Negative mood is an important risk factor for poor clinical outcomes among individuals with musculoskeletal pain. Screening for negative mood can aid in identifying those who may need additional psychological interventions. Limitations of current negative mood screening tools include (1) high response burden, (2) a focus on single dimensions of negative mood, (3) poor precision for identifying individuals with low or high negative mood levels, and/or (4) design not specific for use in populations with orthopaedic conditions and musculoskeletal pain.
(1) Can item response theory methods be used to construct screening tools for negative mood (such as depression, anxiety, and anger) in patients undergoing physical therapy for orthopaedic conditions? (2) Do these tools demonstrate reliability and construct validity when used in a clinical setting?
This was a cross-sectional study involving outpatients having physical therapy in tertiary-care settings. A total of 431 outpatients with neck (n = 93), shoulder (n = 108), low back (n = 119), or knee (n = 111) conditions were enrolled between December 2014 and December 2015, with 24% (103 of 431) seeking care after orthopaedic surgery. Participants completed three validated psychological questionnaires measuring negative mood, resulting in 39 candidate items for item response theory analysis. Factor analysis was used to identify the dimensions (factors) assessed by the candidate items and select items that loaded on the main factor of interest (negative mood), establishing a unidimensional item set. Unidimensionality of an item set suggests they are assessing one main factor or trait, allowing unbiased score estimates. The identified items were assessed for their fit to the graded item response theory model. This model allows for items to vary by the level of difficulty they represent and by their ability to discriminate between patients at different levels of the trait being assessed, in this case, negative mood. Finally, a hierarchical bifactor model where multiple subfactors are allowed to load on an overall factor was used to confirm that the items identified as representing a unidimensional item set explained the large majority of variance of the overall factor, providing additional support for essential unidimensionality. Using the final item bank, we constructed a computer adaptive test administration mode, and reduced item sets were selected to create short forms including items with the highest information (reliability) at targeted score levels of the trait being measured, while also considering clinical content.
We identified a 12-item bank for assessment of negative mood; eight-item and four-item short-form versions were developed to reduce administrative burden. Computer adaptive test administration used a mean ± SD of 8 ± 1 items. The item bank’s reliability (0 = no reliability; 1 = perfect reliability) was 0.89 for the computer adaptive test administration, 0.86 for the eight-item short form, and 0.71 for the four-item short form. Reliability values equal to or greater than 0.7 are considered acceptable for group level measures. Construct validity sufficient for clinical practice was supported by more severe negative mood scores among individuals with a previous episode of pain in the involved anatomical region, pain and activity limitations during the past 3 months, a work-related injury, education less than a college degree, and income less than or equal to USD 50,000.
These newly derived tools include short-form and computer adaptive test options for reliable and valid negative mood assessment in outpatient orthopaedic populations. Future research should determine the responsiveness of these measures to change and establish score thresholds for clinical decision-making.
Orthopaedic providers can use these tools to inform prognosis, establish clinical benchmarks, and identify patients who may benefit from psychological and/or behavioral treatments.