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.
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).
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).
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).
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.
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.