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Background: Depression is a highly prevalent mental disorder, but only a fraction of those affected receive evidence-based treatments. Recently, Internet-based interventions were introduced as an efficacious and cost-effective approach. However, even though depression is a heterogenous construct, effects of treatments have mostly been determined using aggregated symptom scores. This carries the risk of concealing important effects and working mechanisms of those treatments.
Methods: In this study, we analyze outcome and long-term follow-up data from the EVIDENT study, a large (N = 1,013) randomized-controlled trial comparing an Internet intervention for depression (Deprexis) with care as usual. We use Network Intervention Analysis to examine the symptom-specific effects of the intervention. Using data from intermediary and long-term assessments that have been conducted over 36 months, we intend to reveal how the treatment effects unfold sequentially and are maintained.
Results: Item-level analysis showed that scale-level effects can be explained by small item-level effects on most depressive symptoms at all points of assessment. Higher scores on these items at baseline predicted overall symptom reduction throughout the whole assessment period. Network intervention analysis offered insights into potential working mechanisms: while deprexis directly affected certain symptoms of depression (e.g., worthlessness and fatigue) and certain aspects of the quality of life (e.g., overall impairment through emotional problems), other domains were affected indirectly (e.g., depressed mood and concentration as well as activity level). The configuration of direct and indirect effects replicates previous findings from another study examining the same intervention.
Conclusions: Internet interventions for depression are not only effective in the short term, but also exert long-term effects. Their effects are likely to affect only a small subset of problems. Patients reporting these problems are likely to benefit more from the intervention. Future studies on online interventions should examine symptom-specific effects as they potentially reveal the potential of treatment tailoring.
Clinical Trial Registration: ClinicalTrials.gov, Identifier: NCT02178631.
Given the increasing prevalence of chronic kidney disease (CKD) and its impact on health care, it is important to better understand the multiple factors influencing health-related quality of life (HRQOL), particularly since they have been shown to affect CKD outcomes. Determinants of HRQOL as measured by the validated Kidney Disease Quality of Life questionnaire (KDQOL) and the Patient Health Questionnaire depression screener (PHQ-9) were assessed in a routine CKD patient sample, the Greifswald Approach to Individualized Medicine (GANI_MED) renal cohort (N = 160), including a wide range of self-reported data, sociodemographic and laboratory measures. Compared to the general population, CKD patients had lower HRQOL indices. Dialysis was associated with (1) low levels of physical functioning, (2) increased impairments by symptoms and problems, and (3) more effects and burden of kidney disease. HRQOL is seriously affected in CKD patients. However, impairments were found irrespective of eGFR decline and albuminuria. Rather, the comorbid conditions of depression and diabetes predicted a lower HRQOL (physical component score). Further studies should address whether recognizing and treating depression may not only improve HRQOL but also promote survival and lower hospitalization rates of CKD patients.