Publications by authors named "E Petkova"
Background: Available empirical evidence on participant-level factors associated with dropout from psychotherapies for post-traumatic stress disorder (PTSD) is both limited and inconclusive. More comprehensive understanding of the various factors that contribute to study dropout from cognitive-behavioural therapy with a trauma focus (CBT-TF) is crucial for enhancing treatment outcomes.
Objective: Using an individual participant data meta-analysis (IPD-MA) design, we examined participant-level predictors of study dropout from CBT-TF interventions for PTSD.
Article Synopsis
- Precision medicine tailors treatments to individual patients based on their unique characteristics, but often focuses on only one health outcome, which can lead to less effective treatment strategies.
- A new Bayesian multivariate hierarchical model is introduced that combines information from multiple related health outcomes, resulting in more accurate treatment effect estimations compared to traditional single outcome models.
- This method shows improvement in decision-making using data from a COVID-19 treatment trial, demonstrating its ability to reduce errors in treatment decisions and enhance the precision of individual-level treatment efficacy estimations.
Background and objective Comprehensive health literacy and prevention have been the key methods to reduce the spread of human papillomavirus (HPV) and HPV-associated disease development. Raising awareness among young individuals about the risk factors and the ways to prevent the infection is often the starting point of primary prevention. In light of this, we aimed to assess the awareness of midwifery students at Medical University-Pleven about (HPV) and HPV-associated diseases.
View Article and Find Full Text PDFUnsupervised Bayesian classification for models with scalar and functional covariates.
J R Stat Soc Ser C Appl Stat
June 2024
Article Synopsis
- The research discusses an unsupervised classification method using a latent variable to categorize a scalar response into multiple components in a mixture model that includes both scalar and functional covariates.
- It suggests a hierarchical modeling approach, where the first level uses parametric distributions for the scalar response and the second level utilizes a generalized linear model to handle the mixture probabilities.
- Additionally, the method addresses issues with conventional approaches that treat functional covariates as vectors, proposing a Bayesian approach that reduces dimensionality through basis expansions, with practical applications in clinical trials and agricultural settings.
Implementing a Uniform Outcome Measurement Approach for Early Interventions of Autism Spectrum Disorders.
J Am Acad Child Adolesc Psychiatry
July 2024
Objective: Naturalistic developmental behavioral interventions for children with autism spectrum disorder show evidence for effectiveness for specific social communication targets such as joint attention or engagement. However, combining evidence from different studies and comparing intervention effects across those studies have not been feasible due to lack of a standardized outcome measure of broader social communication skills that can be applied uniformly across trials. This investigation examined the usefulness of the Brief Observation of Social Communication Change (BOSCC) as a common outcome measure of general social communication skills based on secondary analyses of data obtained from previously conducted randomized controlled trials of 3 intervention models, Early Social Intervention (ESI), Early Start Denver Model (ESDM) and Joint Attention Symbolic Play Engagement and Regulation (JASPER).
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