Reporting animal research: Explanation and elaboration for the ARRIVE guidelines 2.0

May combine two claims.

Evidence shows that the majority of publications fail to include key information and there is significant scope to improve the reporting of studies involving animal research.

“However, evidence shows that the majority of publications fail to include key information and there is significant scope to improve the reporting of studies involving animal research [1–4].”

• cites [1] C Kilkenny, 2009, Survey of the quality of experimental design, statistical analysis and reporting of research using animals, PLoS ONE sourceSupported
• cites [2] O Florez-Vargas, 2016, Bias in the reporting of sex and age in biomedical research on mouse models, Elife sourcePartly supported

  The Results (‘Reporting of sex and age’; page not available) say that only about 50% of mouse-model papers published since 2012 reported both variables. The Discussion identifies this as a reporting problem, but the study does not establish that a majority of animal-research publications generally omit key information. (LLM, conf=0.86)

  Experimental — accuracy not yet measured
• cites [3] TL Weissgerber, 2018, Why we need to report more than ‘Data were Analyzed by t-tests or ANOVA’, Elife sourceSupported
• cites [4] MR Macleod, 2015, Risk of bias in reports of in vivo research: a focus for improvement, PLoS Biol sourceSupported

The quote only partly states this claim.

Reporting n = 50 when the experimental unit is the mouse is an example of pseudoreplication.

“Reporting n = 50 in this case is an example of pseudoreplication [26].”

• cites [26] SE Lazic, 2010, The problem of pseudoreplication in neuroscientific studies: is it affecting your analysis?, BMC Neurosci sourceSupported

Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

The use of a one-sided test requires justification of why a treatment effect is only of interest when it is in a defined direction and why they would treat a large effect in the unexpected direction no differently from a nonsignificant difference.

“The use of a one-sided test requires justification of why a treatment effect is only of interest when it is in a defined direction and why they would treat a large effect in the unexpected direction no differently from a nonsignificant difference [43].”

• cites [43] GD Ruxton, 2010, When should we use one-tailed hypothesis testing?, Methods Ecol Evol sourceSupported

Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

The Experimental Design Assistant (EDA) is a platform to support researchers in the design of in vivo experiments; it can be used to generate diagrams to represent any type of experimental design.

“The Experimental Design Assistant (EDA) is a platform to support researchers in the design of in vivo experiments; it can be used to generate diagrams to represent any type of experimental design [19].”

• cites [19] N Percie du Sert, 2017, The Experimental Design Assistant, PLoS Biol sourcePartly supported

  The Introduction describes the EDA as a web-based tool that guides researchers in designing animal experiments and produces diagrams of their plans. The section on standard notation describes diagrams for different designs, but our copy does not establish the broader claim that it can represent any type of experimental design. (LLM, conf=0.82)

  Experimental — accuracy not yet measured

Probably not a substantial claim: may not pass S2 (checkable).

For hypothesis-testing experiments, the sample size needs to be justified to ensure experiments are of an optimal size to test the research question.

“For hypothesis-testing experiments, in which inferential statistics are used to estimate the size of the effect and to determine the weight of evidence against the null hypothesis, the sample size needs to be justified to ensure experiments are of an optimal size to test the research question [33,34] (see Item 13. Objectives).”

• cites [33] F Vahidy, 2016, Reporting standards for preclinical studies of stroke therapy, Stroke sourceNot checked — no full text of the source
• cites [34] BS Muhlhausler, 2013, Whole animal experiments should be more like human randomized controlled trials, PLoS Biol sourceSupported

May combine two claims.

There is evidence that in vivo scientists are not sufficiently aware of the importance of reporting the information covered in the guidelines and fail to appreciate the relevance to their work or their research field.

“and there is evidence that in vivo scientists are not sufficiently aware of the importance of reporting the information covered in the guidelines and fail to appreciate the relevance to their work or their research field [12].”

• cites [12] JC McGrath, 2015, Implementing guidelines on reporting research using animals (ARRIVE etc.): new requirements for publication in BJP, Br J Pharmacol sourceSupported

May combine two claims.

Low-powered studies contribute to the poor internal validity of research and risk wasting animals used in inconclusive research.

“Consequently, low-powered studies contribute to the poor internal validity of research and risk wasting animals used in inconclusive research [37].”

• cites [37] H Würbel, 2017, More than 3Rs: The importance of scientific validity for harm-benefit analysis of animal research, Lab animal sourceSupported

Probably not a substantial claim: may not pass S2 (checkable).

To ensure scientific rigour, inclusion and exclusion criteria should be defined before the experiment starts and data are collected.

“To ensure scientific rigour, the criteria should be defined before the experiment starts and data are collected [8,33,48,49].”

• cites [8] MT Avey, 2016, The devil is in the details: incomplete reporting in preclinical animal research, PLoS ONE sourcePartly supported

  The Results section identifies inclusion and exclusion criteria as core reporting items, and the Discussion links rigorous implementation and reporting of such measures to reduced risk of bias. Our copy does not say that these criteria must be defined before the experiment starts or before data collection; that timing is not supported by this source. (LLM, conf=0.82)

  Experimental — accuracy not yet measured
• cites [33] F Vahidy, 2016, Reporting standards for preclinical studies of stroke therapy, Stroke sourceNot checked — no full text of the source
• cites [48] ASC Rice, 2013, Transparency in the reporting of in vivo pre-clinical pain research: The relevance and implications of the ARRIVE (Animal Research: Reporting In Vivo Experiments) guidelines, Scandinavian Journal of Pain sourceNot checked — no full text of the source
• cites [49] Salkind NJ. Encyclopedia of research design: Sage; 2010. sourceNot checked — no full text of the source

Probably not a substantial claim: may not pass S3 (load-bearing).

This document was road tested alongside the revised guidelines with researchers preparing manuscripts describing in vivo research.

“To ensure that the recommendations are as clear and useful as possible to the target audience, this document was road tested alongside the revised guidelines with researchers preparing manuscripts describing in vivo research [13].”

• cites [13] N Percie du Sert, 2020, The ARRIVE guidelines 2.0: Updated guidelines for reporting animal research, PLoS Biol sourceSupported

Probably not a substantial claim: may not pass S3 (load-bearing).

Statistical programmes to help perform a priori sample size calculations exist for a variety of experimental designs and statistical analyses, both freeware and commercial software.

“Statistical programmes to help perform a priori sample size calculations exist for a variety of experimental designs and statistical analyses, both freeware (web-based applets and functions in R) and commercial software [38–40].”

• cites [38] R Core Team, 2017Not checked yet

  Not checked in the free run.

• cites [39] C-YJ Peng, 2012, Power analysis software for educational researchers, The Journal of Experimental Education sourceNot checked — no full text of the source
• cites [40] J Charan, 2013, How to calculate sample size in animal studies?, J Pharmacol Pharmacother sourceSupported

May combine two claims.

Pseudoreplication underestimates the true variability in a study, which can lead to false positives and invalidate the analysis and resulting conclusions.

“It underestimates the true variability in a study, which can lead to false positives and invalidate the analysis and resulting conclusions [26,27].”

• cites [26] SE Lazic, 2010, The problem of pseudoreplication in neuroscientific studies: is it affecting your analysis?, BMC Neurosci sourceSupported
• cites [27] SH Hurlbert, 1984, Pseudoreplication and the design of ecological field experiments, Ecol Monogr sourceNot checked — no full text of the source

May combine two claims.

