Statistical groupings of mental and social health measurements correlate with musculoskeletal capability - A cross sectional study

OBJECTIVE

A better understanding of the degree to which social health factors contribute uniquely to statistical clusters associated with variation in levels of capability might inform targeted whole person care strategies for more comprehensive management of musculoskeletal health. Therefore, we asked: (1) What are the statistical groupings of social and mental health measurements in patients seeking specialty care for musculoskeletal conditions? (2) Do identified psychosocial groupings correspond with different mean magnitudes of incapability accounting for demographic and clinical factors?

METHODS

We included 158 patients seeking musculoskeletal specialty care and collected measures of magnitude of incapability, unhelpful thoughts and distress regarding symptoms, symptoms of depression, symptoms of anxiety, and social health. A k-means clustering algorithm was fit to the data and a linear regression model compared mean PROMIS-PF CAT scores for grouping.

RESULTS

A quantitative social health measure contributed to 4 statistical clusters as follows: 1) relatively low levels of all mental health measures and high social health; 2) greater unhelpful thoughts and distress regarding symptoms, average symptoms of general anxiety and depression, and average social health; 3) higher levels of all mental health measures and severely compromised social health; and 4) severely compromised mental health and lower social health. Magnitude of incapability was significantly greater for groups with worse mental and social health.

CONCLUSION

The finding of a relatively independent association of social and mental health factors with greater incapability supports the importance of introducing comprehensive health strategies in musculoskeletal specialty care. Strategies may include mindset training and case management of social unmet needs.

LEVEL OF EVIDENCE

Level III; Cross-sectional study.