PhD defence Dyllis Aimée van Dijk
Supervisors: Prof. dr. F.P.M.L. Peeters, Prof. dr. J. Spijker
Co-supervisors: Dr. H.G. Ruhé, Dr. Th.M. van den Boogaard
Keywords: Depression, Treatment planning, Waiting times, Dropout
"Improving outpatient depression care: insights into waiting times, dropout, and treatment planning"
This dissertation focuses on how outpatient depression care can be improved. The studies presented explored factors that influence treatment outcomes and evaluated instruments that may support treatment planning.
Longer waiting times were associated with poorer outcomes, underscoring the importance of timely access to care. Furthermore, understanding treatment dropout is crucial for improving outcomes. In the studied population, higher socioeconomic status, more severe depression, and the presence of comorbid disorders were associated with lower dropout rates. In another study, patients with both depression and personality pathology received more psychotherapy sessions than those without such comorbidity, raising questions about the balance between necessary additional care and potential overtreatment. Research into the perspectives of patients and caregivers on successful treatment further emphasized the importance of the therapeutic alliance, and identified the organization of care, specific treatment components, and adherence to guidelines as core concepts of treatment success according to lived experience.
Sixteen prediction instruments available to clinicians were also evaluated. Despite limitations in accuracy and the need for further research, they may support depression treatment planning. One specific instrument, the Dutch Measure for quantification of Treatment Resistance in Depression (DM-TRD), was studied in a large population and predicted poorer outcomes at higher scores; adding a childhood trauma item did not improve its predictive validity.
Overall, reducing waiting times, preventing dropout, careful consideration of treatment intensity, incorporating patient and caregiver perspectives, and the careful use of prediction instruments in treatment planning may all contribute to improving outpatient depression care.
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