Outcomes included health-related quality of life as measured by the short-form 12-item interview (SF-12) physical and mental component summary (PCS and MCS) scores, depression, post-traumatic stress disorder (PTSD), eating disorders, fibromyalgia, other chronic pain, cardiovascular disease risk factors, and cancer.
In cluster 3 (52 patients) we found a reduction of MCS and increase of depression and fatigue (similar to cluster 2) but also a decrease in PCS levels and Bodily Pain (meaning increase in pain).
The results showed acceptance of illness to be positively correlated with quality of life in terms of PCS (rho = 0.43) and MCS (rho = 0.36), and depression and anxiety to be negatively correlated with quality of life in both domains (PCS: rho = -0.39 and rho = -0.56, respectively; MCS: rho = -0.56 and rho = -0.78, respectively).
Baseline scores were compared to post-injury time points for SF-12 subscores (physical and mental; PCS-12, MCS-12) and HADS subscores (depression and anxiety; HADS-D, HADS-A).
Hierarchical analyses showed that after controlling for potential confounding factors (demographics, depression, BMI), sleep quality significantly increased model's predictive power with an R² change (ΔR²) by 3.5% for PCS (adjusted R² = 0.27) and by 2.9% for MCS (adjusted R² = 0.48); for the other SF-12 components ΔR² ranged between 1.4% and 4.6%.
Multiple regression analysis detected the General Fatigue score of the MFI-20 questionnaire and depression identified by the PHQ-9 score as independent variables predicting MCS of the SF-36 in both genders.
Given the great variability of depressive symptoms in patients with or without self-reported depression and medicated or unmedicated status, we elected to use the MCS classification of depressive symptoms for our analysis.