Is self-guided internet-based cognitive behavioural therapy (iCBT) harmful? : An individual participant data meta-analysis

BACKGROUND: Little is known about potential harmful effects as a consequence of self-guided internet-based cognitive behaviour therapy (iCBT), such as symptom deterioration rates. Thus, safety concerns remain and hamper the implementation of self-guided iCBT into clinical practice. We aimed to conduct an individual participant data (IPD) meta-analysis to determine the prevalence of clinically significant deterioration (symptom worsening) in adults with depressive symptoms who received self-guided iCBT compared with control conditions. Several socio-demographic, clinical and study-level variables were tested as potential moderators of deterioration. METHODS: Randomised controlled trials that reported results of self-guided iCBT compared with control conditions in adults with symptoms of depression were selected. Mixed effects models with participants nested within studies were used to examine possible clinically significant deterioration rates. RESULTS: Thirteen out of 16 eligible trials were included in the present IPD meta-analysis. Of the 3805 participants analysed, 7.2% showed clinically significant deterioration (5.8% and 9.1% of participants in the intervention and control groups, respectively). Participants in self-guided iCBT were less likely to deteriorate (OR 0.62, p < 0.001) compared with control conditions. None of the examined participant- and study-level moderators were significantly associated with deterioration rates. CONCLUSIONS: Self-guided iCBT has a lower rate of negative outcomes on symptoms than control conditions and could be a first step treatment approach for adult depression as well as an alternative to watchful waiting in general practice

Efficacy of Self-guided Internet-Based Cognitive Behavioral Therapy in the Treatment of Depressive Symptoms : A Meta-analysis of Individual Participant Data

IMPORTANCE Self-guided internet-based cognitive behavioral therapy (iCBT) has the potential to increase access and availability of evidence-based therapy and reduce the cost of depression treatment. OBJECTIVES To estimate the effect of self-guided iCBT in treating adults with depressive symptoms compared with controls and evaluate the moderating effects of treatment outcome and response. DATA SOURCES A total of 13 384 abstracts were retrieved through a systematic literature search in PubMed, Embase, PsycINFO, and Cochrane Library from database inception to January 1, 2016. STUDY SELECTION Randomized clinical trials in which self-guided iCBT was compared with a control (usual care, waiting list, or attention control) in individuals with symptoms of depression. DATA EXTRACTION AND SYNTHESIS Primary authors provided individual participant data from 3876 participants from 13 of 16 eligible studies. Missing data were handled using multiple imputations. Mixed-effects models with participants nested within studies were used to examine treatment outcomes and moderators. MAIN OUTCOMES AND MEASURES Outcomes included the Beck Depression Inventory, Center for Epidemiological Studies-Depression Scale, and 9-item Patient Health Questionnaire scores. Scales were standardized across the pool of the included studies. RESULTS Of the 3876 study participants, the mean (SD) age was 42.0 (11.7) years, 2531 (66.0%) of 3832 were female, 1368 (53.1%) of 2574 completed secondary education, and 2262 (71.9%) of 3146 were employed. Self-guided iCBT was significantly more effective than controls on depressive symptoms severity (ß =-0.21; Hedges g = 0.27) and treatment response (ß = 0.53; odds ratio, 1.95; 95% CI, 1.52-2.50; number needed to treat, 8). Adherence to treatment was associated with lower depressive symptoms (ß =-0.19; P =.001) and greater response to treatment (ß = 0.90; P <.001). None of the examined participant and study-level variables moderated treatment outcomes. CONCLUSIONS AND RELEVANCE Self-guided iCBT is effective in treating depressive symptoms. The use of meta-analyses of individual participant data provides substantial evidence for clinical and policy decision making because self-guided iCBT can be considered as an evidence-based first-step approach in treating symptoms of depression. Several limitations of the iCBT should be addressed before it can be disseminated into routine care

Is self-guided internet-based cognitive behavioural therapy (iCBT) harmful? An individual participant data meta-analysis