Missing data can impact the sensitivity of the study and lead to biased estimates, distorted power, and loss of information if the missing values are not random.

“Missing data, common in all areas of research, can impact the sensitivity of the study and also lead to biased estimates, distorted power, and loss of information if the missing values are not random [54].”

• cites [54] H Kang, 2013, The prevention and handling of the missing data, Korean J Anesthesiol sourcePartly supported

  The Abstract (page not provided) says missing data reduce statistical power and can bias parameter estimates; the Missing completely at random section adds that power can be lost even when estimates remain unbiased. The paper also describes lost data, but it does not say missing data affect the study’s sensitivity. Its Sensitivity analysis section discusses a method for testing the robustness of results, not a loss of study sensitivity. (LLM, conf=0.84)

  Experimental — accuracy not yet measured

May combine two claims.

In a hypothesis-testing study powered to detect an effect on the primary outcome measure, data on secondary outcomes are used to evaluate additional effects, but subsequent statistical analysis of secondary outcome measures may be underpowered, making results and interpretation less reliable.

“In a hypothesis-testing study powered to detect an effect on the primary outcome measure, data on secondary outcomes are used to evaluate additional effects of the intervention, but subsequent statistical analysis of secondary outcome measures may be underpowered, making results and interpretation less reliable [88,93].”

• cites [88] LK John, 2012, Measuring the prevalence of questionable research practices with incentives for truth telling, Psychol Sci sourceNot checked — no full text of the source
• cites [93] SC Landis, 2012, A call for transparent reporting to optimize the predictive value of preclinical research, Nature sourcePartly supported

  Split into 2 atoms — 0 confirmed, 2 partially supported, 0 disputed, 0 misattributed, 0 unverifiable. Expand the claim to see per-atom verdicts.

  Experimental — accuracy not yet measured

May combine two claims.

Registering a protocol in advance protects the researcher against concerns about selective outcome reporting and provides evidence that the primary outcome reported in the manuscript accurately reflects what was planned.

“Registering a protocol in advance protects the researcher against concerns about selective outcome reporting (also known as data dredging or p-hacking) and provides evidence that the primary outcome reported in the manuscript accurately reflects what was planned [95] (see Item 19. Protocol registration).”

• cites [95] MR Munafò, 2017, A manifesto for reproducible science, Nature Human Behaviour sourceSupported

May combine two claims.

Analysing the data using different methods and selectively reporting those with statistically significant results constitutes p-hacking and introduces bias in the literature.

“Analysing the data using different methods and selectively reporting those with statistically significant results constitutes p-hacking and introduces bias in the literature [90,94].”

• cites [90] KK Tsilidis, 2013, Evaluation of excess significance bias in animal studies of neurological diseases, PLoS Biol sourceSupported
• cites [94] ML Head, 2015, The extent and consequences of p-hacking in science, PLoS Biol sourceSupported

May combine two claims.

The immune or microbiological status of the animals can influence welfare, experimental variability, and scientific outcomes.

“The immune or microbiological status of the animals can also influence welfare, experimental variability, and scientific outcomes [112–114].”

• cites [112] M Mahler Convenor, 2014, FELASA recommendations for the health monitoring of mouse, rat, hamster, guinea pig and rabbit colonies in breeding and experimental units, Lab Anim sourceSupported
• cites [113] DG Baker, 1998, Natural pathogens of laboratory mice, rats, and rabbits and their effects on research, Clin Microbiol Rev sourceNot checked — no full text of the source
• cites [114] EM Velazquez, 2019, Endogenous Enterobacteriaceae underlie variation in susceptibility to Salmonella infection, Nat Microbiol sourceSupported

May combine two claims.

The animals' provenance, health or immune status, and history of previous testing or procedures can influence their physiology and behaviour, as well as their response to treatments, and thus impact on study outcomes.

“The animals’ provenance, their health or immune status, and their history of previous testing or procedures can influence their physiology and behaviour, as well as their response to treatments, and thus impact on study outcomes.”

• cites [16] MF Festing, 2002, Guidelines for the design and statistical analysis of experiments using laboratory animals, ILAR J sourceNot checked — no full text of the source
• cites [112] M Mahler Convenor, 2014, FELASA recommendations for the health monitoring of mouse, rat, hamster, guinea pig and rabbit colonies in breeding and experimental units, Lab Anim sourcePartly supported

  The paper’s introductory passage (indexed as Abstract; page not given) says infections can affect animals’ physiology, including behaviour and immune response, and can confound experimental results. Its health-monitoring discussion also considers immune status and the health history of the facility of origin. It does not establish that previous testing or procedures alter animals’ physiology, behaviour, or responses to treatments. (LLM, conf=0.85)

  Experimental — accuracy not yet measured
• cites [113] DG Baker, 1998, Natural pathogens of laboratory mice, rats, and rabbits and their effects on research, Clin Microbiol Rev sourceNot checked — no full text of the source
• cites [114] EM Velazquez, 2019, Endogenous Enterobacteriaceae underlie variation in susceptibility to Salmonella infection, Nat Microbiol sourcePartly supported

  The Results show that mice from different vendors had different susceptibility to Salmonella infection, and the Abstract links that variation to their gut microbiota and to reproducibility of animal experiments. The cited paper does not establish the claim about prior testing or procedures, behaviour, or responses to treatments generally. The copy provides section labels but no page numbers. (LLM, conf=0.88)

  Experimental — accuracy not yet measured

May combine two claims.

Animal handling can be a source of stress, and the specific method used can affect research outcomes.

“Animal handling can be a source of stress, and the specific method used (e.g., mice picked up by tail or in cupped hands) can affect research outcomes [61,121,122].”

• cites [61] K Gouveia, 2017, Optimising reliability of mouse performance in behavioural testing: the major role of non-aversive handling, Sci Rep sourceSupported
• cites [121] JM Clarkson, 2018, Handling method alters the hedonic value of reward in laboratory mice, Sci Rep sourceSupported
• cites [122] JL Hurst, 2010, Taming anxiety in laboratory mice, Nat Methods sourceNot checked — no full text of the source

Classified as probably not a substantial claim. May combine two claims.

RRIDs are unique and stable, allowing unambiguous identification of reagents or tools used in a study, aiding other researchers to replicate the methods.

“RRIDs are unique and stable, allowing unambiguous identification of reagents or tools used in a study, aiding other researchers to replicate the methods.”

• cites [126] AE Bandrowski, 2016, RRIDs: a simple step toward improving reproducibility through rigor and transparency of experimental methods, Neuron sourceSupported
• cites [127] A Bandrowski, 2016, The Resource Identification Initiative: a cultural shift in publishing, J Comp Neurol sourceSupported

Probably not a substantial claim: may not pass S2 (checkable). May combine two claims.

Reporting the correct nomenclature is crucial to understanding the data and ensuring that the research is discoverable and replicable.

“Reporting the correct nomenclature is crucial to understanding the data and ensuring that the research is discoverable and replicable [116–118].”

• cites [116] S Mallapaty, 2018, In the name of reproducibility, Lab Animal sourceSupported
• cites [117] JP Sundberg, 2010, Commentary: mouse genetic nomenclature: standardization of strain, gene, and protein symbols, Vet Pathol sourcePartly supported

  The Abstract says standard nomenclature is vital for interpreting and recovering mouse experimental data, and the Conclusions link it to searching and retrieving archived data. The Mutant Gene Symbols section says correct annotation allows studies to be compared accurately. These passages support understanding and discoverability, but do not establish that correct nomenclature ensures research is replicable. (LLM, conf=0.83)

  Experimental — accuracy not yet measured
• cites [118] L Montoliu, 2011, Using standard nomenclature to adequately name transgenes, knockout gene alleles and any mutation associated to a genetically modified mouse strain, Transgenic Res sourceNot checked — no full text of the source

Probably not a substantial claim: may not pass S3 (load-bearing).

