Anastasiia G KovalenkoUniversity of Bristol | UB · Medical School
Anastasiia G Kovalenko
Doctor of Philosophy
About
6
Publications
5,184
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Introduction
Current project:
Multiagency interventions to reduce youth violence, exploitation and victimisation: Feasibility and Pilot Study (Youth Endowment Fund) 2024-present
Additional affiliations
Education
September 2017 - February 2024
September 2012 - November 2014
Publications
Publications (6)
In recent years, social campaigns and high-profile cases have brought increased attention to violence against women. Athletes can be role models, shaping both prosocial and antisocial attitudes. Their engagement in violence prevention could be an effective tool to tackle violence against women through bystander intervention. This part of a mixed-me...
Background Treatment burden represents the work patients undertake because of their healthcare, and the impact of that effort on the patient. Most research has focused on older adults (65+) with multiple long-term conditions (MLTC-M) but there are more younger adults (18-65) living with MLTC-M and they may experience treatment burden differently. U...
https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/941380/Bystander_interventions_report.pdf
Violence prevention programs aim to raise awareness, change attitudes, normative beliefs, motivation, and behavioral responses. Many programs have been developed and evaluated, and optimistic claims about effectiveness made. Yet comprehensive guidance on program design, implementation, and evaluation is limited. The aim of this study was to provide...
Many violence prevention programs include a focus on the role of bystanders and third parties in violence prevention training. Central to this work has been the classic social psychological research on the “bystander effect”. However, recent research on bystander behavior shows that the bystander effect does not hold in violent or dangerous emergen...
Questions
Question (1)
Hi All,
I have conducted a pilot study with a small sample (50ppts), 2 groups - intervention (n=34) and control (n=16), pre-post-follow-up design.
I've done linear multiple regressions (similar to ANCOVAs) to see differences between groups post-test adjusted for baseline. As a secondary analysis, I performed mixed-effects models (instead of repeated measures ANOVAs due to missing data issues) to see predicted changes between groups (and post hoc contrasts within groups) over time.
Now I want to compute the effect sizes and predict optimal sample size. As far as I understand it is the G Power calculation, but I am not sure how to do it post mixed-effects models (since the manuals don't provide this option).
Could you please suggest a solution? Thanks