This study aimed to determine the causal role of insomnia-consistent interpretation bias within the cognitive model of insomnia, by modifying this bias in students experiencing subclinical levels of insomnia and assessing subsequent effects on sleep parameters. A sample of 128 students underwent randomization to receive either a single session of online Cognitive Bias Modification-Interpretation (CBM-I) or a sham training. Participants then tracked their pre-sleep worry and sleep parameters for seven consecutive days. Interpretation bias was assessed using an encoding-recognition task specifically designed for insomnia-related interpretation bias. The CBM-I manipulation utilized ambiguous scenarios to redirect participants away from making insomnia-related interpretations. Results revealed that CBM-I effectively decreased insomnia-consistent interpretation bias compared to the sham treatment, with interpretation bias being absent post-training in the CBM-I group. This reduction did not lead to improvements in pre-sleep worry or any sleep parameters. This study has been the first to investigate the causal role of interpretation bias on symptoms of insomnia. Although results indicated this bias to be modifiable, its causality within the cognitive model proves to be more complicated. Future research focusing on optimization of cognitive bias modifications could shed more light on the effects of biased cognitions on insomnia symptoms.
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http://dx.doi.org/10.1016/j.brat.2024.104607 | DOI Listing |
Diabetologia
January 2025
Department of Public Health, University of Helsinki, Helsinki, Finland.
Aims/hypothesis: Eating disorders are over-represented in type 1 diabetes and are associated with an increased risk of complications, but it is unclear whether type 1 diabetes affects the treatment of eating disorders. We assessed incidence and treatment of eating disorders in a nationwide sample of individuals with type 1 diabetes and diabetes-free control individuals.
Methods: Our study comprised 11,055 individuals aged <30 who had been diagnosed with type 1 diabetes in 1998-2010, and 11,055 diabetes-free control individuals matched for age, sex and hospital district.
BMJ Open Gastroenterol
January 2025
Biomedical Sciences, Wollo University, Dessie, Ethiopia.
Objective: Gallstone disease is a prevalent global health issue, but its impact in Africa remains unclear. This study aims to summarise and synthesise available data on the prevalence of gallstone disease across populations in Africa.
Design: Systematic review and meta-analysis, reported in accordance with Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines.
Am J Clin Nutr
January 2025
School of Epidemiology and Public Health, Faculty of Medicine, University of Ottawa, Ottawa, ON, Canada; Clinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, ON, Canada.
Background: Although high-quality nutrition systematic reviews (SRs) are important for clinical decision making, there remains debate on their methodological quality and reporting transparency.
Objectives: The objective of this study was to assess the reliability and reproducibility of a sample of SRs produced by the Nutrition Evidence Systematic Review (NESR) team to inform the 2020-2025 Dietary Guidelines for Americans (DGAs).
Methods: We evaluated a sample of 8 SRs from the DGA dietary patterns subcommittee for methodological quality using the Assessment of Multiple Systematic Reviews 2 (AMSTAR 2) tool and for reporting transparency using the PRISMA 2020 and PRISMA literature search extension (PRISMA-S) checklists.
Cortex
December 2024
Department of Psychology, Neuroscience, and Behaviour, McMaster University, Hamilton, Ontario, Canada.
It has been demonstrated that humans exhibit an attention bias towards the lower visual field (e.g., faster target detection for targets appearing below eye level).
View Article and Find Full Text PDFJ Environ Manage
January 2025
Department of Landscape Architecture, University of Nevada, Las Vegas, NV, USA. Electronic address:
The integration of crowdsourced data has become central to contemporary built environment studies, driven by the rapid growth in digital technologies and participatory approaches that characterize modern urbanism. Despite its potential, a systematic framework for its analysis remains underdeveloped. This review, conducted in accordance with the PRISMA protocol, examines the use of crowdsourced data in shaping the built environment, scrutinizing its applications, crowdsourcing techniques, methodologies, and comparison with other big data forms.
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