Exploring Free Questionnaire Data with Anchor Variables: An Illustration Based on a Study of IT in Healthcare

Exploring Free Questionnaire Data with Anchor Variables: An Illustration Based on a Study of IT in Healthcare

Ned Kock (Texas A&M International University, USA) and Jacques Verville (Auburn University Montgomery, USA)
DOI: 10.4018/jhisi.2012010104
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This paper makes an important methodological contribution regarding the use of free questionnaires, illustrated through a study that shows that a healthcare professional’s propensity to use electronic communication technologies creates opportunities for interaction with other professionals, which would not otherwise be possible only via face-to-face interaction. This in turn appears to increase mutual trust, and eventually improve the quality of group outcomes. Free questionnaires are often used by healthcare information management researchers. They yield datasets without clear associations between constructs and related indicators. If such associations exist, they must first be uncovered so that indicators can be grouped within latent variables referring to constructs, and structural equation modeling analyses be conducted. A novel methodological contribution is made here through the proposal of an anchor variable approach to the analysis of free questionnaires. Unlike exploratory factor analyses, the approach relies on the researcher’s semantic knowledge about the variables stemming from a free questionnaire. The use of the approach is demonstrated using the multivariate statistical analysis software WarpPLS 2.0. The study leads to a measurement model that passes comprehensive validity, reliability, and collinearity tests. It also appears to yield practically relevant and meaningful results.
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Can the use of electronic communication technologies, such as email and social networking tools, improve the quality of the work conducted by groups of healthcare professionals? This paper provides an affirmative answer to this question, while making primarily a methodological contribution regarding the use of free questionnaires in survey research on healthcare information and communication technologies.

The methodological contribution is illustrated through a study showing that a healthcare professional’s propensity to use electronic communication technologies creates opportunities for interaction with other professionals; opportunities that would not otherwise be available only via face-to-face interaction. The end result appears to be an improvement in the quality of the work outcomes generated by groups of healthcare professionals. This improvement seems to be significantly mediated by an increase in mutual trust.

Survey research has been extensively used in the field of information systems and other fields that inform healthcare information management research (Galliers, 1992; Galliers et al., 2006; Ju et al., 2006; Orlikowski & Baroudi, 1991). It has also been extensively used in healthcare information management research itself (Erstad, 2003; Miller et al., 2004). Survey research enables healthcare information management researchers to study human-technology interaction and outcomes based on data that is both geographically distributed and builds on relatively large samples. Geographically distributed datasets are difficult to obtain through data collection approaches that rely on local samples such as field, case, and experimental research (Creswell, 2009). Large samples are typically difficult to obtain through intensive data collection approaches like field, case, and action research (Denzin & Lincoln, 2000; Kock, 2006). As such, survey research provides a good complement to other research approaches used in the field of healthcare information management.

In survey research typically questionnaires are used to collect data about a particular topic (Creswell, 2009; Drew & Hardman, 1985). Questionnaires can be designed with a general topic in mind or, more specifically, with certain constructs in mind (Creswell, 2009; Ehremberg & Goodhart, 1976). The former are referred to here as free questionnaires, where the component questions are not tied to a particular set of constructs. They include questions on a general topic, with the questions not necessarily expected to group around underlying constructs.

When questionnaires are designed with specific constructs in mind, the constructs are purported to be measured through multiple indicators. In this case, each indicator refers to a question-statement in the questionnaire, and is frequently measured on a Likert-type scale. The constructs and indicators are also expected to pass a confirmatory factor analyses (Ehremberg & Goodhart, 1976; Hair et al., 2009).

Even a questionnaire designed with certain constructs in mind may include questions that are not expected to be associated with specific constructs. This may happen as a researcher adds free questions to take advantage of a data collection opportunity. For example, a questionnaire may include 20 questions related to 5 key constructs, and another 15 free questions that are not specifically related to any underlying construct yet are anticipated to provide additional insights into the topic under study.

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