Background Little is known about potential harmful effects as a consequence of self-guided internet-based cognitive behaviour therapy (iCBT), such as symptom deterioration rates. Thus, safety concerns remain and hamper the implementation of self-guided iCBT into clinical practice. We aimed to conduct an individual participant data (IPD) meta-analysis to determine the prevalence of clinically significant deterioration (symptom worsening) in adults with depressive symptoms who received self-guided iCBT compared with control conditions. Several socio-demographic, clinical and study-level variables were tested as potential moderators of deterioration. Methods Randomised controlled trials that reported results of self-guided iCBT compared with control conditions in adults with symptoms of depression were selected. Mixed effects models with participants nested within studies were used to examine possible clinically significant deterioration rates. Results Thirteen out of 16 eligible trials were included in the present IPD meta-analysis. Of the 3805 participants analysed, 7.2% showed clinically significant deterioration (5.8% and 9.1% of participants in the intervention and control groups, respectively). Participants in self-guided iCBT were less likely to deteriorate (OR 0.62, p < 0.001) compared with control conditions. None of the examined participant- and study-level moderators were significantly associated with deterioration rates. Conclusions Self-guided iCBT has a lower rate of negative outcomes on symptoms than control conditions and could be a first step treatment approach for adult depression as well as an alternative to watchful waiting in general practice.This work was funded by the European Commission’s Seventh Framework Program (grant 603098 for the E-COMPARED project). At the time of the study, Dr K. Griffiths was supported by National Health & Medical Research Counselling Fellowship 1059620

Malaria in Kenya during 2020: malaria indicator survey and suitability mapping for understanding spatial variations in prevalence, intervention and risk

Despite the availability of effective interventions malaria continues to be a major public health issue in Kenya, where young children and pregnant women are particularly vulnerable. In this study we examined the spatial distribution of malaria incidence and how this relates to the environmental conditions required for malaria in 2020. The Kenya Malaria Indicator Survey (N=11,549) for 2020 was used with the Local Indicators of Spatial Autocorrelation (LISA) method to determine spatial clusters of malaria and assess their significance as well as interventions in use. Climate data was used with a Fuzzy Overlay method to create malaria risk maps. The findings suggest that malaria incidence is not evenly distributed across Kenya, with some regions having higher rates of transmission and others having lower rates. High-rate clusters of malaria and high-risk areas of malaria transmission could benefit from increased vector control measures

ENDIG: Interactive Geovisualization of Surveillance Systems for Notifiable Diseases in Europe

National disease surveillance systems are among the most important tools for the observation and management of communicable diseases. They help to detect outbreaks and monitor the success of public health responses. The European Union aims to harmonize the European landscape of disease surveillance systems for better interoperability across the member states. However, the progress of these efforts is difficult to assess, as information is available in different formats, written reports or numerous tables for individual diseases. Here we present ENDIG, an interactive geovisualization tool, that makes the existing information easily accessible to end users and researchers in public health and adjoining disciplines. ENDIG allows for convenient exploration about the development of national disease surveillance systems for more than 60 diseases in the EU member states, as well as Iceland, Liechtenstein and Norway, over the course of the past 7 years (2015–2021)

Efficacy of self-guided internet-based cognitive behavioral therapy (iCBT) in treatment of depressive symptoms: An individual participant data meta-analysis

Many studies have found that depressive symptoms can be effectively treated with psychotherapy, pharmacotherapy, or both. Nevertheless, many people with depressive symptoms do not seek help, and even well-resourced health care systems find it difficult to marshal enough qualified therapists to offer psychological interventions. Access barriers to psychotherapy include limited availability of trained clinicians, high cost of treatment, and fear of stigmatization. As a consequence, a significant number of individuals with depressive symptoms remain untreatedThis work was performed under grant 603098 for the European Comparative Effectiveness Research on Internet-based Depression Treatment (E-COMPARED) project funded by the European Commission’s Seventh Framework Program. At the time of the study, Dr Griffiths was supported by National Health & Medical Research Council Fellowship 1059620