Adjusted analysis¹: when groups differ on baseline characteristics (eg, age), analyses of outcome data are statistically modified to account for these differences.

Blinding (masking): in an experimental study, refers to whether patients, clinicians providing an intervention, people assessing outcomes, and/or statisticians were aware or unaware of the group to which patients were assigned. In the design section of Evidence-Based Nursing abstracts of treatment studies, the study is identified as blinded, with specification of who was blinded; unblinded, if all parties were aware of patients' group assignments; or blinded (unclear) if the authors did not report or provide us with an indication of who was aware or unaware of patients' group assignments.

Concealment of randomisation: concealment of randomisation is specified in the design section of Evidence-Based Nursing abstracts of treatment studies as follows: allocation concealed (deemed to have taken adequate measures to conceal allocation to study group assignments from those responsible for assessing patients for entry in the trial [ie, central randomisation; numbered, opaque, sealed envelopes; sealed envelopes from a closed bag; numbered or coded bottles or containers; drugs prepared by the pharmacy; or other descriptions that contain elements convincing of concealment]); allocation not concealed (deemed to have not taken adequate measures to conceal allocation to study group assignments from those responsible for assessing patients for entry in the trial [ie, no concealment procedure was undertaken, sealed envelopes that were not opaque, or other descriptions that contained elements not convincing of concealment]); unclear allocation concealment (the authors did not report or provide a description of an allocation concealment approach that allowed for the classification as concealed or not concealed).

Confidence interval (CI): quantifies the uncertainty in measurement; usually reported as 95% CI, which is the range of values within which we can be 95% sure that the true value for the whole population lies.

Constant comparison²: a procedure used in qualitative research wherein newly collected data are compared in an ongoing fashion with data obtained earlier, to refine theoretically relevant categories.

Data saturation (saturation, redundancy)²: process of collecting data in a qualitative research study to the point where no new themes are generated.

Effect size³: a measure of effect that is typically used for continuous data when different scales are used to measure an outcome and is usually defined as the difference in means between the intervention and control groups divided by the standard deviation of the control or both groups; it can be used for combining results across studies in a meta-analysis.

Ethnography (ethnographic study)²: an approach to inquiry that focuses on the culture or subculture of a group of people, with an effort to understand the world view of those under study.

Grounded theory²: an approach to collecting and analysing qualitative data with the aim of developing theories grounded in real world observations.

Heterogeneity³: the degree to which the effect estimates of individual studies in a meta-analysis differ significantly.

Intention to treat analysis (ITT): all patients are analysed in the groups to which they were randomised, even if they failed to complete the intervention or received the wrong intervention.

Interactionist analysis⁴: a qualitative method that aims to bring out subjective and personal experience through the development of thick description, which illuminates context, meanings, and interpretation instead of just reporting facts.

Log rank test¹: a statistical method for comparing 2 survival curves when censored observations exist.

Meta-analysis¹: a method for combining the results of several independent studies that measure the same outcomes so that an overall summary statistic can be calculated.

Multivariate analysis¹: analysis involving multiple independent or dependent variables.

Number needed to harm (NNH)⁵: number of patients who, if they received the experimental treatment, would lead to 1 additional person being harmed compared with patients who receive the control treatment; this is calculated as 1/absolute risk increase (rounded to the next whole number), accompanied by the 95% confidence interval.

Number needed to treat (NNT): number of patients who need to be treated to prevent 1 additional negative event (or to promote 1 additional positive event); this is calculated as 1/absolute risk reduction (rounded to the next whole number), accompanied by the 95% confidence interval.

Phenomenology²: an approach to inquiry that emphasises the complexity of human experience and the need to understand that experience holistically as it is actually lived.

Relative benefit increase (RBI): the proportional increase in the rates of good events between experimental and control participants; it is reported as a percentage (%).

Relative risk increase (RRI): the proportional increase in bad outcomes between experimental and control participants; it is reported as a percentage (%).

Relative risk reduction (RRR): the proportional reduction in outcome rates of bad events between experimental and control participants; it is reported as a percentage (%).

Stratified randomisation³: used in trials to ensure that equal numbers of participants with a particular characteristic (eg, age) are allocated to each comparison group.

Trend: approaches a predefined level of statistical significance.

Wald test⁶: used to evaluate the significance of individual predictors in a logistic regression equation.