Walker et al, Lab Animal publication - survey data

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Last modified date
  • November 3, 2021
Creator
  • Rebecca Walker
    • ORCID: 0000-0003-3789-3992
    • Affiliation: School of Medicine, Department of Social Medicine
Abstract
  • This national survey aimed to identify how biomedical researchers using vertebrate animals viewed issues of significance for translational science including oversight and public engagement and to analyze how researcher characteristics and animal model choice correlate with those views. Responses from 1,187 researchers showed awareness of, and concerns about, problems of translation, reproducibility, and rigor. Surveyed scientists were nevertheless optimistic about the value of animal studies, favorable about research oversight, and reported openness with nonscientists in discussing their animal work. Differences in survey responses among researchers also point to diverse perspectives within the animal research community on these matters. Most significant was variability associated with the primary type of animal that surveyed scientists used in their work. Other significant divergence in opinion appeared based on professional role factors, including type(s) of degree held, workplace setting, type(s) of funding, experience on an Institutional Animal Care and Use Committee, as well as personal demographic characteristics of age and gender.
Methodology
  • Notes for publicly available data: 1. Data made publicly available for this survey is redacted to protect participant privacy. For this reason, the analyst’s file does not fully match the presented data. Researchers needing access to redacted information should be in touch with Rebecca Walker [rlwalker@email.unc.edu] to discuss options. 2. Figures 1-5 and Tables 1-7 are based on data presented in the survey responses with the exception of data redacted to protect participant privacy. Statistical analysis. All analysis was completed using Stata (version 16.1). Only respondents who completed the survey were included in the analysis. If respondents reached the end of the survey and selected responses to questions on each page the survey was considered complete. Descriptive statistics were generated for all variables with potential implications for attitudes and beliefs related to animal research oversight, public engagement, and the translational value of animal research. Regression analysis was used to identify demographic and attitudinal factors associated with each outcome of interest. Relationships were modeled using logistic regression for binary outcome variables, ordinal logit (ologit) for ordered or Likert-type outcome variables, and multinomial logit for categorical outcome variables. We tested whether ordinal models met the parallel lines assumption using gologit2 with autofit and there were no differences in coefficients across levels, so we used ologit for all ordinal models. For regression models, a one-unit change in an independent variable is associated with a percentage change in the conditional probability of the outcome of interest. Respondents who selected options that were very rare (such as degree other than PhD, MD, or DVM) were excluded from regression analyses that used the variable in question; the excluded response options are shown in Tables 1 and 2. Observations with missing data on any variable were dropped from that specific model but not from the dataset. Scientists’ views on SABV are reported separately.50 Some data on scientists’ perceptions of translational science issues were also used to analyze their views on SABV, as indicated in Table 2.
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Kind of data
  • Text
Resource type
  • Article
License
  • CC0 1.0 Universal
Language
  • English

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