Table 8.

Glossary.

Systematic Review	Use predefined methods to identify, select, and critically appraise all available literature to address a specific research question
Meta-analysis	The statistical combination of quantitative results (pain-associated behavioural outcomes) of 2 or more studies. The methods included in the meta-analysis are the calculation of effect sizes, the pooling of the effects so that the range and distribution of effects can be observed
Study	In this instance, a study refers to the publication. A publication can have multiple experiments in which an intervention is tested in a cohort of animals and a pain-associated behaviour is measured. There can be multiple outcome measures per cohort. Similarly, a study can have multiple experiments.
Comparison and nested comparison	The outcome measure of a treatment group compared to a control (vehicle-treated) group is a comparison. Often the same cohort of animals undergo multiple pain-associated behavioural outcome measurements. In these instances, the comparisons are combined to give one outcome statistic (a nested comparison) that represents the global measure of the outcomes in that comparison.
Effect size	For each comparison, an effect size is calculated using standardised mean difference (SMD). The difference between group means (mean of control group – mean of experimental group) is divided by the pooled variance, which converts all outcome measures into a standardised scale. (A correction factor, 1 or −1 is used to define the direction of the effect size, whether the outcome is better or worse in comparison to the control).
Heterogeneity	Study heterogeneity denotes the variability in outcomes that are not due to measurement errors but other influencing factors (eg, study characteristics). We have estimated heterogeneity using both Cochran's Q and I2 and explored sources of heterogeneity with stratified meta-analysis.
Estimating heterogeneity with Cochran's Q	Q is an estimate of between-study heterogeneity and is calculated from effect sizes. It is based on a chi-squared distribution. A larger Q value denotes larger variation across studies rather than within subjects within a study. The P value of Q is used to indicate the presence or absence of heterogeneity.
Estimating heterogeneity with I2	I2 is the proportion of total variance between studies that is due to true differences in effect sizes, not differences that are due to chance. If I2 = 0% all variation is due to chance alone, 100% all variation is due to differences between the true effect sizes between studies.  0-25%—very low heterogeneity  25-50%—low heterogeneity  50-75%—moderate heterogeneity  >75%—high heterogeneity
Stratified analysis	Studies that share a particular characteristic, eg, sex, strain, animal model, will be more similar than studies that do not share the same characteristic. Stratified analysis allows us to partition the heterogeneity between groups of similar studies and between groups of studies to determine whether the differences are statistically significant.
Animal model	Whole in vivo animal models of pathological or injury-related persistent pain, eg, tissue injury, cancer, chemotherapy-induced, inflammation, or nerve damage. Persistent pain was defined as studied over a period of hours, days, weeks, or months.
Pain-associated behavioural outcome	These were when pain was declared the reason for assessment by the authors. Behavioural outcomes include:  Evoked limb withdrawal to mechanical, heat, or cold stimuli  Spontaneous, eg, weight-bearing difference, spontaneous foot lifting, grimace scale, and nocifensive behaviour)  Complex, eg, open-field test (thigmotaxis) and burrowing
Antinociception	Attenuation of pain-associated behaviour