scholarly journals Cognitive Bias Modification for Behavior Change in Alcohol and Smoking Addiction: Bayesian Meta-Analysis of Individual Participant Data

2019 ◽  
Vol 29 (1) ◽  
pp. 52-78 ◽  
Author(s):  
Marilisa Boffo ◽  
Oulmann Zerhouni ◽  
Quentin F. Gronau ◽  
Ruben J. J. van Beek ◽  
Kyriaki Nikolaou ◽  
...  
PLoS ONE ◽  
2017 ◽  
Vol 12 (4) ◽  
pp. e0175107 ◽  
Author(s):  
Haining Liu ◽  
Xianwen Li ◽  
Buxin Han ◽  
Xiaoqian Liu

2017 ◽  
Vol 59 (8) ◽  
pp. 831-844 ◽  
Author(s):  
Georgina Krebs ◽  
Victoria Pile ◽  
Sean Grant ◽  
Michelle Degli Esposti ◽  
Paul Montgomery ◽  
...  

2020 ◽  
Vol 7 (6) ◽  
pp. 506-514 ◽  
Author(s):  
Liviu A Fodor ◽  
Raluca Georgescu ◽  
Pim Cuijpers ◽  
Ştefan Szamoskozi ◽  
Daniel David ◽  
...  

2015 ◽  
Vol 206 (1) ◽  
pp. 7-16 ◽  
Author(s):  
Ioana A. Cristea ◽  
Robin N. Kok ◽  
Pim Cuijpers

BackgroundCognitive bias modification (CBM) interventions are strongly advocated in research and clinical practice.AimsTo examine the efficiency of CBM for clinically relevant outcomes, along with study quality, publication bias and potential moderators.MethodWe included randomised controlled trials (RCTs) of CBM interventions that reported clinically relevant outcomes assessed with standardised instruments.ResultsWe identified 49 trials and grouped outcomes into anxiety and depression. Effect sizes were small considering all the samples, and mostly non-significant for patient samples. Effect sizes became non-significant when outliers were excluded and after adjustment for publication bias. The quality of the RCTs was suboptimal.ConclusionsCBM may have small effects on mental health problems, but it is also very well possible that there are no significant clinically relevant effects. Research in this field is hampered by small and low-quality trials, and by risk of publication bias. Many positive outcomes are driven by extreme outliers.


2018 ◽  
Author(s):  
Melvyn Zhang ◽  
Jiangbo Ying ◽  
Guo Song ◽  
Daniel SS Fung ◽  
Helen Smith

UNSTRUCTURED Background: Traditional psychological therapies focus mainly on modification of individuals’ conscious decision-making process. Unconscious processes such as cognitive biases have been found to be accountable for various psychiatric psychopathologies. The advances in technologies have transformed how bias modification programs are being delivered. Objective: We seek to synthesize the current evidence of web-based cognitive bias modification for psychiatric disorders, by identifying the range of conditions targeted and their current efficacy. We wish to determine if web-based attention bias modification is as efficacious as compared to conventional methods. Methods and analysis: A systematic review will be conducted, and all studies types will be included. There will not be any restrictions on the participants included in the study. A search will be conducted on the respective databases up till 2017. Selection of studies will be by the Preferred Reporting Items for Systematic Review and Meta-analyses (PRISMA-P) guidelines. Quality assessment of the included studies will be assessed using the Cochrane Risk of Bias tool (for randomized trials) and the Newcastle-Ottawa scale for other study designs. A narrative synthesises of the identified articles will be conducted. A meta-analysis will be considered, only if there are sufficient articles in a domain for statistical analysis. Ethical approval for the current protocol and the planned systematic review was not required. Results: Results synthesized would be disseminated using conference presentation or published works in peer-reviewed journals. Conclusions: This review is of importance given how technology transformed the delivery of conventional therapies. The findings from this review will provide guidance for future research involving technology and cognitive bias modification interventions. Registration details: International Prospective Register for Systematic Reviews (PROSPERO) number 2017 CRD42017074754


PLoS ONE ◽  
2014 ◽  
Vol 9 (6) ◽  
pp. e100925 ◽  
Author(s):  
Claudia Menne-Lothmann ◽  
Wolfgang Viechtbauer ◽  
Petra Höhn ◽  
Zuzana Kasanova ◽  
Simone P. Haller ◽  
...  

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