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Related Concept Videos

Data Validation01:03

Data Validation

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Data validation is an essential part of a comprehensive assessment. Validation is confirming or verifying and opening the door to gathering more assessment data as it clarifies vague or unclear data. The process of checking and verifying the collected information is called data validation. The primary purpose of data validation is to ensure data is as free from error, bias, and misinterpretation as possible.
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According to obedience research, we may harm others under the forceful pressures of an authority figure (Milgram, 1974). How about if the inappropriate orders were delivered with less force? The increasing interdependence between nurses and physicians compelled Hofling and his colleagues to explore nurses’ reactions to a potentially harmful medical request made by the perceived authority figure, the doctor (Hofling, Brotzman, Dalrymple, Graves, & Pierce, 1966). In this situation,...
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The Scientific Method in Nursing Process01:18

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The scientific method provides the foundation for any research. It is the most reliable and objective of all forms of gaining knowledge and guides in applying research-based evidence in practice and conducting future research.
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Theories play an essential role in organizing patient care. Theories refer to a proposed or followed belief, policy, or procedure that is the basis for action. Nursing theories are knowledge-based concepts that guide nurses' actions, influence nursing education and practice, and allow nurses to care for their patients.
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Nomology, validity, and interprofessional research: The missing link(s).

Rachel S Rauvola1,2, Erick P Briggs2, Leslie J Hinyard3

  • 1Center for Interprofessional Education and Research, Saint Louis University , St. Louis, MO, USA.

Journal of Interprofessional Care
|February 14, 2020
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Summary
This summary is machine-generated.

Improving interprofessional research requires better scale validation. This paper emphasizes construct validity, offering a guide for developing and validating measurement tools in interprofessional studies.

Keywords:
Interprofessional researchconstruct validitynomological networksscale developmentscale validation

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Area of Science:

  • Health Professions Education
  • Interprofessional Healthcare
  • Measurement in Health Sciences

Background:

  • Calls for increased rigor in interprofessional research highlight the need for improved measurement tools.
  • Current interprofessional scale development often lacks robust validation, particularly regarding convergent and discriminant validity.
  • Establishing nomological networks and construct validity is foundational for interprofessional theory, research, and practice.

Purpose of the Study:

  • To underscore the critical importance of construct validation for interprofessional measurement instruments.
  • To review existing interprofessional scales and their validation methodologies.
  • To provide practical recommendations and a step-by-step guide for future scale development and validation in interprofessional research.

Main Methods:

  • Literature review of key concepts in construct validation.
  • Analysis of extant interprofessional scales and their reported validation evidence.
  • Development of a procedural guide for scale development and validation.

Main Results:

  • Limited evidence of convergent and discriminant validity in current interprofessional scale validation efforts.
  • Identification of gaps in the methodological rigor of interprofessional measurement tools.
  • A comprehensive guide for researchers and scale developers is proposed.

Conclusions:

  • Enhanced construct validation is essential for advancing interprofessional research rigor.
  • The proposed guide offers a structured approach to developing and validating reliable interprofessional measurement tools.
  • Adoption of these recommendations will strengthen the foundation of interprofessional theory, research, and practice.