glossary

Evaluation and Measurement in implementation science involves measuring and evaluating the implementation process and its outcomes. Researchers use a variety of metrics and evaluation tools to assess fidelity to the intervention, sustainability, and the impact on target populations.

Evidence-Based Implementation emphasizes the importance of using rigorous research methods to study the implementation process itself. Researchers in this field use a range of methodologies to assess the effectiveness of implementation strategies and to develop best practices for bringing evidence-based interventions into practice.

A scientific procedure undertaken to make a discovery, test a hypothesis, or demonstrate a known fact by investigating the change of one variable and how it has an effect on another variable.

An interview conducted with a small group of people, all at one time, to explore ideas and discuss experiences of a particular topic or phenomenon. Focus groups are usually facilitated by at least one researcher who provides specific topics or prompts; there may be other researchers present to take notes or make observations.

Research funded by industry or other vested interests may be susceptible to bias in favor of the funder’s agenda or products. This can influence study design, analysis, and reporting.

In the case of quantitative research, statistical methods are used to achieve results that are ‘generalisable’ from a sample to the sampled population. In the case of qualitative research, the context and findings are described and defined so that the conclusions can be applied or transferred to other settings.

Heterogeneity is the degree of dissimilarity among cases concerning a particular characteristic; for example, a population of hospital staff is a group of people with a high degree of disciplinary heterogeneity, as this includes cleaners, nurses, doctors, porters, and many more groups besides.

A hypothesis (plural hypotheses) is a precise, testable statement of what the researchers predict/s will be the outcome of the study.

Implementation Strategies involve the development and testing of strategies and techniques to promote the uptake of evidence-based practices. These strategies may include training and education, quality improvement initiatives, policy changes, and stakeholder engagement.

The situation, event, treatment or variable introduced to affect an outcome.

An interview is a conversation where questions are asked and answers are given.

Interviews can be:

• Structured – follows a set of pre-determined questions which are asked of all participants in the same order, and answers are scored using a standard scoring system; this is a quantitative data collection method
• Unstructured – no pre-determined questions, perhaps a loose topic guide, but the interview is largely free-flowing and guided by the participant’s focus and interest; this is a qualitative data collection method
• Semi-structured – this is the most commonly used approach in qualitative studies; interviews follow a clear topic guide or interview schedule with a specific research focus, but the order of questions is flexible in response to participants’ answers, and the interviewer may include or exclude questions depending on how relevant they are to the ongoing discussion

This occurs when the measurement tools or procedures used in the research are inaccurate or inconsistent. It can include errors in data collection, instrumentation, or interpretation of results.

A statistical technique that combines results from multiple studies to provide a quantitative summary of findings on a particular research question or topic.

The principles, procedures, and strategies of research used in a study for gathering information, analysing data, and drawing conclusions.

Mixed methods research integrates quantitative and qualitative research to help you gain a more complete picture. Mixed methods are often used in the behavioral, health, and social sciences, especially in multidisciplinary settings and complex situational or societal research.

An objective statement is based on facts and observations. Objective information is provable, measurable and observable

Also known as experimenter bias, this occurs when the researchers’ expectations or beliefs influence the study outcomes or participants’ behavior. This can happen consciously or unconsciously.

Questions which are used to obtain qualitative data, which cannot be answered with a simple one-word answer.

Outcomes (also called events or endpoints) are variables that are monitored during a study to document the impact that a given intervention or exposure has on the health of a given population. Typical examples of outcomes are cure, clinical worsening, and mortality.

Outcomes are the measured behaviors, attitudes, measurements or other characteristics of a sample or population that research seeks to explain.

A person that takes part in an experiment or study.

Peer Review and Publication: High-quality quantitative research is often subjected to peer review, where experts in the field assess the study’s methodology, analysis, and conclusions. Successful research is then published in academic journals or presented at conferences

A small scale research study that is conducted before a larger, final study. The pilot study gives researchers a chance to identify any problems with their proposed sampling scheme, methodology, or data collection process.

Policy and Systems Change in implementation science can inform policy decisions and lead to changes in systems and structures that support the adoption and sustainability of evidence-based practices.

All members of a clearly defined group.

A pragmatic trial is a type of research study that aims to find out what works best in real-life situations, like in everyday medical practice. Instead of focusing on perfect conditions, it looks at how treatments or interventions perform in the real world with diverse patients and settings.

A research design that measures outcomes in a group before and after an intervention or exposure, without a control group, to assess changes over time within the same population.

First-hand information that has been collected by the researcher for the purpose of their study.

People are recruited into cohort studies regardless of their exposure or outcome status.

This refers to the tendency of researchers, journals, or publishers to selectively publish studies with positive or statistically significant results, while suppressing studies with negative or null findings. This can lead to an overestimation of the true effect size of a phenomenon.

Qualitative research is a method used to explore and understand the richness and complexity of human experiences, opinions, and behaviors. It relies on non-numerical data, such as interviews, observations, or open-ended surveys, to gain insights into the “why” and “how” of a phenomenon. Qualitative research is often used when you want to explore underlying meanings, motivations, or context.

