Scale developers often provide evidence of content validity by computing a content validity index (CVI), using ratings of item relevance by content experts. We analyzed how nurse researchers have defined and calculated the CVI, and found considerable consistency for item-level CVIs (I-CVIs). However, there are two alternative, but unacknowledged, methods of computing the scale-level index (S-CVI). One method requires universal agreement among experts, but a less conservative method averages the item-level CVIs. Using backward inference with a purposive sample of scale development studies, we found that both methods are being used by nurse researchers, although it was not always possible to infer the calculation method. The two approaches can lead to different values, making it risky to draw conclusions about content validity. Scale developers should indicate which method was used to provide readers with interpretable content validity information.

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The content validity index: Are you sure you know what's being reported? critique and recommendations

This study sought to conduct a review of content validity, which is an important phase of processes of construction and adaptation of measurement instruments. Research of comprehensive literature was conducted by means of a review of national and international databases. Initially, a description of the conceptual basis and the measurement methods used in content validity was made, with emphasis on its application in the healthcare area. It was seen that controversy exists in the literature on the terminology and concept of content validity. The recommended procedures used to check content validity during the construction and adaptation processes of instruments were described, especially the judges' assessment, which can involve qualitative and quantitative procedures. The number, selection and qualification of these judges were also described. The different methods used to quantify the level of agreement among the experts were verified, mainly the Content Validity Index (CVI). This study described aspects of the content validity process, one of the procedures to be considered by healthcare researchers and professionals who are interested in using reliable and appropriate measurements and instruments scales for given population groups.

https://www.scielosp.org/pdf/csc/2011.v16n7/3061-3068/pt

Validade de conteúdo nos processos de construção e adaptação de instrumentos de medidas

In this AMEE Guide, we consider the design and development of self-administered surveys, commonly called questionnaires. Questionnaires are widely employed in medical education research. Unfortunately, the processes used to develop such questionnaires vary in quality and lack consistent, rigorous standards. Consequently, the quality of the questionnaires used in medical education research is highly variable. To address this problem, this AMEE Guide presents a systematic, seven-step process for designing high-quality questionnaires, with particular emphasis on developing survey scales. These seven steps do not address all aspects of survey design, nor do they represent the only way to develop a high-quality questionnaire. Instead, these steps synthesize multiple survey design techniques and organize them into a cohesive process for questionnaire developers of all levels. Addressing each of these steps systematically will improve the probabilities that survey designers will accurately measure what they intend to measure.

/pdf/developing-questionnaires-for-educational-research-amee-2fsofqbwlm.pdf

Developing questionnaires for educational research: AMEE Guide No. 87

Introduction: The importance of content validity in the instrument psychometric and its relevance with reliability, have made it an essential step in the instrument development. This article attempts to give an overview of the content validity process and to explain the complexity of this process by introducing an example. Methods: We carried out a methodological study conducted to examine the content validity of the patient-centered communication instrument through a two-step process (development and judgment). At the first step, domain determination, sampling (item generation) and instrument formation and at the second step, content validity ratio, content validity index and modified kappa statistic was performed. Suggestions of expert panel and item impact scores are used to examine the instrument face validity. Results: From a set of 188 items, content validity process identified seven dimensions includes trust building (eight items), informational support (seven items), emotional support (five items), problem solving (seven items), patient activation (10 items), intimacy/friendship (six items) and spirituality strengthening (14 items). Content validity study revealed that this instrument enjoys an appropriate level of content validity. The overall content validity index of the instrument using universal agreement approach was low; however, it can be advocated with respect to the high number of content experts that makes consensus difficult and high value of the S-CVI with the average approach, which was equal to 0.93. Conclusion: This article illustrates acceptable quantities indices for content validity a new instrument and outlines them during design and psychometrics of patient-centered communication measuring instrument.

https://jcs.tbzmed.ac.ir/PDF/JCS-4-165.pdf

Design and Implementation Content Validity Study: Development of an instrument for measuring Patient-Centered Communication

