Instrument Development Based on Content Analysis
8.3 Limitations
Defining and operationalising concepts that are relevant to nursing science is the main challenge that researchers face during instrument development. Using content analysis to operationalise a concept will also identify key contents and provide ways to measure the studied concept. Not every definition is expected to cover all of the factors of a specific phenomenon, but an instrument must include a clear definition before it can measure some construct. Another risk of instrument development is that patients’ and researchers’ understandings of the content of items may differ.
Therefore, researchers should encourage respondents to contact them if any item in the questionnaire is unclear. To further mitigate this risk, researchers could ask patients to evaluate the instrument’s content at different stages of the instrument development process (e.g., pilot testing). However, it is important to keep in mind that researchers and patients have different theoretical perspectives of the studied phenomenon, which may further complicate the instrument development process.
Instrument development is also difficult in that there are no straightforward rules for how many items an instrument should include. Hence, the researcher must make some tough choices when deleting or adding items to the developed instrument. For example, retaining too many items may artificially inflate the Cronbach’s alpha value, which—even though a positive result in terms of internal reliability—may signal that the instrument includes too many items. On the other hand, deleting numerous items may improve homogeneity as well as utility in clinical practice, but may increase the risk that the instrument does not sufficiently cover each factor of the studied phenomenon.
In addition, the suitability of the applied analytical methods will inevitably affect the reliability of the results; hence, ensuring that data and correlation matrices meet
Bartlett’s (p < 0.001) and Kaiser-Meyer-Olkin (p > 0.60) criteria is a good bench- mark. However, it is important to note that the correlations between variables may increase when missing values are replaced with mean values. Furthermore, large sample sizes can sometimes contribute to part of the observed statistical signifi- cance and may lead to overestimates of the number of significant factors. For this reason, researchers may elect to use a scree test instead of eigenvalues to restrict the number of factors when the instrument is tested using a large sample.
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H. Kyngäs et al. (eds.), The Application of Content Analysis in Nursing Science Research, https://doi.org/10.1007/978-3-030-30199-6_9
M. Kääriäinen (*)
Research Unit of Nursing Science and Health Management, Oulu University, Oulu, Finland Medical Research Center Oulu, Oulu University Hospital, Oulu, Finland
e-mail: [email protected] K. Mikkonen · H. Kyngäs
Research Unit of Nursing Science and Health Management, Oulu University, Oulu, Finland e-mail: [email protected]; [email protected]