Multidimensional screening for predicting pain problems in adults: a systematic review of screening tools and validation studies

Elke Veirman*, Dimitri M.L. Van Ryckeghem, Annick De Paepe, Olivia J Kirtley, Geert Crombez

*Corresponding author for this work

Research output: Contribution to journalReview articlepeer-review


Screening tools allowing to predict poor pain outcomes are widely used. Often these screening tools contain psychosocial risk factors. This review (1) identifies multidimensional screening tools that include psychosocial risk factors for the development or maintenance of pain, pain-related distress, and pain-related disability across pain problems in adults, (2) evaluates the quality of the validation studies using Prediction model Risk Of Bias ASsessment Tool (PROBAST), and (3) synthesizes methodological concerns. We identified 32 articles, across 42 study samples, validating 7 screening tools. All tools were developed in the context of musculoskeletal pain, most often back pain, and aimed to predict the maintenance of pain or pain-related disability, not pain-related distress. Although more recent studies design, conduct, analyze, and report according to best practices in prognosis research, risk of bias was most often moderate. Common methodological concerns were identified, related to participant selection (eg, mixed populations), predictors (eg, predictors were administered differently to predictors in the development study), outcomes (eg, overlap between predictors and outcomes), sample size and participant flow (eg, unknown or inappropriate handling of missing data), and analysis (eg, wide variety of performance measures). Recommendations for future research are provided.

Original languageEnglish
Article numbere775
JournalPain reports
Issue number5
Publication statusPublished - 26 Dec 2019

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