Identifying subgroups based on self-management skills in primary care patients with moderate medically unexplained physical symptoms.

OBJECTIVE:Medically Unexplained Physical Symptoms (MUPS) are a major burden on both patients and society and frequently develop into chronic MUPS. Self-management interventions may prevent moderate MUPS from becoming chronic. Tailoring interventions to the patient population is strongly recommended. This can be facilitated by identifying subgroups based on self-management skills. This study aimed to identify these subgroups and their clinical profiles in primary care patients with moderate MUPS. METHODS:A cross-sectional study was performed on baseline measurements from a randomized clinical trial (PARASOL-study). To identify subgroups based on self-management skills, a hierarchical cluster analysis was conducted for adults with moderate MUPS from primary health care centers. Self-management skills were measured with the Health education impact Questionnaire. Cluster variables were seven constructs of this questionnaire. Additionally, specific patient profiles were determined by comparing the identified clusters on the clinical variables pain, fatigue and physical functioning. RESULTS:Four subgroups were identified: High-Self-Management Skills (SMS) (n = 29), Medium-SMS (n = 55), Low-SMS (n = 49) and Active & Low Distress-SMS (n = 20). The latter showed a distinctly different pattern on cluster variables, while the other subgroups differed significantly on means of the cluster variables (p < .001). On clinical variables, significant differences between subgroups were mainly found on fatigue and physical functioning. CONCLUSION:This study found four specific subgroups based on self-management skills in moderate MUPS-patients. One subgroup demonstrated a distinctly different pattern on self-management skills. In other subgroups, more similar patterns on self-management skills were found that negatively correlated with pain and fatigue and positively correlated with physical functioning.