This subproject is one of many research subprojects utilizing theresources provided by a Center grant funded by NIH/NCRR. The subproject andinvestigator (PI) may have received primary funding from another NIH source,and thus could be represented in other CRISP entries. The institution listed isfor the Center, which is not necessarily the institution for the investigator.A number of well publicized cases involving breaches of normative scientific behavior have lead to a new concern with the integrity of the research enterprise. A review of the state of recent initiatives to address research integrity by the National Research Council recommended three key efforts: 1) develop measures for the assessment of research integrity, 2) identify the environmental or career events that influence research integrity, and 3) develop effective educational interventions. In the present effort, two studies will be conducted, one examining graduate research assistants and one examining working professionals in the health, biological, and social sciences. Participants will be asked to complete three measures of ethical decision making tailored to scientific work. These measures will be used to both identify the critical components of effective training and to identify the work climate variables and career events that influence ethical decision making. The data gathered in this effort will also be used to validate a set of prototype instruments for the assessment of research integrity and the environmental variables that influence integrity across researchers' career. A.
Specific Aims : The research undertaking here is an infrastructure research and, consequently, no specific hypothesis were made. Despite this, the study has very specific and important short and long term aims that it seeks to accomplish.
Specific Aims :1. Provide evidence for the reliability and validity of low-fidelity simulation assessments intended to appraise the propensity for ethical decision-making on tasks involving issues such as data reporting, authorship, and treatment of animals and human participants.2. Assess the prevalence of unethical decisions in low-fidelity simulations across populations (e.g., graduate students, professionals), fields (e.g., social, biological, and health sciences) and institutions.3. Provide evidence for the reliability and validity of measures of individual, group, and organizational environmental influences on research integrity.4. Identify the environmental events operating at the individual, group, and organizational levels related to, or correlated with, a lack of integrity in decision-making and asses the relative magnitude of these relationships across different levels of analysis.5. Identify whether responsible conduct of research (RCR) training leads to improved ethical decision-making using assessments applicable to health, biological and social sciences.6. Identify the crucial elements or features of training programs that lead to relatively large improvements in the ethical decision-making of scientists.7. Examine the effects of RCR training on scientists' ethical decision-making over time. Long term:1. Provide the infrastructure for studying research integrity and ethical decision-making in scientific research.2. Provide key insights into the crucial features in RCR training design.3. Provide initial insights into understanding key individual and environmental variables that affect the research integrity and ethical decision-making in scientific researchers.4. Provide to the literature three potential scientific ethical decision-making measures assessed on psychometric principles.5. Provide the National Institute for Health (NIH) and the National Research Council (NCR) a basis to make inferences about the current state of scientific research with regard to research integrity and ethical decision-making in terms of prevalence and key causes.6. Provide the research community impetus to conduct further studies into understanding and advancing research integrity and ethical decision-making within fields (e.g., within Social Sciences) and across fields (e.g., between Biological Sciences and Health Sciences).
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