Predicting Work Disability Related to Spinal Pain: A Systematic Review of the Most Clinically Relevant Tools

Musculoskeletal disorders, especially spinal conditions, are leading causes of disability, contributing significantly to work absenteeism and socio-economic burden. Rehabilitation is essential for promoting sustainable return to work (RTW). However, clinicians need reliable tools with appropriate psychometric properties to determine patients' risk of persistent work disability and tailor interventions. This systematic review objectives were to (1) identify clinically useful questionnaires that enable clinicians to identify individuals with spinal pain (back or neck pain) at risk of work disability, and (2) document the psychometric properties of the identified questionnaires.

A systematic search was conducted in three databases from inception to 01/10/2025, to retrieve relevant studies. Studies were included if they reported self-administered questionnaires with ≤ 15 items predicting RTW outcomes in spinal disorders. Tools were evaluated based on psychometric properties (calibration, discrimination), and pragmatic characteristics (number of items, readability).

Seventeen studies were retrieved including 16 unique questionnaires of which four demonstrated sufficient discrimination capability. From these, the Örebro musculoskeletal pain questionnaire 10-items (ÖMPQ- 10), STarT Back screening tool (SBST), and a single item from the ÖMPQ- 25 demonstrated acceptable to excellent discrimination for low back pain populations, but showed lower discrimination for mixed or neck pain populations.

The SBST, ÖMPQ- 10, and single items from the ÖMPQ- 25 performed best in predicting RTW outcomes for low back pain. No questionnaire had sufficient discriminatory capability for neck pain. These results should be interpreted with caution, as the overall risk of bias assessment remains unclear for the OMPQ- 10 and high for the SBST. Further research is necessary to develop or validate tools specific to neck pain and mixed populations.