The ARRIVE reporting guideline for writing animal research articles
How to use this reporting guideline
You can use reporting guidelines throughout your research process.
- When writing: Consider using a writing guide to draft your manuscript or protocol.
- After writing: Complete a checklist and include it with your journal submission.
- To learn: Consult the guidance whenever you need it.
However you use ARRIVE, please cite it.
Applicability criteria
Summary of guidance
Although you should describe all items below, you can decide how to order and prioritize items most relevant to your study, findings, context, and readership whilst keeping your writing concise. You can read how ARRIVE was developed in the FAQs.
| Item name | What to write |
| Essential 10 | |
| 1. Study Design | |
| 1a. The groups being compared | For each experiment, describe the groups being compared, including control groups. If you did not use a control group, explain why. |
| 1b. The experimental unit | Describe the experimental unit (e.g., a single animal, litter, or cage of animals). |
| 2. Sample Size | |
| 2a. Number of Experimental Units | Specify the exact number of experimental units allocated to each group, and the total number in each experiment. Also indicate the total number of animals used. |
| 2b. Sample Size Justification | Explain how the sample size was decided. Provide details of any a priori sample size calculation, if done. |
| 3. Inclusion and Exclusion Criteria | |
| 3a. Inclusion and exclusion criteria | Describe any criteria used for including or excluding animals (or experimental units) during the experiment, and data points during the analysis. Specify if these criteria were established a priori. If no criteria were set, state this explicitly. |
| 3b. Exclusions and Attritions | For each experimental group, report any animals, experimental units, or data points not included in the analysis and explain why. If there were no exclusions, state so. |
| 3c. Numbers analysed | For each analysis, report the exact value of n in each experimental group. |
| 4. Randomisation | |
| 4a. Randomisation Use | State whether randomisation was used to allocate experimental units to control and treatment groups. If done, provide the method used to generate the randomisation sequence. |
| 4b. Confounders | Describe the strategy used to minimise potential confounders such as the order of treatments and measurements, or animal/cage location. If confounders were not controlled, state this explicitly. |
| 5. Blinding/Masking | Describe who was aware of the group allocation at the different stages of the experiment (during the allocation, the conduct of the experiment, the outcome assessment, and the data analysis). |
| 6. Outcome Measures | |
| 6a. Outcome Measures | Clearly define all outcome measures assessed (e.g., cell death, molecular markers, or behavioural changes). |
| 6b. Primary Outcome Measure | For hypothesis-testing studies, specify the primary outcome measure, i.e., the outcome measure that was used to determine the sample size. |
| 7. Statistical Methods | |
| 7a. Statistical Methods used for each Analysis | Provide details of the statistical methods used for each analysis, including software used. |
| 7b. Statistical Assumptions | Describe any methods used to assess whether the data met the assumptions of the statistical approach, and what was done if the assumptions were not met. |
| 8. Experimental Animals | |
| 8a. Species-appropriate Details | Provide species-appropriate details of the animals used, including species, strain and substrain, sex, age or developmental stage, and, if relevant, weight. |
| 8b. Further Information | Provide further relevant information on the provenance of animals, health/immune status, genetic modification status, genotype, and any previous procedures. |
| 9. Experimental Procedures | |
| 9a. What was done | What was done, how it was done, and what was used. |
| 9b. When and how often procedures were conducted | For each experimental group, including controls, describe when and how often procedures were performed. |
| 9c. Where procedures were conducted | For each experimental group, including controls, describe where procedures were conducted (including detail of any acclimatisation periods). |
| 9d. Why procedures were done | For each experimental group, including controls, describe why procedures were conducted. |
| 10. Results | |
| 10a. Summary/Descriptive Statistics per group | For each experiment conducted, including independent replications, report a summary/descriptive statistics for each experimental group, with a measure of variability where applicable (e.g., mean and SD, or median and range). |
| 10b. Effect sizes and confidence intervals | For each experiment conducted, including independent replications, report the effect size with a confidence interval, if applicable. |
| Recommended Set | |
| 11. Abstract | Provide an accurate summary of the research objectives, animal species, strain and sex, key methods, principal findings, and study conclusions. |
| 12. Background | |
| 12a. Rationale | Include sufficient scientific background to understand the rationale and context for the study, and explain the experimental approach. |
| 12b. Species and model | Explain how the animal species and model used address the scientific objectives and, where appropriate, the relevance to human biology. |
| 13. Objectives | Clearly describe the research question, research objectives and, where appropriate, specific hypotheses being tested. |
| 14. Ethical statement | Provide the name of the ethical review committee or equivalent that has approved the use of animals in this study and any relevant licence or protocol numbers (if applicable). If ethical approval was not sought or granted, provide a justification. |
| 15. Housing and husbandry | Provide details of housing and husbandry conditions, including any environmental enrichment. |
| 16. Animal Care and Monitoring | |
| 16a. Reducing pain, suffering, and distress | Describe any interventions or steps taken in the experimental protocols to reduce pain, suffering, and distress. |
| 16b. Adverse events | Report any expected or unexpected adverse events. |
| 16c. Humane endpoints | Describe the humane endpoints established for the study, the signs that were monitored, and the frequency of monitoring. If the study did not set humane endpoints, state this. |
| 17. Interpretation/ scientific implications | |
| 17a. Interpretation/scientific implications | Interpret the results, taking into account the study objectives and hypotheses, current theory, and other relevant studies in the literature. |
| 17b. Limitations | Comment on the study limitations, including potential sources of bias, limitations of the animal model, and imprecision associated with the results. |
| 18. Generalisability/translation | Comment on whether, and how, the findings of this study are likely to generalise to other species or experimental conditions, including any relevance to human biology (where appropriate). |
| 19. Protocol registration | Provide a statement indicating whether a protocol (including the research question, key design features, and analysis plan) was prepared before the study, and if and where this protocol was registered. |
| 20. Data Access | Provide a statement describing if and where study data are available. |
| 21. Declaration of interests | |
| 21a. Conflicts of interests | Declare any potential conflicts of interest, including financial and nonfinancial. If none exist, this should be stated. |
| 21b. Funding | List all funding sources (including grant identifier) and the role of the funder(s) in the design, analysis, and reporting of the study. |
We like publishing transparent research because we think it’s more likely to be used and cited. That’s why we ask authors to use reporting guidelines.
