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Year : 2021  |  Volume : 33  |  Issue : 3  |  Page : 260-262

The validation of questionnaires

Department of Research, AMMA Healthcare Research Gurukul, Kochi, Kerala, India

Date of Submission14-Jan-2021
Date of Decision17-Jan-2021
Date of Acceptance17-Jan-2021
Date of Web Publication08-Dec-2021

Correspondence Address:
Dr. Praveen K Nirmalan
AMMA Healthcare Research Gurukul, Kochi, Kerala
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Source of Support: None, Conflict of Interest: None

DOI: 10.4103/kjo.kjo_12_21

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We have previously described the design and development of a questionnaire. It is important to establish the validity of a questionnaire before it is administered to a population. A series of inter-related tests are required to determine the validity of a questionnaire. Questionnaires pass through an iterative process that includes the development of items, testing of the validity, revision of items, revision of the conceptual basis of the test, retesting, and repetition of the process till the questionnaire is finalized. The process of validation of a questionnaire continues if the questionnaire is in use. In this manuscript, we briefly describe the conceptual basis of the different methods that are used to establish the validity of questionnaires and item retention and exclusion.

Keywords: Internal consistency, item response theory, questionnaire, validation

How to cite this article:
Nirmalan PK. The validation of questionnaires. Kerala J Ophthalmol 2021;33:260-2

How to cite this URL:
Nirmalan PK. The validation of questionnaires. Kerala J Ophthalmol [serial online] 2021 [cited 2022 Jan 19];33:260-2. Available from: http://www.kjophthal.com/text.asp?2021/33/3/260/331915

  Introduction Top

Validity refers to the interpretations of measurements and is fundamental to the development and interpretations of tests.[1],[2] A questionnaire (or scale or test) has a specific purpose. The interpretations of the scores or results of the questionnaire must relate to the specific purpose of the questionnaire.[1],[2],[3] Validity provides a quantitative description of the support provided by evidence and theory to the interpretation of test scores.[1],[2],[3]

Structural validity

The scale or questionnaire generally follows one of three models.[4],[5],[6] The most common model is a quantitative model that uses the levels or degree of the target construct to differentiate individuals.[4],[5],[6] The other models include class models that categorize individuals into qualitatively different groups and the more complex dynamic models.[4],[5],[6] The structural validity implies that the internal structure of the questionnaire parallels the external structure of the target condition and reflects the underlying variance.[4],[7] Structural validity includes empirical assessments based on nontest parameters, tests for internal consistency focused on inter-item and item-total measures, and item response theory (IRT) assessments based on latent traits. Empirical assessments are useful at the stage of questionnaire development although they are usually used in external validation these days. Empirical assessments include the administration of the item pool to a clinical and community sample.[2],[8] The differences in mean item scores are then used in conjunction with other parameters to determine inclusion or exclusion of an item.

Internal consistency is widely used in the development of a questionnaire. Item-total correlations are generally used to determine if an item must be retained or excluded and can be done when developing a single scale.[1],[9],[10] However, an exploratory factor analysis (EFA) is a better and preferable option if the questionnaire has hierarchical constructs or multiple constructs. The EFA helps to identify the underlying dimensions (unidimensional or multidimensional) that are subsequently used for scale construction. The initial step is a principal factor analysis or a principal component analysis. Items that have loading factors 0.35–0.40 and items that have similar or stronger loadings on other factors are eliminated from the item pool of questions.[11],[12],[13] Confirmatory factor analysis is then used to further explore the structural validity of the questionnaire.[1],[11],[12],[13],[14] The loading of items in the factor analysis is used to explore the redundancy or similarity of items and the correlation of the items with the theoretical basis of the questionnaire and other items in the questionnaire.[1],[9],[10],[11],[12],[13],[14]