Maternal diet affects offspring body weight.

“Maternal diet affects offspring body weight [183].”

• cites [183] SA Bayol, 2007, A maternal ‘junk food’ diet in pregnancy and lactation promotes an exacerbated taste for ‘junk food’ and a greater propensity for obesity in rat offspring, Br J Nutr sourceSupported

Probably not a substantial claim: may not pass S2 (checkable).

Testing a specific hypothesis has implications for both the study design and the data analysis.

“Testing a specific hypothesis has implications for both the study design and the data analysis [16,167].”

• cites [16] MF Festing, 2002, Guidelines for the design and statistical analysis of experiments using laboratory animals, ILAR J sourceNot checked — no full text of the source
• cites [167] J Kimmelman, 2014, Distinguishing between exploratory and confirmatory preclinical research will improve translation, PLoS Biol sourceSupported

Probably not a substantial claim: may not pass S3 (load-bearing).

Temperature and humidity modifies tumour progression.

“Temperature and humidity | Modifies tumour progression [186].”

• cites [186] KM Kokolus, 2013, Baseline tumor growth and immune control in laboratory mice are significantly influenced by subthermoneutral housing temperature, Proc Natl Acad Sci U S A sourcePartly supported

  The Results report slower tumor growth and fewer lung metastases in mice housed at thermoneutral rather than standard temperatures. Materials and Methods says humidity was controlled, but the paper does not report testing whether humidity modifies tumour progression. (LLM, conf=0.89)

  Experimental — accuracy not yet measured

Probably not a substantial claim: may not pass S2 (checkable).

The ethical statement provides editors, reviewers, and readers with assurance that studies have received ethical oversight.

“The ethical statement provides editors, reviewers, and readers with assurance that studies have received this ethical oversight [12].”

• cites [12] JC McGrath, 2015, Implementing guidelines on reporting research using animals (ARRIVE etc.): new requirements for publication in BJP, Br J Pharmacol sourceSupported

Probably not a substantial claim: may not pass S3 (load-bearing).

Systematic reviews can inform the choice of animal model by providing a comprehensive overview of the models used along with their benefits and limitations.

“They can also inform the choice of animal model by providing a comprehensive overview of the models used along with their benefits and limitations [160–162].”

• cites [160] MT Avey, 2015, The use of systematic reviews and reporting guidelines to advance the implementation of the 3Rs, Journal of the American Association for Laboratory Animal Science: JAALASNot checked — no full text of the source
• cites [161] CR Hooijmans, 2013, Progress in using systematic reviews of animal studies to improve translational research, PLoS Med sourceSupported
• cites [162] ES Sena, 2014, Systematic reviews and meta-analysis of preclinical studies: why perform them and how to appraise them critically, J Cereb Blood Flow Metab sourcePartly supported

  The Introduction says systematic reviews provide a less biased summary of preclinical evidence, and the ‘External and Construct Validity’ section gives an example of a review identifying which animals predominate in stroke studies. That section also discusses limitations in how animal models represent human disease. Our copy does not say that reviews provide a comprehensive account of the benefits and limitations of each model or explicitly recommend them for choosing a model. (LLM, conf=0.81)

  Experimental — accuracy not yet measured

May combine two claims.

Abstracts often either do not contain enough information for screening or contain information that is inconsistent with the results in the rest of the manuscript.

“However, abstracts often either do not contain enough information for this purpose [11] or contain information that is inconsistent with the results in the rest of the manuscript [154,155].”

• cites [11] K Hair, 2019, A randomised controlled trial of an intervention to improve compliance with the ARRIVE guidelines (IICARus), Research Integrity and Peer Review sourceCould not verify

  This source is cited for the claim that abstracts contain information inconsistent with the rest of the manuscript; the insufficient-information claim has a separate citation. The Discussion and Results address compliance with ARRIVE reporting guidelines, but no passage found by searching for abstracts, inconsistencies, and manuscript results assesses whether abstracts contradict manuscript results. (LLM, conf=0.73)

  Experimental — accuracy not yet measured
• cites [154] RM Pitkin, 1999, Accuracy of data in abstracts of published research articles, JAMA sourceNot checked — no full text of the source
• cites [155] I Boutron, 2014, Impact of spin in the abstracts of articles reporting results of randomized controlled trials in the field of cancer: the SPIIN randomized controlled trial, J Clin Oncol sourceNot checked — no full text of the source

Probably not a substantial claim: may not pass S2 (checkable).

In studies in which statistical power is low and/or hypothesis-testing is inappropriate, providing the effect size and confidence interval indicates how small or large an effect might really be, so a reader can judge the biological significance of the data.

“In studies in which statistical power is low and/or hypothesis-testing is inappropriate, providing the effect size and confidence interval indicates how small or large an effect might really be, so a reader can judge the biological significance of the data [151,152].”

• cites [151] D Moher, 2010, CONSORT 2010 Explanation and Elaboration: updated guidelines for reporting parallel group randomised trials, BMJ sourcePartly supported

  Split into 2 atoms — 0 confirmed, 2 partially supported, 0 disputed, 0 misattributed, 0 unverifiable. Expand the claim to see per-atom verdicts.

  Experimental — accuracy not yet measured
• cites [152] S Nakagawa, 2007, Effect size, confidence interval and statistical significance: a practical guide for biologists, Biol Rev Camb Philos Soc sourceNot checked — no full text of the source

Probably not a substantial claim: may not pass S2 (checkable). May combine two claims.

Different studies may be sensitive to different environmental factors, and particular aspects of the environment necessary to report may depend on the type of study.

“Different studies may be sensitive to different environmental factors, and particular aspects of the environment necessary to report may depend on the type of study [176].”

• cites [176] 2014, Guidance for the description of animal research in scientific publications, ILAR J sourceSupported

May combine two claims.

In a systematic review of the effect of the MVA85A vaccine on tuberculosis challenge in animals, the largest preclinical trial did not include the vaccine name in the abstract or keywords of the publication; the paper was only included in the systematic review following discussions with experts in the field.

“For example, in a systematic review of the effect of the MVA85A vaccine on tuberculosis challenge in animals, the largest preclinical trial did not include the vaccine name in the abstract or keywords of the publication; the paper was only included in the systematic review following discussions with experts in the field [157].”

• cites [157] R Kashangura, 2015, Effects of MVA85A vaccine on tuberculosis challenge in animals: systematic review, Int J Epidemiol sourceSupported

Probably not a substantial claim: may not pass S3 (load-bearing).

Environmental enrichment reduces susceptibility to osteoarthritis.

“Environmental enrichment | Reduces anxiety [196,197], stress [196,197], and abnormal repetitive behaviour [198–200]. Reduces susceptibility to epilepsy [201] and osteoarthritis [202] and modifies the pathology of neurological disorders [203]. Increases foraging behaviour in fish [204].”