Quantitative research is a method that involves the collection of numerical data and employs statistical analysis to draw conclusions. It focuses on quantifying variables and relationships between them. This approach is suitable for research questions that seek to establish patterns, correlations, and generalizable findings. Surveys, experiments, and structured observations are common tools in quantitative research.

A set of written questions with a choice of answers, devised for the purposes of a survey or statistical study.

A study design where participants are randomly allocated into treatment and control groups, allowing for rigorous evaluation of the effectiveness of interventions while controlling for confounding variables.

In studies that rely on self-reported data, participants may inaccurately recall past events or experiences, leading to biased results.

In qualitative research, “reflexivity” refers to the process of a researcher reflecting on their beliefs, values, and biases, and how these influence their interpretation and understanding of the research data. Many different factors can influence how a researcher interprets qualitative data, including their background, experiences, and any pre-existing knowledge or experience of the phenomenon they are studying. These factors can also impact how the researcher approaches the study design and interacts with participants.

Reliability relates to the consistency of the results.

The quality of measurement in terms of consistency and/or repeatability, that is whether something (such as a result obtained in a study) can be replicated. There are many different types of reliability e.g. test-retest reliability, inter-rater reliability. Related to but distinct from validity

Taken from King’s Improvement Science (2018) KIS glossary of terms used in improvement and implementation. King’s Improvement Science Glossary

This involves selectively reporting only certain outcomes or analyses that support the researchers’ conclusions, while omitting others that may be less favorable.

The extent to which research subjects in a sample represent the population from which the sample was selected.

Transparent and well-documented study designs contribute to the reproducibility of research. Other researchers should be able to replicate the study based on the provided design and methods, verifying the robustness of the findings.

Research is a systematic process of gathering information or data to answer a question or solve a problem. It involves a series of steps, including planning, data collection, analysis, and interpretation, all aimed at gaining a deeper understanding of a particular topic.

Bias in research can occur at various stages of the research process and can manifest in different forms. Here are some common sources of bias in research

For example

Selection Bias: This occurs when the sample population is not representative of the target population. For instance, if participants are not randomly selected or if certain groups are systematically excluded, the results may not be generalizable.

Sampling Bias: Related to selection bias, sampling bias occurs when the method used to recruit participants results in a non-representative sample. This can happen due to self-selection or convenience sampling methods.

A clear statement in the form of a question of the specific issue that a researcher wishes to answer using a research study.

Understanding the Research-Practice Gap in Implementation science involves identifying and addressing the barriers and facilitators that affect the successful adoption and implementation of evidence-based practices in various settings. These barriers can include factors like organizational culture, policy constraints, and individual attitudes.

A study design that analyzes existing data from past records or databases to identify a cohort of individuals who were exposed to a risk factor or intervention, then follows them forward in time to assess outcomes.

A section of the population that is selected to participate in a research study.

In quantitative research, this sample is often used to represent the population as a whole – findings are intended to be generalisable.

In qualitative research, the sample is often used to gain insight into a broad range of different experiences of a population – findings are not generalisable.

The number of subjects or participants in a study.

The process of selecting a subgroup of a population (i.e. sample) to participate in a research study.

In quantitative research, samples are often intended to be representative, i.e., findings are intended to be generalised to the entire population.

In qualitative research, samples are often intended to capture a range of different experiences within a population.

Scaling Up in implementation science involves considerations for expanding the reach of interventions to larger populations or broader geographic areas while maintaining their quality and effectiveness.

Pre-existing data. The data could have been from a newspaper, diary entry or even data collected by another researcher or study.

Stakeholder Engagement involving key stakeholders, such as healthcare providers, administrators, policymakers, and community members, is crucial in implementation science. Their input and buy-in can significantly impact the success of implementation efforts.

Study design is the blueprint or roadmap for how you will conduct your research. It outlines the structure and methodology of your study, helping you make informed decisions about data collection, analysis, and interpretation. The choice of study design depends on your research objectives and the type of data you need.

A subjective statement relies on assumptions, beliefs, and opinions, and is influenced by personal feelings, experiences, and individual context.

Each researcher, participant, and observer has their unique lens through which they view the world, and these individual perspectives inevitably shape their experiences, interactions, and interpretations.

Subjectivity is often contrasted with objectivity, which aims to eliminate personal bias or perspective and seek universal, verifiable truths. However, in psychology research, the understanding of human experience is deeply intertwined with personal meaning-making, and thus subjectivity is an important aspect to consider for researchers, particularly when using qualitative research methods.

A rigorous synthesis of existing research to provide a comprehensive summary of evidence on a specific topic or question.

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In qualitative research, the context and findings are described and defined so that the conclusions can be applied or transferred to other settings.

Validity refers to the accuracy of the study in measuring what it intends to measure

A measurable attribute or characteristics of a person, group or object that varies within the sample under investigation.