6SQuID: 6 Steps in Quality Intervention Development: A framework used to develop interventions in a transparent and systematic way.
Acceptability: The extent to which people delivering or receiving an intervention consider it to be appropriate or acceptable.
Action research: The iterative process of communities identifying their problems, planning, taking action and then evaluating the results, aimed at improving the lives of those communities involved in the research.
Activity/Action: Part of an intervention aimed at reducing a risk factor (or risk factors). An intervention may consist or a single activity (e.g. mass media campaign) or multiple activities (e.g. 20mph signs, plus educational campaign, plus legal enforcement).
Anonymised data: Data that has been processed in such a manner that personal data cannot be attributed to a specific individual.
Assets: The resources of an individual, community or system that can be utilised to increase the acceptability, sustainability and effectiveness of the intervention. these can be tangible such as land or buildings, but also intangible such as education, skills and community solidarity.
Assets-based approach: Asset-based approaches emphasise the need to redress the balance between meeting needs and nurturing the strengths and resources of people and communities. They are ways of valuing and building on the skills, successes and strengths of individuals and communities, which focus on the positive capacity of individuals and communities rather than solely on their needs, deficits and problems. These assets can act as the foundation from which to build a positive future. The identification and mobilisation of an individual’s or a community’s assets can help them overcome some of the challenges they face and create a shared vision and ownership of the intervention.
Association: Statistical relationship between two or more events, characteristics, or other variables.
Bias: Any systematic error introduced into data collection and analysis by selecting or encouraging one outcome or answer over others within an evaluation
Big Data: Data sets that are too large or complex to be dealt with by traditional data-processing application software. These data contain greater variety, arriving in increasing volumes and with more velocity, and may be analysed computationally to reveal patterns, trends, and associations, especially relating to human behaviour and interactions.
Biodiversity: The variability among living organisms from all sources, including terrestrial, marine and other aquatic ecosystems, and the ecological complexes of which they are part. It includes diversity within and between species, and between ecosystems.
Blue space: Outdoor environments—either natural or manmade—that prominently feature water and are accessible to humans either proximally (being in, on or near water) or distally/virtually (being able to see, hear or otherwise sense water). Examples include oceans, rivers, canals, lakes and the land immediately surrounding these environments.
Built environment: Constructed environments that include buildings, roads and other infrastructure as well as urban squares, parks, plazas and other human-made environments that are part of the urban fabric.
Causal loop. A causal loop is a circular chain of variables affecting one another in turn. So one variable would affect a second variable and so on. The last variable in the loop would affect the first variable.
Causal loop diagrams: Causal loop diagrams can be used to show the relationships between causal factors and how they operate within a system (or systems).
Causality: Cause is what makes something else happen; effect refers to what results. Cause is the why something happened and effect is the what happened. In intervention development we often refer to effect as the outcome or outcomes.
Change mechanism: a lever which triggers a sequence of outcomes in an outcomes chain.
Citizen science: encompasses the active participation of members of the public in research. Participation can range from collecting data to all aspects of the research process, including generation of research questions, data collection, analysis, evaluation and reporting.
Cohort: A group of people sharing a common demographic experience. The most common cohort is a group of people born in the same year (birth cohort), but there are numerous other examples, such as those who, in the same period of time, married (marriage cohorts), or migrated (migration cohorts).
Community empowerment: A process where people work together to make change happen in their communities by having more power and influence over what matters to them.
Community engagement: A way of developing a working relationship between public bodies (e.g. local councils) and community groups. Good community engagement means that both groups can understand and act on the needs or issues of community experiences, helping to achieve positive change.
Community: A general term referring to the people who are connected by a common interest including geography (living in a locality or to the locality itself) or a shared interest.
Complex interventions: May have multiple, interacting components and non-linear causal pathways, with variability in the content, context and mode of delivery, as well as the unpredictability of their effect on outcomes.
Complex systems: systems that provide the conditions that allow complexity to arise (e.g., feedbacks, non-equilibrium, lack of central control, heterogeneity and/ numerosity of its constituents elements) and, as result, present one or more of the following features: spontaneous order or self-organization, nonlinearity, robustness, nested structure, history and memory, and adaptive behaviour.
Complexity: A state of being complex, confusing or entangled.
Confidence Interval: A range of values for a variable of interest, e.g., a rate, constructed so that this range has a specified probability of including the true value of the variable. The specified probability is called the confidence level, and the end points of the confidence interval are called the confidence limits.