The use of animation and multimedia for learning is now further extended by the provision of entire Virtual Reality Learning Environments (VRLE). This highlights a shift in Web-based learning from a conventional multimedia to a more immersive, interactive, intuitive and exciting VR learning environment. VRLEs simulate the real world through the application of 3D models that initiates interaction, immersion and trigger the imagination of the learner. The question of good pedagogy and use of technology innovations comes into focus once again. Educators attempt to find theoretical guidelines or instructional principles that could assist them in developing and applying a novel VR learning environment intelligently. This paper introduces the educational use of Web-based 3D technologies and highlights in particular VR features. It then identifies constructivist learning as the pedagogical engine driving the construction of VRLE and discusses five constructivist learning approaches. Furthermore, the authors provide two case studies to investigate VRLEs for learning purposes. The authors conclude with formulating some guidelines for the effective use of VRLEs, including discussion of the limitations and implications for the future study of VRLEs.

Investigating learners' attitudes toward virtual reality learning environments: Based on a constructivist approach

Social scientists frequently study complex constructs. Despite the plethora of measures for these constructs, researchers may need to create their own measure for a particular study. When a measure is created, psychometric testing is required, and the first step is to study the content validity of the measure. The purpose of this article is to demonstrate how to conduct a content validity study, including how to elicit the most from a panel of experts by collecting specific data. Instructions on how to calculate a content validity index, factorial validity index, and an interrater reliability index and guide for interpreting these indices are included. Implications regarding the value of conducting a content validity study for practitioners and researchers are discussed. Key words: constructs; content validity; measure; psychometric testing ********** Researchers in the social sciences study complex constructs for which valid and reliable measures are needed. The measures should be brief, clear, and easy to administer. Measures that are too long or difficult to read may result in a lowered response rate or inaccurate responses. In addition, the measure must be appropriate for use in the targeted population. For example, measures designed for use with heterogeneous populations may not be appropriate for a specific population with certain characteristics. A plethora of measures exist with known psychometric properties, but researchers may need to develop a new measure for a particular construct because no measure exists that operationalizes the construct as the researcher conceptualized it. In these circumstances, a content validity study should be conducted. VALIDITY Traditionally, three types of validity may be demonstrated: content, criterion, and construct validity. Content Validity Content validity refers to the extent to which the items on a measure assess the same content or how well the content material was sampled in the measure. Content validity can be characterized as face validity or logical validity. Face validity indicates that the measure appears to be valid, "on its face." Logical validity indicates a more rigorous process, such as using a panel of experts to evaluate the content validity of a measure. Nunnally and Bernstein (1994) did not distinguish among different types of content validity; but presented alternative ways of assessing content validity. They suggested evaluating content validity by demonstrating internal consistency through correlating the scores from the measure with another measure of the same construct and by showing change in posttest scores over pretest scores. Criterion Validity Criterion validity is demonstrated by finding a statistically significant relationship between a measure and a criterion (Nunnally & Bernstein, 1994). Criterion validity is considered the "gold standard," and usually a correlation is used to assess the statistical relationship. For example, the Graduate Record Examination (GRE) has been found to predict graduate school success (as measured by the first-year grade-point average) for certain disciplines (Rubio, Rubin, & Brennan, 2003). Three types of criterion validity are postdictive, concurrent, and predictive. If the criterion has occurred, the validity is postdictive. The validity is concurrent if the criterion exists at the same time as the construct measured. The GRE example demonstrates predictive validity, because graduate school success (criterion) occurs after taking the GRE (measure). According to Nunnally and Bernstein, a correlation of .30 indicates adequate criterion validity. Construct Validity Anastasi and Urbina (1997) described construct validity as "the extent to which the test may be said to measure a theoretical construct or trait" (p. 126). Three kinds of construct validity are factorial, known groups; and convergent and discriminant (or divergent) validity. …

E. Suzanne Lee

Papers

Objectifying Content Validity: Conducting a Content Validity Study in Social Work Research