Best practices in reporting analyses of questionnaires as objective rating scales of variable measures

Introduction
Questionnaires are frequently used as rating scales of latent variables such as knowledge, anxiety and treatment outcomes. However, reporting the steps involved before generating the final ‘measures’ often fails to present known limitations and robust solutions to the problems common in questionnaire data.

Aim
To highlight some common problems in questionnaire data and suggest techniques of constructing objective measures during rating scale analysis.

Background
The majority of questionnaire designers generate variable measures, either for educational or clinical research purposes, without providing adequate explanations of the steps taken to address inherent limitations that may worsen the error terms in the outcome measure. On the background that the usefulness of any measure depends on the least allowable error implies that best practice approach must be adopted during rating scale analysis. The best practice model states that the highest quality of scientific information in a discipline be engaged in addressing pertinent problems. Hence this paper proposes practical solutions to some shortcomings in reporting questionnaire analysis, based on modern theories of objective measurement in advanced statistics.

Conclusion
Cursory attention is given to the problems in questionnaire analysis as most users do not convincingly justify the applied measurement techniques before presenting variable estimation. Reporting the techniques used to address data complexity by engaging objective measurement parameters ensures best practice and emphasises the credibility of the outcome measure.

Implications
For a variable measure to be immediately useful, having limited error terms comparable to rating scales such as a clinical thermometer or height measure from a measuring tape, known limitations predisposing to increasing error must be identified and objectively resolved.