• cites [202] A Salvarrey-Strati, 2008, The influence of enrichment devices on development of osteoarthritis in a surgically induced murine model, ILAR J sourcePartly supported

  The Severity of OA section reports lower histological OA scores with one enrichment device, the Shepherd Shack, than with the other devices, but the difference was not statistically significant (p = 0.07). All mice developed OA after surgery. The paper therefore suggests a device-specific effect on disease severity in a surgically induced mouse model, not a general reduction in susceptibility to developing OA. (LLM, conf=0.89)

  Experimental — accuracy not yet measured

May combine two claims.

Human clinical trials initiated based on insufficient or misleading animal research evidence increase research waste and negatively influence the risk-benefit balance for research participants.

“Similarly, human clinical trials initiated based on insufficient or misleading animal research evidence increase research waste and negatively influence the risk-benefit balance for research participants [229,232].”

• cites [229] S Wieschowski, 2018, Preclinical efficacy studies in investigator brochures: do they enable risk–benefit assessment?, PLoS Biol sourcePartly supported

  The Introduction (page not specified) says risk–benefit assessment in early human trials depends heavily on animal evidence, and the paper states that poor preclinical study design and reporting thwart that assessment. It does not establish that trials launched on insufficient or misleading evidence increase research waste or demonstrate a worsened risk–benefit balance for participants. (LLM, conf=0.84)

  Experimental — accuracy not yet measured
• cites [232] I Chalmers, 2014, How to increase value and reduce waste when research priorities are set, The Lancet sourceNot checked — no full text of the source

Probably not a substantial claim: may not pass S2 (checkable). May combine two claims.

Limitations are unavoidable in scientific research, and describing them is essential to share experience, guide best practice, and aid the design of future experiments.

“Limitations are unavoidable in scientific research, and describing them is essential to share experience, guide best practice, and aid the design of future experiments [228].”

• cites [228] MA Puhan, 2012, Discussing study limitations in reports of biomedical studies- the need for more transparency, Health Qual Life Outcomes sourcePartly supported

  The Introduction (page not provided) calls candid discussion of limitations crucial to scientific discourse and says it informs higher-quality future studies. The Discussion section (page not provided) recommends using limitations to guide future research and study design. The copy does not establish that limitations are unavoidable in all scientific research or specifically say that describing them guides best practice. (LLM, conf=0.83)

  Experimental — accuracy not yet measured

Probably not a substantial claim: may not pass S3 (load-bearing).

If the experiment is testing the efficacy of a treatment, the occurrence of adverse events may alter the balance between treatment benefit and risk.

“If the experiment is testing the efficacy of a treatment, the occurrence of adverse events may alter the balance between treatment benefit and risk [34].”

• cites [34] BS Muhlhausler, 2013, Whole animal experiments should be more like human randomized controlled trials, PLoS Biol sourceSupported

Probably not a substantial claim: may not pass S3 (load-bearing).

Environmental enrichment increases foraging behaviour in fish.

“Environmental enrichment | Reduces anxiety [196,197], stress [196,197], and abnormal repetitive behaviour [198–200]. Reduces susceptibility to epilepsy [201] and osteoarthritis [202] and modifies the pathology of neurological disorders [203]. Increases foraging behaviour in fish [204].”

• cites [204] VA Braithwaite, 2005, Environmental variability in the early rearing environment generates behaviourally flexible cod: implications for rehabilitating wild populations, Proceedings of the Royal Society B-Biological Sciences sourceSupported

May combine two claims.

Untreated pain can affect the animals' biology and add variability to the experiment.

“Untreated pain can affect the animals’ biology and add variability to the experiment; however, specific pain management procedures can also introduce variability, affecting experimental data [212,213].”

• cites [212] P Jirkof, 2017, Side effects of pain and analgesia in animal experimentation, Lab Anim (NY) sourceSupported
• cites [213] L Carbone, 2016, Pain and laboratory animals: publication practices for better data reproducibility and better animal welfare, PLoS ONE sourceSupported

Probably not a substantial claim: may not pass S3 (load-bearing).

The EDA can be used to generate a time-stamped PDF, which sets out key elements of the experimental design.

“The EDA can also be used to generate a time-stamped PDF, which sets out key elements of the experimental design [19].”

• cites [19] N Percie du Sert, 2017, The Experimental Design Assistant, PLoS Biol sourcePartly supported

  The Introduction section on improving the reliability of experimental results and analysis (Fig. 1 workflow; page not available in our copy) says users can export a PDF report containing the EDA diagram and information about the experiment’s internal validity. It does not say the PDF is time-stamped. (LLM, conf=0.87)

  Experimental — accuracy not yet measured

May combine two claims.

Registering a protocol before the start of the experiment enhances scientific rigour and protects the researcher against concerns about selective reporting of results.

“Registering a protocol before the start of the experiment enables researchers to demonstrate that the hypothesis, approach, and analysis were planned in advance and not shaped by data as they emerged; it enhances scientific rigour and protects the researcher against concerns about selective reporting of results [239,240].”

• cites [239] RM Kaplan, 2015, Likelihood of null effects of large NHLBI clinical trials has increased over time, PLoS ONE sourcePartly supported

  The Results section says prospective declaration of primary outcomes prevents investigators from selecting a favorable outcome to report, and the Discussion says preregistration constrained post hoc changes to hypotheses. The paper thus supports the selective-reporting and transparency rationale for preregistration, but it does not say that registration protects researchers personally from concerns about selective reporting, and its evidence concerns clinical trials rather than experiments generally. (LLM, conf=0.83)

  Experimental — accuracy not yet measured
• cites [240] C Allen, 2018, Open Science challenges, benefits and tips in early career and beyond, PsyArXivNot matched

  Couldn’t be matched to a paper in Crossref, so it can’t be checked.

Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

In the Registered Report format, protocols undergo peer review, and if accepted, the journal commits to publishing the completed research regardless of the results obtained.

“For example, in the Registered Report format offered by an increasing number of journals, protocols undergo peer review, and if accepted, the journal commits to publishing the completed research regardless of the results obtained [237].”

• cites [237] CD Chambers, 2014, Instead of "playing the game" it is time to change the rules: Registered Reports at AIMS Neuroscience and beyond, AIMS Neuroscience sourceSupported

Probably not a substantial claim: may not pass S3 (load-bearing).

An increasing number of publishers and funding bodies require authors or grant holders to make their data publicly available.

“An increasing number of publishers and funding bodies require authors or grant holders to make their data publicly available [247].”

• cites [247] V Stodden, 2013, Toward reproducible computational research: an empirical analysis of data and code policy adoption by journals, PLoS ONE sourcePartly supported

  The Discussion reports an increase from 2011 to 2012 in journals requiring data sharing, and the Introduction says NSF and NIH require dataset disclosure. But the Introduction describes sharing with other researchers, while some journal policies provide data only upon request; it does not establish that authors or grant holders must make data publicly available. Page numbers are not supplied in our copy. (LLM, conf=0.82)

  Experimental — accuracy not yet measured

Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

In such cases, power calculations are not appropriate and sample sizes can be estimated based on operational capacity and constraints.

“In such cases, power calculations are not appropriate and sample sizes can be estimated based on operational capacity and constraints [44].”

• cites [44] PS Reynolds, 2019, When power calculations won’t do: Fermi approximation of animal numbers, Lab Animal sourceNot checked — no full text of the source

Probably not a substantial claim: may not pass S3 (load-bearing), S4 (based). May combine two claims.

Two-sided tests with a nondirectional alternative hypothesis are much more common and allow researchers to detect the effect of a treatment regardless of its direction.

“Two-sided tests with a nondirectional alternative hypothesis are much more common and allow researchers to detect the effect of a treatment regardless of its direction.”

