"Blue flags", development of a short clinical questionnaire on work-related psychosocial risk factors - a validation...

Working conditions substantially influence health, work ability and sick leave. Useful instruments to help clinicians pay attention to working conditions are lacking in primary care (PC). The aim of this study was to test the validity of a short "Blue flags" questionnaire, which focuses on work-related psychosocial risk factors and any potential need for contacts and/or actions at the workplace.

From the original"The General Nordic Questionnaire" (QPS_Nordic) the research group identified five content areas with a total of 51 items which were considered to be most relevant focusing on work-related psychosocial risk factors. Fourteen items were selected from the identified QPS_Nordic content areas and organised in a short questionnaire "Blue flags". These 14 items were validated towards the 51 QPS_Nordic items. Content validity was reviewed by a professional panel and a patient panel. Structural and concurrent validity were also tested within a randomised clinical trial.

The two panels (n = 111) considered the 14 psychosocial items to be relevant. A four-factor model was extracted with an explained variance of 25.2%, 14.9%, 10.9% and 8.3% respectively. All 14 items showed satisfactory loadings on all factors. Concerning concurrent validity the overall correlation was very strong r_s = 0.87 (p < 0.001).). Correlations were moderately strong for factor one, r_s = 0.62 (p < 0.001) and factor two, r_s = 0.74 (p < 0.001). Factor three and factor four were weaker, bur still fair and significant at r_s = 0.53 (p < 0.001) and r_s = 0.41 (p < 0.001) respectively. The internal consistency of the whole "Blue flags" was good with Cronbach's alpha of 0.76.

The content, structural and concurrent validity were satisfactory in this first step of development of the "Blue flags" questionnaire. In summary, the overall validity is considered acceptable. Testing in clinical contexts and in other patient populations is recommended to ensure predictive validity and usefulness.