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. 2014 Sep 11;16(9):e207.
doi: 10.2196/jmir.3511.

Applying computer adaptive testing to optimize online assessment of suicidal behavior: a simulation study

Derek Paul De Beurs  1 , Anton Lm de Vries, Marieke H de Groot, Jos de Keijser, Ad Jfm Kerkhof
Affiliations

Applying computer adaptive testing to optimize online assessment of suicidal behavior: a simulation study

Derek Paul De Beurs et al. J Med Internet Res. .

Abstract

Background: The Internet is used increasingly for both suicide research and prevention. To optimize online assessment of suicidal patients, there is a need for short, good-quality tools to assess elevated risk of future suicidal behavior. Computer adaptive testing (CAT) can be used to reduce response burden and improve accuracy, and make the available pencil-and-paper tools more appropriate for online administration.

Objective: The aim was to test whether an item response-based computer adaptive simulation can be used to reduce the length of the Beck Scale for Suicide Ideation (BSS).

Methods: The data used for our simulation was obtained from a large multicenter trial from The Netherlands: the Professionals in Training to STOP suicide (PITSTOP suicide) study. We applied a principal components analysis (PCA), confirmatory factor analysis (CFA), a graded response model (GRM), and simulated a CAT.

Results: The scores of 505 patients were analyzed. Psychometric analyses showed the questionnaire to be unidimensional with good internal consistency. The computer adaptive simulation showed that for the estimation of elevation of risk of future suicidal behavior 4 items (instead of the full 19) were sufficient, on average.

Conclusions: This study demonstrated that CAT can be applied successfully to reduce the length of the Dutch version of the BSS. We argue that the use of CAT can improve the accuracy and the response burden when assessing the risk of future suicidal behavior online. Because CAT can be daunting for clinicians and applied scientists, we offer a concrete example of our computer adaptive simulation of the Dutch version of the BSS at the end of the paper.

Keywords: Internet; computing methodologies; psychometrics; risk assessment; suicidal ideation; suicide.

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Conflict of interest statement

Conflicts of Interest: None declared.

Figures

Figure 1
Figure 1
Example of category response curve for item 7 (frequency of thinking about suicide). Number and colors (0: black; 1: red; 2: green) reflect answer options.
Figure 2
Figure 2
Relationship between level of theta and the number of administered items under stop rule 1. The curve represents test information as a function of theta.
Figure 3
Figure 3
Concrete example of a result of a CAT simulation.
See this image and copyright information in PMC

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References

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