Classified as probably not a substantial claim. May combine two claims.

Study design can influence the statistical power of an experiment, and the power calculation used needs to be appropriate for the design implemented.

“Study design can influence the statistical power of an experiment, and the power calculation used needs to be appropriate for the design implemented.”

Probably not a substantial claim: may not pass S3 (load-bearing).

The choice of control or comparator group is dependent on the experimental objective.

“The choice of control or comparator group is dependent on the experimental objective.”

Probably not a substantial claim: may not pass S3 (load-bearing).

Reporting the total number of animals used in the study is useful to identify whether any were reused between experiments.

“Reporting the total number of animals used in the study is also useful to identify whether any were reused between experiments.”

Probably not a substantial claim: may not pass S2 (checkable).

For complex study designs, a visual representation is more easily interpreted than a text description.

“For complex study designs, a visual representation is more easily interpreted than a text description, so a timeline diagram or flowchart is recommended.”

Probably not a substantial claim: may not pass S3 (load-bearing).

For antibody or tissue production, the number of animals needed is determined by the amount required and the production ability of an individual animal.

“For example, the number of animals needed for antibody or tissue production is determined by the amount required and the production ability of an individual animal.”

Probably not a substantial claim: may not pass S3 (load-bearing).

Controversy exists within the statistics community on when it is appropriate to use a one-sided test.

“Controversy exists within the statistics community on when it is appropriate to use a one-sided test [42].”

• cites [42] LS Freedman, 2008, An analysis of the controversy over classical one-sided tests, Clin Trials sourceNot checked — no full text of the source

Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

Analyses such as ANOVA and chi-squared are based on asymmetrical distributions (F-distribution and chi-squared distribution) with only one tail; therefore, these tests do not have a directionality option.

“Note that analyses such as ANOVA and chi-squared are based on asymmetrical distributions (F-distribution and chi-squared distribution) with only one tail. Therefore, these tests do not have a directionality option.”

Probably not a substantial claim: may not pass S3 (load-bearing).

In early feasibility or pilot studies, the number of animals required depends on the purpose of the study.

“In early feasibility or pilot studies, the number of animals required depends on the purpose of the study.”

Probably not a substantial claim: may not pass S2 (checkable).

Diagrams facilitate the identification of which treatments and procedures were applied to specific animals or groups of animals and at what point in the study these were performed.

“Diagrams facilitate the identification of which treatments and procedures were applied to specific animals or groups of animals and at what point in the study these were performed.”

Probably not a substantial claim: may not pass S2 (checkable). May combine two claims.

Selectively excluding some experimental groups is misleading and should be avoided.

“Selectively excluding some experimental groups (for example, because the data are inconsistent or conflict with the narrative of the paper) is misleading and should be avoided [20].”

• cites [20] The BMJ. Scientific misconduct [cited 2020 Jan 10]. https://www.bmj.com/about-bmj/resources-authors/forms-policies-and-checklists/scientific-misconductNot checked yet

  Not checked in the free run.

Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

The sample size in each group at the start of the study may be different from the n numbers in the analysis; this information helps readers identify attrition or exclusions and in which group they occurred.

“The sample size in each group at the start of the study may be different from the n numbers in the analysis (see Item 3. Inclusion and exclusion criteria); this information helps readers identify attrition or if there have been exclusions and in which group they occurred.”

May combine two claims.

Sample sizes that are too large (overpowered studies) raise ethical issues over unnecessary use of animals and may produce trivial findings that are statistically significant but not biologically relevant.

“Sample sizes that are too small (i.e., underpowered studies) produce inconclusive results, whereas sample sizes that are too large (i.e., overpowered studies) raise ethical issues over unnecessary use of animals and may produce trivial findings that are statistically significant but not biologically relevant [35].”

• cites [35] MD Jennions, 2003, A survey of the statistical power of research in behavioral ecology and animal behavior, Behav Ecol sourceNot checked — no full text of the source

Probably not a substantial claim: may not pass S3 (load-bearing), S4 (based). May combine two claims.

Positive controls can be used to support the interpretation of negative results or determine if an expected effect is detectable.

“Positive controls can be used to support the interpretation of negative results or determine if an expected effect is detectable.”

Probably not a substantial claim: may not pass S3 (load-bearing).

When the objective of the preliminary study is primarily logistic or operational, the number of animals needed is generally small.

“When the objective of the preliminary study is primarily logistic or operational (e.g., to improve procedures and equipment), the number of animals needed is generally small.”

Probably not a substantial claim: may not pass S3 (load-bearing).

If each cell taken from the mouse is randomly allocated to different treatments and assessed individually, the cell might be regarded as the experimental unit.

“If, however, each cell taken from the mouse is then randomly allocated to different treatments and assessed individually, the cell might be regarded as the experimental unit.”

Probably not a substantial claim: may not pass S3 (load-bearing).

Choosing the appropriate calculator or algorithm to use depends on the type of outcome measures and independent variables, and the number of groups.

“Choosing the appropriate calculator or algorithm to use depends on the type of outcome measures and independent variables, and the number of groups.”

Probably not a substantial claim: may not pass S3 (load-bearing).

For studies in which the outcome is the successful generation of a sample or a condition, the number of animals is determined by the probability of success of the experimental procedure.

“For studies in which the outcome is the successful generation of a sample or a condition (e.g., the production of transgenic animals), the number of animals is determined by the probability of success of the experimental procedure.”

Probably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing).

Diagrams help to communicate complex design features such as whether factors are crossed or nested, blocking, or repeated measurements over time on the same experimental unit.

“They also help to communicate complex design features such as whether factors are crossed or nested (hierarchical/multilevel designs), blocking (to reduce unwanted variation, see Item 4. Randomisation), or repeated measurements over time on the same experimental unit (repeated measures designs); see [16–18] for more information on different design types.”

• cites [16] MF Festing, 2002, Guidelines for the design and statistical analysis of experiments using laboratory animals, ILAR J sourceNot checked — no full text of the source
• cites [17] ST Bate, 2014 sourceNot checked — no full text of the source
• cites [18] G Ruxton, 2017Not checked yet

  Not checked in the free run.

Probably not a substantial claim: may not pass S3 (load-bearing).

Exclusion criteria may result from technical or welfare issues such as complications anticipated during surgery or circumstances in which test procedures might be compromised.

“Exclusion criteria may result from technical or welfare issues such as complications anticipated during surgery or circumstances in which test procedures might be compromised (e.g., development of motor impairments that could affect behavioural measurements).”

Probably not a substantial claim: may not pass S3 (load-bearing).

Reporting exclusions may also provide important safety information for human trials.

“It may also provide important safety information for human trials (e.g., exclusions related to adverse effects).”

Probably not a substantial claim: may not pass S2 (checkable). May combine two claims.

Reporting losses helps the reader to understand the experimental design process, replicate methods, and provide adequate tracking of animal numbers in a study, especially when sample size numbers in the analyses do not match the original group numbers.

“Reporting losses will help the reader to understand the experimental design process, replicate methods, and provide adequate tracking of animal numbers in a study, especially when sample size numbers in the analyses do not match the original group numbers.”

Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

There are many legitimate reasons for experimental attrition, some of which are anticipated and controlled for in advance, but some data loss might not be anticipated.

“There are many legitimate reasons for experimental attrition, some of which are anticipated and controlled for in advance (see subitem 3a on defining exclusion and inclusion criteria), but some data loss might not be anticipated.”

Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

Data points may be excluded from analyses because of an animal receiving the wrong treatment, unexpected drug toxicity, infections or diseases unrelated to the experiment, sampling errors, or other human error.

“For example, data points may be excluded from analyses because of an animal receiving the wrong treatment, unexpected drug toxicity, infections or diseases unrelated to the experiment, sampling errors (e.g., a malfunctioning assay that produced a spurious result, inadequate calibration of equipment), or other human error (e.g., forgetting to switch on equipment for a recording).”

Classified as probably not a substantial claim.

Blinding is a strategy used to minimise subjective biases.

“Blinding is a strategy used to minimise these subjective biases.”

Probably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing).

Blinding during outcome assessment is especially important, particularly if there is a subjective element.

“Blinding is especially important during outcome assessment, particularly if there is a subjective element (e.g., when assessing behavioural changes or reading histological slides) [83].”

• cites [83] R Rosenthal, 1963, The effect of experimenter bias on the performance of the albino rat, Behav Sci sourceNot checked — no full text of the source

May combine two claims.

Using a validated method of randomisation helps minimise selection bias and reduce systematic differences in the characteristics of animals allocated to different groups.

“Using a validated method of randomisation helps minimise selection bias and reduce systematic differences in the characteristics of animals allocated to different groups [62–64].”

• cites [62] KF Schulz, 1995, Empirical evidence of bias. Dimensions of methodological quality associated with estimates of treatment effects in controlled trials, JAMA sourceNot checked — no full text of the source
• cites [63] KF Schulz, 2002, Allocation concealment in randomised trials: defending against deciphering, Lancet sourceNot checked — no full text of the source
• cites [64] TC Chalmers, 1983, Bias in treatment assignment in controlled clinical trials, N Engl J Med sourceNot checked — no full text of the source

May combine two claims.

Using appropriate randomisation methods during allocation to groups ensures that each experimental unit has an equal probability of receiving a particular treatment and provides balanced numbers in each treatment group.

“Using appropriate randomisation methods during the allocation to groups ensures that each experimental unit has an equal probability of receiving a particular treatment and provides balanced numbers in each treatment group.”

Probably not a substantial claim: may not pass S3 (load-bearing).

Exclusion criteria may also reflect the ethical principles of a study in line with its humane endpoints.

“Exclusion criteria may also reflect the ethical principles of a study in line with its humane endpoints (see Item 16. Animal care and monitoring).”

Probably not a substantial claim: may not pass S2 (checkable).

Reporting exclusions and attritions provides valuable information to other investigators evaluating the results or who intend to repeat the experiment or test the intervention in other species.

“Reporting exclusions and attritions provides valuable information to other investigators evaluating the results or who intend to repeat the experiment or test the intervention in other species.”

Probably not a substantial claim: may not pass S2 (checkable). May combine two claims.

Reporting the criteria used to exclude animals or data points in the manuscript helps readers with the interpretation of the data and provides crucial information to other researchers wanting to adopt the model.

“Whereas exclusion criteria and humane endpoints are typically included in the ethical review application, reporting the criteria used to exclude animals or data points in the manuscript helps readers with the interpretation of the data and provides crucial information to other researchers wanting to adopt the model.”

Probably not a substantial claim: may not pass S3 (load-bearing).

Criteria for excluding samples or data include failure to meet quality control standards, such as insufficient sample volumes, unacceptable levels of contaminants, poor histological quality.

“Criteria for excluding samples or data include failure to meet quality control standards, such as insufficient sample volumes, unacceptable levels of contaminants, poor histological quality, etc.”

Probably not a substantial claim: may not pass S2 (checkable).

The exact number of experimental units analysed in each group is essential information for the reader to interpret the analysis.

“The exact number of experimental units analysed in each group (i.e., the n number) is essential information for the reader to interpret the analysis; it should be reported unambiguously.”

Probably not a substantial claim: may not pass S3 (load-bearing).

If the person assessing the outcome cannot be blinded to group allocation, some, but not all, sources of bias could be mitigated by sending data for analysis to a third party who has no vested interest in the experiment and does not know whether a treatment is expected to improve or worsen the outcome.

“If the person assessing the outcome cannot be blinded to the group allocation (e.g., obvious phenotypic or behavioural differences between groups), some, but not all, of the sources of bias could be mitigated by sending data for analysis to a third party who has no vested interest in the experiment and does not know whether a treatment is expected to improve or worsen the outcome.”

Probably not a substantial claim: may not pass S3 (load-bearing), S4 (based).

Randomising the order of examination can reduce bias.

“Randomising the order of examination can also reduce bias.”

Probably not a substantial claim: may not pass S3 (load-bearing).

Allocation concealment together with randomisation helps minimise selection bias, which can introduce systematic differences between treatment groups.

“Together with randomisation, allocation concealment helps minimise selection bias, which can introduce systematic differences between treatment groups.”

Probably not a substantial claim: may not pass S2 (checkable).

Blinding during data analysis is important because the analyst makes many semisubjective decisions such as applying data transformation to outcome measures, choosing methods for handling missing data, and handling outliers.

“This type of blinding is often neglected but is important, as the analyst makes many semisubjective decisions such as applying data transformation to outcome measures, choosing methods for handling missing data, and handling outliers.”

Probably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing). May combine two claims.

Summary/descriptive statistics provide a quick and simple description of the data; they communicate quantitative results easily and facilitate visual presentation.

“Summary/descriptive statistics provide a quick and simple description of the data; they communicate quantitative results easily and facilitate visual presentation.”

Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

The outcome measure is potentially affected by the treatments or interventions being tested but also by other factors, such as the properties of the biological samples and technical considerations.

“The outcome measure is potentially affected by the treatments or interventions being tested but also by other factors, such as the properties of the biological samples (sex, litter, age, weight, etc.) and technical considerations (cage, time of day, batch, experimenter, etc.).”

Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

Categorical data are summarised by counts and percentages or proportions and are analysed by tests of proportions; these analysis methods assume that data are binary, ordinal or nominal, and independent.

“For example, categorical data are summarised by counts and percentages or proportions and are analysed by tests of proportions; these analysis methods assume that data are binary, ordinal or nominal, and independent [18].”

• cites [18] G Ruxton, 2017Not checked yet

  Not checked in the free run.

Probably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing). May combine two claims.

Standard acclimatisation periods may vary between research laboratories, and this information cannot be inferred by readers.

“Standard acclimatisation periods may vary between research laboratories, and this information cannot be inferred by readers.”

Probably not a substantial claim: may not pass S2 (checkable). May combine two claims.

This relationship has to be managed in the statistical analysis by including cage/litter/animal effects in the model or by aggregating the outcome measure to the cage/litter/animal level.

“This relationship has to be managed in the statistical analysis by including cage/litter/animal effects in the model or by aggregating the outcome measure to the cage/litter/animal level.”

Probably not a substantial claim: may not pass S3 (load-bearing).

If the assumptions are incorrect, the conclusions may not be valid.

“If the assumptions are incorrect, the conclusions may not be valid.”

Probably not a substantial claim: may not pass S3 (load-bearing), S4 (based). May combine two claims.

If the sample size is small, tests for normality will struggle to detect non-normality; if the sample size is large, the tests will detect unimportant deviations.

“However, these tests have to be used cautiously. If the sample size is small, they will struggle to detect non-normality; if the sample size is large, the tests will detect unimportant deviations.”

May combine two claims.

Reporting animal characteristics enables other researchers to repeat the experiment and generalise the findings.