Robin Lavery
Editor, International Journal of World Medicine
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Animal research
When ARRIVE refers to animal research it is referring to in vivo animal research. This is the use of non-human animals, sometimes known as model organisms, in experiments that seek to control the variables that affect the behavior or biological system under study. This approach can be contrasted with field studies in which animals are observed in their natural environments or habitats. Animal research varies on a continuum from pure research, focusing on developing fundamental knowledge of an organism, to applied research, which may focus on answering some questions of great practical importance, such as finding a cure for a disease. Source” The ARRIVE guidelines apply to all areas of bioscience research involving living animals. That includes mammalian species as well as model organisms such as Drosophila or Caenorhabditis elegans. Each item is equally relevant to manuscripts centred around a single animal study and broader-scope manuscripts describing in vivo observations along with other types of experiments. The exact type of detail to report, however, might vary between species and experimental setup; this is acknowledged in the guidance provided for each item. Source
Bias
The over- or underestimation of the true effect of an intervention. Bias is caused by inadequacies in the design, conduct, or analysis of an experiment, resulting in the introduction of error.Source
Descriptive and inferential statistics
Descriptive statistics are used to summarise the data. They generally include a measure of central tendency (e.g., mean or median) and a measure of spread (e.g., standard deviation or range). Inferential statistics are used to make generalisations about the population from which the samples are drawn. Hypothesis tests such as ANOVA, Mann-Whitney, or t tests are examples of inferential statistics.Source
Effect size
Quantitative measure of differences between groups, or strength of relationships between variables.Source
Experimental unit
Biological entity subjected to an intervention independently of all other units, such that it is possible to assign any two experimental units to different treatment groups. Sometimes known as unit of randomisation.Source
External validity
Extent to which the results of a given study enable application or generalisation to other studies, study conditions, animal strains/species, or humans.Source
False negative
Statistically nonsignificant result obtained when the alternative hypothesis (H1) is true. In statistics, it is known as the type II error.Source
False positive
Statistically significant result obtained when the null hypothesis (H0) is true. In statistics, it is known as the type I error.Source
Independent variable
Variable that either the researcher manipulates (treatment, condition, time) or is a property of the sample (sex) or a technical feature (batch, cage, sample collection) that can potentially affect the outcome measure. Independent variables can be scientifically interesting, or nuisance variables. Also known as predictor variable.Source
Internal validity
Extent to which the results of a given study can be attributed to the effects of the experimental intervention, rather than some other, unknown factor(s) (e.g., inadequacies in the design, conduct, or analysis of the study introducing bias).Source
Nuisance variable
Variables that are not of primary interest but should be considered in the experimental design or the analysis because they may affect the outcome measure and add variability. They become confounders if, in addition, they are correlated with an independent variable of interest, as this introduces bias. Nuisance variables should be considered in the design of the experiment (to prevent them from becoming confounders) and in the analysis (to account for the variability and sometimes to reduce bias). For example, nuisance variables can be used as blocking factors or covariates.Source
Null and alternative hypotheses
The null hypothesis (H0) is that there is no effect, such as a difference between groups or an association between variables. The alternative hypothesis (H1) postulates that an effect exists.Source
Outcome measure
Any variable recorded during a study to assess the effects of a treatment or experimental intervention. Also known as dependent variable, response variable.Source
Power
For a predefined, biologically meaningful effect size, the probability that the statistical test will detect the effect if it exists (i.e., the null hypothesis is rejected correctly).Source
Sample size
Number of experimental units per group, also referred to as n.Source