Confounder: A factor that is associated with both an intervention and the outcome of interest. For example, if people in the experimental group of a controlled trial are younger than those in the control group, it will be difficult to decide whether a lower risk of death in one group is due to the intervention or the difference in age. Age is then said to be a confounder, or a confounding variable. Randomisation is used to minimise imbalances in confounding variables between experimental and control groups. Confounding is a major concern in non-randomised trials.
Construct: Component part of theory.
Co-production: An approach in which researchers, practitioners and the public work together, sharing power and responsibility from the start to the end of the project, including the generation of knowledge.
Cost-effectiveness: Whether the intervention can be effective at affordable costs.
Data zone (DZ): Data zones are the key geography for small area statistics in Scotland.
Data Linkage: Data linkage is the process of joining together records that pertain to the same entity, such as an individual or an area, usually within a Trusted Research Environment. Records (or data) can be sourced from secondary or administrative data sources or primary data collection.
Dependent variable: In a statistical analysis, the outcome variable(s) or the variable(s) whose values are a function of other variable(s) (called independent variable(s) in the relationship under study).
Determinant: A variable associated with an increased risk of an outcome. For example, poverty is a determinant of non- communicable diseases.
Dissemination: communicating the findings of a research project to a wide range of people who might find it useful. This can be done through producing reports, publishing articles in journals or newsletters, issuing press releases or giving talks at conferences.
Distal risk factor: A risk factor that is more distant from the level of the individual and is less modifiable (e.g. poverty) but will result in bigger health impacts.
Ecosystem services: the components of nature that are directly and indirectly enjoyed, consumed, or used in order to maintain or enhance human well-being.
Effectiveness: The impact of an intervention in the real world.
Efficacy: The impact of an intervention under ideal circumstances, such as in a laboratory.
Emergent property: In relation to complex systems, this term described a behaviour, feature or outcome of the system that results from the relationships between its constituent elements, but that is difficult to predict and is qualitatively different from the behaviours or features of the components of the system. For example, we can understand how neurones in the brain transmit information. The fact that this simple process maintains our memories and allows us to dream and imagine is not predictable and is qualitatively different from the activities of individual neurones.
Ethics: A system of moral principles which we use to guide our decision making as we navigate the process of intervention development.
Evaluability assessment: A pre-evaluation activity designed to maximise the chances that any subsequent evaluation of programmes, practices, or policies will result in useful information.
Evaluation: An assessment, as systematic and impartial as possible, of the effects of an intervention, including effects on outcomes, costs, acceptability, and the wider systems in which it is implemented.
Feasibility: Testing whether it is practical to implement the intervention, or collect the data needed for a fuller evaluation.
Fishbone diagram: Also called a cause and effect diagram or Ishikawa diagram. This is a diagram used to visualise the possible causes of a problem and facilitates the sorting of causes into categories.
Geographic Information Systems (GIS): Computer-based systems for managing, analysing and presenting geographically referenced data. The National Records of Scotland geography branch uses ArcGIS for its postcode digitising and data analysis work.
Green Infrastructure: A network of multi-functional green space and other vegetated features (e.g. street trees, planting, green rooves), urban and rural, which can deliver a wide range of environmental and quality of life benefits for local communities. Sometimes termed ‘Green/Blue Infrastructure’ if specifically including water features.
Green space: An area of land that includes vegetation (such as trees, grassland, scrub); may be private or publicly accessible. Often includes water features even if not specified as green/blue space.
Grey literature: Any type of literature that is not published in the academic literature. It is usually published by non-research related organisations to share their results for funders, stakeholders and the general public.
Groundswell: Groundswell aims to identify how we can use urban green and blue spaces (UGBS) to reduce health inequalities. It is a five-year consortium across the UK of Universities, communities and policy makers, striving to make outdoor spaces healthy for all.
Hard to modify risk factor: A risk factor that is difficult but not impossible to change. Examples include poverty, substandard housing, etc.
Health inequalities: Refer to differences in health outcomes between different groups within the population. Health inequalities have been shown across income, ethnicity, gender, disability, sexual orientation and social class. These factors have also been shown to interact with one another.
Hypothesis: A proposed explanation made on the basis of limited evidence as a starting point for further investigation. In a trial, this would be a statement relating to the possible different effect of the interventions on an outcome.
Ideology: set of normative (usually political or moral) principles and values underpinning ‘commonsense’ attitudes and views about how the world ought to be, or normative rationalisation of how the world is. Can also denote ‘hidden values’ underpinning actions and views that work in the interests of a minority not the majority.