“It enables other researchers to repeat the experiment and generalise the findings.”

Probably not a substantial claim: may not pass S3 (load-bearing), S4 (based). May combine two claims.

The assumptions for data used in parametric tests (such as a t test, z test, ANOVA, etc.) are that the data are continuous, the residuals from the analysis are normally distributed, the responses are independent, and different groups have similar variances.

“For example, the assumptions for data used in parametric tests (such as a t test, z test, ANOVA, etc.) are that the data are continuous, the residuals from the analysis are normally distributed, the responses are independent, and different groups have similar variances.”

May combine two claims.

Effect sizes are often not reported in animal research, but they are relevant to both exploratory and hypothesis-testing studies.

“Effect sizes are often not reported in animal research, but they are relevant to both exploratory and hypothesis-testing studies.”

Probably not a substantial claim: may not pass S3 (load-bearing).

If the residuals of the analysis are not normally distributed, the assumption may be satisfied using a data transformation in which the same mathematical function is applied to all data points to produce normally distributed data.

“If the residuals of the analysis are not normally distributed, the assumption may be satisfied using a data transformation in which the same mathematical function is applied to all data points to produce normally distributed data (e.g., loge, log10, square root).”

Probably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing), S4 (based).

Categorical data can be expressed as counts, frequencies, or proportions.

“Categorical data can be expressed as counts, frequencies, or proportions.”

May combine two claims.

Different types of outcome measures (binary, categorical, or ordinal) require different methods of analysis and have different sets of assumptions.

“Other types of outcome measures (binary, categorical, or ordinal) will require different methods of analysis, and each will have different sets of assumptions.”

• cites [18] G Ruxton, 2017Not checked yet

  Not checked in the free run.

Classified as probably not a substantial claim.

The hierarchy that can exist in an experiment can induce a clustering effect; for example, cage, litter, or animal effects can occur when the outcomes measured for animals from the same cage/litter, or for cells from the same animal, are more similar to each other.

“The hierarchy can induce a clustering effect; for example, cage, litter, or animal effects can occur when the outcomes measured for animals from the same cage/litter, or for cells from the same animal, are more similar to each other.”

Probably not a substantial claim: may not pass S3 (load-bearing).

For continuous data, descriptors include a measure of central tendency and a measure of variability to help readers assess the precision of the data collected.

“For continuous data, these descriptors include a measure of central tendency (e.g., mean, median) and a measure of variability (e.g., quartiles, range, standard deviation) to help readers assess the precision of the data collected.”

May combine two claims.

Animals of the same strain but from different sources, or animals obtained from the same source but at different times, may be genetically different.

“For example, animals of the same strain but from different sources, or animals obtained from the same source but at different times, may be genetically different [16].”

• cites [16] MF Festing, 2002, Guidelines for the design and statistical analysis of experiments using laboratory animals, ILAR J sourceNot checked — no full text of the source

Classified as probably not a substantial claim.

Reporting animal characteristics enables readers to assess whether the animal characteristics chosen for the experiment are relevant to the research objectives.

“It also enables readers to assess whether the animal characteristics chosen for the experiment are relevant to the research objectives.”

Probably not a substantial claim: may not pass S3 (load-bearing).

In some cases, reporting the developmental stage is more informative than chronological age-for example, in juvenile Xenopus, in which rate of development can be manipulated by incubation temperature.

“In some cases, however, reporting the developmental stage is more informative than chronological age—for example, in juvenile Xenopus, in which rate of development can be manipulated by incubation temperature [109].”

• cites [109] MK Khokha, 2002, Techniques and probes for the study of Xenopus tropicalis development, Dev Dyn sourceNot checked — no full text of the source

Probably not a substantial claim: may not pass S3 (load-bearing), S4 (based). May combine two claims.

Statistical significance is usually quantified and evaluated against a preassigned threshold, with p < 0.05 often used as a convention.

“Statistical significance is usually quantified and evaluated against a preassigned threshold, with p < 0.05 often used as a convention.”

Probably not a substantial claim: may not pass S4 (based).

Hypothesis tests are based on assumptions about the underlying data.

“Hypothesis tests are based on assumptions about the underlying data.”

Probably not a substantial claim: may not pass S3 (load-bearing).

To reduce the risk of bias, some factors can be taken into account in the design of the experiment, for example, by using blocking factors in the randomisation.

“To reduce the risk of bias, some of these factors can be taken into account in the design of the experiment, for example, by using blocking factors in the randomisation (see Item 4. Randomisation).”

Probably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing). May combine two claims.

An experiment designed to detect a hypothesised effect will likely need to be analysed with inferential statistics, and a statistical estimation of the sample size will need to be performed a priori.

“For example, an experiment designed to detect a hypothesised effect will likely need to be analysed with inferential statistics, and a statistical estimation of the sample size will need to be performed a priori (see Item 2. Sample size).”

Probably not a substantial claim: may not pass S2 (checkable).

Explaining the purpose of the study by describing the research question(s) allows readers to determine whether the study is relevant to them.

“Explaining the purpose of the study by describing the question(s) that the research addresses allows readers to determine whether the study is relevant to them.”

Probably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing). May combine two claims.

Ethical statements promote transparency and understanding about the use of animals in research and foster public trust.

“This also promotes transparency and understanding about the use of animals in research and fosters public trust.”

Probably not a substantial claim: may not pass S2 (checkable).

Readers can assess the relevance of the model organism, procedures, outcomes measured, and analysis used when the purpose of the study is explained.

“Readers can also assess the relevance of the model organism, procedures, outcomes measured, and analysis used.”

May combine two claims.

Exploratory research investigates many possible effects and is likely to yield more false positive results because some will be positive by chance.

“In contrast, exploratory research investigates many possible effects and is likely to yield more false positive results because some will be positive by chance.”

Probably not a substantial claim: may not pass S2 (checkable), S4 (based).

Knowing whether a study is exploratory or hypothesis-testing is critical to its interpretation.

“Knowing whether a study is exploratory or hypothesis-testing is critical to its interpretation.”

May combine two claims.

The abstract is often used as a screening tool by readers to decide whether to read the full article or whether to select an article for inclusion in a systematic review.

“The abstract is often used as a screening tool by readers to decide whether to read the full article or whether to select an article for inclusion in a systematic review.”

Probably not a substantial claim: may not pass S3 (load-bearing).

Hypothesis-testing studies have a predefined primary outcome measure, which is used to assess the evidence in support of the specific research question.

“Hypothesis-testing studies also have a predefined primary outcome measure, which is used to assess the evidence in support of the specific research question (see Item 6. Outcome measures).”

Probably not a substantial claim: may not pass S3 (load-bearing).

Tank colour affects stress in aquatic species.

“Tank colour affects stress in aquatic species [179,180].”

• cites [179] AM Holmes, 2016, Impact of tank background on the welfare of the African clawed frog, Xenopus laevis (Daudin), Appl Anim Behav Sci sourceNot checked — no full text of the source
• cites [180] M Pavlidis, 2013, Husbandry of zebrafish, Danio rerio, and the cortisol stress response, Zebrafish sourceNot checked — no full text of the source

May combine two claims.

The environment determines the health and wellbeing of the animals, and every aspect of it can potentially affect their behavioural and physiological responses, thereby affecting research outcomes.

“The environment determines the health and wellbeing of the animals, and every aspect of it can potentially affect their behavioural and physiological responses, thereby affecting research outcomes [175].”

