This Shiny app (http://shiny.rstudio.com) converts scores between the Positive and Negative Syndrome Scale (PANSS; Kay et al., 1987, Schizophr Bull, 13: 261-276) and the Scale for the Assessment of Positive Symptoms or Scale for the Assessment of Negative Symptoms (SAPS/SANS; Andreasen, 1984, 1983, University of Iowa). Beyond conversions for global indices of positive and negative symptoms (van Erp et al., 2014, Schizophr Res, 152: 289-294), the app allows converting positive (delusions, disorganization, hallucinations) and negative (amotivation, expressivity, cognition) subscores between scales, as described in Grot et al, 2021, Psychiatry Res, 305:114199, doi: 10.1016/j.psychres.2021.114199 (preprint doi: 10.31234/osf.io/9nzd8).
Interactive conversion equations are available in the software R through the Shiny package: install.packages("shiny") and install.packages("shinyjs"). Scores conversion between scales will be performed using the following command line: shiny::runGitHub("pnplab/convert_app").
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Choose all conversions you wish to perform by selecting from the list of possible options, either from PANSS to SAPS/SANS or SAPS/SANS to PANSS, and either for total positive/negative scores or subscores (delusions, disorganization, hallucinations, amotivation, expressivity, cognition).
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Select a csv (comma separated variables) input file that has the same number of columns than the number of input variables. Note the order of columns must be in the exact same order as the list of input variables. Check the
Ignore First Linecheck box if you have names header at the top of your input file so the app can skip the first line. -
The requested converted scores will appear in a table at the right of the interface. The first columns are the input variables while the last columns provide the output variables. You can toggle between plots to visualize graphical representations of the conversions. A larger circle reflects an increased proportion of subjects with a given score. Converted scores can be downloaded as a new csv file with
Download the output file.
PANSS Positive symptoms
PANSS_positive = mean(PANSS01-PANSS07)
PANSS_delusions = mean(PANSS01, PANSS05 - PANSS07)
PANSS_disorganization = PANSS02
PANSS_hallucinations = PANSS03
PANSS Negative symptoms
PANSS_negative = mean(PANSS08-PANSS14)
PANSS_expressivity = mean(PANSS08, PANSS10, PANSS13)
PANSS_amotivation = mean(PANSS09, PANSS11)
PANSS_cognition = mean(PANSS12)
SAPS Positive symptoms
SAPS_total = mean(SAPS01 - SAPS06, SAPS08 - SAPS19, SAPS21 - SAPS24, SAPS26 - SAPS33)
SAPS_summary = mean(SAPS07, SAPS20, SAPS25, SAPS34)
SAPS_delusions = SAPS20
SAPS_disorganization = mean(SAPS25, SAPS34)
SAPS_hallucinations = SAPS07
SANS Negative symptoms
SANS_total = mean(SANS01 - SANS07, SANS09 - SANS12, SANS14 - SANS16, SANS18 - SANS21, SANS23 - SANS24)
SANS_summary = mean(SANS08, SANS13, SANS17, SANS22, SANS25)
SANS_expressivity = mean(SANS08, SANS13)
SANS_amotivation = mean(SANS17, SANS22)
SANS_cognition = SANS25
PANSS_positive = 1.499 + 1.079 * SAPS_total
PANSS_positive = 1.325 + 0.631 * SAPS_summary
PANSS_negative = 1.016 + 0.962 * SANS_total
PANSS_negative = 0.953 + 0.753 * SANS_summary
PANSS_delusions = 1.265 + 0.494 * SAPS_delusions
PANSS_disorganization = 1.234 + 0.979 * SAPS_disorganization
PANSS_hallucinations = 1.235 + 0.859 * SAPS_hallucinations
PANSS_expressivity = 0.977 + 0.752 * SANS_expressivity
PANSS_amotivation = 0.698 + 0.843 * SANS_amotivation
PANSS_cognition = 2.455 + 0.436 * SANS_cognition
SAPS_total = -0.543 + 0.528 * PANSS_positive
SAPS_summary = -0.637 + 0.918 * PANSS_positive
SANS_total = -0.370 + 0.721 * PANSS_negative
SANS_summary = -0.363 + 0.883 * PANSS_negative
SAPS_delusions = -0.849 + 1.293 * PANSS_delusions
SAPS_disorganization = -0.245 + 0.481 * PANSS_disorganization
SAPS_hallucinations = -0.773 + 0.941 * PANSS_hallucinations
SANS_expressivity = -0.541 + 0.907 * PANSS_expressivity
SANS_amotivation = 0.430 + 0.677 * PANSS_amotivation
SANS_cognition = 0.492 + 0.329 * PANSS_cognition