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Home / Equine Research Bank / Vet Sci / Identifying Sources of Potential Bias When Using Online Surv...
Veterinary sciences2020; 7(3); 140; doi: 10.3390/vetsci7030140

Identifying Sources of Potential Bias When Using Online Survey Data to Explore Horse Training, Management, and Behaviour: A Systematic Literature Review.

Abstract: Owner-reported behavioural observations form an essential part of the veterinarians' diagnosis and treatment plan. The way we train and manage horses affects their behaviour and, in turn, their health and welfare. Current horse training and management practices are largely driven by traditional techniques and longstanding methodologies. These approaches generally lack an evidence base for evaluation purposes. The absence of evidence and evaluation contributes to the persistent use of risky practices and this, in turn, increases risk of potential harms for both horse and rider, and fuels questioning of the equine industry's current social license to operate. Objective evidence is required to make training and management decisions based on demonstrable best practice. Large-scale experimental or intervention studies using horses are generally not practical because of the associated costs and logistics of gaining ethical approval. Small studies generally lack statistical power and are subject to the effects of many forms of bias that demand caution in the interpretation of any observed effects. An alternative to collecting large amounts of empirical data is the use of owner-reported observations via online survey. Horse owners are ideally placed to report on the domestic equine triad of training, management, and behaviour. The current article highlights three sources of potential bias in a systematic review of literature on large-scale online studies of horse owners' observational reports that met the following selection criteria: English-language, published, peer-reviewed articles reporting on studies with over 1000 respondents and open access to the survey instrument. The online surveys were evaluated for three common forms of bias: recall, confirmation, and sampling bias. This review reveals that online surveys are useful for gathering data on the triad of horse training, management, and behaviour. However, current use of online surveys to collect data on equitation science (including horse training, management, and behaviour) could be improved by using a standardised and validated tool. Such a tool would facilitate comparisons among equine and equitation science studies, thus advancing our understanding of the impacts of training and management on horse behaviour. The authors of the current review suggest the use of a standardised behavioural and management assessment tool for horses. Such a tool would help define what constitutes normal behaviour within geographically disparate populations of horses, leading to improvements in rider safety and horse welfare.
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Publication Date: 2020-09-22 PubMed ID: 32971754PubMed Central: PMC7558402DOI: 10.3390/vetsci7030140Google Scholar: Lookup
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Summary

This research summary has been generated with artificial intelligence and may contain errors and omissions. Refer to the original study to confirm details provided. Submit correction.

This research article is focused on the exploration of potential bias in using online survey data to investigate horse training, management, and behaviour. By conducting a systematic review of existing literature on this topic, the authors propose the development of a standardized tool to enhance the reliability of online surveys, thus ensuring more accurate horse management practices and ultimately improving both rider safety and horse welfare.

Objective and Methodology

  • The study was designed to investigate potential sources of bias in online surveys that solicit owner-reported observations on horse training, management, and behaviour.
  • Online surveys are increasingly used to gather data due to the cost and logistical challenges of large-scale experimental studies with horses.
  • The authors conducted a systematic review of English-language, peer-reviewed articles reporting on studies with over 1000 respondents and open access to the survey instrument.
  • The focus was on identifying three common forms of bias: recall bias (errors due to the lapse in time between an event and recall of that event), confirmation bias (tendency to accept information supporting existing ideas and reject contrasting evidence), and sampling bias (occurs when a sample is not representative of the population it’s supposed to represent).

Findings and Implications

  • Based on the review, the authors concluded that online surveys have potential in gathering large amounts of data on horse training, management, and behaviour.
  • However, the authors also identified serious flaws due to recall, confirmation, and sampling bias in existing studies using online surveys in equitation science.
  • To address these biases, the authors proposed the use of a standardized behavioural and management assessment tool for horse owners filling out surveys.
  • Such a tool would allow for more accurate comparisons among different equine science studies and improve the understanding of the impacts of training and management on horse behaviour.
  • The authors argue that having more accurate, standardized data could help define what is considered normal horse behaviour across different geographic populations.
  • The overall aim is to improve rider safety and horse welfare through the identification and use of evidence-based best practices in horse training and management.

Cite This Article

APA
Fenner K, Hyde M, Crean A, McGreevy P. (2020). Identifying Sources of Potential Bias When Using Online Survey Data to Explore Horse Training, Management, and Behaviour: A Systematic Literature Review. Vet Sci, 7(3), 140. https://doi.org/10.3390/vetsci7030140

Publication

Veterinary sciences
ISSN: 2306-7381
NlmUniqueID: 101680127
Country: Switzerland
Language: English
Volume: 7
Issue: 3
PII: 140

Researcher Affiliations

Fenner, Kate
  • Sydney School of Veterinary Science, Faculty of Science, University of Sydney, Sydney, NSW 2006, Australia.
Hyde, Michelle
  • Sydney School of Veterinary Science, Faculty of Science, University of Sydney, Sydney, NSW 2006, Australia.
Crean, Angela
  • Sydney School of Veterinary Science, Faculty of Science, University of Sydney, Sydney, NSW 2006, Australia.
McGreevy, Paul
  • Sydney School of Veterinary Science, Faculty of Science, University of Sydney, Sydney, NSW 2006, Australia.

Conflict of Interest Statement

The authors declare no conflict of interest.

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