The IRT is another method that can be used after EFA to assess structural integrity, especially in short-form questionnaires.[10],[15],[16] IRT presumes that each item response reflects an underlying construct. IRT also presumes that an item characteristic curve can describe the item–trait relationship as a monotonically increasing function. IRT tries to identify specific items that provide maximum information for everyone and based on their level of the underlying dimension. IRT considers an item as optimal if the respondent has a 50% probability of responding correctly. IRT is also used to estimate item difficulty and item discrimination. The ability to estimate the individual item–trait level without administering a fixed set of items is a major advantage with IRT.[16],[17] This allows the development of computer-aided tests (CATs) that can be scaled up in difficulty based on the underlying capability of the person and through a subset of items that are maximally informative for each person. CATs are equally efficient and can provide trait-level information using fewer items than a conventional questionnaire.[16],[17]

Evaluation of the psychometric properties

The development of the questionnaire may lead to a revision of the theoretical concept underlying the questionnaire like how individual items are revised.[1],[9],[11] An initial step is to examine the response distributions of individual items. Items that have a highly skewed distribution (floor and ceiling effects) or questions where most respondents provide a similar response must be considered for elimination.[1],[9],[11] These unbalanced questions provide little information, weakly correlate with other items, and lead to highly unstable correlational results.[1],[9],[11]

The next step is to determine the items to eliminate or retain in the questionnaire. Each item in the questionnaire should measure only one thing.[1] However, we must look at the differences between internal consistency and unidimensionality. Internal consistency describes the intercorrelations between items of a scale. Cronbach's coefficient alpha is a test that is commonly used to determine internal consistency with a threshold of ≥0.80 suggesting that the item can be retained.[18],[19],[20] Unidimensionality indicates whether the items in a scale assess a single underlying factor and is, therefore, a better measure of the validity of a questionnaire.[21],[22] The often-used Cronbach's coefficient alpha is of limited use in the determination of unidimensionality. The Cronbach's coefficient alpha is also a function of the scale length and average inter-item correlation (AIC) and can lead to an imperfect measure of internal consistency.[18],[22] Several highly correlated items, many moderately correlated items, and various combinations of scale length and AIC can lead to erroneous measures of internal consistency using Cronbach's alpha test.[18],[22] Cronbach's alpha test cannot be used if the number of items in a questionnaire is more than 40.[1],[18],[22]

An AIC that falls between 0.15 and 0.5 is considered a better measure than the Cronbach's coefficient alpha.[21],[22] However, the AIC alone cannot establish the unidimensionality of the questionnaire. A higher AIC can be obtained by averaging many higher coefficients with many lower ones. It is, therefore, necessary to examine the range and distribution of these correlations and not focus only on the AIC.[21],[22] Thus, the AIC and majority of the inter-item correlations should range between 0.15 and 0.50 to ensure unidimensionality.[1],[21],[22]

External validity

The process of external validation of a questionnaire continues if that questionnaire is in use. Clear conceptualization of the theory, development of specific and relevant item pools, and assessment of convergent and discriminant validity during the scale development help to understand what the questionnaire measures and what it does not.[1]

Convergent validity is examined by assessing the relationships between indicators of the same construct.[23] Discriminant validity examines the relation of a measure with indicators of other constructs and looks to establish that highly correlated constructs within hierarchical models are empirically distinct from one another. Discriminant validity is established by showing that convergent correlations are significantly higher than discriminant coefficients.[1],[23] Criterion validity is shown through the significant relation of a test with theoretically relevant nontest outcomes (e.g., clinical diagnoses and arrest records). Incremental validity demonstrates that the measure adds significantly to the prediction of a criterion over and above what can be predicted by other sources of data.[23]

  Conclusion Top

The design, development, and validation of a questionnaire involves several stages of testing and revision to establish validity. Changes to the structure of the questionnaire in terms of addition or deletion of questions, rewording questions, and change in response scales affect the validity of the questionnaire and impact on the interpretation of results. Questionnaires are developed for specific contexts in specific populations. It is important to retest the validity of a questionnaire when it is applied in a new context or a different population or when a translated version of the questionnaire is used.

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Conflicts of interest

There are no conflicts of interest.

  References Top

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Watson D. Objective tests as instruments of psychological theory and research. In: Cooper H, editor. Handbook of Research Methods in Psychology. Foundations, Planning, Measures, and Psychometrics. Vol. 1. Washington, DC: American Psychological Association; 2012. p. 349-69.  Back to cited text no. 14
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