• cites [175] T Nevalainen, 2014, Animal husbandry and experimental design, ILAR J sourceNot checked — no full text of the source

Probably not a substantial claim: may not pass S2 (checkable). May combine two claims.

A transparent and accurate abstract increases the utility and impact of the manuscript and allows readers to assess the reliability of the study.

“A transparent and accurate abstract increases the utility and impact of the manuscript and allows readers to assess the reliability of the study [153].”

• cites [153] RB Haynes, 1990, More informative abstracts revisited, Ann Intern Med sourceNot checked — no full text of the source

Probably not a substantial claim: may not pass S3 (load-bearing).

Exploratory research helps researchers to design hypothesis-testing experiments by choosing what variables or outcome measures to focus on in subsequent studies.

“Exploratory research helps researchers to design hypothesis-testing experiments by choosing what variables or outcome measures to focus on in subsequent studies.”

Probably not a substantial claim: may not pass S3 (load-bearing).

Temperature and humidity regulates sexual differentiation in zebrafish.

“Regulates sexual differentiation in zebrafish [187].”

• cites [187] C Lawrence, 2007, The husbandry of zebrafish (Danio rerio): A review, Aquaculture sourceNot checked — no full text of the source

Probably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing).

Hypothesis-testing studies may collect additional information for exploratory purposes.

“Hypothesis-testing studies may collect additional information for exploratory purposes; it is important to distinguish which hypotheses were prespecified and which originated after data inspection, especially when reporting unanticipated effects or outcomes that were not part of the original study design.”

Probably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing), S4 (based). May combine two claims.

A typical exploratory study may measure multiple outcomes and look for patterns in the data or relationships that can be used to generate hypotheses.

“A typical exploratory study may measure multiple outcomes and look for patterns in the data or relationships that can be used to generate hypotheses.”

Probably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing), S4 (based).

Independent replication and meta-analysis can further increase the confidence in conclusions.

“Independent replication and meta-analysis can further increase the confidence in conclusions.”

Classified as probably not a substantial claim. May combine two claims.

The confidence interval for the effect indicates how precisely the effect has been estimated and tells the reader about the strength of the effect.

“The confidence interval for the effect indicates how precisely the effect has been estimated and tells the reader about the strength of the effect [150].”

• cites [150] DG Altman, 2005, Why we need confidence intervals, World J Surg sourceNot checked — no full text of the source

Probably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing).

Systematic reviews of the animal literature provide the most convincing evidence that a research question has not been conclusively addressed, by showing the extent of current evidence within a field of research.

“Systematic reviews of the animal literature provide the most convincing evidence that a research question has not been conclusively addressed, by showing the extent of current evidence within a field of research.”

Probably not a substantial claim: may not pass S3 (load-bearing).

Environmental enrichment reduces susceptibility to epilepsy.

“Environmental enrichment | Reduces anxiety [196,197], stress [196,197], and abnormal repetitive behaviour [198–200]. Reduces susceptibility to epilepsy [201] and osteoarthritis [202] and modifies the pathology of neurological disorders [203]. Increases foraging behaviour in fish [204].”

• cites [201] R Auvergne, 2002, Delayed kindling epileptogenesis and increased neurogenesis in adult rats housed in an enriched environment, Brain Research sourceNot checked — no full text of the source

Probably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing).

The use of humane endpoints can help minimise harm while allowing the scientific objectives to be achieved.

“The use of humane endpoints can help minimise harm while allowing the scientific objectives to be achieved [219].”

• cites [219] C Hendriksen, 2011Not checked yet

  Not checked in the free run.

Probably not a substantial claim: may not pass S2 (checkable).

Reporting adverse events allows other researchers to plan appropriate welfare assessments and minimise the risk of these events occurring in their own studies.

“Reporting adverse events allows other researchers to plan appropriate welfare assessments and minimise the risk of these events occurring in their own studies.”

Probably not a substantial claim: may not pass S2 (checkable).

A thorough description of the procedures used to alleviate pain, suffering, and distress provides practical information for researchers to replicate the method.

“A thorough description of the procedures used to alleviate pain, suffering, and distress provides practical information for researchers to replicate the method.”

Probably not a substantial claim: may not pass S2 (checkable). May combine two claims.

Discussing the limitations of the work is important to place the findings in context, interpret the validity of the results, and ascribe a credibility level to its conclusions.

“Discussing the limitations of the work is important to place the findings in context, interpret the validity of the results, and ascribe a credibility level to its conclusions [227].”

• cites [227] JP Ioannidis, 2007, Limitations are not properly acknowledged in the scientific literature, J Clin Epidemiol sourceNot checked — no full text of the source

Probably not a substantial claim: may not pass S3 (load-bearing).

Exploratory results derived from additional outcomes may be underpowered and less reliable.

“Exploratory results derived from additional outcomes should not be described as conclusive, as they may be underpowered and less reliable.”

Probably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing).

Publishing score sheets of the clinical signs that were monitored can help guide other researchers to develop clinically relevant welfare assessments, particularly for studies reporting novel procedures.

“Publishing score sheets of the clinical signs that were monitored [221] can help guide other researchers to develop clinically relevant welfare assessments, particularly for studies reporting novel procedures.”

• cites [221] DB Morton, 2000, A systematic approach for establishing humane endpoints, ILAR J sourceNot checked — no full text of the source

Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

Datasets can be independently cited in their own right, which provides additional credit for authors.

“Datasets can also be independently cited in their own right, which provides additional credit for authors.”

Classified as probably not a substantial claim.

Sharing adequately annotated data allows others to replicate data analyses so that results can be independently tested and verified.

“Sharing adequately annotated data allows others to replicate data analyses so that results can be independently tested and verified.”

Classified as probably not a substantial claim.

The identification of funding sources allows the reader to assess any competing interests and any potential sources of bias.

“The identification of funding sources allows the reader to assess any competing interests and any potential sources of bias.”

Classified as probably not a substantial claim. May combine two claims.

Data sharing allows others to explore new topics and increases the impact of the study, potentially preventing unnecessary use of animals and providing more value for money.

“This allows others to explore new topics and increases the impact of the study, potentially preventing unnecessary use of animals and providing more value for money.”

Probably not a substantial claim: may not pass S1 (asserted), S2 (checkable), S3 (load-bearing), S4 (based).

Enough evidence may have accumulated in the literature to justify further research in another species or in humans.

“Alternatively, enough evidence may have accumulated in the literature to justify further research in another species or in humans.”

Probably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing), S4 (based).

Findings from a novel, exploratory study may be used to inform future research in a broadly similar context.

“Findings from a novel, exploratory study may be used to inform future research in a broadly similar context.”

Probably not a substantial claim: may not pass S3 (load-bearing).

The practice of independently citing datasets is gaining increasing recognition and acceptance.

“This practice is gaining increasing recognition and acceptance [250].”

• cites [250] Data Citation Synthesis Group, 2014Not checked yet

  Not checked in the free run.

Classified as probably not a substantial claim. May combine two claims.

Data sharing allows the data to be repurposed and new datasets to be created by combining data from multiple studies.

“Data sharing allows the data to be repurposed and new datasets to be created by combining data from multiple studies (e.g., to be used in secondary analyses).”

Probably not a substantial claim: may not pass S3 (load-bearing).

A time-stamped PDF from the EDA can be used to demonstrate that the study conduct, analysis, and reporting were not unduly driven by emerging data.

“This can be used to demonstrate that the study conduct, analysis, and reporting were not unduly driven by emerging data.”